Comparative impacts of wind and photovoltaic generation on energy storage for small islanded electricity systems

This paper addresses the annual energy storage requirements of small islanded electricity systems with wind and photovoltaic (PV) generation, using hourly demand and resource data for a range of locations in New Zealand. Normalised storage capacities with respect to annual demand for six locations with winter-peaking demand profiles were lower for wind generation than for PV generation, with an average PV:wind storage ratio of 1.768:1. For two summer-peaking demand profiles, normalised storage capacities were lower for PV generation, with storage ratios of 0.613:1 and 0.455:1. When the sensitivity of storage was modelled for winter-peaking demand profiles, average storage ratios were reduced. Hybrid wind/PV systems had lower storage capacity requirements than for wind generation alone for two locations. Peak power for storage charging was generally greater with PV generation than with wind generation, and peak charging power increased for the hybrid systems. The results are compared with those for country-scale electricity systems, and measures for minimising storage capacity are discussed. It is proposed that modelling of storage capacity requirements should be included in the design process at the earliest possible stage, and that new policy settings may be required to facilitate a transition to energy storage in fully renewable electricity systems.     

Profiling the regional wind power fluctuation in China

As China starts to build 6 10-GW wind zones in 5 provinces by 2020, accommodating the wind electricity generated from these large wind zones will be a great challenge for the regional grids. Inadequate wind observing data hinders profiling the wind power fluctuations at the regional grid level. This paper proposed a method to assess the seasonal and diurnal wind power patterns based on the wind speed data from the NASA GEOS-5 DAS system, which provides data to the study of climate processes including the long-term estimates of meteorological quantities. The wind power fluctuations for the 6 largest wind zones in China are presented with both the capacity factor and the megawatt wind power output. The measured hourly wind output in a regional grid is compared to the calculating result to test the analyzing model. To investigate the offsetting effect of dispersed wind farms over large regions, the regional correlations of hourly wind power fluctuations are calculated. The result illustrates the different offsetting effects of minute and hourly fluctuations.     

Will British weather provide reliable electricity?

There has been much academic debate on the ability of wind to provide a reliable electricity supply. The model presented here calculates the hourly power delivery of 25 GW of wind turbines distributed across Britain's grid, and assesses power delivery volatility and the implications for individual generators on the system. Met Office hourly wind speed data are used to determine power output and are calibrated using Ofgem's published wind output records. There are two main results. First, the model suggests that power swings of 70% within 12 h are to be expected in winter, and will require individual generators to go on or off line frequently, thereby reducing the utilisation and reliability of large centralised plants. These reductions will lead to increases in the cost of electricity and reductions in potential carbon savings. Secondly, it is shown that electricity demand in Britain can reach its annual peak with a simultaneous demise of wind power in Britain and neighbouring countries to very low levels. This significantly undermines the case for connecting the UK transmission grid to neighbouring grids. Recommendations are made for improving ‘cost of wind’ calculations. The authors are grateful for the sponsorship provided by The Renewable Energy Foundation.     

The interaction of wind power generation with electricity demand in the context of a small grid

An investigation into the integration of the intermittent electricity output of a hypothetical wind farm in Malta with the actual electricity demand for one particular year is reported. Available hourly wind data from three sites for 2001 were analysed. The probability density of the load resulting from the reduction of the renewable output from the electricity demand on an hourly basis was determined by a convolution method. The calculated shift in the load duration extends over the whole spectrum of power demand. The equivalent power at the most favourable site was considerably higher than the nominal value commonly in use. In view of the limited availability of sites for wind farms in Malta rotor designs better suited to the lower wind speed régime inland should be considered.     

The impact of the North Atlantic Oscillation on electricity markets: A case study on Ireland

The North Atlantic Oscillation (NAO) is a large-scale atmospheric circulation pattern driving climate variability in north-western Europe. As the deployment of wind-powered generation expands on electricity networks across Europe, the impacts of the NAO on the electricity system will be amplified. This study assesses the impact of the NAO, via wind-power generation, on the electricity market considering thermal generation costs, wholesale electricity prices and wind generation subsidies. A Monte Carlo approach is used to model NAO phases and generate hourly wind speed time-series data, electricity demand and fuel input data. A least-cost unit commitment and economic dispatch model is used to simulate an island electricity system, modelled on the all-island Irish electricity system. The impact of the NAO obviously depends on the level of wind capacity within an electricity system. Our results indicate that on average a switch from negative to positive NAO phase can reduce thermal generation costs by up to 8%, reduce wholesale electricity prices by as much as €1.5/MWh, and increase wind power generators' revenue by 12%.     

