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Wind resource assessment using SODAR and meteorological mast – A case study of Pakistan
Abstract
A wind assessment process can make or break the economics of wind plant development. Lack of credible data is one of the major reasons for faulty predictions and inaccurate estimations of the energy production from wind farms. This paper provides a concise, yet comprehensive analysis of state-of-the-art wind site assessment techniques, including a detailed survey of their strengths and pitfalls. The analysis of each technique addresses issues that may affect the power production estimates to an undesirable degree. It also overviews parameters such as survey time, coverage area, cost, and feasibility for each technique according to the site chosen for the assessment. A case study at the end presents independent surveys carried out in the Kallarkahar region of Pakistan using the latest site assessment techniques. The collected data sets are examined in order to unearth discrepancies affecting the assessment process in the surveys.
... That is the most precise tool to measure wind speed and it is generally accepted as standard for wind speed measurement. It represents the necessary last stage of the site potential assessment; however, previous analysis to identify the most suitable area have to be performed [50]. If the accuracy is surely the edge of such method, the main current disadvantage is its economic cost, due to the complicate maintenance and technical issues related to their height that should be similar to the one of a WTG [51]. ...
... Moreover, it is noteworthy that in order to have a reliable set of data, anemometers have to be installed in a specific site for more than one year continuously; during this period, the instruments can be damaged for extreme weather conditions, increasing the overall cost of the measuring campaign [55]. Moreover, in remote areas, higher engagement and supervision cost are required further increasing the overall measurement campaign cost [50]. Thus, preliminary analysis is needed; one of the most well-known way is the retrieval of wind speed and direction from remote sensing [27]. ...
... LiDAR tool was first developed in the 1970s and very early started evolving using cryogenically-cooled carbon dioxide and techniques for stable optical alignment [58]. LiDAR has a working principle similar to radar [50]. As a matter of fact, LiDAR uses a laser from coherent light generated by its device and that is reflected back by the several particles suspended in the air (e.g. ...
A method for assessing and mapping the wind energy potential of near- and off-shore areas by means of multi sensor satellites (i.e. the recently launched Sentinel 1) is shown in this paper and applied to a case study area in the north-west coast of the Sicily island. The presented method aims at i) preliminary identifying the best sites for wind turbine generators installation and/or ii) estimating the average wind potential in small areas (e.g. archipelagos) for energy planning purposes. Firstly, a detailed literature review of existing techniques for wind speed estimation has been carried out, considering the most traditional methods (e.g. meteorological masts), remote sensing techniques and including a thorough review on the use of Synthetic Aperture Radar (SAR) methods integrated with Geophysical Model Functions (GMFs) for wind speed retrieval. This review enables to identify CMOD5 (C Geophysical model function 5) as the best performing GMF overcoming the CMOD4 accuracy issues in high wind speed conditions. Thus, the method has been detailly described and showcased through the analysis of the case study. SAR images from the Sentinel 1 satellite have been processed by means of the Sentinel Application Platform (SNAP) software. Afterwards, the wind speed and direction have been mapped through a Geographic Information System software. Lastly, the mean wind climate has been extrapolated for a specific Region Of Interest by the Environment for Visualizing Images (ENVI) 4.8 software. Consequentially, six hot spots characterized by high-energy potential have been identified as possible sites for possible installations of wind turbine generators.
... Regarding SoDAR solutions, suggested in [16], they can present rootmean-square errors of around 2% compared to mast-mounted cup anemometers. In [17], the results between SoDAR and the cup anemometer show some differences mainly due to the measurement field campaigns, which were conducted in different locations. A comparison between LiDAR, SoDAR and mast-mounted cup anemometer was carried out in [18]. ...
... According to [19], the SoDAR is highly dependent on temperature variation in the atmosphere, which is a substantial drawback compared to LiDAR solutions. However, a cost analysis reveals that SoDAR equipment is cheaper than the LiDAR [17]. ...
... Methodology used Year [13] Comparison between LiDAR and two databases (ECMWF and HWM07) 2017 [17] Comparison between SoDAR and cup anemometer 2017 [21] Power law applied to anemometer measurements 2011 [25] Comparison between D-H model and power law 2017 [32] Revised power-law model 2018 [26] Anemometers at different heights 2010 [27] Comparison between LiDAR and data collected in a nearby place 2013 [28] Adaptive neuro-fuzzy method 2011 [30] Artificial neural network 2017 [33] Comparison between power law, logarithmic law and real data 2015 [34] Power law for low speed conditions (prevailing air and thermal pollution) 2017 with and without exogenous variables. A review of methodologies used in some of the previously mentioned studies is summarized in Table 1. ...
Wind power plants are becoming a generally accepted resource in the generation mix of many utilities. At the same time, the size and the power rating of individual wind turbines have increased considerably. Under these circumstances, the sector is increasingly demanding an accurate characterization of vertical wind speed profiles to estimate properly the incoming wind speed at the rotor swept area and, consequently, assess the potential for a wind power plant site. The present paper describes a shape-based clustering characterization and visualization of real vertical wind speed data. The proposed solution allows us to identify the most likely vertical wind speed patterns for a specific location based on real wind speed measurements. Moreover, this clustering approach also provides characterization and classification of such vertical wind profiles. This solution is highly suitable for a large amount of data collected by remote sensing equipment, where wind speed values at different heights within the rotor swept area are available for subsequent analysis. The methodology is based on z-normalization, shape-based distance metric solution and the Ward-hierarchical clustering method. Real vertical wind speed profile data corresponding to a Spanish wind power plant and collected by using a commercialWindcube equipment during several months are used to assess the proposed characterization and clustering process, involving more than 100000 wind speed data values. All analyses have been implemented using open-source R-software. From the results, at least four different vertical wind speed patterns are identified to characterize properly over 90% of the collected wind speed data along the day. Therefore, alternative analytical function criteria should be subsequently proposed for vertical wind speed characterization purposes.
... The aerodynamic performance characteristics of a hybrid VAWT using computational techniques were analyzed by Sun et al. [8]. The analysis revealed that the Savonius turbine blade with a greater distance of blades from the central shaft resulted in a large C p (0. 25) compared to the other configurations. Machlin [3] studied the effect of shroud addition on a hybrid VAWT. ...
... Moreover, based on wind classifications, wind class 5 having an excellent wind resource with a wind speed range of 7.3-8.0 m/sec was selected [24,25]. The basic relationship to estimate power produced by a wind turbine is given by Eq 1 [26]. ...
This research emphasizes designing a straight-bladed Double-Darrieus hybrid vertical axis wind turbine (VAWT) with a high power coefficient as well as self-starting capability. Computational fluid dynamics analysis was performed using the sliding and dynamic meshing techniques. Various datasets were employed in the design of experiments to determine optimal configurations. A quadratic equation based on a regression model was established, and response surface methodology was applied to determine the accuracy of the model by analysis of variance, goodness of fit, investigation of residuals, and R-squared values. The optimized chord length, number of blades, pitch angle, distance of blades from the central rotating shaft, and rotor height were obtained as 0.547 m, 03, -3.41 deg, 0.789 m, and 1.605 m, respectively. A standard H-rotor Darrieus configuration, comprising symmetric airfoils and existing Darrieus-Savonius hybrid VAWTs were also analyzed for comparison. The positive static torque coefficient at all azimuth angles indicates that the proposed hybrid wind turbine is completely self-starting. The output power of the standard Darrieus configuration is substantially zero below a wind speed of 3.65 m/s, indicating that it is not capable of converting the kinetic energy of the airflow into electrical power below this specified value. On the contrary, the self-starting speed of the proposed hybrid wind turbine is as low as 2.81 m/s with a rated power of 1.522 kW at a wind speed of 7.5 m/s. The capability of the proposed hybrid wind turbine with a better power coefficient and transforming wind energy, even at low wind speeds, extends its utilization for various small to large-scale power projects. The proposed approach enables the determination of the optimum design configuration of a hybrid vertical axis wind turbine, along with a high-fidelity analysis in the early design phase.
... Both the techniques have the advantages of real-time response and convenience. However, due to the structural complexity of aerosols for LIDAR and noise for SODAR, these two techniques cannot obtain accurate measurements when the measuring distance is long or the wind speed is fast [12]- [14]. ...
... POD has provided a means of representing a wind field by a group of basis vectors, thus enabling the wind field to be reconstructed in a very short time period, which can be an effective method for short-term wind forecasts in real time, just using a limited number of sensor measurement of the wind velocities at certain locations. However, the reconstruction process is an under-determined process, or rank-deficient problem, reflected by the dimensions of the matrix M in (12). ...
Physical and data-based approach for wind forecast has been under rapid development recently. Yet challenges remain when high spatial resolutions of the velocity distributions are desired for a wind farm. One of the major causes is the huge computation load that cannot be accomplished in time for a large area. In this study, a method for rapid wind field reconstruction is developed that can provide refined spatial resolution. The method first generates a large number of numerical wind fields using computational fluid dynamics, and extracts the basis vectors of dramatically reduced dimensions by means of Proper Orthogonal Decomposition. With the basis vectors a wind field can be rapidly reconstructed in an inverse process based on limited measurement data by the sensors. A procedure is proposed to optimize the solution process, which effectively leads to optimal sensor placement. Both simulations and experimental are carried out to evaluate the methods. The results are compared and good agreements are observed. IEEE
... The long-term trend of energy also plays a key role in assessment and development and site construction in the region. Komal evaluated the wind energy of Pakistan by comparing the SODAR data with the measured data and found that it is economically feasible to use SODAR data to evaluate wind energy [12]. Saulat evaluated and predicted Pakistan's wind energy resources based on the previous studies using site data and pointed out that Pakistan owns optimistic wind energy resources, but the development is slow, and put forward decision-making suggestions on the utilization of wind energy to develop resources [13]. ...
Wind energy resource is an important support for the sustainable development of Antarctica. The evaluation of wind energy potential determines the feasibility and economy of wind power generation in Antarctica, among which mastering the variation rule of wind energy resource is the key to realizing the effective utilization of polar wind energy. Based on the 6-h ERA-5 reanalysis data of ECMWF from January 1981 to December 2020, this paper systematically analyzed the long-term variation trend of Antarctic wind energy resource by using the climate statistical analysis method and the least square fitting, with the comprehensive consideration of a series of key indicators such as Wind Power Density, Effective Wind Speed Occurrence, Energy Level Occurrence, and Stability. The results show that it indicates a positive trend for wind power density (0.5~2 W × m−2 × a−1), effective wind speed occurrence (2~3%/a), energy level occurrence (0.1~0.2%/a), and coefficient of variation (−0.005/a) in the South Pole—Kunlun station and the central region of Queen Maud land. The westerly belt exhibits a decreasing index (−0.5%/a) in terms of stability trend, indicating a positive potential. Kemp Land, the Ross Island—Balleny Islands waters show shortages in all indicators. The wind power density in the Antarctic region is stronger in spring and summer than in autumn and winter, with the weakest in autumn. Based on the above indicators, the variation trend in the East Antarctic coast, Wilhelm II Land—Wilkes Land, the South Pole—Kunlun station, and the westerlies is generally superior.
... At the end of this section, the reconstruction time with a different number of sensors based on POD and Tucker's decomposition was discussed, which was crucial for the reconstruction of the unsteady wind field. Based on the boundary condition 90 • , 8 m/s, four groups of sensors (5,10,15,20) were designed to discuss the time required for reconstruction, and the results are shown in Table 7. With the increase in the number of sensors, the time required for reconstruction also increased accordingly. ...
Short-term wind power forecasting is crucial for updating the wind power trading strategy, equipment protection and control regulation. To solve the difficulty surrounding the instability of the statistical model and the time-consuming nature of the physical model in short-term wind power forecasting, two innovative wind field reconstruction methods combining CFD and a reduced-order model were developed. In this study, POD and Tucker decomposition were employed to obtain the spatial–temporal information correlation of 2D and 3D wind fields, and their inverse processes were combined with sparse sensing to reconstruct multi-dimensional unsteady wind fields. Simulation and detailed discussion were performed to verify the practicability of the proposed algorithms. The simulation results indicate that the wind speed distributions could be reconstructed with reasonably high accuracy (where the absolute velocity relative error was less than 0.8%) using 20 sensors (which only accounted for 0.04% of the total data in the 3D wind field) based on the proposed algorithms. The factors influencing the results of reconstruction were systematically analyzed, including all-time steps, the number of basis vectors and 4-mode dimensions, the diversity of CFD databases, and the reconstruction time. The results indicated that the reconstruction time could be shortened to the time interval of data acquisition to synchronize data acquisition with wind field reconstruction, which is of great significance in the reconstruction of unsteady wind fields. Although there are still many studies to be carried out to achieve short-term predictions, both unsteady reconstruction methods proposed in this paper enable a new direction for short-term wind field prediction.
