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Prototype large-scale renewable energy system optimisation for Victoria, Australia

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... Both studies share the necessity of recruiting typically 25–30 GW of dispatchable capacity in the form of either biofuelled gas turbines (Elliston) or geothermal plants (AEMO). Huva et al. [23] assume gas-fired back-up in their study of Victoria. The studies by Elliston et al., AEMO and Huva et al. point to a number of shortcomings in need of improvement or further investigation (see a summary in Trainer [24]): first, in the studies listed in the previous paragraph, spatial generator and transmission locations are pre-selected and fixed, and/or temporal resolution is limited . ...
... Short et al. [42] simplify the year-long modelling period to 17 time slices, characterising each slice by typical resource potentials and probabilities describing resource variability. Similarly, Huva et al. [23] explain how large weather data and RAM requirements of their downward-gradient optimisation technique prevented both an hourly run over a whole year, as well as the utilisation of every geographical grid point available. They create a pseudo-year by splicing together seasonal snapshots in order to reduce runtime, and apply site pre-selection methods. ...
... Figs. 8 and 9 in Huva et al. [23] (compare with [63]), and in the order of 10% in a UK study including a quarter of demand supplied by natural gas ([60], p. 21, scenario Re.80). 13 Voorspools and D'haeseleer [65], Hoogwijk et al. [66], Meibom et al. [67], Holttinen [68], Resch et al. [69]. ...
... Most studies use historical time series weather data to calculate the electricity generation from solar PV and wind farms. Some of these studies use high resolution mesoscale weather models to produce the weather data [77]. Other studies use observed or satellitederived measurements for a discrete number of locations over longer time periods to calculate the daily average and minimum resource availability [33]. ...
... There is considerable variation in the spatial resolution for calculating renewable generation in different areas. While most studies are regional or national scale, a 1.5 km spatial resolution is used in [77]. The finer spatial resolution can simulate more precise solar PV or wind generation in different areas, with the optimization determining the best location for the plants. ...
... [21,90,91] examined whether it is technically feasible to meet electricity demand with estimated renewable generation output based on historical data of demand and primary renewable resource availability in the NEM. [77] used mesoscale numerical weather models to examine cross-correlations between solar and wind generation with demand for the state of Victoria. [92] find that incremental costs of high renewable electricity systems increase approximately linearly as the share grows from zero to 80%, and then demonstrate a small degree of non-linear escalation, related to the inclusion of more costly renewable electricity generation technologies such as solar thermal electricity. ...
Conference Paper
This thesis explores the least cost combination of renewable generation technolo- gies, transmission interconnectors and storage capacity in different supply and de- mand scenarios in the Australian National Electricity Market (NEM) regions. Aus- tralia faced high retail electricity prices due to investment in the electricity distri- bution system, significant increase in greenhouse gas emissions (144% compared to 1990 levels) from electricity sector. In the same time peak demand decreased in most states because of energy conservation, on-site generation and industry evolu- tion. Future plans like reduce greenhouse gas emissions by 26% by 2030, use of energy storage (e.g. batteries, concentrated solar thermal power system), increase use of renewables will require a reshape and rethinking of the current energy sys- tem. Although the high renewable penetration system in the NEM regions has been widely discussed, there is lack of co-optimization of the renewable technologies, transmission expansion and storage capacity together. Besides, most studies use historical demand data when optimizing the system, without a detailed assumption of the demand changed by various factors. This study contributes to the current research by building in a depth demand model based on social behaviour, buildings and ambient temperature to analyse the possible changes on demand. A Genetic Algorithm (GA) together with an electric- ity dispatch simulation model at hourly temporal resolution was used in this study. The benefit of this approach consists in co-optimization the renewable generation technologies, transmission interconnectors and storage capacity in the NEM system in different renewable mix and demand scenarios.