High value wind: A method to explore the relationship between wind speed and electricity locational marginal price

Wind and solar resources are, by nature, spatially distributed and temporally variable. The process of siting generators that use these renewable resources and integrating them into the electricity system therefore raises different issues than the same process for combustion facilities does. A method for discovering wind power sites with the highest value to the electricity system was developed and is illustrated here using data for the state of Michigan. This method combines readily available hourly average 10 m wind speed data with wholesale electricity price data, as hourly locational marginal price (LMP). The 10 m wind speed data from 72 sites were extrapolated vertically to 80 m turbine hub height, converted to wind power density, and interpolated horizontally via kriging to reconstruct a continuous surface. LMP data from 178 generator nodes were allocated across space using Thiessen polygons. High LMP was interpreted as a signal of insufficiency or weakness in the electricity system, and wind energy was considered a possible remedy. The method, implemented in a GIS, identifies when and where peaks in LMP and wind power density co-occur and highlights these events as high value. As the drive to incorporate more renewable generators into the electricity system increases, this method will help locate the most desirable sites based on wind resource characteristics and the structure of the larger electricity system. Proposing a new way to think about the value of the wind resource to the electricity system is a primary contribution of this work.     

The capacity credit of wind power: A theoretical analysis

A probabilistic model of capacity credit (or value) is constructed for wind power in an electricity grid, The model-which is initially based on the assumptions that electricity supply, electricity demand and the output of a system of aerogenerators are Normally distributed and that the conventional power plant in the grid comprises units of identical capacity—provides simple analytical expressions for four different concepts of capacity credit and elucidates the qualitative differences between them.Two of these concepts of wind power capacity credit, the “equivalent conventional capacity” and the “equivalent firm capacity”, are then studied in more detail by introducing a much more realistic probability distribution of wind power output than the Normal distribution and by calculating the Loss of Load Probability. For small penetrations of wind power into the grid, the capacity credit is approximately equal to the average wind power output, while for large penetrations the credit tends to a limit which is determined by the probability of zero wind power and the conventional plant characteristics.     

Industrial electricity demand for Turkey: A structural time series analysis

This research investigates the relationship between Turkish industrial electricity consumption, industrial value added and electricity prices in order to forecast future Turkish industrial electricity demand. To achieve this, an industrial electricity demand function for Turkey is estimated by applying the structural time series technique to annual data over the period 1960 to 2008. In addition to identifying the size and significance of the price and industrial value added (output) elasticities, this technique also uncovers the electricity Underlying Energy Demand Trend (UEDT) for the Turkish industrial sector and is, as far as is known, the first attempt to do this. The results suggest that output and real electricity prices and a UEDT all have an important role to play in driving Turkish industrial electricity demand. Consequently, they should all be incorporated when modelling Turkish industrial electricity demand and the estimated UEDT should arguably be considered in future energy policy decisions concerning the Turkish electricity industry. The output and price elasticities are estimated to be 0.15 and − 0.16 respectively, with an increasing (but at a decreasing rate) UEDT and based on the estimated equation, and different forecast assumptions, it is predicted that Turkish industrial electricity demand will be somewhere between 97 and 148 TWh by 2020.     

Adequacy evaluation of wind power generation systems

This paper attempts to assess the adequacy of wind power generation systems using the data collected from seven wind farms in Muppandal, Tamilnadu (India) with a total capacity of 37 MW. A Monte Carlo model simulation is incorporated in the algorithm to obtain the hourly power output of wind farms, which also takes into account the unavailability of wind turbines. A typical load demand profile is used to examine the chronological hourly wind power generation for each month. The reliability index of LOLE (loss of load expectation) is used to estimate the reliable contribution of wind farm power generation.     

Wind turbine generator trends for site‐specific tailoring

Turbine optimization for specific wind regimes and climate conditions is becoming more common as the market expands into new territories (offshore, low‐wind regimes) and as technology matures. Tailoring turbines for specific sites by varying rotor diameter, tower height and power electronics may be a viable technique to make wind energy more economic and less intermittent. By better understanding the wind resource trends and evaluating important wind turbine performance parameters such as specific power (ratio of rated power and rotor swept area), developers and operators can optimize plant output and better anticipate operational impacts. This article presents a methodology to evaluate site‐specific wind data for turbine tailoring. Wind characteristics for the Tehachapi wind resource area in California were utilized for this study. These data were used to evaluate the performance of a range of wind turbine configurations. The goal was to analyse the variations in wind power output for the area, assess the changes in these levels with the time of day and season and determine how turbine configuration affects the output. Wind turbine output was compared with California statewide system electrical demand to evaluate the correlation of the wind resource site with local peak demand loads. A comparison of the commercial value of electricity and corresponding wind generation is also presented using a time‐dependent valuation methodology. Copyright © 2005 John Wiley & Sons, Ltd.     

