Revision of reserve requirements following wind power integration in island power systems

This contribution studies the impact of wind power on the operation of island power systems. The analysis focuses on the available flexibility of thermal generation to balance wind power variations and prediction errors. This issue is highly relevant for small and medium sized islands where interconnections are absent and the smoothing of variations is limited due to a small geographical surface. The main objective is to determine if additional reserve requirements are necessary for ensuring reliable wind power integration in an isolated transmission system. In this context, a case study is performed for Cyprus, a medium-sized island, where wind developments towards 2020 schedule an installed capacity of 300 MW, reaching 7% of the annual electricity consumption. Simulations with installed wind power capacities up to 400 MW show that the current available flexibility in the generation system is inadequate to balance real-time wind power fluctuations and prediction errors. Consequently, large amounts of wind curtailment and demand shedding may be expected. Therefore, current reserve requirements should be revised, in order to reliably facilitate wind power into the system. Furthermore, the impact of introducing natural gas for electricity generation in Cyprus on the reserve requirements, following wind power integration, is examined.     

Contribution of pumped hydro storage to integration of wind power in Kenya: An optimal control approach

This paper investigates the benefit of optimally integrating wind power in Kenya with pumped hydro storage. The approach includes development of an optimal control strategy to deploy paired wind and pumped hydro storage resources, for the Lake Turkana Wind Power project. The stochastic model, which maximizes expected revenue over the planning horizon, is developed taking into the consideration the structure and running of the Kenya electricity market. The 300 MW Lake Turkana Wind Power wind farm is simulated using wind speed data from Marsabit, which is in close proximity to the Lake Turkana region. From the simulation of the wind farm, we find that the daily pattern exhibited by the wind speeds, does not match the average daily load pattern. Pumped hydro storage reduces the systems total power output shortage by 46%. This approach to operation could alleviate the significant economic burden of the take-or-pay purchase agreement that led to the removal of financial backing of the project by the World Bank. The use of pumped hydro storage in conjunction with the wind farm is also found to increase the expected daily revenue of the wind farm by over ten thousand dollars.     

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.     

Power output variations of co-located offshore wind turbines and wave energy converters in California

The electric power generation of co-located offshore wind turbines and wave energy converters along the California coast is investigated. Meteorological wind and wave data from the National Buoy Data Center were used to estimate the hourly power output from offshore wind turbines and wave energy converters at the sites of the buoys. The data set from 12 buoys consists of over 1,000,000 h of simultaneous hourly mean wind and wave measurements. At the buoys, offshore wind farms would have capacity factors ranging from 30% to 50%, and wave farms would have capacity factors ranging from 22% to 29%. An analysis of the power output indicates that co-located offshore wind and wave energy farms generate less variable power output than a wind or wave farm operating alone. The reduction in variability results from the low temporal correlation of the resources and occurs on all time scales. Aggregate power from a co-located wind and wave farm achieves reductions in variability equivalent to aggregating power from two offshore wind farms approximately 500 km apart or two wave farms approximately 800 km apart. Combined wind and wave farms in California would have less than 100 h of no power output per year, compared to over 1000 h for offshore wind or over 200 h for wave farms alone. Ten offshore farms of wind, wave, or both modeled in the California power system would have capacity factors during the summer ranging from 21% (all wave) to 36% (all wind) with combined wind and wave farms between 21% and 36%. The capacity credits for these farms range from 16% to 24% with some combined wind and wave farms achieving capacity credits equal to or greater than a 100% wind farm because of their reduction in power output variability.     

Estimation of variability and predictability of large‐scale wind energy in The Netherlands

This paper presents a data‐driven approach for estimating the degree of variability and predictability associated with large‐scale wind energy production for a planned integration in a given geographical area, with an application to The Netherlands. A new method is presented for generating realistic time series of aggregated wind power realizations and forecasts. To this end, simultaneous wind speed time series—both actual and predicted—at planned wind farm locations are needed, but not always available. A 1‐year data set of 10‐min averaged wind speeds measured at several weather stations is used. The measurements are first transformed from sensor height to hub height, then spatially interpolated using multivariate normal theory, and finally averaged over the market resolution time interval. Day‐ahead wind speed forecast time series are created from the atmospheric model HiRLAM (High Resolution Limited Area Model). Actual and forecasted wind speeds are passed through multi‐turbine power curves and summed up to create time series of actual and forecasted wind power. Two insights are derived from the developed data set: the degree of long‐term variability and the degree of predictability when Dutch wind energy production is aggregated at the national or at the market participant level. For a 7.8 GW installed wind power scenario, at the system level, the imbalance energy requirements due to wind variations across 15‐min intervals are ±14% of the total installed capacity, while the imbalance due to forecast errors vary between 53% for down‐ and 56% for up‐regulation. When aggregating at the market participant level, the balancing energy requirements are 2–3% higher. Copyright © 2008 John Wiley & Sons, Ltd.     