... Resource availability Limits of production Solar PV Overall average yearly capacity factor of approx. 0.24, calculated from local meteorological model data for each time slice of the model (obtained from ACCESS for Timor Leste [26]) Limited by area availability for solar panels in the village ...
... Wind Overall average yearly capacity factor of approx. 0.28, calculated from local meteorological model data for each time slice of the model (obtained from the ACCESS for Timor Leste [26]) ...
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Energy access targets at national, sub-national, and local levels, are often not specified in great detail – and tend to focus on supply. Another approach to better inform policy and investment might benefit from an indicator that focuses on the services derived from electricity access. To provide support for decision-making, this research investigates the costs of reaching different levels of energy access in rural areas, with a case study of a village in the Ainaro district of Timor Leste. Utilizing the multi-tier definition of energy access proposed in the World Bank's “Global Tracking Framework” for Sustainable Energy for All, we present results both on the cost difference of achieving different tiers of energy access, and on the comparison among selected electrification and cooking options. Results show that in the period 2010–2030 achieving the highest tier of electricity access could be as much as seventy-five times more costly than achieving the lowest one. In addition moving across tiers, least cost solutions shift from stand-alone to mini-grid and finally grid connected options as electricity access increases. Regarding cooking, moving from open fires to some of the more modern solutions has the potential to reduce overall costs over the same period.
... Various studies have investigated the complementarity [12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27]. These studies have mostly focused on the complementarity between VGR outputs. ...
... These studies have mostly focused on the complementarity between VGR outputs. Most of them have found the flattening effect of aggregated VGR output; for reference, the wind-solar hybrid systems have been the most studied systems [12][13][14][15][16][17][18][19][20]. A combination of solar and hydro systems, and that combination plus wind or ocean-wave systems, have also been addressed [21][22][23][24][25][26][27]. ...
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This study examines the effect of the complementarity between the variable generation resources (VGRs) and the load on the flexibility of the power system. The complementarity may change the ramping capability requirement, and thereby, the flexibility. This effect is quantified using a flexibility index called the ramping capability shortage expectation (RSE). The flexibility is evaluated for different VGR mix scenarios under the same VGR penetration level, and an optimal VGR mix (i.e., one that maximizes flexibility) is obtained. The effect of the complementarity of the wind and PV outputs on the flexibility is investigated for the peak-load day of 2016 for the Korean power system. The result shows that the RSE value for the optimal VGR mix scenario is 6.95% larger than that for the original mix scenario.
... A number of authors have now reported modelling results for 100% renewable, or predominantly renewable, electricity systems (Ackermann et al., 2009;Mason et al., 2010aMason et al., , 2010bWright and Hearps, 2010;Denholm and Hand, 2011;Troster et al., 2011;Van dePutte and Short, 2011;Elliston et al., 2012;Huva et al., 2012;Budischak et al., 2013). Modelling results for a 99% renewable European grid system, at hourly resolution over a 30 year period, were reported by Troster et al. (2011) and Van dePutte and Short (2011), following on from earlier work by Ackermann et al. (2009) PV, 4-5% geothermal, 11-14% biomass, 4-5% concentrating solar power, 3% wave/tidal, 8-11% hydro and 1% gas on an installed capacity basis, were found to be technically and economically feasible. ...
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In this paper, issues of security of supply, energy spillage control, and peaking options, within a fully renewable electricity system, are addressed. We show that a generation mix comprising 49% hydro, 23% wind, 13% geothermal, 14% pumped hydro energy storage peaking plant, and 1% biomass-fuelled generation on an installed capacity basis, was capable of ensuring security of supply over an historic 6-year period, which included the driest hydrological year on record in New Zealand since 1931. Hydro spillage was minimised, or eliminated, by curtailing a proportion of geothermal generation. Wind spillage was substantially reduced by utilising surplus generation for peaking purposes, resulting in up to 99.8% utilisation of wind energy. Peaking requirements were satisfied using 1550 MW of pumped hydro energy storage generation, with a capacity factor of 0.76% and an upper reservoir storage equivalent to 8% of existing hydro storage capacity. It is proposed that alternative peaking options, including biomass-fuelled gas turbines and demand-side measures, should be considered. As a transitional policy, the use of fossil-gas–fuelled gas turbines for peaking would result in a 99.8% renewable system on an energy basis. Further research into whether a market-based system is capable of delivering such a renewable electricity system is suggested.
