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Accurate wind turbine annual energy computation by advanced modeling
Abstract
Renewable energy is the ultimate goal to mitigate global greenhouse gas emissions, and to have energy independence. Renewable energy computation is best accomplished by taking into account the annualized statistical wind power availability. In this paper, the annual energy has been accurately computed for a wind turbine (WT) by an advanced modeling, taking into account the characteristics of the WT and the environment. Accounting for the parameters affecting the output energy, is implemented in order to correctly model the system. This helps in monitoring the power generation, and sizing of the wind farm. Mainly, two scenarios are discussed. First, accuracy of WT modeling when the wind speed only affects the output power. Second, accuracy of air density modeling when many parameters affect the WT output power which include wind speed, power coefficient, elevation above sea level, temperature, pressure and humidity. It is shown that accurate modeling has a considerable impact on the computed annual energy extracted from a single WT and thus the whole wind farm. This will have a major impact on the sizing of the wind farm, and hence affects the net present cost of the entire system.
Renewable energy sources penetrate our recent life very deeply. They have more expansion chances in the nearest future, especially in stand-alone and micro grid fields. Due to the uncertainty of the weather and the nonmatching between the generated energy and demand, a hybrid energy storage system (HESS) is required. The optimization computations are the best way to select the optimal values for the capacity, sizes and quantities of the stand-alone hybrid renewable energy system (HRES) to satisfy the load demands of the available climate conditions. In this paper, the HRES which includes PV panels, wind turbines, battery banks, hydrogen tanks with fuel cells and electrolyzers has been tested and optimized using a tri-level optimization problem. Using Matlab software, the simulation results validate that the proposed method converged quickly and accurately to the optimal solution. The total capital cost was between 231,750. The maximum average efficiency
was 83.53% at a minimum total capital cost of 67 which were achieved in the same summer month presented in July.
Wind Turbines (WTs) are exposed to harsh conditions and can experience extreme weather, such as blizzards and cold waves, which can directly affect temperature monitoring. This paper analyzes the effects of ambient conditions on WT monitoring. To reduce these effects, a novel WT monitoring method is also proposed in this paper. Compared with existing methods, the proposed method has two advantages: (1) the changes in ambient conditions are added to the input of the WT model; (2) an Extreme Learning Machine (ELM) optimized by Genetic Algorithm (GA) is applied to construct the WT model. Using Supervisory Control and Data Acquisition (SCADA), compared with the method that does not consider the changes in ambient conditions, the proposed method can reduce the number of false alarms and provide an earlier alarm when a failure does occur.
Renewable energy is the ultimate goal for mitigating global greenhouse gas emissions, and for national energy sufficiency. Optimal renewable power plant design is best accomplished by taking into account the annualized statistical wind power availability. In this paper, the annual energy has been accurately computed for a wind turbine (WT) by an advanced modeling, taking into account the characteristics of the WT and the environment. Accounting for the parameters affecting the output energy, is implemented in order to correctly model the system. This helps in monitoring the power generation and sizing of the wind farm. Mainly, two scenarios are discussed. First, accuracy of WT modeling when the wind speed only affects the output power. Second, accuracy of air density modeling, among the many parameters affecting the WT output power, such as wind speed, power coefficient, elevation above sea level (a.s.l), temperature, pressure and humidity. It is shown that accurate modeling has a considerable impact on the computed annual energy extracted from a single WT and thus the whole wind farm. This will have a major impact on the sizing of the wind farm, and hence affects the net present cost of the entire system.