... However, long-term U time series are usually limited to a few sites of national meteorological services [15]. Since non-routine wind measurements are complex and expensive, an initial assessment of the wind climate before the U measurement is needed [16]. ...
Many different wind speed models support assessing the wind climate. Depending on their development, spatiotemporal resolution, and intended use, typical wind
speed model types are wind atlases, reanalysis products, regional climate, and global climate models. They realistically represent different properties of the wind climate. For the first time, 68 wind speed models of different types are assessed for their predictive power for (1) mean wind speed, (2) wind speed distribution, and (3) temporal variability. In addition, eight ensembles of individual models from each model type are created and validated. The hypothesis is tested that ensembles of
wind speed models generally improve model accuracy. For the validation, 148 wind speed time series with a data availability of at least ten years in 1979 to 2014 were used. The measurement sites were separated into flat and open, and mountainous locations. The results reveal the improved model performance of ensembles compared to individual models. Only wind atlases are capable of estimating wind speed properties at mountainous locations. Their median coefficient of determination related to mean wind speed at mountainous sites is 0.81 but less than 0.15 for any other model type. One important conclusion is that individual models may not be appropriate for wind resource assessment without prior validation. Furthermore, ensembles are recommended to improve predictive power for any wind climate properties. The results indicate how well the different model types can reproduce the analyzed wind speed characteristics.
... The major sources, as described in Figure 6, are journal articles. The highest number of articles are from Renewable and Sustainable Energy Reviews [7,26,[29][30][31][32][33][34][35][36][37][38][39][40][41][42][43][44], the Journal of Basic & Applied Sciences [45][46][47][48], and Environmental Science and Pollution Research [15,49,50]. The details are provided in Figure 8. ...
Energy is the driver of the socioeconomic growth and development of a country. In the pursuit of available and affordable sources of energy, nations around the world have forgotten the sustainability angle and are facing an energy crisis. The developing world has initiated development plans in an unsustainable way, causing a demand-supply gap and leading to very high energy prices. Renewable energy gives us a solution to this circular crisis. The recent world has seen significant investment in renewables, particularly in the wind energy sector. The investment was initiated as a government spending program, but is now taken up by the private sector. The current study presents a thorough analysis of the prospects for wind energy and the means and measures required to fully capacitate the sector in Pakistan. In Pakistan's three largest provinces, there is tremendous potential for wind energy, which requires proper utilization and exploration for sustained socioeconomic development. This study is based on the mixed-methods approach. In the first phase, content analysis was caried out using the systematic literature review (SLR) technique. Relevant content analysis was performed using the PRISMA diagram. A total of two hundred and thirty-nine (239) documents were scanned; however, only eighty-two (82) were included after the removal of duplications and irrelevant documents. Moreover, short interviews were conducted with entrepreneurs, and themes have been prescribed. The study found that commercially feasible wind energy potential is particularly abundant in Pakistan's Sindh and Balochistan regions. The country's diverse geography makes it ideal for wind turbine installations at various sites. The renewable energy policy should be revisited to incentivize the use of wind energy to ensure the nationally determined contributions (NDCs)' commitments are assured to achieve sustainable development by 2030. Pakistan has seen rapid development in the wind energy sector with around 4 percent of electric power being generated through wind farms in just over 13 years. In order to exploit the potential, there is a need for significant public and private joint efforts.
... Currently, there are some studies on the macro zoning of wind farms. In [9,10], zoning of wind farms is conducted in the practical engineering field considering the empirical reference radius of a representative area (1) The determination of the number of met mast is mostly dependent on engineering experience, and this method lacks reasonable quantitative calculation. (2) The current zoning methods can not directly and automatically get zoning results, and human subjective judgment accounts for a certain proportion in the process. ...
In order to promote the wind monitoring accuracy and provide a quantitative planning method for met mast layout in practical projects, this paper proposes a two-stage layout method for met mast based on discrete particle swarm optimization (DPSO) zoning and micro quantitative siting. Firstly, according to the wind turbines layout, rotational empirical orthogonal function and hierarchical clustering methods are used to preliminarily determine zoning number. Considering the geographical proximity of wind turbines and the correlation of wind speed, an optimal macro zoning model of wind farm based on improved DPSO is established. Then, combined with the grid screening method and optimal layout evaluation index, a micro quantitative siting method of met mast is proposed. Finally, the rationality and efficiency of macro zoning method based on improved DPSO, as well as the objectivity and standardization of micro quantitative siting, are verified by an actual wind farm.
... The wind potential recorded is in between 6.2 to 6.9m/s in the Pakistan coastal region Karachi. The government has put in eight 300W turbines in Baluchistan and six 500W turbines in Sindh and it absolutely was all over that it's cost-effective and technically doable choice for electrification of remote villages [4][5][6][7][8]. ...
The solar irradiation and wind speed show random as well as periodic variations as a function of variations in the weather. In this paper, an effort is made to detect, analyze, model and predict in order to be able to forecast the variations in solar irradiations and the wind parameters to be able to efficiently employ these renewable energy sources in meeting the current and future power needs of Karachi mega city. Important Solar and Wind Parameters GHI (Global Horizontal Irradiation): is the sum of direct and diffuse components of solar radiation in kilo watt hour per meter square. DNI (Direct Normal Irradiation): is the solar irradiation component that directly touches the surface in kilo watt hour per meter square. DNIcs: Direct normal irradiance under clear sky DNIcn: Maximum direct normal radiation under cloudy sky during the day (W/m 2) DHI (Diffuse Horizontal Irradiation): is the solar irradiation component that is scattered by the atmosphere in kilo watt hour per meter square. DHIcs: Diffuse horizontal irradiance under clear sky GTI (Global Tilted Irradiation): Sum of direct and diffuse solar radiation falling on a tilted surface of fixed-mounted PV modules in kilo watt hour per meter square. PVOUT (PV Electricity output): Amount of energy, converted by a PV system into electricity [kWh/kWp]. OPTA (Optimum angle): Optimum inclination of an inclined and fixed PV modules for a specific azimuth (orientation TEMP (Air Temperature at 2 meters above ground): Air temperature [ºC or ºF] determines the temperature of PV cells and modules ELE (Elevation): Represents terrain elevation (altitude) relative to the sea level [m or ft]. Location (site): Site of interest can be located by latitude and longitude values System size: Total DC capacity (installed power) of a PV system is considered Global Research Review-ISSN: 2737-8551 Azimuth: Orientation of the PV modules. Inclination: Tilt of PV modules measured from a horizontal surface as a reference. A: Apparent extra-terrestrial irradiance (W/m 2) B: Atmospheric attenuation coefficient (W/m 2) C: A dimensionless constant Cn: Cloud cover index DHI (Diffuse horizontal irradiance) (W/m 2)-z: The zenith angle is similar to the elevation TI: Turbulence intensity WSmax: wind speed max WSmin: wind speed min WSmean: wind speed mean WSsd: wind speed stddev WAsP: Software, as wind industry-standard GWA: Global wind alliance 1. Introduction Majority of Researchers have always tried to investigate various aspects of the energy in Pakistan. However, very few researchers have studied the energy profile of southern part of Pakistan, namely Karachi region. According to these researchers, the current state of energy in Pakistan shows a consistent dependence on the traditional fossil fuels. There is constant deficit in the traditional fossil fuel-based energy resources while the lack of progress persists in the exploration and consumption of wind and solar energy sectors [1-3]. Studies on southern regions of Pakistan indicate that there is a highly promising wind energy potential of over 50,000MW with a median wind speed of over 7m/s at 80m height in most of the coastal regions of Sindh and Baluchistan. This Coastal Belt of Pakistan is endued with a wind passageway that is 60km wide (Gharo Kati Bandar) and 180km long (up to Hyderabad). The wind potential recorded is in between 6.2 to 6.9m/s in the Pakistan coastal region Karachi. The government has put in eight 300W turbines in Baluchistan and six 500W turbines in Sindh and it absolutely was all over that it's cost-effective and technically doable choice for electrification of remote villages [4-8]. The southern Pakistan has around 1100 kilometers of the coastal line with the ample amount of wind energy potential. However, the earlier researchers have focused on the specific wind corridors only. Through these earlier approaches by these researchers, the specific regions of interest or wind corridors have been proved to have theoretically optimum wind potential. Moreover, the future challenges in implementation of the wind energy have also remained the focus [5]. The researchers have also investigated the potential of reducing energy consumption by using daylight through domes in roofs. They have used the energy Plus software to analyze the energy capacity in buildings in Karachi city. The authors have found the ways to reduce the customer energy bills and by saving the bills they have claimed to avert the energy crisis. Some other researchers have suggested Automatic Metering Interface (AMI) for Karachi and Lahore. They have proposed the hybrid system model for Lahore and Karachi consists of smart meter, gateway (i.e., data concentrator (DC)) and meter data management system (MDMS) [9]. According to prior research on energy, Pakistan is facing a large gap between the demand and supply of energy. This gap exists due to large energy demand and no investment in energy resources since last several decades, so energy crises persist. These researchers have attempted to discuss the transition towards the green energy resources in order to fulfil this
... The device either produces a voltage proportional to speed wind or records the number of revolutions per unit time electronically . To measure wind direction, anemometers are frequently employed in conjunction with wind vanes (Khan and Tariq 2018;Guerrero-Villar et al. 2019). Another type of anemometer is an ultrasonic anemometer, which detects the phase of sound changes, and a laser anemometer, which uses coherently scattered light from wind waves. ...
Energy is the source of economic growth, and energy consumption indicates the country’s state of development. Energy engineering is a relatively new technical discipline. It is increasingly considered as a significant step in meeting carbon reduction targets, which can produce a variety of appealing outcomes that are useful to humanity’s evolution. Many countries have adopted national policies to decrease pollution by reducing fossil fuel use and increasing renewable energy usage by alleviating climate change (wind and solar, etc.). The ever-growing need for renewable sources has led to economic and technological problems, such as wind energy, essential for effective grid control, and the design of a wind project. Precise estimates offer network operators and power system designers vital information for the generation of an appropriate wind turbine and controlling demand and supply power. This work provides an in-depth study of the proliferation of artificial intelligence (AI) in the prediction of wind energy generation. The devices employed to calculate wind speed are examined and discussed, with a focus on studies recently published. This review’s findings show that AI is being employed in power wind energy measurement and forecasts. When compared to individual systems, the hybrid AI system gives more accurate findings. The discussion also found that correct handling and calibration of the anemometer can increase predicting accuracy. This conclusion suggests that increasing the accuracy of wind forecasting can be accomplished by lowering equipment errors that measure the meteorological parameter and mitigate carbon emission.
... In recent years, the lack of GESs assessment potential data in large areas due to the use of time-consuming traditional methods is not unexpected and is contributing to creating so-called forgotten areas (Nezhad et al., 2021a). It should be noted that the use of the traditional measurement tools such as cup anemometers, gliders, ships, and buoys is very expensive, time-consuming (they must be installed in the desired location for more than a year), and require maintenance (Khan and Tariq, 2018). ...
Due to the growing use of Green Energy Sources (GESs), the activities of mapping, monitoring, measurement, and detection of various GESs have become crucial. Assessing and measuring GESs are very complex since different environmental conditions occur. This importance is even greater when researchers face a shortage of measuring instruments and tools in many parts of the world. GES assessment is a challenging task that requires accurate and continuous measurement methods. Currently, traditional methods are very time-consuming and require spending money and human sources. So, the use of accurate and fast measurement methods and tools assessing measuring GESs potential are seriously recommended, which can greatly help the growth of the use of GESs, especially to cover and focus large areas. Satellite remote sensing is used to observe the environment in many fields and new and fast applications. Satellites remote sensing technologies and techniques for GESs assessing are fast, accurate, and can help to reduce costs and decision-making risks of GESs converters installations projects and provide suitable products to the public end-users. These could also be used to identify regions of interest for energy converter installations and to accurately identify new areas with interesting potentials. In this case, researchers can dramatically reduce the possibility of significant error in assessment methods. There is a lack of in-situ measuring tools mainly due to their high economic costs in the interested areas; an accurate analysis was carried out to assess the GESs energy potential. Since there are only limited options for further expanding the measurement over large areas, the use of satellites makes it easier to overcome in-situ limitations. Actually, to use and develop it as much as possible, a correct interdisciplinary understanding is needed. Satellite remote sensing technology for identifying suitable areas for GESs power plants could be a powerful tool that is constantly increasing in its new and fast applications but requires good planning to apply it in various GESs converters installations projects. In this article, a comprehensive review on wind, wave, biomass, geothermal sources assessment using Sentinel-1 (S-1) Synthetic Aperture Radar (SAR) satellite estimation has been summarized along with the different techniques available to measure GESs using satellites. In the paper, several of the successful estimation techniques were introduced in each section and compared for the understanding of limitations and strengths of different methods of GESs availability evaluation.