Market behaviour with large amounts of intermittent generation

This paper evaluates the impact of intermittent wind generation on hourly equilibrium prices and output, using data on expected wind generation capacity and demand for 2020. Hourly wind data for the period 1993–2005 are used to obtain wind output generation profiles for thirty regions (onshore and offshore) across Great Britain. Matching the wind profiles for each month to the actual hourly demand (scaled to possible 2020 values), we find that the volatility of prices will increase, and that there is significant year-to-year variation in generators’ profits. Above-average wind speeds lead to below-average prices, but annual revenues for British wind generators (producing more in the winter) are almost as great as for base-load generators. In the presence of significant market power (the equivalent of two symmetric firms owning fossil-fuelled capacity, rather than six), the level of prices more than doubled, and their volatility increased. However, wind generators’ average revenues rose by 20% less than those of base-load plant.     

Integrating wind output with bulk power operations and wholesale electricity markets

Wind farms have three characteristics that complicate their widespread application as an electricity resource: limited control, unpredictability and variability. Therefore the integration of wind output into bulk power electric systems is qualitatively different from that of other types of generators. The electric system operator must move other generators up or down to offset the time‐varying wind fluctuations. Such movements raise the costs of fuel and maintenance for these other generators. Not only is wind power different, it is new. The operators of bulk power systems have limited experience in integrating wind output into the larger system. As a consequence, market rules that treat wind fairly—neither subsidizing nor penalizing its operation—have not yet been developed. The lack of data and analytical methods encourages wind advocates and sceptics to rely primarily on their biases and beliefs in suggesting how wind should be integrated into bulk power systems. This project helps fill this data and analysis gap. Specifically, it develops and applies a quantitative method for the integration of a wind resource into a large electric system. The method permits wind to bid its output into a short‐term forward market (specifically, an hour‐ahead energy market) or to appear in real time and accept only intrahour and hourly imbalance payments for the unscheduled energy it delivers to the system. Finally, the method analyses the short‐term (minute‐to‐minute) variation in wind output to determine the regulation requirement the wind resource imposes on the electrical system. Copyright © 2002 John Wiley & Sons, Ltd.     

Assessment of wind characteristics and wind turbine characteristics in Taiwan

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.     

Demand response from the non-domestic sector: Early UK experiences and future opportunities

Demand response is believed by some to become a major contributor towards system balancing in future electricity networks. Shifting or reducing demand at critical moments can reduce the need for generation capacity, help with the integration of renewables, support more efficient system operation and thereby potentially lead to cost and carbon reductions for the entire energy system.In this paper we review the nature of the response resource of consumers from different non-domestic sectors in the UK, based on extensive half hourly demand profiles and observed demand responses. We further explore the potential to increase the demand response capacity through changes in the regulatory and market environment.The analysis suggests that present demand response measures tend to stimulate stand-by generation capacity in preference to load shifting and we propose that extended response times may favour load based demand response, especially in sectors with significant thermal loads.     

Assessment of alternative energy sources for generation ofelectricity in the UK following privatisation of the electricity supplyindustry

The structure of the industry in Europe is reviewed along with profiles of electricity generation in Europe and the UK. The size, geographic location, and time scale of future electricity demand in the UK are evaluated, and shortfalls between estimated demand and predicted generation are assessed. Alternative energy sources are examined. These include tidal power from the proposed Severn Estuary Scheme, development of pumped storage such as that proposed at Craigroyston above Loch Lomond, small-scale hydro using low head hydro-turbines permitting development of previously uneconomic schemes on rivers, wind power from wind farms which would utilize the favorable wind patterns which exist in the UK, use of North Sea gas for combined cycle plant, development of small-scale coal-fired stations, particularly those which use the more efficient and cleaner fluidized bed system, and utilizing wave power     

Wind power as a clean-energy contributor

Modern and sophisticated wind generators rated at up to 5 MW are in use on- and offshore in many European and other countries. They are made by a large and financially strong industry. In 2006, there were 1672 wind turbines in use in the UK, making up 2.5% of UK's electricity-generating capacity but producing under 1% of its electricity. The UK uses only about 1% of its wind power potential. Making use of more wind will involve developing new materials, new techniques and new mathematical modelling methods. The machines will need to be more reliable and robust, and will require a more flexible electricity system to feed into. In the longer term, there may be bigger machines of up to 10 MW, perhaps used in tandem with advanced electricity-storage technology. The growth of a European rather than UK power grid may allow renewables, including wind, to play a larger role.     