This paper investigates the impact of the wind turbine (WT) modeling on a hybrid wind-photovoltaic (PV) system installed in a city in Jordan. A closer look is taken at the parameters affecting the output power to accurately model the system. This helps in monitoring the turbine performance, sizing of the wind farm and the entire hybrid system, which will definitely affect the annual energy extracted (AEE) from a single WT as well as the entire wind turbines (WTs). Also, the cost of the hybrid system such as the net present cost (NPC), the grid operating cost (GOC) and the cost of energy (COE) will be affected. Six WT models are added to Hybrid Optimization Multiple Energy Resources software in order to see the sizing and cost effects of the new system. A step-by-step analysis and design of each proposed WT model and its effects on the hybrid system are presented. Results show that as the WT simplified models change from the cubic, quadratic, toward the linear one, the resulting system has a significant percentage error in the estimation of the cost as well as AEE. Also, the number of WTs increases at the system level till it becomes a wind only configuration in the linear model. But, this is at the penalty of the imprecise sizing solution, which leads to wrong estimates for the project investment. Therefore, the WT has to be modeled accurately by considering many parameters such as the air density, e.g., geographic elevation. The results show that the WT model designed at sea level shows error estimates in both AEE and the system cost from the one designed at actual temperature or elevation above sea level (a.s.l). The simple WT models will not deliver the AEE theoretically calculated. This energy deficit will be substituted by the more expensive on-grid conventional power plant fuel energy. In other words, in order to solve a real problem, the real values for parameters affecting the WT model have to be considered. The same procedure can be applied in other locations around the world.
Wind turbine power curve modeling is an important tool in turbine performance monitoring and power forecasting. There are several statistical techniques to fit the empirical power curve of a wind turbine, which can be classified into parametric and nonparametric methods. In this paper, we study four of these methods to estimate the wind turbine power curve. Polynomial regression is studied as the benchmark parametric model, and issues associated with this technique are discussed. We then introduce the locally weighted polynomial regression method, and show its advantages over the polynomial regression. Also, the spline regression method is examined to achieve more flexibility for fitting the power curve. Finally, we develop a penalized spline regression model to address the issues of choosing the number and location of knots in the spline regression. The performance of the presented methods is evaluated using two simulated data sets as well as an actual operational power data of a wind farm in North America.
The wind speeds of a wind farm are not always available or accurately measurable due to uncontrollable events such as anemometer failures or data transmission errors. However, the data are of great importance for wind resource assessment and wind speed prediction. In this paper, a vertically correlated echelon model (CEM) is proposed to interpolate the missing data of wind speeds by utilizing the correlation of wind speeds at different heights. First, the data of wind speed are checked according to a national standard. Second, the model based on the correlation of wind speeds at different heights is proposed for short interval of missing data. Third, the proposed method is compared with typical interpolation methods and its advantages and disadvantages are discussed. Finally, the uncertainty of the proposed method is analyzed for improved evaluation of interpolation errors.
Hybrid renewable energy systems (HRES) are becoming popular for remote area power generation applications due to advances in renewable energy technologies and subsequent rise in prices of petroleum products. Economic aspects of these technologies are sufficiently promising to include them in developing power generation capacity for developing countries. Research and development efforts in solar, wind, and other renewable energy technologies are required to continue for, improving their performance, establishing techniques for accurately predicting their output and reliably integrating them with other conventional generating sources. The paper describes methodologies to model HRES components, HRES designs and their evaluation. The trends in HRES design show that the hybrid PV/wind energy systems are becoming gaining popular. The issues related to penetration of these energy systems in the present distribution network are highlighted.
The second edition of the highly acclaimed Wind Power in Power Systems has been thoroughly revised and expanded to reflect the latest challenges associated with increasing wind power penetration levels. Since its first release, practical experiences with high wind power penetration levels have significantly increased. This book presents an overview of the lessons learned in integrating wind power into power systems and provides an outlook of the relevant issues and solutions to allow even higher wind power penetration levels. This includes the development of standard wind turbine simulation models. This extensive update has 23 brand new chapters in cutting-edge areas including offshore wind farms and storage options, performance validation and certification for grid codes, and the provision of reactive power and voltage control from wind power plants. Key features: Offers an international perspective on integrating a high penetration of wind power into the power system, from basic network interconnection to industry deregulation; Outlines the methodology and results of European and North American large-scale grid integration studies; Extensive practical experience from wind power and power system experts and transmission systems operators in Germany, Denmark, Spain, UK, Ireland, USA, China and New Zealand; Presents various wind turbine designs from the electrical perspective and models for their simulation, and discusses industry standards and world-wide grid codes, along with power quality issues; Considers concepts to increase penetration of wind power in power systems, from wind turbine, power plant and power system redesign to smart grid and storage solutions. Carefully edited for a highly coherent structure, this work remains an essential reference for power system engineers, transmission and distribution network operator and planner, wind turbine designers, wind project developers and wind energy consultants dealing with the integration of wind power into the distribution or transmission network. Up-to-date and comprehensive, it is also useful for graduate students, researchers, regulation authorities, and policy makers who work in the area of wind power and need to understand the relevant power system integration issues.