... The Intergovernmental Panel on Climate Change (IPCC) has proposed several options to reduce GHG pollution. CO 2 emissions are responsible for 75% of anthropogenic GHG emissions (Khan and Tariq 2018); hence, lowering them will have the most significant impact on mitigating global warming. These guidelines, such as the use of intermittent green energies, are on target to keep global warming below 2°C ...
Energy security and environmental measurements are incomplete without renewable energy; therefore, there is a dire need to explore new energy sources. Hence, this study aimed to measure the wind power potential to generate renewable hydrogen (H2), including its production and supply cost. This study used first-order engineering model and net present value to measure the levelized cost of wind-generated renewable hydrogen by using the data source of the Pakistan Meteorological Department and State Bank of Pakistan. Results showed that the use of surplus wind and renewable hydrogen energy for green economic production is suggested as an innovative project option for large-scale hydrogen use. The key annual running expenses for hydrogen are electricity and storage costs, which have a significant impact on the costs of renewable hydrogen. The results also indicated that the project can potentially cut carbon dioxide (CO2) pollution by 139 million metric tons and raise revenue for wind power plants by US$2998.52 million. The renewable electrolyzer plants avoided CO2 at a rate of US$24.9–36.9/ton under baseload service, relative to US$44.3/ton for the benchmark. However, in the more practical mid-load situation, these plants have significant benefits. Further, the wind-generated renewable hydrogen delivers 6–11% larger annual rate of return than the standard CO2 catch plant due to their capacity to remain running and supply hydrogen to the consumer through periods of plentiful wind and heat. Also, the measured levelized output cost of hydrogen (LCOH) was US$6.22/kgH2, and for the PEC system, it was US$8.43/kgH2. Finally, it is a mutually agreed consensus among environmental scientists that the integration of renewable energy is the way forward to increase energy security and environmental performance by ensuring uninterrupted clean and green energy. This application has the potential to address Pakistan’s urgent issues of large-scale surplus wind- and solar-generated energy, as well as rising energy demand.
... Pakistan has significant potential of wind energy. It has estimated installable potential of 346000 MW wind energy in Pakistan [47]. The total assessment of wind energy in various part of Pakistan is necessary to highlight the potential of investments avenues for both public and private sectors. ...
Clean energy potential can be used on a large scale in order to achieve cost competitiveness and market effectiveness. This paper offers sufficient information to choose renewable technology for improving the living conditions of the local community while meeting energy requirements by employing the notion of q-rung orthopair fuzzy numbers (q-ROFNs). In real-world situations, a q-ROFN is exceptionally useful for representing ambiguous/vague data. A multi-criteria decision-making (MCDM) is proposed in which the parameters have a prioritization relationship and the idea of a priority degree is employed. The aggregation operators (AOs) are formed by awarding non-negative real numbers known as priority degrees among strict priority levels. Consequently, some prioritized operators with q-ROFNs are proposed named as "q-rung orthopair fuzzy prioritized averaging (q-ROFPA d) operator with priority degrees and q-rung orthopair fuzzy prioritized geometric (q-ROFPG d) operator with priority degrees". The results of the proposed approach are compared with several other related studies. The comparative analysis results indicate that the proposed approach is valid and accurate which provides feasible results. The characteristics of the existing method are often compared to other current methods , emphasizing the superiority of the presented work over currently used operators. Additionally, the effect of priority degrees is analyzed for information fusion and feasible ranking of objects.
... Khan & Tariq (2018) provides a concise, yet comprehensive analysis of state-of-the-art wind site assessment techniques, including a detailed survey of their strengths and pitfalls. ...
There is an acute energy shortage in Pakistan today and a need for new affordable energy sources that can ease the misery of the starved energy masses. At the moment, not only do traditional sources of energy such as hydrogen and thermal energy grow; the government is also focusing on the vast potential of renewables such as solar, wind, biogas, waste and other energy sources. The renewable energy sources are now more conducive as compared with conventional energy sources, because they are environmentally friendly with zero emissions. Among several renewable energies, wind energy is growing most rapidly globally. Wind energy is highly prominent with its sustainability and low environmental impact. The prime objective of this paper is to analyze and evaluate the wind energy characteristics and wind power potential at University of Karachi. For the period from January 2017 to December 2017, wind speed time series data are available for the study site, measured in each 1-minute interval at the height of 10 m. The Weibull Distribution (WD) function is used to determine the wind energy and power potential of the site being studied. Six numerical methods are applied for evaluating the distribution parameters shape (k) and scale (c) i.e., Maximum Likelihood Method (MLM), Modified Maximum Likelihood Method (MMLM), Empirical Method (EM), Graphical Method (GM), Method of Moments (MoM) and Energy Pattern Factor Method (EPFM). The Correlation Coefficient and RMSE values have also been determined that show the reliability of the fitted distribution function and accuracy of the estimation methods. Wind power densities and frequency distributions of wind speed at the heights of 10m and 30m along with estimated wind power expected to be generated through off-grid wind turbines is calculated. Analysis and comparison of six numerical methods is presented in this paper to determine the Weibull scale and shape parameters for the available wind data. The yearly mean wind speed of the considered site is 3.059m/s and has wind power density of 80.309 W/m2 at 30m height with high power density during April to August (highest in June with wind speed 5.923m/s and power density 192.035W/m2). The economic evaluation is also carried out to illustrate wind turbine installation feasibility. For some small stand-alone systems, the candidate website is therefore recommended.
... Remote sensing devices are used more widely in conjunction with met masts to conduct power performance assessments (Khan and Tariq, 2018;Rehman, Mohandes and Alhems, 2018). ...
Tidal stream energy has the potential to contribute to a diverse future energy mix. As the industry moves towards commercialisation and array scale deployment, there is an opportunity to better understand the uncertainties around energy yield assessments. Energy yield assessments are used widely in the wind industry to evaluate the potential energy production from a prospective project. One of the key challenges is to quantify and reduce uncertainty in energy yield assessment. This thesis investigates ways to achieve this through utilising lessons learnt from the established wind industry. An evaluation of both the wind and tidal energy yield assessment process is conducted, highlighting where synergies can be used to increase understanding of uncertainty for the nascent tidal industry. The processes are comparable starting with a campaign to collect site data to characterise the resource at the measurement location. The next stage is to evaluate the long term variations, however this is where the two methods differ. Analysis of long term wind effects requires correlations to be made between short term site data and long term reference data from alternative sources. An assessment of tidal variations over longer periods utilises harmonic analysis, which is capable of deconstructing the individual astronomical variations of the tide and reconstructing them to predict future variations. Despite harmonic analysis being able to determine the astronomical effects of the tide, there are uncertainties in the measurements of tidal flow which are associated with non-astronomical effects. Effects such as turbulence introduce uncertainty when evaluating measured tidal data. This is one area which is investigated further in the thesis. Methods to evaluate the turbulence intensity from real ADCP data are investigated. The next stages require creating a numerical model of the site to extrapolate the data spatially to other areas of interest (such as a turbine location). Energy yield predictions for both wind and tidal are made by combining a power curve with the long term resource. The energy yield outputs are then adjusted to account for energy losses and uncertainties are applied to produce final energy yield values with the attributed probability values associated. Statistical methods are applied to harmonic analysis to assess the level of uncertainty in long term predictions of tidal variations. A method using spectral analysis is applied to evaluate the residuals between measured and modelled data and proves to be accurate at determining missing tidal constituents from the analysis. A method for evaluating the turbulence intensity of the flow is shown, to better understand the stochastic nature of the tidal signal. An investigation is conducted to assess the propagation of bed friction uncertainty, in hydrodynamic modelling, and the resulting impact on the predicted power output from a theoretical fence of tidal turbines spanning a tidal channel. The methodology is based on first conducting sensitivity studies by varying a parameter in the model and calculating the power. Then using a mean and standard deviation for the input parameter, the impact of the uncertainty can be transferred to the estimate of power. The results show that a larger uncertainty associated with the bed roughness tends to over predict the estimation of power. This work aims to inform the standardisation of practices and guidelines in tidal resource assessment and to support developers, consultants and financiers in future tidal energy yield assessments. The final chapter includes procedural recommendations for future tidal energy projects, summarising methods to calculate uncertainty and recommendations to reduce them.
... In this regard, basic, fast and cost-free measurement methods could help to identify unobserved areas with suitable potential and can reduce the overall OW farm construction project cost. There are many different tools and techniques for wind energy potential assessment, analysis, detection and reporting, for instance, cup anemometers, SOnic Detection And Ranging (SODAR) [8], Light Detection And Ranging (LiDAR) [9], Synthetic Aperture Radar (SAR) satellite data [10], numerical simulation and reanalysis dataset [11,12]. ...
The correct strategy for monitoring and assessing marine Renewable Energy Sources (RESs) is of great importance for local/national sustainable development. To achieve this goal, it is necessary to measure in the most precise possible manner the local/regional RESs potential. This is especially true for Offshore Wind (OW) energy potential, since the most precise techniques are long and expensive, and are not able to assess the RESs potential of large areas. Today, Remote Sensing (RS) satellites can be considered the most important land and marine observation tools. The RS tools can be used to identify the interested areas for future OW energy converters installations in large and small-scale areas. In this study, the OW energy potential has been analysed by means of a 40 years wind speed data from the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis dataset of the Samothraki island surrounding area in the Mediterranean Sea. The OW speed potential has been analysed by means of monthly data from ECMWF Interim reanalysis (ERA-Interim) datasets using the Network Common Data Form (NetCDF) format. Automatically, analyses have been carried out using the Region Of Interest (ROI) tool and Geographical Information System (GIS) software in order to extract information about the OW speed assessment of the Samothraki island area. The primary results of this study show that the southwest area of Samothraki island has good potential for future OW farms installation (bottom fixed and floating version) in near and offshore areas. This study shows the OW energy potential per location, as well as the trend of OW speed, which has changed over the past 40 years in the Mediterranean Sea.
... Mast measured wind data for at least three years is required for estimation of wind power potential. In-accurate data is main reason behind the error in estimations and prediction of energy production for wind projects due to which many projects may have the less estimated capacity by as much as 60 percent [8]. This problem increases the importance of reliable wind data which is only possible using wind masts. ...
The aim of the study is to evaluate reanalysis wind data with mast measured data at Hawks Bay, Karachi, in the coastal region of Pakistan. MERRA and MERRA-2 reanalysis datasets, assimilated by NASA global data assimilation system, are evaluated in this study. The comparison between wind data has been performed for 10 m, 50 m and 80 m heights using hourly and daily data. Statistical Analysis using correlation coefficient (R), mean bias error (MBE), standard deviation of errors (STDE) and root mean square error (RMSE) was used for comparison. MERRA-2 data shows better results for wind speed at 10 m and for wind direction at 80 m in terms of statistical parameters and correlation coefficient. R of wind speed for MERRA-2 at 10 m are 0.70 and 0.91 for hourly and daily data respectively whereas R of wind direction at 80 m are 0.66 and 0.76 for hourly and daily data respectively. The wind energy industry is in developing phases in Pakistan, the present work will contribute towards the exploration of wind energy potential of the southern region of the country.
... However, this equipment is very expensive and needs to be installed in a study area for more than one year to get enough data; on the other hand, high maintenance and repair costs are required [24,25]. Consequentially, it is very important to develop new methods that can help to identify suitable areas faster and economically. ...
... However, this equipment is very expensive and needs to be installed in a study area for more than one year to get enough data; on the other hand, high maintenance and repair costs are required [24,25]. Consequentially, it is very important to develop new methods that can help to identify suitable areas faster and economically. ...