... The above optimizations are sensitive to storage efficiency, which, for instance varies from 0.9 to 0.6 between pumped-hydro and hydrogen [32]. In a context closer to operational conditions, i) production data over the Pacific Northwest region in the US and forecasting simulations show that a mix can reduce the reserve requirement, i.e. the generation reserve hold by operators [247] and, ii) the geographical choice of solar-and wind-plant settings in southern Australia influences the economic cost of reserve requirement [248]. ...
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A major part of renewable electricity production is characterized by a large degree of intermittency driven by the natural variability of climate factors such as air temperature, wind velocity, solar radiation, precipitation, evaporation, and river runoff. The main strategies to handle this intermittency include energy-storage, -transport, -diversity and -information. The three first strategies smooth out the variability of production in time and space, whereas the last one aims a better balance between production and demand. This study presents a literature review on the space-time variability of climate variables driving the intermittency of wind-, solar- and hydropower productions and their joint management in electricity systems. A vast body of studies pertains to this question bringing results covering the full spectrum of resolutions and extents, using a variety of data sources, but mostly dealing with a single source. Our synthesis highlights the consistency of these works, and, besides astronomic forcing, we identify three broad climatic regimes governing the variability of renewable production and load. At sub-daily time scales, the three considered renewables have drastically different pattern sizes in response to small scale atmospheric processes. At regional scales, large perturbation weather patterns consistently control wind and solar production, hydropower having a clearly distinct type of pattern. At continental scales, all renewable sources and load seem to display patterns of constant space characteristics and no indication of marked temporal trends.
... The work by Huva et al. [78] presents a regional assessment for 100% RE generation where sites were selection was based on the results of Weather Research and Forecasting (WRF) model [79]). Optimisation of the system was performed in two phases, the first simple analysis for meeting demand with only a combination of wind and solar energy, followed up with a more complex analysis incorporating 2 GWh of PHS as well as biogas backup in order to meet synthesised demand in all cases. ...
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The proliferation of non-scheduled generation from renewable electrical energy sources such concentrated solar power (CSP) presents a need for enabling scheduled generation by incorporating energy storage; either via directly coupled Thermal Energy Storage (TES) or Electrical Storage Systems (ESS) distributed within the electrical network or grid. The challenges for 100% renewable energy generation are: to minimise capitalisation cost and to maximise energy dispatch capacity. The aims of this review article are twofold: to review storage technologies and to survey the most appropriate optimisation techniques to determine optimal operation and size of storage of a system to operate in the Australian National Energy Market (NEM). Storage technologies are reviewed to establish indicative characterisations of energy density, conversion efficiency, charge/discharge rates and costings. A partitioning of optimisation techniques based on methods most appropriate for various time scales is performed: from “whole of year”, seasonal, monthly, weekly and daily averaging to those best suited matching the NEM bid timing of five minute dispatch bidding, averaged on the half hour as the trading settlement spot price. Finally, a selection of the most promising research directions and methods to determine the optimal operation and sizing of storage for renewables in the grid is presented.
... Liu et al. [13] established a mathematical model of dynamic energy system based on superior control theories, and analyzed the superior strategy for the replacement of renewable energy on fossil energy. Huva et al. [14] presented results from a prototype renewable energy network optimization model, and estimated potential power output for various combinations of wind and solar farms across a large domain of several hundred kilometers and calculated the required back-up power capacity needed to meet demand. Motaz Amer [15] presented a method for the optimization of the power generated from a Hybrid Renewable Energy Systems in order to achieve the load of typical house as example of load demand. ...