This book addresses the key concerns regarding the operation of wind turbines in cold climates, and focuses in particular on the analysis of icing and methods for its mitigation. Topics covered include the implications of cold climates for wind turbine design and operation, the relevance of icing for wind turbines, the icing process itself, ice prevention systems, and thermal anti-icing system design. In each chapter, care is taken to build systematically on the basic knowledge, providing the reader with the level of detail required for a thorough understanding. An important feature is the inclusion of several original analytical and numerical models for ready computation of icing impacts and design assessment. The breadth of the coverage and the in-depth scientific analysis, with calculations and worked examples relating to both fluid dynamics and thermodynamics, ensure that the book will serve not only as a textbook but also as a practical manual for general design tasks.
This paper investigates the impact of the wind turbine (WT) modeling on a hybrid wind-photovoltaic (PV) system installed in a city in Jordan. A closer look is taken at the parameters affecting the output power to accurately model the system. This helps in monitoring the turbine performance, sizing of the wind farm and the entire hybrid system, which will definitely affect the annual energy extracted (AEE) from a single WT as well as the entire wind turbines (WTs). Also, the cost of the hybrid system such as the net present cost (NPC), the grid operating cost (GOC) and the cost of energy (COE) will be affected. Six WT models are added to Hybrid Optimization Multiple Energy Resources software in order to see the sizing and cost effects of the new system. A step-by-step analysis and design of each proposed WT model and its effects on the hybrid system are presented. Results show that as the WT simplified models change from the cubic, quadratic, toward the linear one, the resulting system has a significant percentage error in the estimation of the cost as well as AEE. Also, the number of WTs increases at the system level till it becomes a wind only configuration in the linear model. But, this is at the penalty of the imprecise sizing solution, which leads to wrong estimates for the project investment. Therefore, the WT has to be modeled accurately by considering many parameters such as the air density, e.g., geographic elevation. The results show that the WT model designed at sea level shows error estimates in both AEE and the system cost from the one designed at actual temperature or elevation above sea level (a.s.l). The simple WT models will not deliver the AEE theoretically calculated. This energy deficit will be substituted by the more expensive on-grid conventional power plant fuel energy. In other words, in order to solve a real problem, the real values for parameters affecting the WT model have to be considered. The same procedure can be applied in other locations around the world.
This paper investigates the feasibility of wind-photovoltaic (PV) penetration into an existing utility grid system for the city of Ibrahimyya in Jordan. Ibrahimyya is selected because it enjoys both high annual wind speed of 7.27 m/s and high annual solar radiation of 6.05 kWh/m2/day. Two sizing methods are presented using MATLAB and hybrid optimization multiple energy resources software. Thousands of iterations have been carried out in order to get the global autonomous sizing solution that is used for economic analysis. Results show that three CS6X-310 PV panels and eight GE1.5sle-77 wind turbines are the optimal choice. A step-by-step analysis of the proposed system is presented. The net present cost (NPC) is 65069349/kWh. A sensitivity analysis on interest rate, inflation rate, wind power law exponent, annual average daily energy demand, and fuel price is implemented to assess the robustness of the system. The results prove the feasibility to apply the proposed hybrid wind-PV system for this city. The same procedure can be applied anywhere.