The elaboration of a methodology for accurately assessing the potentialities of blue renewable energy sources is a key challenge among the current energy sustainability strategies all over the world. Consequentially, many researchers are currently working to improve the accuracy of marine renewable assessment methods. Nowadays, remote sensing (RSs) satellites are used to observe the environment in many fields and applications. These could also be used to identify regions of interest for future energy converter installations and to accurately identify areas with interesting potentials. Therefore, researchers can dramatically reduce the possibility of significant error. In this paper, a comprehensive SWOT (strengths, weaknesses, opportunities, and threats) analysis is elaborated to assess RS satellite potentialities for offshore wind (OW) estimation. Sicily and Sardinia-the two biggest Italian islands with the highest potential for offshore wind energy generation-were selected as pilot areas. Since there is a lack of measuring instruments, such as cup anemometers and buoys in these areas (mainly due to their high economic costs), an accurate analysis was carried out to assess the marine energy potential from offshore wind. Since there are only limited options for further expanding the measurement over large areas, the use of satellites makes it easier to overcome this limitation. Undoubtedly, with the advent of new technologies for measuring renewable energy sources (RESs), there could be a significant energy transition in this area that requires proper orientation of plans to examine the factors influencing these new technologies that can negatively affect most of the available potential. Satellite technology for identifying suitable areas of wind power plants could be a powerful tool that is constantly increasing in its applications but requires good planning to apply it in various projects. Proper planning is only possible with a better understanding of satellite capabilities and different methods for measuring available wind resources. To this end, a better understanding of interdisciplinary fields with the exchange of updated information between different sectors of development, such as universities and companies, will be most effective. In this context, by reviewing the available satellite technologies, the ability of this tool to measure the marine renewable energies (MREs) sector in large and small areas is considered. Secondly, an attempt is made to identify the strengths and weaknesses of using these types of tools and techniques that can help in various projects. Lastly, specific scenarios related to the application of such systems in existing and new developments are reviewed and discussed.
... There are a variety of methods for estimating the wind resources at a site, including the use of meteorological data [12][13][14][15][16], field measurements for measure-correlate-predict (MCP) methods [17][18][19][20] or Sound Detection and Ranging (SODAR) [21], and modeled resource data [11,22]. In order to appraise the available wind energy for power generation from micrometeorological data, Gunturu et al. [23] inspected the shape parameters for the Weibull velocity distribution of wind across the United States to identify the locations with high power densities; however, the Weibull model is merely an approximation of the wind speed, whose value is usually small, and thus the results of wind power density (WPD) cannot be accurate. ...
Various wind resource assessment (WRA) methods have been applied to explore the feasibility of installing wind turbines for urban wind energy harvest. Nevertheless, there are only limited computational fluid dynamics (CFD) studies available to consider WRA around high-rise buildings in realistic urbanized areas. This paper presents a numerical assessment of urban wind energy potential, specifically pursuing to overcome the limitations of former studies by addressing the following points: i) conducting a large-scale wind power estimation by employing the meticulous topography in realistic compact high-rise urban area; ii) validating CFD simulations with the on-site measurements in two seasons; iii) obtaining the annual mean wind speed, wind power density and turbulence intensity between the existing high-rise building features, including building geometry, roof geometry, presence or absence of upstream obstacles, arrangements of integrated building complex and parallel high-rise buildings; iv) investigating the local installation locations of wind turbines and the distances from rooftop sidewalls or lowest mounting heights above rooftops with high power densities and acceptable turbulence intensities for wind energy harvest. The results of this wind resource assessment suggest an effective strategy of turbine installation for implementing urban wind power potential in a realistic compact high-rise urban area.
... Effect of Weibull shape parameter on wind power density (P D ). Chang, 2011;Chaurasiya et al., 2018;Indhumathy et al., 2014;Khahro et al., 2014b;Khan and Tariq, 2018;Mirhosseini et al., 2011;Rehman et al., 2012Rehman et al., , 2020Safari and Gasore, 2010). ...
Continuous probability distributions have long been used to model the wind data. No single distribution can be declared accurate for all locations. Therefore, a comparison of different distributions before actual wind resource assessment should be carried out. Current work focuses on the application of three probability distributions, i.e. Weibull, Rayleigh, and lognormal for wind resource estimation at six sites along the coastal belt of Pakistan. Four years’ (2015–2018) wind data measured each 60-minutes at 50 m height for six locations were collected from Pakistan Meteorological Department. Comparison of these distributions was done based on coefficient of determination ( R ² ), root mean square error, and mean absolute percentage deviation. Comparison showed that Weibull distribution is the most accurate followed by lognormal and Rayleigh, respectively. Wind power density ( P D ) was evaluated and it was found that Karachi has the highest wind speed and P D as 5.82 m/s and 162.69 W/m ² , respectively, while Jiwani has the lowest wind speed and P D as 4.62 m/s and 76.76 W/m ² , respectively. Furthermore, feasibility of annual energy production (AEP) was determined using six turbines. It was found that Vestas V42 shows the worst performance while Bonus 1300/62 is the best with respect to annual energy production and Bonus 600/44 is the most economical. Finally, sensitivity analysis was carried out.
... The validity of this particular model is determined with respect to method used and scope of research. This study uses two-parameter Weibull distribution model to estimate wind potential at multiple locations and this model has been found to be valid when compared with previous historical data (Bilir et al., 2015a;Carta et al., 2009;Chang, 2011;Chaurasiya et al., 2017;Indhumathy et al., 2014;Khahro et al., 2014b;Khan and Tariq, 2018;Mirhosseini et al., 2011;Rehman et al., 2012Rehman et al., , 2020Safari and Gasore, 2010). ...
Current work focusses on the wind potential assessment in South Punjab. Eleven locations from South Punjab have been analyzed using two-parameter Weibull model (with Energy Pattern Factor Method to estimate Weibull parameters) and five years (2014–2018) hourly wind data measured at 50 m height and collected from Pakistan Meteorological Department. Techno-economic analysis of energy production using six different turbine models was carried out with the purpose of presenting a clear picture about the importance of turbine selection at particular location. The analysis showed that Rahim Yar Khan carries the highest wind speed, highest wind power density, and wind energy density with values 4.40 ms ⁻¹ , 77.2 W/m ² and 677.76 kWh/m ² /year, respectively. On the other extreme, Bahawalnagar observes the least wind speed i.e. 3.60 ms ⁻¹ while Layyah observes the minimum wind power density and wind energy density as 38.96 W/m ² and 352.24 kWh/m ² /year, respectively. According to National Renewable Energy Laboratory standards, wind potential ranging from 0 to 200 W/m ² is considered poor. Economic assessment was carried out to find feasibility of the location for energy harvesting. Finally, Polar diagrams drawn to show the optimum wind blowing directions shows that optimum wind direction in the region is southwest.
... In addition, the mast is equipped with lightning protection equipment to maximize the service life of the instruments. In wind field measurements, cup-anemometer is usually selected as the standard acquisition instrument for its simple installation and high accuracy (Khan and Tariq, 2018;Kristensen, 1999Kristensen, , 1998. Therefore, a 3-cup anemometer and a direction sensor are equipped at the top of the mast. ...
As a clean and highly valuable renewable energy, wind energy has gradually become an important
branch of energy technology. By means of measurement methods, the wind characteristics, energy
applications for distributed wind energy source (DWES) in six sites in Henduan Mountains and
economic evaluation are investigated. According to the results, the wind characteristics including wind
speed and wind direction in mountainous regions are affected significant by topography. Wind speed is
season-dependent, while the mean wind direction is not. The maximum wind speed occurs in spring,
the minimum wind speed occurs in summer. As for extreme value distribution, the wind data in
mountainous areas are more in line with Frechet distribution type. By using Weibull distribution
function, Weibull parameters are calculated and energy potential are estimated with five methods.
Estimation methods suitable for coastal areas can also be used for energy assessment in mountain
environments. The maximum wind power density is over 200 W/m2
, occurred in Zanli site, while
the minimum value is less than 10 W/m2
in Yimen-A. Similar to mean wind characteristics, wind
power density shows strong seasonality, with the maximum value in spring and the lowest value
in summer. In addition, power generation facilities should be built in valleys or on the top of the
mountain, and should not be built in the flat land surrounded by mountains. And the total cost of
1kWh wind-generated electricity is 0.305 CNY/kWh and 0.406 CNY/kWh with different type of wind
turbine.
... The device generates a voltage related to wind speed or electronically records the number of revolutions per unit time. Generally, anemometers are associated with wind vanes to detect the wind direction [40,41]. Other types of anemometers include ultrasonic anemometers that detect changes in the phase of a sound, and laser anemometers that use coherently scattered light from air. ...
To sustain the clean environment by reducing fossil fuels based energies and increasing the integration of renewable-based energy sources i.e., wind and solar power have become the national policy for many countries. The increasing demand for renewable energy sources, such as wind has created interest in the economic and technical issues related to the integration into the power grids. Having intermittent nature, wind generation forecasting is a crucial aspect of ensuring the optimum grid control and design power plant. Accurate forecasting provides essential information to power grid operators and system designers in generating an optimal wind power plant and to balance the power supply and demand. In this paper, we present an extensive review of wind forecasting methods and the prolific of Artificial Neural Network (ANN) in this regard. The instrument used to measure the wind assimilation is analyzed and discussed, specifically, studies that were published from May 1st, 2014 to May 1st, 2018. The results of the review demonstrate the increased application of ANN into wind power generation forecasting. Considering the component limitation of other systems, the trend of deploying the ANN and its hybrid systems are attractive than other individual methods. The review further revealed that high forecasting accuracy could be achieved through proper handling and calibration of the wind-forecasting instrument and method.
... Mast measured wind data for at least three years is required for estimation of wind power potential. In-accurate data is main reason behind the error in estimations and prediction of energy production for wind projects due to which many projects may have the less estimated capacity by as much as 60 percent [8]. This problem increases the importance of reliable wind data which is only possible using wind masts. ...
The aim of the study is to evaluate reanalysis wind data with mast measured data at Hawks Bay, Karachi, in the coastal region of Pakistan. MERRA and MERRA-2 reanalysis datasets, assimilated by NASA global data assimilation system, are evaluated in this study. The comparison between wind data has been performed for 10 m, 50 m and 80 m heights using hourly and daily data. Statistical Analysis using correlation coefficient (R), mean bias error (MBE), standard deviation of errors (STDE) and root mean square error (RMSE) was used for comparison. MERRA-2 data shows better results for wind speed at 10 m and for wind direction at 80 m in terms of statistical parameters and correlation coefficient. R of wind speed for MERRA-2 at 10 m are 0.70 and 0.91 for hourly and daily data respectively whereas R of wind direction at 80 m are 0.66 and 0.76 for hourly and daily data respectively. The wind energy industry is in developing phases in Pakistan, the present work will contribute towards the exploration of wind energy potential of the southern region of the country.
... There are many different methods and techniques for wind assessment, analysis, detection and reporting such as, cup anemometers, SOnic Detection And Ranging (SODAR) [28], Light Detection And Ranging (LiDAR) [29], Synthetic Aperture Radar (SAR) Satellite data using Geophysical Model Functions (GMFs), numerical simulation [30] and reanalysis dataset (ECMWF, ERA5 [31], NARR and MERRA [32]). The nearshore and offshore wind field retrieval method has been developed recently based on the data and dataset from satellite images and techniques of image processing. ...
Mediterranean islands have the advantage of favourable climatic conditions to use different marine renewable energy sources. Remote sensing can provide data to determine wind energy production potential and observational activity to identify, assess and detect suitable points in large marine areas. In this paper, a new combined model has been developed to integrate wind speed assessment, mapping and forecasting using Sentinel 1 satellite data through images processing and Adaptive Neuro-Fuzzy Inference System and the Bat algorithm. Synthetic Aperture Radar (SAR) satellite images from the Sentinel 1 satellite have been used in order to detect offshore and nearshore wind potential. Particularly, Sentinel 1 images have been analysed by means of the SNAP software. Then, to extract data about wind speed and direction, a GIS software for mapping the wind climate has been used. This new methodology has been applied to the North-Central coasts of Sardinia Island and then focused on six main small islands of La Maddalena archipelago. Furthermore, ten Hot Spots (HSs) have been identified as interesting because of their high-energy potential and the possibility to be considered as sites for future implementation of Wind Turbine Generators (WTGs). Finally, the ten identified HS have been used as input data to train and test the proposed forecast model.
... Existing approaches for wind resource assessment may be classified into two main categories: measured model (e.g. measured meteorological data [2], LIDAR method [3] and SODAR technology [4], etc.) and numerical model. Due to the limited stations and sensors, the geo-statistical methods should be utilized to obtain the wind potential of the entire region, which may neglect the micro-scale effects [5]. ...
Wind resource assessment and wind farm micro-siting over complex terrain are essential for wind power management and wind farm operation. A coupled approach is presented for wind resource assessment over a complex topography in Changsha, China, and an improved Genetic Algorithm (GA) is introduced for optimization of wind turbines micro-siting. The Computational Fluid Dynamics (CFD) with Realizable k-ε turbulence closure is adopted to simulate the atmospheric boundary layer flow over the complex terrain, and the results are validated by the wind tunnel tests. Long-term on-site measurements from a meteorological station are combined with the CFD results to evaluate the wind energy potential over the complex terrain. A semi-analytical approach is proposed for prediction of yearly wind power generation at the turbine site, and the Jensen-Katic model is utilized in consideration of the wake effects. The improved GA is presented based on the wind resource map. The schemes with different grid discretization are studied. The results showed that the proposed approach is effective for wind resource assessment and wind turbines micro-siting.