Impact of hourly wind power variations on the system operation in the Nordic countries

The variations of wind power production will increase the flexibility needed in the system when significant amounts of load are covered by wind power. When studying the incremental effects that varying wind power production imposes on the power system, it is important to study the system as a whole: only the net imbalances have to be balanced by the system. Large geographical spreading of wind power will reduce variability, increase predictability and decrease the occasions with near zero or peak output. The goal of this work was to estimate the increase in hourly load‐following reserve requirements based on real wind power production and synchronous hourly load data in the four Nordic countries. The result is an increasing effect on reserve requirements with increasing wind power penetration. At a 10% penetration level (wind power production of gross demand) this is estimated as 1·5%–4% of installed wind capacity, taking into account that load variations are more predictable than wind power variations. Copyright © 2004 John Wiley & Sons, Ltd.     

Error analysis of short term wind power prediction models

The integration of wind farms in power networks has become an important problem. This is because the electricity produced cannot be preserved because of the high cost of storage and electricity production must follow market demand. Short-long-range wind forecasting over different lengths/periods of time is becoming an important process for the management of wind farms. Time series modelling of wind speeds is based upon the valid assumption that all the causative factors are implicitly accounted for in the sequence of occurrence of the process itself. Hence time series modelling is equivalent to physical modelling. Auto Regressive Moving Average (ARMA) models, which perform a linear mapping between inputs and outputs, and Artificial Neural Networks (ANNs) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS), which perform a non-linear mapping, provide a robust approach to wind power prediction. In this work, these models are developed in order to forecast power production of a wind farm with three wind turbines, using real load data and comparing different time prediction periods. This comparative analysis takes in the first time, various forecasting methods, time horizons and a deep performance analysis focused upon the normalised mean error and the statistical distribution hereof in order to evaluate error distribution within a narrower curve and therefore forecasting methods whereby it is more improbable to make errors in prediction.     

世界风力发电现状与前景预测

全球可再生能源发电装机容量中风电占有压倒性优势,今后可望成为欧洲、亚洲、北美的主要电力来源.2011年中国以62GW的累计装机容量蝉联世界第一,按照我国“十二五”规划目标,预计到2015年风电装机容量将达到1×108kW,年发电量1900×108kW·h.GWEC和Greenpeace预测,今后20年风力发电将成为世界主力电源,2030年装机容量有可能达到23×108kW,可供应世界电力需求的22％.欧美正大力开发海上风电产业.欧洲是世界海上风电发展的先驱和产业中心,欧洲企业不仅拥有自己的核心技术,而且还向世界各地输出技术,今后欧洲海上风力发电将急速增长.美国采取与英国、德国等欧洲厂家相同的战略,大力发展海上风力发电.我国海上风电产业刚刚起步,预计2015年海上风电装机500×104kW.日本学者大岛教授推算了不同电源的发电成本:包括政府财政补贴,运行年限30年的核电站发电成本为12.06日元/(kW·h);按标准设备利用率,风力发电成本11.30日元/(kW·h),与核电相比已经有竞争力.假设风况好时设备利用率达到35％,发电成本为7.95日元/(kW·h),比核电低得多.     

Applying portfolio theory to the electricity sector: Energy versus power

Portfolio theory has found its way in numerous applications for optimizing the electricity generation mix of a particular region. Existing models, however, consider typically a single time period and correspondingly do not properly account for actual dispatch constraints and energy sources with a non-dispatchable, variable output. This paper presents a portfolio theory model that explicitly distinguishes between installed capacity (power), electricity generation (energy) and actual instantaneous power delivery. This way, the variability of wind power and ramp limits of conventional power plants are correctly included in the investment optimization. The model is written as a quadratically constrained programming problem and illustrated in a case study. The results show that the introduction of wind power can be motivated to lower the risk on generation cost, albeit to smaller levels than typically reported in the literature. This wind power deployment further requires the need for sufficiently rampable technologies, to deal with its fluctuating output.