This paper investigates the feasibility of wind-PV penetration into an existing utility grid system for Ibrahimyya city in Jordan. Ibrahimyya is selected because it enjoys both high annual wind speed of 7.27 m/s and high annual solar radiation of 6.05 kWh/m2/day. Two sizing methods are presented using MATLAB and HOMER softwares. But, thousands of iterations have been carried out in HOMER to get the global autonomous sizing solution that is used for economic analysis. Results show that 3 CS6X-310 PV panels and 8 GE1.5sle-77 wind turbines are the optimal choice. A step-by-step analysis of the proposed system is presented. The net present cost (NPC) is /kWh. A sensitivity analysis on interest rate, inflation rate, wind power law exponent and fuel price is implemented to assess the robustness of the system. The results prove the feasibility to apply the proposed Hybrid Wind-PV system for this city. The same procedure can be applied anywhere.
A wind turbine power curve essentially captures the performance of the wind turbine. The power curve depicts the relationship between the wind speed and output power of the turbine. Modeling of wind turbine power curve aids in performance monitoring of the turbine and also in forecasting of power. This paper presents the development of parametric and nonparametric models of wind turbine power curves. Parametric models of the wind turbine power curve have been developed using four and five parameter logistic expressions. The parameters of these expressions have been solved using advanced algorithms like genetic algorithm (GA), evolutionary programming (EP), particle swarm optimization (PSO), and differential evolution (DE). Nonparametric models have been evolved using algorithms like neural networks, fuzzy c-means clustering, and data mining. The modeling of wind turbine power curve is done using five sets of data; one is a statistically generated set and the others are real-time data sets. The results obtained have been compared using suitable performance metrics and the best method for modeling of the power curve has been obtained.
In this paper, a methodology of sizing optimization of a stand-alone hybrid wind/PV/diesel energy system is presented. This approach makes use of a deterministic algorithm to suggest, among a list of commercially available system devices, the optimal number and type of units ensuring that the total cost of the system is minimized while guaranteeing the availability of the energy. The collection of 6 months of data of wind speed, solar radiation and ambient temperature recorded for every hour of the day were used. The mathematical modeling of the main elements of the hybrid wind/PV/diesel system is exposed showing the more relevant sizing variables. A deterministic algorithm is used to minimize the total cost of the system while guaranteeing the satisfaction of the load demand. A comparison between the total cost of the hybrid wind/PV/diesel energy system with batteries and the hybrid wind/PV/diesel energy system without batteries is presented. The reached results demonstrate the practical utility of the used sizing methodology and show the influence of the battery storage on the total cost of the hybrid system. (author)
The author had wide experience as an electrical engineer in major US companies before becoming an academic professor. His expertise led him to study power generation from renewables, especially wind and photovoltaic power. This textbook has been developed from his teaching and research, and from his experience as an associate editor of the Solar Energy Journal, published by the International Solar Energy Association. This background explains the electrical engineering character of the book, and its nominal division into four parts: wind, photovoltaic, system integration and ancillary power. The division is ‘nominal’, because various fundamental aspects of power generation and analysis pop-up somewhat indiscriminately throughout the text. The book will be well used in mid-year degree courses in engineering, but, by keeping close to present reality, it will also be interesting and informative for professional engineers. Thus
This paper proposes the use of wind power as a source of electricity in a new city being developed in the Duqm area of Oman. Recent wind speed measurements taken at the Duqm metrological station are analyzed to obtain the annual and monthly wind probability distribution profiles represented by Weibull parameters. The monthly average mean wind speed ranges between 2.93 m/s in February and 9.76 m/s in July, with an annual average of 5.33 m/s.
A techno-economic evaluation of a wind power project is presented to illustrate the project’s viability. Given Duqm’s wind profile and the power curve characteristics of a V90-1.8 turbine, an annual capacity factor of 0.36 is expected. For the base-case assumptions, the cost of electricity is about 0.08 per kWh for discount rates of 5% and 10%, respectively. These values are higher than that of the existing generation system, due to the subsidized prices of domestically available natural gas. However, given high international natural gas prices, the country’s long-term LNG export obligations, and the expansion of natural gas-based industries, investments in wind power in Duqm can be justified. A feed-in tariff and
capital cost allowance policies are recommended to facilitate investments in this sector.