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Facing the mounting pressures of meeting energy and environment needs and reducing its dependence for fossil fuels, China needs to make more effort to develop renewable energy. This paper attempts to use portfolio theory to optimize China's overall energy system with considering the learning curve effect of renewable energy cost and the characteristic of fossil energy cost increasing over time. It also takes into account additional factors such as environmental costs of coal consumption and various growth rates of the cumulative R&D (research and development) capacity for solar power. This research has found that the development of renewable energy in China has tremendous potential but it will not replace fossil energy in the next decades. The sensitivity analysis of this paper indicates that development of solar power is driven not only by the cumulative installed capacity but also by the cumulative R&D capacity.
... Scenarios with close to 100% renewable production are investigated in numerous studies within a wide range of methodological frameworks and geographical boundaries. Some carry out advanced operational and economic modeling [10], [11], [1], [12], [13], while others concentrate on fundamental systemic aspects of VREs integration in order to gain a better understanding of existing options, opportunities and threats [14], [6], [5], [15], [16]. ...
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The transitional path towards a highly renewable power system based on wind and solar energy sources is investigated considering their intermittent and spatially distributed characteristics. Using an extensive weather-driven simulation of hourly power mismatches between generation and load, we explore the interplay between geographical resource complementarity and energy storage strategies. Solar and wind resources are considered at variable spatial scales across Europe and related to the Swiss load curve, which serve as a typical demand side reference. The optimal spatial distribution of renewable units is further assessed through a parameterized optimization method based on a genetic algorithm. It allows us to explore systematically the effective potential of combined integration strategies depending on the sizing of the system, with a focus on how overall performance is affected by the definition of network boundaries. Upper bounds on integration schemes are provided considering both renewable penetration and needed reserve power capacity. The quantitative trade-off between grid extension, storage and optimal wind-solar mix is highlighted. This paper also brings insights on how optimal geographical distribution of renewable units evolves as a function of renewable penetration and grid extent.
... The available technologies are onshore wind, large-scale photovoltaics, pumped hydro and gas-fired back-up. The back-up hydro and gas models utilised are originally outlined in Huva et al. (2012). The energy model requires that demand is met by the mixture of technologies and the total cost will vary based on the amount that each resource is deployed. ...
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... After the suitable location is determined, the conversion systems need to be developed. For this purpose, numerous research groups and communities have conducted research on wind energy conversion system designs and prototypes, for example Vries in [7] and Huva et al. in [8]. Not only land-based conversion systems, but also sea based system as can be found in [9] and [10] as examples. ...
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The present study uses Quikscat data to assess the offshore wind energy potential at the Eastern part of Indonesia, around the Sulawesi and Maluku Islands. Weibull distribution with two parameters is used to represent the characteristics and distribution of the wind model. In order to confirm the accuracy of computations, statistical and numerical methods are used to compute the Weibull parameters which are regression analysis, maximum likelihood method and moment method. The obtained power density is used to draw monthly wind power maps for the sea areas around the islands. The maps are used to determine the most suitable location of a mobile conversion system every month. Moreover, by assuming that a NM72/2000 NEG Micon is installed, Monte Carlo Simulation is performed to determine the expected power percentage produced by the system every month.
... This spin-up period is discarded and not used in subsequent analyses. Typical spin up times vary from 2 to 3[38,39], 6[16,40], 12 h[41,42]to 24 h[31]and could extend to days[37]. Of the various physical and chemical parameterizations, the coupled planetary boundary layer (PBL) and surface layer (SL) processes have been found to consistently influence boundary layer winds the most[43][44][45]. ...