... With the rapid growth of modern technologies, onsite sensing systems for wind velocity fields also play an increasingly important role. Sodar-based [4] and Lidar-based [5] wind profiling are two representative remote sensing techniques. However, there are still some limitations that need to be overcome and more techniques to be developed to achieve reliable wind forecasts for commercial use. ...
In a real wind farm,complex airflow conditions result in complexities of wind speed and direction,with possibly significant intermittency and fluctuations.This problem can be alleviated if the wind speed distribution over a wind farm is known in advance.In this paper,a new method is proposed for real-time wind field reconstruction for large areas, based on the idea of a “virtual time”, i.e., a time span needed for an object to travel across a certain distance.The distribution of wind speed and direction can be acquired prior to its occurrence in the wind farm with refined spatial resolutions.A procedure is also developed to stabilize the solution process,and this stabilization leads to an optimal allocation of the wind speed sensors;this allocation is necessary for the efficient use of a limited number of sensors.The reconstruction algorithm has been substantially studied,and a mathematical quantity was correlated to the reconstruction error.This correlation enables us to obtain good reconstruction results by using the Greedy algorithm we proposed in this study.Simulation and experimental results demonstrated the strong feasibility of successful reconstructions by our proposed algorithm.Moreover,the sensor optimization scheme not only reduces the error significantly but also improves the efficiency of sensor applications;this improvement should apply to a wide range of conditions.
... In this simulation we use the MPPT control and FOC command strategies [19]. To improve system efficiency, turbine speed is adjusted as a function of wind speed to maximize output power. ...
... In the field of the evaluation of the wind potential, the scientific literature proposes recent studies on different areas of the globe; among them: the study of wind resource assessment offshore the Atlantic Iberian coast with the WRF model in Spain [7]; Use of spatio-temporal calibrated wind shear model to improve accuracy of wind resource assessment in the USA [8]; 3D statistical mapping of Germany 's wind resource using WSWS [9]; Wind resource assessment and economics of electric generation at four locations in Sinai Peninsula, Egypt [10]; Multi criteria decision analysis for offshore wind energy potential in Egypt [11]; Wind energy characteristics and wind park installation in Shark El-Ouinat, Egypt [12]; Offshore wind resource assessment and wind power plant optimization in the Gulf of Thailand [13]; Offshore wind resource assessment of Persian Gulf using uncertainty analysis and GIS [14]; Wind resource assessment using SODAR and meteorological mast -A case study of Pakistan [15]; Wind resource potential assessment using a long term tower measurement approach: A case study of Beijing in China [16]; Validation of wind resource in 14 locations of Nepal [17]; Statistical learning approach for wind resource assessment in United Kingdom [18]; Wind resource assessment of Northern Cyprus in Turkey [19]; A new methodology for urban wind resource assessment in Portugal [20] et. The wind resource assessment around coastal areas of the Korean peninsula [21][22]. ...
The aim of this paper is to evaluate the wind potential in southwestern Algeria, according to months, seasons and entire years and contribute to the updating of the wind map in Algeria at 10 m from the ground, using hourly data for wind collected over a period of more than 30 years. The wind data analysis was done using the Weibull function at 10 m from the ground. Then we did the statistical analysis, which includes several fundamental properties, such as Weibull parameters, mean wind speed and average power density. The results give the city of Tindouf as the one with the highest annual average speed with 5.39 m/s at 10 m from the ground. As for the temporal study, it gives that spring is the best windy period.
... There are various methods found in literature for wind assessment. A comprehensive discussion on site assessment is conducted by using the two kinds of instruments, ie, light detection and ranging (LiDAR) and sound detection and ranging (SODAR) in Khan and Tariq, 24 whereas a thorough discussion on wind turbines installation and their selection is provided in Baloch et al 25 and Hussain Baloch et al. 26 However, a discussion on installation of Multi terminal DC (MTDC) systems for offshore wind farms and the methods for handling the faults is described in Nadeem et al. 27 Moreover, to address the estimated errors in wind output power and electricity requirements, a two-stage stochastic mixed integer coninc programming (MICP) model is proposed and to validate through a detailed analysis carried out over various case studies of a 34-node distribution system under different conditions, while to show its potential and effectiveness a 135-node system with two substations is used in Home-Ortiz et al. 28 The wind-based renewable energy generation systems have recently received the attention of the researchers for 1the assimilation of demand response and energy storage systems in the joint distribution and generation expansion planning for isolated systems. 29 The comprehensive modeling based on stochastic control for location, type, and size of new energy generation farms, storage units, and the distribution assets to be installed, reinforced, or replaced are proposed and discussed in the literature . ...
Demand response is considered to be a realistic and comparatively inexpensive solution aimed at increasing the penetration of renewable generations into the bulk electricity systems. The work in this paper highlights the demand response in conjunction with the optimal capacity of installed wind energy resources allocation. Authors proposed a total annual system cost model to minimize the cost of allocating wind power generating assets. This model contains capacity expansion, production, uncertainty, wind variability, emissions, and elasticity in demand to find out cost per hour to deliver electricity. A large‐scale electric grid (25 GW) is used to apply this model. Authors discovered that demand response based on interhourly system is not as much helpful as demand response grounded on intrahourly system. According to results, 32% wind generation share will provide the least cost. It is also worth noting that optimal amount of wind generation is much sensitive to installation cost as well as carbon tax. Optimal wind planning model in conjunction with demand response is presented. Adding wind energy resources can reduce uncertainty costs more than production costs. Interhourly demand response is not as useful as intrahourly demand response. Optimal wind resource level is as sensitive to carbon tax as to first cost.
... In addition to the potential of onshore wind energy, Pakistan also has favorable offshore wind power resources, and its utilization can achieve a considerable share of electricity generation. Moreover, harnessing offshore sources can combat the air pollution in Pakistan [30]. Hydrogen is found to be a significant and most abundant chemical element in the world, constituting about 75% of the elemental mass of the earth [31]. ...
In this study, we developed a new hybrid mathematical model that combines wind-speed range with the log law to derive the wind energy potential for wind-generated hydrogen production in Pakistan. In addition, we electrolyzed wind-generated power in order to assess the generation capacity of wind-generated renewable hydrogen. The advantage of the Weibull model is that it more accurately reflects power generation potential (i.e., the capacity factor). When applied to selected sites, we have found commercially viable hydrogen production capacity in all locations. All sites considered had the potential to produce an excess amount of wind-generated renewable hydrogen. If the total national capacity of wind-generated was used, Pakistan could conceivably produce 51,917,000.39 kg per day of renewable hydrogen. Based on our results, we suggest that cars and other forms of transport could be fueled with hydrogen to conserve oil and gas resources, which can reduce the energy shortfall and contribute to the fight against climate change and global warming. Also, hydrogen could be used to supplement urban energy needs (e.g., for Sindh province Pakistan), again reducing energy shortage effects and supporting green city programs. View Full-Text
Keywords: mathematical programming; wind power; renewable energy; renewable hydrogen
... In recent years, it has even been possible to develop a resource assessment study using modern anemometers such as LiDAR (Doppler-effect-type laser-based anemometer) obtaining wind data at different heights at a given location [10]. SODAR (sonic detection and ranging) and meteorological masts can also be used [11], by means of on-site anemometry observation [12], and single anemometers can be used in complex terrain for resource assessment purposes [13]. ...
A novel multi-criteria methodology for the identification of defective anemometers is shown in this paper with a benchmarking approach: it is called MIDAS: multi-technique identification of defective anemometers. The identification of wrong wind data as provided by malfunctioning devices is very important, because the actual power curve of a wind turbine is conditioned by the quality of its anemometer measurements. Here, we present a novel method applied for the first time to anemometers' data based on the kernel probability density function and the recent reanalysis ERA5. This estimation improves classical unidimensional methods such as the Kolmogorov-Smirnov test, and the use of the global ERA5's wind data as the first benchmarking reference establishes a general method that can be used anywhere. Therefore, adopting ERA5 as the reference, this method is applied bi-dimensionally for the zonal and meridional components of wind, thus checking both components at the same time. This technique allows the identification of defective anemometers, as well as clear identification of the group of anemometers that works properly. After that, other verification techniques were used versus the faultless anemometers (Taylor diagrams, running correlation and RMSE, and principal component analysis), and coherent results were obtained for all statistical techniques with respect to the multidimensional method. The developed methodology combines the use of this set of techniques and was able to identify the defective anemometers in a wind farm with 10 anemometers located in Northern Europe in a terrain with forests and woodlands. Nevertheless, this methodology is general-purpose and not site-dependent, and in the future, its performance will be studied in other types of terrain and wind farms.
... Several studies [1]- [29] characterizing and analyzing the technical and economical feasibility of wind-farms use the operating environment data without considering their quality. Rodrigo et al. [30] and Khan and Tariq [31] presented an approach to evaluate the data collected using LIDARS (LIght Detection And Ranging) and SODAR (Sonic Detection And Ranging) sensors. Astolfi et al. ...
the aim of this paper is to analyze the quality of the operating and environment data collected on a site of wind-turbines power production system. The data relate to characteristic parameters of the meteorological conditions (wind-speed, wind-direction, temperature, …) and the facility operating conditions (rotation speed of power generator, bearing temperature, voltage and power delivered, …). The data were collected from January 1st to December 31, 2016 (one year) and were measured every ten minutes in the region of Nouakchott-Mauritania. We analyzed correlations between wind-speed measurements at different heights (10 m, 30 m and 90 m). The variations of the wind-speed and the turbulence indices as a function of direction were estimated. The analysis showed a strong influence of interactions between the towers and the wind-speed on the quality of the measurements. For instance, the turbulence index and the mean wind-speed can range from 0.15 to 0.45 and from 2.5 to 6m/s in the direction influenced by the tower.
This work presents a new methodology to evaluate the influence of wind speed data corrections in the fit of the Weibull distribution. Corrections are made for data measured by Sonic Detection and Ranging (SODAR) and MERRA-2 base data. SODAR data are corrected through Turbulence Intensity (TI). The MERRA-2 data correction uses National Institute of Meteorology (INMET) weather station data to find a local scale factor. The results showed that the corrected data present a better fit in the Weibull distribution and evidence that corrections are necessary when wind speed averages are used to evaluate the wind resource. Wind speed data were also applied to simulate the energy production by a commercial turbine to demonstrate the contrast in the total energy generated. The new methodology shows that IT must be considered in the evaluation of wind resources.
Wind energy is a mature and cost-effective solution to greenhouse gas emission reduction and climate change mitigation. Wind resource assessment is the most pivotal activity before wind farm development since it determines the bankability of the wind project. Based on the joint use of a Doppler wind sodar (sonic detection and ranging) system and a microwave radiometer, this paper investigates the wind and thermal characteristics and wind energy resources in a coastal region of Hong Kong. First, wind climatology and variability, as well as their correlation with large-scale and local meteorological and geographical conditions, are analyzed and discussed. Then, statistical distributions of wind speed are evaluated, and the goodness-of-fit of the Weibull, Kappa, Wakeby, Normal-Weibull mixture, and Weibull-Weibull mixture distributions is assessed. Subsequently, the probability distribution and variation of atmospheric stability are examined, and their effects on vertical wind shear, wind profile, and wind speed at turbine hub height are revealed. Lastly, the spatiotemporal variation of wind power density is investigated with attention paid to air density. The results presented in this paper are expected to offer insights into coastal wind and thermal characteristics, provide references for vertical extrapolation of wind speed and wind turbine load evaluation, and facilitate wind farm development in coastal regions.