a b s t r a c t In the present work a computation of wind shear coefficients (WSCs) based on 1-h measured wind data has been performed by three stations located over coastal sites in Southern Italy, i.e., Brindisi (BR), Portoscuso (PS) and Termini Imerese (TI). Wind observations have been collected through a 6-year period (January 1, 1997 to December 31, 2002) by wind mast recording at the same two sensor heights (i.e., 10 and 50 m AGL), thus enabling a proper wind profile analysis. WSC overall mean values were found to be 0.271 at BR, 0.232 at PS, and 0.150 at TI. In addition, a detailed analysis has been carried out to describe the WSC yearly, monthly and diurnal variation, as well as by wind direction. The characteristics of z 0 surface roughness length have been also investigated as an estimate for neutral stability conditions only, resulting in overall mean values of 0.526 m at BR, 0.287 m at PS, and 0.027 m at TI. The z 0 variation by year, month and hour of the day, as well as by wind direction, has been analysed, too. The European "Corine Land Cover 2000" classification of the study areas has been employed to deeply investigate the land use influence on both WSC and z 0 characteristics as a function of wind direction. Based on temperature and pressure surface measurements, the computation of site-specific mean air density as well as monthly variation has been also performed. Site-related 50-m wind resource has been assessed by means of wind roses and wind speed frequency distributions, as well as Weibull's parameters. The potential turbine-converted wind energy yield has been also investigated, enabling to detect, for each site, the most suitable 50-m hub height turbine model regardless of its rated power. Furthermore, a number of comparisons have been made to assess the discrepancy in 50-m energy yield resulting if using data extrapolated from 10 m, both with 0.143 default and overall mean WSC value, instead of actually 50-m measured data.
This paper uses the data from seven wind farms at Muppandal, Tamil Nadu, India, collected for three years from April 2002 to March 2005 for the estimation of energy yield from wind farms. The model is developed with the help of neural network methodology, and it involves three input variables-wind speed, relative humidity, and generation hours-and one output variable, which give the energy output from wind farms. The modeling is done using MATLAB software. The most appropriate neural network configuration after trial and error is found to be 3-5-1 (3 input layer neurons, 5 hidden layer neurons, 1 output layer neuron). The mean square error for the estimated values with respect to the measured data is 7.6times10-3. The results demonstrate that this work is an efficient energy yield estimation tool for wind farms.
The optimal design of the renewable energy system can significantly improve the economical and technical performance of power supply. In this paper, the technical-economic optimization study of a stand-alone hybrid PV/wind system (HPWS) in Corsica Island is presented.Therefore, the primary objective of this study is to estimate the appropriate dimensions of a stand-alone HPWS that guarantee the energy autonomy of a typical remote consumer with the lowest levelised cost of energy (LCE). A secondary aim is to compare the performance and the optimal sizing of two system configurations. Finally, to study the impact of the renewable energy potential quality on the system size, the optimum dimensions of system are defined for five sites in Corsica Island. In this context, a complete sizing model is developed, able to predict the optimum system configuration on the basis of LCE. Accordingly, an integrated energy balance analysis is carried out for the whole time period investigated.The simulation results indicate that the hybrid system is the best option for all the sites considered in this study, yielding lower LCE. Thus, it provides higher system performance than PV or wind systems alone. The choice of the system configuration type affects the state of charge variation profile, especially at low wind potential sites, while the system size and the LCE are significantly influenced. It is shown that the LCE depends largely on the renewable energy potential quality. At high wind potential site, more than 40% of the total production energy is provided by the wind generator, while at low wind potential sites, less than 20% of total production energy is generated by the wind generator.