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Numerical wind mapping is currently the wind power industry's standard for preliminary assessments for sites of good wind resources. Of the various available numerical models, numerical weather prediction (NWP) models are best suited for modeling mesoscale wind flows across small islands. In this study, the Weather Research and Forecast (WRF) NWP model was optimized for simulating the wind resources of the Caribbean islands of Trinidad and Tobago in terms of spin-up period for developing mesoscale features, the input initial and boundary conditions, and the planetary boundary layer (PBL) parameterizations. Hourly model simulations of wind speed and wind direction for a one-month period were compared with corresponding 10 m level wind observations. The National Center for Environmental Prediction (NCEP)-Department of Energy (DOE) reanalysis of 1.875 horizontal resolution was found to be better suited to provide initial and boundary conditions (ICBCs) over the 1 resolution NCEP final analysis (FNL); 86% of modeled wind speeds were within-2 m/s of measured values at two locations when the coarse resolution NCEP reanalysis was used as compared with 55-64% of modeled wind speeds derived from FNL. Among seven PBL schemes tested, the Yonsei University PBL scheme with topographic drag enabled minimizes the spatial error in wind speed (mean bias error +0.16 m/s, root-mean-square error 1.53 m/s and mean absolute error 1.21 m/s) and is capable of modeling the bimodal wind speed histogram. These sensitivity tests provide a suitable configuration for the WRF model for mapping the wind resources over Trinidad and Tobago, which is a factor in developing a wind energy sector in these islands.
... Biofuel and hydro-potential were used to plug gaps caused during low-resource periods, and biofuelled generation was capped at 20 TWh. Other national and inter-state-level studies that examine high penetration of renewable electricity in Australia are Huva et al. [33], Vithayasrichareon and MacGill [34], Turner et al. [35], Lu et al. [2], and Riesz et al. [6]. ...
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... One class of main approaches consists of downwardgradient methods, such as Mixed-Integer Linear Programming [2] which have the advantages of being robust and converging usually reliably and rapidly to a maximum. Disadvantages are the implicit assumption of a single global minimum as well as the representation of the supply-demand balance as a large set of individual constraints, leading to a high-dimensional system with consequent requirements on computer memory. ...
... Energies 2018, 11, x FOR PEER REVIEW 2 of 23 electric power system in Japan, electric power generation is dominated by thermal power plants. The daily startup or shut down schedules of thermal power plants are planned a day prior to the target day, and these plants can absorb changes in demand (Huva et al. [10]; Udagawa et al. [11,12], TEPCO website [13]). Achieving an adaptable supply of electric power and minimizing the total costs of electric power control are the most essential aims of electric power companies. ...
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The installation of renewable energy generation resources (such as photovoltaic arrays and wind-turbine generators) in a microgrid is important because a microgrid can increase the penetration of renewable energies in a smart grid. A community may be a grid-tied microgrid in which an energy management system may dispatch elastic loads (such as air conditioning systems). This paper investigates the optimal sizing of renewable energy generation resources in a community microgrid. The cost of renewables and community welfare are optimized while the comfort zone of indoor temperature in all homes is maintained using air conditioning systems. Community welfare is ensured by minimizing the purchased power from and maximizing the sold power to the utility grid with different time-of-use electricity tariffs. Since the problem of interest involves a large number of variables and chronological constraints, Markov models of photovoltaic power generation, wind generation, load and temperature are utilized to reduce the numbers of variables and constraints. The Markov-based optimization problem is then solved using the interior-point algorithm. The simulation results, based on a smart community of 50 homes, reveal the applicability of the proposed method.
Article
Electrical energy storage (EES) has the potential to enable a transition to clean energy in the future as it brings flexibility into the electricity network. Uncertainties exist around EES regarding technology, costs, business models and market structures but experts agree on EES being beneficial. This study offers an economic analysis of the role of EES in low-carbon electricity supply. A GIS-supported hourly simulation study of Australia assesses the impact of adding EES to wind and solar generation on levelised cost of electricity (LCOE), installed capacity, generation mix and energy spillage. The study finds that EES deployment is able to lower LCOE in scenarios with high penetration of renewable sources. In the case study of Australia, it is found that EES between 90 and 180 GWh capacity can be economic for cost levels below 1,000 AU$ kWh ⁻¹ . In addition, the study finds that EES can reduce LCOE by 13–22%, reduce installed capacity by up to 22%, and reduce spilled energy by up to 76%. It is shown that the generation mix is highly influenced by the magnitude of EES deployed.