This study aims to optimize the design parameters of a vertical axis wind turbine using design of experiments (DOE). Response surface methodology combined with desirability optimization was used to optimize multiple parameters such as the chord length, number of blades, aspect ratio, and pitch angle. The range of contributing parameters was selected using one factor at a time (OFAT) approach, and the performance parameters were evaluated by applying the double multiple streamtube theory. Datasets retrieved from the Q-Blade open-source software were employed in the DOE to determine the optimal configurations. Based on response surface investigation, a quadratic model was established and the accuracy of the model was determined by applying analysis of variance, goodness of fit, normal plot of residuals, and R-squared values. The optimized chord length, number of blades, pitch angle, and aspect ratio were 0.546 m, 03, −2.82°, and 0.808, respectively. The maximum power coefficient of 0.45 was obtained at a tip speed ratio of 3 from the optimized design parameters. The analysis revealed an increase of approximately 8.43% in the maximum power coefficient of the proposed wind turbine. A 3D unsteady computational fluid dynamics model along with Reynolds-Averaged Navier-Stokes equations were utilized to verify the obtained results, and a maximum difference of less than 1.5% was found. A standard H-rotor Darrieus configuration obtained from the OFAT approach was also tested at different wind speeds for comparison. The analysis revealed that when the wind speed was less than 3.85 m/sec, the standard Darrieus produced no power; however, the self-starting speed of the optimized VAWT was as low as 3.22 m/sec. This novel design methodology provides guidelines for obtaining optimum design configurations and can help in achieving high-fidelity analysis in the early design phase.
Cutting down the reliance on fossil fuels and utilization of wind energy as green energy source requires detailed resource exploration using some probability distribution. In contrast to literature methods which are based on first and second moment of Weibull Probability Distribution (WPD) for its parametric estimation, the new method proposed in this study (called Method of Four Moments Mixture, MFMM) combines the effect of first four moments of WPD. This model is based on the squared deviation (deviation of sample from population) of first four moments; minimization of which using Nelder-Mead algorithm estimates parameters of WPD. In order to assess its comprehensive effectiveness, this method has been validated using large dataset i.e. five years wind data measured at 50 m height for thirty-six stations (in Pakistan) for parametric estimation and it has been compared with six past methods using MAPE, RMSE and R². To rank all seven methods, Global Performance Indicator (GPI) was evaluated and it was found that MFMM is the best method for all stations. Therefore, it can be effectively used in wind resource assessment of various geographical regions in the world.
Pakistan is currently experiencing an acute energy shortage and urgently needs new sources of affordable energy that could ease the misery of the starved masses of energy. At present, the government is increasing not only conventional energy sources such as hydel and thermals, but is also focusing on the vast potential of renewable energy sources such as solar, wind, biogas, waste-to-energy, etc. Renewable sources of energy are more favorable these days because these are environment friendly with zero emissions as compared to conventional energy sources. Wind energy is most rapidly growing, among several renewable energy sources, worldwide. Wind energy, with its sustainability and low environmental impact, is highly prominent. The prime objective of this paper is to analyze and evaluate the wind energy characteristics and wind power potential at Keti Bandar. Time series wind speed data for the study site, measured at each 10-min interval at the height of 85m, 60m, 30m and 10m is available for the period November 2009 to October 2010. The data is interpolated for the height of 80m for the discussion in study. Weibull Distribution (WD) function is used to determine wind power potential for the investigated site and the distribution parameters shape (k) and scale (c) are estimated by using six numerical methods Maximum Likelihood Method (MLM), Modified Maximum Likelihood Method (MMLM), Empirical Method (EM), Graphical Method (GM), Method of Moments (MoM) and Energy Pattern Factor Method (EPFM). Wind power densities and frequency distributions of wind speed at the heights of 80m, 60m and 30m along with estimated wind power expected to be generated through commercial wind turbines is calculated. Analysis and comparison of six numerical methods is presented in this paper to determine the Weibull scale and shape parameters for the available wind data. The yearly mean wind speed of the considered site is 6.874 m/s and has wind power density of 198.965 W/m2 at 80m height with high power density during summers (highest in May with average wind speed 9.070 m/s and power density 457.037 W/m2) . Economic evaluation, to exemplify feasibility of installing wind turbines, is also done. Thus, the candidate site is recommended for some small stand-alone systems.
Wind energy is gaining popularity, especially across the countries with strong and continuous wind currents. Pakistan is bestowed with multiple wind corridors with prospective energy extraction, mainly concentrated along the coastline. This work aims to analyze the effectiveness and feasibility of wind energy potential in Pakistan coastline by choosing four unique zones (Karachi, Ormara, Pasni, and Gawadar) through analysis and demonstration for a 50 MW wind farm. Four years of seasonal data is used for the selected zones, reflecting the wind effectiveness in wind speed, wind density, and wind directions. Computer-based predictive models and artificial neural networks are also implemented to forecast the wind effectiveness, primarily based on the observed wind seasonal data. The wind farm’s feasibility is proposed through a comparative evaluation for various turbine designs considering both geographical,
installation, operational and financial factors. The factors of energy output, economic feasibility, environmental
impact, and fuel-saving are analyzed for multiple locations and turbine designs. Critical observations,
data, and findings are presented and discussed in detail for all zones. Zone 1 has a highest capacity
factor of 46% followed by 40.4% (Zone 2), 29.3% (Zone 3), 37.5% (Zone 4). The study revealed that Karachi
is the best-suited location for a 50 MW wind farm with the highest wind speed and the lowest variation
in wind direction annually. It also represented the highest internal rate of return, benefit-to-cost ratio,
and annual saving with a minimum payback period (4.5–7.2 years) for various commercially available
turbine designs.
Wind energy is gaining popularity, especially across the countries with strong and continuous wind currents.
Pakistan is bestowed with multiple wind corridors with prospective energy extraction, mainly concentrated
along the coastline. This work aims to analyze the effectiveness and feasibility of wind energy
potential in Pakistan coastline by choosing four unique zones (Karachi, Ormara, Pasni, and Gawadar)
through analysis and demonstration for a 50 MW wind farm. Four years of seasonal data is used for
the selected zones, reflecting the wind effectiveness in wind speed, wind density, and wind directions.
Computer-based predictive models and artificial neural networks are also implemented to forecast the
wind effectiveness, primarily based on the observed wind seasonal data. The wind farm’s feasibility is
proposed through a comparative evaluation for various turbine designs considering both geographical,
installation, operational and financial factors. The factors of energy output, economic feasibility, environmental
impact, and fuel-saving are analyzed for multiple locations and turbine designs. Critical observations,
data, and findings are presented and discussed in detail for all zones. Zone 1 has a highest capacity
factor of 46% followed by 40.4% (Zone 2), 29.3% (Zone 3), 37.5% (Zone 4). The study revealed that Karachi
is the best-suited location for a 50 MW wind farm with the highest wind speed and the lowest variation
in wind direction annually. It also represented the highest internal rate of return, benefit-to-cost ratio,
and annual saving with a minimum payback period (4.5–7.2 years) for various commercially available
turbine designs.
Wind energy is gaining popularity, especially across the countries with strong and continuous wind currents. Pakistan is bestowed with multiple wind corridors with prospective energy extraction, mainly concentrated along the coastline. This work aims to analyze the effectiveness and feasibility of wind energy potential in Pakistan coastline by choosing four unique zones (Karachi, Ormara, Pasni, and Gawadar) through analysis and demonstration for a 50 MW wind farm. Four years of seasonal data is used for the selected zones, reflecting the wind effectiveness in wind speed, wind density, and wind directions. Computer-based predictive models and artificial neural networks are also implemented to forecast the wind effectiveness, primarily based on the observed wind seasonal data. The wind farm's feasibility is proposed through a comparative evaluation for various turbine designs considering both geographical, installation, operational and financial factors. The factors of energy output, economic feasibility, environmental impact, and fuel-saving are analyzed for multiple locations and turbine designs. Critical observations , data, and findings are presented and discussed in detail for all zones. Zone 1 has a highest capacity factor of 46% followed by 40.4% (Zone 2), 29.3% (Zone 3), 37.5% (Zone 4). The study revealed that Karachi is the best-suited location for a 50 MW wind farm with the highest wind speed and the lowest variation in wind direction annually. It also represented the highest internal rate of return, benefit-to-cost ratio, and annual saving with a minimum payback period (4.5-7.2 years) for various commercially available turbine designs. Ó 2021 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Ain Shams University. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/ by-nc-nd/4.0/).
Energy security and environmental measurements are incomplete without renewable energy therefore there is a dire need to explore new energy sources. Therefore, the aim of this study is to measure the wind power potential to generate the renewable hydrogen including its production and supply cost. We used first order eneginnering model and net present value to measure the levelized cost of wind generated renewable hydrogen by using the data source of Pakistan metorological department and State bank of Paksitan. Results shows that the use of surplus wind and renewable hydoregn energy for green economic production is suggested as an innovative project option for large-scale hydrogen use. The key annual running expenses for hydrogen are electricity and storage cost, which have a major impact on the costs of renwable hydrogen. Also, the results indicates that project has the potential to cut CO 2 pollution by 139 million metric tons and raise revenue for wind power plants by 2998.52 million dollars. The renewable electrolyzer plants avoided CO 2 at a rate of 24.9–36.9 $/ton under baseload service, relative to 44.3 $/ton for the benchmark. However, in the more practical mid-load situation, these plants have a significant benefit. Further, the wind generated renewable hydrogen deliver a 6–11% larger than annual rate of return than the standard CO 2 catch plant due to their capacity to remain running and supply hydrogen to the consumer through periods of plentiful wind and heat. Also, the measured levelized output cost of hydrogen (LCOH) was 6.22$/kgH 2 and for the PEC system, it was 8.43 $/kgH 2 . Finally, its mutually agreed consensus of the environmental scientist that integration of renewable energy is the way forward to increase energy security and environmental performance by ensuring uninterrupted clean and green energy. Further, this application has the potential to address Pakistan’s urgent issues of large-scale surplus wind and solar-generated energy, as well as rising enegry demand.
This book comprises the select proceedings of the International Conference on Future Learning Aspects of Mechanical Engineering (FLAME) 2020. This volume focuses on several emerging interdisciplinary areas involving mechanical engineering. Some of the topics covered include automobile engineering, mechatronics, applied mechanics, structural mechanics, hydraulic mechanics, human vibration, biomechanics, biomedical Instrumentation, ergonomics, biodynamic modeling, nuclear engineering, and agriculture engineering. The contents of this book will be useful for students, researchers as well as professionals interested in interdisciplinary topics of mechanical engineering.
Uttarakhand, a northern state of India, has a total area of 53,483 km2 of which 86% are hilly region and 65% are covered by forest. Present work aims Wind power potential assessment of different parts of Uttarakhand. Wind speed pattern, Weibull distribution is used to analyze the wind potential of different locations having different geographical conditions. Power produce by wind turbine is calculated for these locations. The average wind speed (Mean) observed is 5–6 m/s. in these locations. Wind speed observed after observation is enough for wind power production.
باد پدیده¬ای نامنظم است که سبب برخی از پدیده¬های جوی می¬شود و تغییراتی شدید و ناگهانی دارد. اثرات مختلفی که تندبادها بر پرواز هواپیماها دارند در کنار خطرات ناشی از توفان برای مناطق مسکونی و صنعتی و کشاورزی، همچنین اثر گذاری مستقیم باد بر بسیاری از صنایع از جمله نیروگاه¬های بادی، ضرورت بررسی بیشتر عنصر باد را ایجاب می¬کند. ابزارهای اندازه¬گیری باد از جمله ابزار سنجش در محل، مانند بادسنج¬ و سنجش از دور مانند رادار، هر یک با قابلیت¬ها و الزامات خاص خود، در سنجش باد بکار گرفته می¬شوند. روش¬های متنوعی نیز برای کشف پدیده¬های مرتبط و پیش¬بینی این پدیده¬ها در کنار پیش¬بینی کمّی سرعت و جهت باد ابداع شده و مورد استفاده قرار گرفته¬اند. این مقاله در کنار گذری بر مفاهیم مرتبط نظیر تلاطم و چینش باد، ابزارهای سنجش در محل و سنجش از دور سرعت و جهت باد را بررسی کرده و چارچوب¬های نوین اندازه-گیری سرعت و جهت باد، شامل روش¬های هوشمند و مبتنی بر اینترنت اشیا که موجب تحولی در امر داده¬برداری و دریافت و نمایش داده¬ها شده است را معرفی و مقایسه¬ای بین روش¬های پیش¬بینی باد ارائه می¬کند. همچنین در این مقاله مقایسه¬ای بین روش سنجش در محل (استفاده از داده¬های باد اندازه¬گیری شده توسط رادیوسوند) و روش سنجش از راه دور (داده¬های VVP و CAPPI تولید شده توسط رادار داپلر باند S در اهواز) صورت گرفته است که نتایج نشان می¬دهد که در ارتفاعات بالا این دو مقدار .به هم نزدیک شده و میزان اختلاف به حداقل می¬رسد
This paper aims to present a detailed analysis of the performance of a wind-farm using the wind turbine power measurement standard IEC61400-12-1 (2017). Ten minutes averaged wind data are obtained from LIDAR over the period of twelve months and it is compared with the 38 years’ data from weather station with the objective of determining the wind resources at the wind-farm. The performance of one of the wind turbines located in the wind-farm is assessed by comparing the wind power potential of the wind turbine with its actual power production. Our analysis shows that the wind farm under study is rated as ‘good’ in terms of wind power production and has wind power density of 479 W/m2. The annual wind-farm’s income is estimated based on the real-data collected from the wind turbines. The effect of price of electricity and the spot prices of Norwegian-Swedish green certificate on the income will be illustrated by means of a Monte-Carlo Simulation (MCS) approach. Our study provides a different perspective of wind resource evaluation by analyzing LIDAR measurements using Windographer and combines it with the lesser explored effects of price components on the income using statistical tools.