The present paper presents a methodology to perform the optimal sizing of an autonomous hybrid PV/wind system. The methodology aims at finding the configuration, among a set of systems components, which meets the desired system reliability requirements, with the lowest value of levelized cost of energy.Modelling a hybrid PV/wind system is considered as the first step in the optimal sizing procedure. In this paper, more accurate mathematical models for characterizing PV module, wind generator and battery are proposed. The second step consists to optimize the sizing of a system according to the loss of power supply probability (LPSP) and the levelized cost of energy (LCE) concepts.Considering various types and capacities of system devices, the configurations, which can meet the desired system reliability, are obtained by changing the type and size of the devices systems. The configuration with the lowest LCE gives the optimal choice.Applying this method to an assumed PV/wind hybrid system to be installed at Corsica Island, the simulation results show that the optimal configuration, which meet the desired system reliability requirements (LPSP=0) with the lowest LCE, is obtained for a system comprising a 125 W photovoltaic module, one wind generator (600 W) and storage batteries (using 253 Ah). On the other hand, the device system choice plays an important role in cost reduction as well as in energy production.
Wind farms operating in island systems are subject to output power limitations, related with technical constraints of the conventional generating units, namely the minimum loading levels of the thermal units (technical minima) and a dynamic penetration limit, applied for stability purposes. Evaluation of the expected wind energy yield in isolated island systems requires, therefore, proper consideration, not only of the prevailing wind conditions at the installation site, but also of the power limitations imposed by the system, which ultimately depend on the total load demand. In the paper, a methodology is presented for the evaluation of the wind energy absorption capability of island systems and the expected energy yield of wind farms operating therein. This methodology is currently applied in Greece for the determination of the power restrictions applied to existing and new wind farms, to schedule new wind capacity tenders and for the evaluation of the expected energy yield of new investments for permitting and financing purposes.
This paper develops the Hybrid Solar-Wind System Optimization Sizing (HSWSO) model, to optimize the capacity sizes of different components of hybrid solar-wind power generation systems employing a battery bank. The HSWSO model consists of three parts: the model of the hybrid system, the model of Loss of Power Supply Probability (LPSP) and the model of the Levelised Cost of Energy (LCE). The flow chart of the HSWSO model is also illustrated. With the incorporated HSWSO model, the sizing optimization of hybrid solar-wind power generation systems can be achieved technically and economically according to the system reliability requirements. A case study is reported to show the importance of the HSWSO model for sizing the capacities of wind turbines, PV panel and battery banks of a hybrid solar-wind renewable energy system.
Wind characteristics and wind turbine characteristics in Taiwan have been thoughtfully analyzed based on a long-term measured data source (1961–1999) of hourly mean wind speed at 25 meteorological stations across Taiwan. A two-stage procedure for estimating wind resource is proposed. The yearly wind speed distribution and wind power density for the entire Taiwan is firstly evaluated to provide annually spatial mean information of wind energy potential. A mathematical formulation using a two-parameter Weibull wind speed distribution is further established to estimate the wind energy generated by an ideal turbine and the monthly actual wind energy generated by a wind turbine operated at cubic relation of power between cut-in and rated wind speed and constant power between rated and cut-out wind speed. Three types of wind turbine characteristics (the availability factor, the capacity factor and the wind turbine efficiency) are emphasized. The monthly wind characteristics and monthly wind turbine characteristics for four meteorological stations with high winds are investigated and compared with each other as well. The results show the general availability of wind energy potential across Taiwan.
System power reliability under varying weather conditions and the corresponding system cost are the two main concerns for designing hybrid solar–wind power generation systems. This paper recommends an optimal sizing method to optimize the configurations of a hybrid solar–wind system employing battery banks. Based on a genetic algorithm (GA), which has the ability to attain the global optimum with relative computational simplicity, one optimal sizing method was developed to calculate the optimum system configuration that can achieve the customers required loss of power supply probability (LPSP) with a minimum annualized cost of system (ACS). The decision variables included in the optimization process are the PV module number, wind turbine number, battery number, PV module slope angle and wind turbine installation height. The proposed method has been applied to the analysis of a hybrid system which supplies power for a telecommunication relay station, and good optimization performance has been found. Furthermore, the relationships between system power reliability and system configurations were also given.
Wind turbines in cold climates: icing impacts and mitigation systems
- L Battisti
Modern Wind Generators
- ragheb
The international standard atmosphere (isa)
- cavcar