Article
This paper presents an improved energy scheduling and output smoothing scheme for storage aided utility scale PV systems. A weighted energy scheduling approach is adopted to create a demand-like storage discharge pattern for the peak demand period, and thus ensures enhanced performance with well-fitted supply-demand curve and flat net load variation. A hybrid robust smoothing method is then proposed by blending a Double Grid Search Support Vector Machine (DGS-SVM) aided power prediction module with the First-In-First-Out (FIFO) aided robust smoothing module. With the System Advisor Model (SAM) and Matlab, the actual hourly and minute interval data sets for Australia are used for case studies, demonstrating the enhanced effectiveness and efficiency of the proposed scheme.
Technical Report
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The Technical Note series provides an outlet for a variety of NCAR manuscripts that contribute in specialized ways to the body of scientific knowledge but which are not suitable for journal, monograph, or book publication. Reports in this series are issued by the NCAR Scientific Divisions; copies may be obtained on request from the Publications Office of NCAR. Designation symbols for the series include: EDD: IA:
Article
Full-text available
The wind and solar energy are omnipresent, freely available, and environmental friendly. The wind energy systems may not be technically viable at all sites because of low wind speeds and being more unpredictable than solar energy. The combined utilization of these renewable energy sources are therefore becoming increasingly attractive and are being widely used as alternative of oil-produced energy. Economic aspects of these renewable energy technologies are sufficiently promising to include them for rising power generation capability in developing countries. A renewable hybrid energy system consists of two or more energy sources, a power conditioning equipment, a controller and an optional energy storage system. These hybrid energy systems are becoming popular in remote area power generation applications due to advancements in renewable energy technologies and substantial rise in prices of petroleum products. 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 aim of this paper is to review the current state of the design, operation and control requirement of the stand-alone PV solar-wind hybrid energy systems with conventional backup source i.e. diesel or grid. This Paper also highlights the future developments, which have the potential to increase the economic attractiveness of such systems and their acceptance by the user.
Article
Full-text available
This article presents the results of analyses of large-scale integration of wind power, photo voltaic (PV) and wave power into a Danish reference energy system. The possibility of integrating Renewable Energy Sources (RES) into the electricity supply is expressed in terms of the ability to avoid excess electricity production. The different sources are analysed in the range of an electricity production from 0 to 100% of the electricity demand. The excess production is found from detailed energy system analyses on the computer model EnergyPLAN. The analyses have taken into account that certain ancillary services are needed in order to secure the electricity supply system.The idea is to benefit from the different patterns in the fluctuations of different renewable sources. And the purpose is to identify optimal mixtures from a technical point of view. The optimal mixture seems to be when onshore wind power produces approximately 50% of the total electricity production from RES. Meanwhile, the mixture between PV and wave power seems to depend on the total amount of electricity production from RES. When the total RES input is below 20% of demand, PV should cover 40% and wave power only 10%. When the total input is above 80% of demand, PV should cover 20% and wave power 30%. Meanwhile the combination of different sources is alone far from a solution to large-scale integration of fluctuating resources. This measure is to be seen in combination with other measures such as investment in flexible energy supply and demand systems and the integration of the transport sector.
Conference Paper
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The optimal sizing of a small autonomous hybrid power system can be a very challenging task, due to the large number of design settings and the uncertainty in key parameters. This problem belongs to the category of combinatorial optimization, and its solution based on the traditional method of exhaustive enumeration can be proved extremely time-consuming. This paper proposes a binary genetic algorithm in order to solve the optimal sizing problem. Genetic algorithms are popular optimization metaheuristic techniques based on the principles of genetics and natural selection and evolution, and can be applied to discrete or continuous solution space problems. The obtained results prove the performance of the proposed methodology in terms of solution quality and computational time.