A GIS-based Decision Support System has been developed within the OCEANLIDER project to find optimal placement for green energy generation from oceanic energy. The DSS performs Multi-Criteria Evaluation, MCE, to help in the decision making. The scenario is defined as a combination of the device (power generation from wave or sea current energy) and its geographical location. The criteria used in the decision are physical constraints, together with operational, resource-related, and environmental constraints. Each criterion is computed using both Boolean and fuzzy values, and they can be combined in multiple ways (fuzzy-and, fuzzy-or, weighted linear combination). Finally, the MCE is done using Ordered Weighted Average to allow for multiple actors, multiple risk policies.
Many wind energy projects report poor performance as low as 60% of the predicted performance. The reason for this is poor resource assessment and the use of new untested technologies and systems in remote locations. Predictions about the potential of an area for wind energy projects (through simulated models) may vary from the actual potential of the area. Hence, introducing accurate site assessment techniques will lead to accurate predictions of energy production from a particular area. We solve this problem by installing a Wireless Sensor Network (WSN) to periodically analyze the data from anemometers installed in that area. After comparative analysis of the acquired data, the anemometers transmit their readings through a WSN to the sink node for analysis. The sink node uses an iterative algorithm which sequentially detects any faulty anemometer and passes the details of the fault to the central system or main station. We apply the proposed technique in simulation as well as in practical implementation and study its accuracy by comparing the simulation results with experimental results to analyze the variation in the results obtained from both simulation model and implemented model. Simulation results show that the algorithm indicates faulty anemometers with high accuracy and low false alarm rate when as many as 25% of the anemometers become faulty. Experimental analysis shows that anemometers incorporating this solution are better assessed and performance level of implemented projects is increased above 86% of the simulated models.
A new ground-based wind profiling technology-a scanned bistatic sodar-is described. The motivation for this design is to obtain a "mastlike" wind vector profile in a single atmospheric column extending from the ground to heights of more than 200 m. The need for this columnar profiling arises from difficulties experienced by all existing lidars and sodars in the presence of nonhorizontally uniform wind fields, such as found generically in complex terrain. Other advantages are described, including improved signal strength from turbulent velocity fluctuations, improved data availability in neutral atmospheric temperature profiles, improved rejection of rain echoes, and improved rejection of echoes from fixed (nonatmospheric) objects. Initial brief field tests indicate that the scattered intensity profile agrees with theoretical expectations, and bistatic sodar winds are consistent with winds from standard mast-mounted instruments.
We describe briefly some of the challenges met by the designers of the foundation systems for offshore wind energy developments. Although some experience from the offshore oil and gas industry proves valuable, the size and nature of typical wind turbines means that the loadings on the foundations are quite different from those encountered previously offshore. The most economical solutions are also likely to differ from those conventionally used offshore. We highlight the possibilities of a novel form of foundation: the suction caisson.
Detailed knowledge of the wind resource is necessary in the developmental and operational stages of a wind farm site. As wind turbines continue to grow in size, masts for mounting cup anemometers-the accepted standard for resource assessment-have necessarily become much taller, and much more expensive. This limitation has driven the commercialization of two remote sensing (RS) tools for the wind energy industry: The LIDAR and the SODAR, Doppler effect instruments using light and sound, respectively. They are ground-based and can work over hundreds of meters, sufficient for the tallest turbines in, or planned for, production. This study compares wind measurements from two commercial RS instruments against an instrumented mast, in upland (semi-complex) terrain typical of where many wind farms are now being installed worldwide. With appropriate filtering, regression analyses suggest a good correlation between the RS instruments and mast instruments: The RS instruments generally recorded lower wind speeds than the cup anemometers, with the LIDAR more accurate and the SODAR more precise.
An autonomous Doppler sodar wind profiling system has been designed, built, tested, and then deployed for 2 years at a remote site in Coats Land, Antarctica. The system is designed around a commercially available phased-array sodar (a Scintec flat-array sodar, FAS64) and powered from five modular power system units. Each power unit comprises two batteries, two photovoltaic solar panels, and two vertical axis wind generators, plus charging control and isolation circuitry. The sodar's main processing unit is located at the antenna, but is controlled from a manned research station 50 km distant, in real time, by a line-of-sight UHF radio link. Data from an integral automatic weather station (AWS) are also transmitted over the radio link, allowing meteorologically informed decisions on whether or not to operate the Doppler sodar. Over the 2-yr experiment dozens of sounding episodes, lasting from a few hours to a few days, were obtained. Successful soundings were obtained in temperatures down to -33 degrees C, and wind speeds up to 12 in s(-1). In general, the wind data quality was good, but the range was disappointing, probably as a result of the strongly stable atmospheric conditions that were experienced. The wind profiling system that is described has been used to obtain the first remote wintertime observations of katabatic winds over the Antarctic continent.
Field studies conducted at Owens Lake, California, provide direct measurements of sand flux on sand sheets with zero to 20 per cent cover of salt grass. Results from 12 different sand transport events show that aerodynamic roughness length and threshold wind shear velocity increase with vegetation cover as measured by vertically projected cover and roughness density (lambda). This results in a negative exponential decrease in sediment flux with increasing vegetation cover such that sand transport is effectively eliminated when the vertically projected cover of salt grass is greater than 15 per cent. A general empirical model for the relation between sand flux and vegetation cover has been derived and can be used to predict the amount of vegetation required to stabilize sand dune areas. (C) 1998 John Wiley & Sons, Ltd.
2): USAL, UK (3): QinetiQ Ltd, UK (4): CENER, Spain (5): CRES, GR (6): VESTAS APAC, DK Summary Cup anemometers need met masts for their mounting and the costs associated with the purchase, erection and instrumentation of the met masts increases rapidly with height. The evolution of new multi-MW wind turbines has resulted in increased hub heights and increased rotor diameters, thus making remote sensing an important issue for wind energy applications. Remote sensing techniques offer the ability to determine wind speed and direction at several heights using a ground-based instrument which operates via the transmission and detection of light (LIDAR) or sound (SODAR). Sodars have extensively been used in meteorological applications for wind speed measurements while both sodars and lidars are newcomers to the strict demands posed by wind energy applications. The need for remote sensing measurements is obvious, yet in order for these measurements to become accepted, there is a need for documenting how the instruments measure the wind along with developing calibration methods. In the meantime there is a need, as a first step, to test and document the response of the instruments against the existing standard, i.e. the cup anemometer. Within the UPWIND EU-project, work package 6 deals with remote sensing measurements using LIDARs (LIght Detection And Ranging) and SODARs (SOund Detection And Ranging). The scope of this work package is to gather the existing experience in this field, generate new data and improved analysis methods, and eventually create the basis for the introduction of these techniques in wind energy applications. The work done so far within the project, which also forms the basis for the present paper, consists of the following: • Concise description of the measurement principles using lidars and sodars. • The principles for the calibration of the instruments. • Preliminary results from measurement campaigns in both flat and complex terrain and comparisons to cup and sonic anemometers. • The efforts to better understand and improve the operation of the instruments. Finally the future plans and targets of the project will be briefly presented.
Given the significant rise of the utilization of wind energy the accurate assessment of the wind potential is becoming increasingly important. Direct applications of wind assessment techniques include the creation of wind maps on a local scale (typically 5 20 km) and the micrositing of wind turbines, the estimation of vertical wind speed variations, prospecting on a regional scale (>100 km), estimation of the long-term wind resource at a given site, and forecasting. The measurement of wind speed and direction still widely relies on cup anemometers, though sonic anemometers are becoming increasingly popular. Moreover, remote sensing by Doppler techniques using the backscattering of either sonic beams (SODAR) or light (LIDAR) allowing for vertical profiling well beyond hub height are quickly moving into the mainstream. Local wind maps are based on the predicted modification of the regional wind flow pattern by the local atmospheric boundary layer which in turn depends on both topographic and roughness features and the measured wind rose obtained from one or several measurement towers within the boundaries of the planned development site. Initial models were based on linearized versions of the Navier-Stokes equations, whereas more recently full CFD models have been applied to wind farm micrositing. Linear models tend to perform well for terrain slopes lower than about 25% and have the advantage of short execution times. Long-term performance is frequently estimated from correlations with nearby reference stations with concurrent information and continuous time series over a period of at least 10 years. Simple methods consider only point-to-point linear correlations; more advanced methods like multiple regression techniques and methods based on the theory of distributions will be discussed. Both for early prospecting in regions where only scarce or unreliable reference information is available, wind flow modeling on a larger scale (mesoscale) is becoming increasingly popular.
A mobile Doppler lidar based on an injection-seeded diode-pumped Nd:YAG pulsed laser with a high repetition rate was developed to measure the sea surface wind (SSW) with high spatial and temporal resolution. The system was operated during the 2007 Qingdao International Regatta to measure the distribution of SSW in the racing area in real time with 50-100 m horizontal resolution and 2-10 min temporal resolution. An observation of nonuniform distribution of SSW is presented. The lidar results are compared with both buoy and wind tower measurements, which show good agreement. This lidar can be used advantageously for the 2008 Olympic sailing games as well as for observing mesoscale and microscale meteorology processes.
This volume features research and case studies across a variety of industries to showcase technological innovations and policy initiatives designed to promote renewable energy and sustainable economic development. The first section focuses on policies for the adoption of renewable energy technologies, the second section covers the evaluation of energy efficiency programs, and the final section provides evaluations of energy technology innovations.
Environmental concerns, energy availability, and political pressure have prompted governments to look for alternative energy resources that can minimize the undesirable effects for current energy systems. For example, shifting away from conventional fuel resources and increasing the percentage of electricity generated from renewable resources, such as solar and wind power, is an opportunity to guarantee lower CO2 emissions and to create better economic opportunities for citizens in the long run.
Including discussions of such of timely topics and issues as global warming, bio-fuels, and nuclear energy, the editors and contributors to this book provide a wealth of insights and recommendations for sustainable energy innovations.
All commercial LIDARs and SODARs are monostatic and hence sample distributed volumes to construct wind vector components. We use an analytic potential flow model to estimate errors arising for a range of LIDAR and SODAR configurations on hills and escarpments. Wind speed errors peak at a height relevant to wind turbines and can be typically 20%.
A fully comprehensive introduction to smart grid standards and their applications for developers, consumers and service providers The critical role of standards for smart grid has already been realized by world-wide governments and industrial organizations. There are hundreds of standards for Smart Grid which have been developed in parallel by different organizations. It is therefore necessary to arrange those standards in such a way that it is easier for readers to easily understand and select a particular standard according to their requirements without going into the depth of each standard, which often spans from hundreds to thousands of pages. The book will allow people in the smart grid areas and in the related industries to easily understand the fundamental standards of smart grid, and quickly find the building-block standards they need from hundreds of standards for implementing a smart grid system. The authors highlight the most advanced works and efforts now under way to realize an integrated and interoperable smart grid, such as the NIST Framework and Roadmap for Smart Grid Interoperability Standards Release 2.0, the IEC Smart Grid Standardization Roadmap, the ISO/IECs Smart Grid Standards for Residential Customers, the ZigBee/HomePlugs Smart Energy Profile Specification 2.0, IEEEs P2030 Draft Guide for Smart Grid Interoperability of Energy Technology and Information Technology Operation with the Electric Power System (EPS), and End-Use Applications and Loads, and the latest joint research project results between the worlds two largest economies, US and China. The book enables readers to fully understand the latest achievements and ongoing technical works of smart grid standards, and assist industry utilities, vendors, academia, regulators, and other smart grid stakeholders in future decision making. The book begins with an overview of the smart grid, and introduces the opportunities in both developed and developing countries. It then examines the standards for power grid domain of the smart grid, including standards for blackout prevention and energy management, smart transmission, advanced distribution management and automation, smart substation automation, and condition monitoring. Communication and security standards as a whole are the backbone of smart grid and their standards, including those for wired and wireless communications, are then assessed. Finally the authors consider the standards and on-going work and efforts for interoperability and integration between different standards and networks, including the latest joint research effort between the worlds two largest economies, US and China. A fully comprehensive introduction to smart grid standards and their applications for developers, consumers and service providers Covers all up-to-date standards of smart grid, including the key standards from NIST, IEC, ISO ZigBee, IEEE, HomePlug, SAE, and other international and regional standardization organizations. The Appendix summarizes all of the standards mentioned in the book Presents standards for renewable energy and smart generation, covering wind energy, solar voltaic, fuel cells, pumped storage, distributed generation, and nuclear generation standards. Standards for other alternative sources of energy such as geothermal energy, and bioenergy are briefly introduced Introduces the standards for smart storage and plug-in electric vehicles, including standards for distributed energy resources (DER), electric storage, and E-mobility/plug-in vehicles The book is written in an accessible style, ideal as an introduction to the topic, yet contains sufficient detail and research to appeal to the more advanced and specialist reader. © 2015 John Wiley & Sons Singapore Pte. Ltd. All rights reserved.