Article
Full-text available
The renewable power generation aggregated across Europe exhibits strong seasonal behaviors. Wind power generation is much stronger in winter than in summer. The opposite is true for solar power generation. In a future Europe with a very high share of renewable power generation those two opposite behaviors are able to counterbalance each other to a certain extent to follow the seasonal load curve. The best point of counterbalancing represents the seasonal optimal mix between wind and solar power generation. It leads to a pronounced minimum in required stored energy. For a 100% renewable Europe the seasonal optimal mix becomes 55% wind and 45% solar power generation. For less than 100% renewable scenarios the fraction of wind power generation increases and that of solar power generation decreases.
Article
Wind is the world's fastest growing electric energy source. Because it is intermittent, though, wind is not used to supply baseload electric power today. Interconnecting wind farms through the transmission grid is a simple and effective way of reducing deliverable wind power swings caused by wind intermittency. As more farms are interconnected in an array, wind speed correlation among sites decreases and so does the probability that all sites experience the same wind regime at the same time. The array consequently behaves more and more similarly to a single farm with steady wind speed and thus steady deliverable wind power. In this study, benefits of interconnecting wind farms were evaluated for 19 sites, located in the midwestern United States, with annual average wind speeds at 80 m above ground, the hub height of modern wind turbines, greater than 6.9 m s-1 (class 3 or greater). It was found that an average of 33% and a maximum of 47% of yearly averaged wind power from interconnected farms can be used as reliable, baseload electric power. Equally significant, interconnecting multiple wind farms to a common point and then connecting that point to a far-away city can allow the long-distance portion of transmission capacity to be reduced, for example, by 20% with only a 1.6% loss of energy. Although most parameters, such as intermittency, improved less than linearly as the number of interconnected sites increased, no saturation of the benefits was found. Thus, the benefits of interconnection continue to increase with more and more interconnected sites.
Book
This book covers the subject on global, synoptic and more localised scales as well the important issue of climate change variability in four major sections. The first section introduces the basic science of the atmosphere: its physical structure and composition, and the planetary circulation that lays the foundation for Australasian weather and climate. The next section describes the characteristics of airmasses and atmospheric motion, explains the interactions that produce mid latitude and tropical weather systems, and discusses weather forecasting in this region. The book then focuses on selected aspects of the mesoscale, regional and local weather systems. Finally, past climate change, contemporary variability and future scenarios are examined, and the possible links between human activity and climate variability are outlined, with particular emphasis on this region.
Article
In Ontario (Canada), the integration of renewable power is a priority policy goal. Since 2004, the circumstances under which the integration of renewable power is evaluated have changed due to successive changes in price as well as concerns that its over-production may add to grid congestion. This research investigates the value of increasing complementarity (both proximate and geographically dispersed) of wind and solar resources as a means by which electricity planners and researchers might advance electricity sustainability in Ontario. More specifically, this paper asks the following questions: 1) Does the combination of solar and wind resources in selected locations in Ontario serve to ‘smooth out’ power production, i.e., decrease instances of both high and low values, as compared to either resource producing individually? 2) Can this ‘smoothness’ be further improved by dispersing these resources geographically amongst locations? and 3) Does increasing the number of locations with solar and wind resources further ‘smooth out’ power production? Three years (2003–2005) of synchronous, hourly measurements of solar irradiance and wind speeds from Environment Canada’s Canadian Weather Energy and Engineering Data Sets (CWEEDS) are used to derive dimensionless indices for four locations in Ontario (Toronto, Wiarton, Sault Ste. Marie and Ottawa). These indices are used to develop three transparent and accessible methods of analysis: (1) graphical representation; (2) percentile ranking; and (3) using a theoretical maximum as a proxy for capacity. The article concludes that the combination of solar and wind within locations and amongst two locations improves ‘smoothness’ in power production, as compared to when each resource is produced on its own; moreover, it is further improved once more than two resources and two locations are combined. However, there is neither further benefit, nor drawback, associated with the geographic dispersion of complementarity between solar in one location and wind in another, when compared to both resources in one location.