The turbulent environment experienced by ground vehicles is currently not well understood. Due to this, and other historical reasons, the aerodynamic testing of automobiles is usually conducted in extremely low-turbulence wind tunnels (<1%), which is in clear contradiction with the small amount of wind data available to date for these heights. This work presents a series of turbulence measurements made in a range of different on-road terrains and traffic conditions. This data was captured using multi-hole pressure probes mounted to the front of a test vehicle traveling at a road speed of 100 km/h. Analysis of the data shows how both the turbulence intensities and turbulent length scales are modified by terrain type, road side obstacles and the upstream wakes of other moving vehicles.
The Mobile Satellite System Architectures and Multiple Access Techniques Workshop served as a forum for the debate of system and network architecture issues. Particular emphasis was on those issues relating to the choice of multiple access technique(s) for the Mobile Satellite Service (MSS). These proceedings contain articles that expand upon the 12 presentations given in the workshop. Contrasting views on FDMA-, CDMA-, and TDMA-based architectures are presented, and system issues relating to signaling, spacecraft design, and network management constraints are addressed. An overview article that summarizes the issues raised in the numerous discussion periods of the workshop is also included. iii FOREWORD The mobile satellite industry is at a critical juncture, given the imminent procurement of satellites for the Canadian and U.S. Mobile Satellite Service (MSS)
Ambient background noise is a common problem for poor Doppler sodar performance. This noise can be active or passive and broad-band or narrow-band. Active broad-band noise decreases the sounding range of the sodar by decreasing the signal-to-noise ratio. Active narrow-band noise can be interpreted as erroneous wind values. Passive noise sources are objects which reflect the transmitted acoustic pulse back to the sodar with zero Doppler shift. Use of acoustic shielding is discussed as a method of noise pollution control by isolating the side lobe energy of the transmitted acoustic pulse. At the same time, these acoustic shields are effective in blocking out active ambient background noise. Previous studies which experienced noise interference are shown as examples of problems that are frequently encountered.
In view of the intermittency and uncertainty associated with both the electricity production sector of restructured power system and their competitive markets, it is necessary to develop an appropriate risk managing scheme. So that it is desirable to trade-off between optimum utilization of intermittent generation resources (i.e. renewable energy resources), uncertain market prices and related risks in order to maximize participants' benefits and minimize the corresponding risks in the multi-product market environment. The main goal of this paper is to investigate risk management by introducing a novel multi-risk index to quantify expected downside risk (EDR) which is caused by both the wind power and market price uncertainties. Value-at-Risk (VaR) method is used to assess the mentioned risk issue by the proposed weighted EDR, so that an optimal trade-off between the profit and risk is made for the system operations. Also, the roulette wheel mechanism is employed for random market price scenario generation wherein the stochastic procedure is converted into its respective deterministic equivalents. Moreover, the autoregressive integrated moving average (ARIMA) model is employed to characterize the stochastic wind farm (WF) generation by predetermined mean level and standard deviation of wind behavior as well as temporal correlation. The problem is formulated as a mixed-integer stochastic framework for a hydro-wind power system scheduling and tested on a generation company (GENCO).
The environmental advantage of distributed energy resources (DERs) application has attracted lots of research attention and encouraged to implement clean power producers. In spite of the environmental benefits of renewable energy sources application as distributed power generation, the variability of renewable energy, e.g. wind power uncertainty, can potentially endanger the operation of electric power system. This paper presents a new techno-economic factor (TEF) for DERs based on the effect of their generation on network losses and the relationship between active/reactive power loss and generated power from thermal power plants. In order to simultaneously investigate these new factors and wind power uncertainty on power network operation, a stochastic Security Constrained Unit Commitment (SCUC) for 24 h is defined consisting of generation and emission costs. The simulation results of IEEE57-bus case study show the effective role of RES application on operational cost minimization.
This paper presents information on the wind and terrain parameters at the Texas Tech Wind Engineering Research Field Laboratory. Details of the meteorological tower and instrumentation are given, as well as a description of the meteorological data which has been collected so far. The data and terra parameters will assist researchers in performing wind tunnel simulations.
With the increased interest in remote sensing of wind information in recent years, it is important to determine the reliability and accuracy of new wind measurement technologies if they are to replace or supplement conventional tower-based measurements. In view of this, HydroChina Corporation and the United States National Renewable Energy Laboratory (NREL) conducted a comparative test near a wind farm in Hebei Province, China. We present the results of an analysis characterizing the measurement performance of a state-of-the-art Sound Detection and Ranging (sodar) device when compared to a traditional tower measurement program. NREL performed the initial analysis of a three-month period and sent the results to HydroChina. When another month of data became available, HydroChina and their consultant Beijing Millenium Engineering Software (MLN) repeated NREL's analysis on the complete data set, also adding sensitivity analysis for temperature, humidity, and wind speed (Section 6). This report presents the results of HydroChina's final analysis of the four-month period.
A multifrequency phased-array Doppler sodar system has been installed recently at the National Atmospheric Research Laboratory (NARL) for the continuous observation of the lower atmosphere from near ground to the atmospheric boundary layer (ABL). The NARL sodar, developed in technical collaboration with the Society for Applied Microwave Electronics Engineering and Research (SAMEER), was built using piezoceramic tweeters, which are capable of generating 100-W acoustic power. In favorable atmospheric conditions, the sodar gives wind profiles up to 1 km. The performance evaluation is one of the most important aspects for quality assurance of sodar operations. This paper presents the first results of experimental observations of the NARL sodar system and its scientific validation. The NARL sodar has been validated using the simultaneous observation of another sodar system (Scintec model MFAS64). Various physical parameters of the atmosphere are derived using the results obtained from both of the systems. Comparison of simultaneous measurements by both of the sodars, located about 100 m apart, shows good agreement on wind speed, wind direction, and vertical wind variance. The correlation coefficient of more than 0.80 in wind speed and direction between the sodars shows the usefulness of the system for observing the atmosphere and deriving physical parameters below the ABL.
Simultaneous measurements of turbulent vertical velocity fluctuations at a height of 300 ft. measured by means of a fixed anemometer, small floating balloons, and airplane gust equipment at Brookhaven are presented. The resulting Eulerian (fixed anemometer) turbulence energy spectra are similar to the Lagrangian (balloon) spectra but with a displacement toward higher frequencies.
Wind measurements estimated using acoustic sounding systems are compared with direct measurements obtained at a 300 m antenna mast. Different meteorological periods, including very stable to unstable stratification and weak to strong winds, were investigated. It is demonstrated that satisfactory results may be obtained using a simple monostatic Doppler device combined with an appropriate evaluation method. Preliminary tests on an angle of arrival sodar system showed its ability to obtain reasonable wind measurements at least under stable conditions.
Assessment of the relative windiness of afforestation sites has enabled the development of site classification for species selection, growth rate and wind hazard. The current development of a quantitative classification of wind risk requires a method of estimating the probability of strong winds. The relationship between wind strength and probability is commonly derived from several years of measurements at the site of interest. This is not practical when assessing wind risk for a land use rather than a single engineering structure. However, the extreme value distribution that represents the relationship between strength and probability can be derived from the mean wind climate, as represented by parameters of the parent Weibull distribution. The relationship between these parameters and previous estimates of relative windiness developed from tatter flags is explored using wind measurements from reference sites in upland Britain. A strong relationship is established between a modified geographic predictor and the Weibull c parameter. Satisfactory predictions of the Weibull c parameter are obtained for a number of validation sites using this regression and the parameters are used to derive estimates of the 1:50 year return period wind speed. A relationship between predicted and measured wind speed is also found using a dataset derived from low elevation Meteorological Office sites, but an offset is found. It is unclear whether this reflects a difference between the wind climates sampled, the effects of local surface roughness, or differences in equipment sensitivity. Further work is required to extend the method to low wind speed and high roughness sites.
A short version of the history of the cup anemometer precedes a more technical discussion of the special features of this instrument. These include its extremely linear calibration and the non-linearity of its response to wind speed changes. A simple conceptual model by Schrenk is used to demonstrate this and to explain why the cup anemometer is able to start from a zero rotation rate at zero wind to one corresponding to a sudden change in the ambient wind speed to a finite value. The same model is used to show that the cup anemometer should be characterized by a distance constant rather than by a time constant. The bias in the measured mean wind speed due to the random variations in the three velocity components is discussed in terms of standard, semiquantitative turbulence models, and the main thesis is that this bias is overwhelmingly dominated by the fluctuations of the lateral wind velocity component, i.e. the wind component perpendicular to the mean wind direction, and not, as is often assumed, by the longitudinal wind velocity component. It is shown theoretically and tested experimentally that the bias due to lateral wind velocity fluctuations can be significantly reduced by means of a special data processing of the simultaneous signals from a cup anemometer and a wind vane. This means that, with care, the overall overspeeding can be reduced to less than 1%. Copyright
An attempt is made to simulate the Centennial wind farm consisting of 83 wind turbines. The farm is located in the Coulee municipality region near Swift Current, Southern Saskatchewan (Canada). The Wind Atlas Analysis and Application Program and other mapping programs were used for generating the annual energy production (AEP). Based on the generated wind atlas and using both the meteorological data for a period of 10 years (2000–2009), and a vector map with height contour and surface roughness lines, the total AEP for the wind farm was calculated. In addition, AEPs of the wind farm were individually calculated for 2007, 2008 and 2009. The results of the simulated model were compared to the actual values for 3 years. The average absolute deviation between the predicted and actual mean AEP values was found to be less than 7%.
The paper describes the general characteristics of a non-orthogonal
sonic anemometer array. The effects of line-averaging and spatial
separation (between mid-points of the horizontal paths) are analyzed and
spatial transfer functions are derived for power spectra of the
longitudinal, lateral and vertical velocity components. While
line-averaging always causes spectral attenuation at wavenumbers larger
than 1/l (where l is the sonic path length), spatial separation produces
cross-contamination between the horizontal velocity spectra at
wavenumbers exceeding 1/d (where d is the separation distance). For an
array with a 120° angle between the horizontal sonic paths the net
effect of this cross-contamination is to overestimate the longitudinal
velocity spectrum and underestimate the lateral velocity spectrum. The
separation distance which yields maximum flatness in the transfer
function for the longitudinal component is found to be 0.6 l.Also
discussed are the effects of aliasing and long-term trends on the shape
of the computed spectrum and spectral correction for the spatial
transfer function in the context of these effects.
For the 1968 Kansas atmospheric surface-layer experiment, a supplementary analysis is made of the evaluation procedure. Available data on the ratio of wind speeds measured on separate booms show a variation with wind direction which is too large for an open mast. Actually the Kansas mast appears to have carried a bulky array of apparatus at the sonic anemometer levels. It is shown that the air flow interference caused by this obstacle can be satisfactorily estimated by way of potential flow calculations. From these it follows that the sonic anemometer measurements probably have undervalued the free-flow eddy stress by 20% to 30%, which implies that the simultaneous drag plate measurements of stress were generally correct. Also the overestimation of the mean wind speed by the Kansas cup anemometer is found to have been 6% rather than 10%. Some Kansas evaluation results are amended accordingly. The von Krmn constant is found to be 0.41 rather than 0.35, and the near-adiabatic eddy diffusivity ratio K
H
/K
M
becomes 1.0 rather than 1.3. The flux-gradient relations (Businger et al., 1971) after similar revision no longer differ significantly from those obtained elsewhere.
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Development of a standardised cup anemometer suited to wind energy applications
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Component failure simulation tool for optimal electrical configuration and repair strategy design of off-shore wind farms. in: OCEANS
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LIDAR campaign at Buena Vista wind farm: An examination of hill speedup flows
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A study of wind power potential at Kallar Kahar-Chakwal (Punjab) using SODAR