Article
We study the numerical performance of a limited memory quasi-Newton method for large scale optimization, which we call the L-BFGS method. We compare its performance with that of the method developed by Buckley and LeNir (1985), which combines cycles of BFGS steps and conjugate direction steps. Our numerical tests indicate that the L-BFGS method is faster than the method of Buckley and LeNir, and is better able to use additional storage to accelerate convergence. We show that the L-BFGS method can be greatly accelerated by means of a simple scaling. We then compare the L-BFGS method with the partitioned quasi-Newton method of Griewank and Toint (1982a). The results show that, for some problems, the partitioned quasi-Newton method is clearly superior to the L-BFGS method. However we find that for other problems the L-BFGS method is very competitive due to its low iteration cost. We also study the convergence properties of the L-BFGS method, and prove global convergence on uniformly convex problems.
Article
This paper presents the methodology and results of the overall energy system analysis of a 100% renewable energy system. The input for the systems is the result of a project of the Danish Association of Engineers, in which 1600 participants during more than 40 seminars discussed and designed a model for the future energy system of Denmark. The energy system analysis methodology includes hour by hour computer simulations leading to the design of flexible energy systems with the ability to balance the electricity supply and demand. The results are detailed system designs and energy balances for two energy target years: year 2050 with 100% renewable energy from biomass and combinations of wind, wave and solar power; and year 2030 with 50% renewable energy, emphasising the first important steps on the way. The conclusion is that a 100% renewable energy supply based on domestic resources is physically possible, and that the first step towards 2030 is feasible to Danish society. However, Denmark will have to consider to which degree the country shall rely mostly on biomass resources, which will involve the reorganisation of the present use of farming areas, or mostly on wind power, which will involve a large share of hydrogen or similar energy carriers leading to certain inefficiencies in the system design.
Article
Solar and wind energy systems are omnipresent, freely available, environmental friendly, and they are considered as promising power generating sources due to their availability and topological advantages for local power generations. Hybrid solar–wind energy systems, uses two renewable energy sources, allow improving the system efficiency and power reliability and reduce the energy storage requirements for stand-alone applications. The hybrid solar–wind systems are becoming popular in remote area power generation applications due to advancements in renewable energy technologies and substantial rise in prices of petroleum products. This paper is to review the current state of the simulation, optimization and control technologies for the stand-alone hybrid solar–wind energy systems with battery storage. It is found that continued research and development effort in this area is still needed for improving the systems’ performance, establishing techniques for accurately predicting their output and reliably integrating them with other renewable or conventional power generation sources.
Article
In this paper, we describe a method for constructing regional electricity demand data sets at 30 min intervals, which are consistent with climate change scenarios. Specifically, we modify a commonly used linear regression model between regional electricity demand and climate to also describe intraday variability in demand so that regional load duration curves (LDCs) can be predicted. The model is evaluated for four different Australian states that are participants in the Australian National Electricity Market (NEM) and the resultant data sets are found to reproduce each state's LDCs with reasonable accuracy. We also apply the demand model to CSIRO's Mk 3 global climate model data sets that have been downscaled to 60 km resolution using CSIRO's conformal-cubic atmospheric model to estimate how LDCs change as a consequence of a 1 °C increase in the average temperature of Australian state capital cities. These regional electricity demand data sets are then useful for economic modelling of electricity markets such as the NEM.
Article
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.
Current status of research on optimum sizing of stand-alone hybrid solar-wind power generation systems A current and future state of art development of hybrid energy system using wind and PV-solar: a review
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