The impact of large scale atmospheric circulation patterns on wind power generation and its potential predictability: A case study over the UK

Over recent years there has been an increasing deployment of renewable energy generation technologies, particularly large-scale wind farms. As wind farm deployment increases, it is vital to gain a good understanding of how the energy produced is affected by climate variations, over a wide range of time-scales, from short (hours to weeks) to long (months to decades) periods.By relating wind speed at specific sites in the UK to a large-scale climate pattern (the North Atlantic Oscillation or “NAO”), the power generated by a modelled wind turbine under three different NAO states is calculated. It was found that the wind conditions under these NAO states may yield a difference in the mean wind power output of up to 10%. A simple model is used to demonstrate that forecasts of future NAO states can potentially be used to improve month-ahead statistical forecasts of monthly-mean wind power generation.The results confirm that the NAO has a significant impact on the hourly-, daily- and monthly-mean power output distributions from the turbine with important implications for (a) the use of meteorological data (e.g. their relationship to large-scale climate patterns) in wind farm site assessment and, (b) the utilisation of seasonal-to-decadal climate forecasts to estimate future wind farm power output. This suggests that further research into the links between large-scale climate variability and wind power generation is both necessary and valuable.     

Pre-feasibility study of wind power generation in holyrood, newfoundland

The largest commercial thermal generating plant in Newfoundland is in Holyrood, Conception Bay. It has a generating capacity of 500 MW of electricity. During peak generation (winter months), the plant runs at near capacity with generation reaching as high as 500 MW. In addition to thermal generation about 900 MW is supplied to the grid by a number of hydro plants. This paper presents a pre-feasibility study of 25% of thermal power generation using wind turbines in the Holyrood area. Purpose of supplementing power generation from the thermal plant is to reduce emissions and fuel costs. Simulation results indicate that 16 Enercon's E-66, 2 MW wind turbines if installed near the site will provide a 25% renewable fraction. Supplementing 25% of the generation at Holyrood with wind power will reduce the cost of energy by CA$0.013/kWh. It will also reduce carbon emissions by almost 200,000 tons/year. This study indicates that a wind farm project at the Holyrood thermal generation station site is feasible.     

Wind resource assessment of the Southern Appalachian Ridges in the Southeastern United States

The analysis of wind data collected throughout the Southern Appalachian Mountain region of the Southeastern US is presented. Data were collected at 50 m above ground level on nine ridge top sites between 2002 and 2005. Monthly average wind speeds, power densities, wind sheers, and turbulence intensities, along with monthly maximum gusts, are presented. Measured annual average wind speeds are compared to AWS TrueWind predictions. Diurnal variations in wind speed are also reported. Annual wind roses for each site are presented. Annual wind speeds range from 5.5 to 7.4 m/s with the highest annual average wind speeds found on ridges near the northern TN–NC border. A 20% winter and nighttime enhancement of the wind speed was observed. The prevailing wind is from the westerly directions. The estimated annual energy outputs from a small wind farm consisting of fifteen 1.5 MW GE turbines range from 50 to 75 MkWh, and estimated capacity factors range from 25% to 35%. This analysis suggests that ridges in the region are suitable for utility-scale wind development.     

Impacts of large-scale wave integration into a transmission-constrained grid

This paper presents a study of large-scale wave energy integration in which transmission constraints are considered. The Vancouver Island electrical grid is considered and is modelled using PLEXOS^® Integrated Energy Model software. The model incorporates the current transmission grid, the existing fleet of main generation stations and ten potential wave farm sites with a total generation capacity of 500 MW. The objectives are to investigate: 1) the potential contribution of wave power toward energy self-sufficiency, 2) the effects of transmission constraints on the viability of alternative wave farm sites, 3) the impacts of wave integration on the load profile. Findings suggest that wave energy integration can significantly reduce the energy dependency on neighbouring jurisdictions but the current grid infrastructure is not adequate to fully support 500 MW of wave power. In this regard, it is shown that potential wave power integration can significantly benefit from transmission expansion for particular pathways. Further, results show that wave integration leads to reductions in the share of energy supplied from other sources and that this reduction follows an annual pattern. This periodic trend is particularly important for a hydro-dominated (energy-limited) grid where water level in reservoirs is managed on monthly and yearly bases.     

Wind resource assessment of the Jordanian southern region

Wind data in terms of annual, seasonal and diurnal variations at Queira, which is located in the southern part of Jordan was studied and analyzed. For this purpose, long-term wind speed data for a period of 12 years (1990–2001) was used. The analysis showed that the seasonal and diurnal pattern of wind speed matches the electricity load pattern of the location. Higher winds of the order of 6 m/s and more were observed during both the summer months of the year (May–August) and peak hours (1100–1500) of the day. The wind duration availability is discussed as the number of hours during which the wind remained in certain wind speed intervals. The possibility of electricity generation from wind power at Queira was carried out using three different wind energy systems of sizes 100, 22 kW rated power, and a wind farm consisting of 25 small wind turbines; each of 4 kW rated power with hub heights of 20, 30, and 40 m. The energy production analysis showed higher production from the wind farm with a 20 m hub height than the production from the other two wind turbines. Similarly, the cost analysis showed that the lowest generation costs of 1 kWh were obtained for the wind farm compared to the other two wind turbines. The possibility of water pumping using the wind farm was also investigated. The results showed that water pumping using wind turbines is an appropriate alternative for the photovoltaic water pumping in the region.     

Variability and uncertainty of wind power in the California electric power system

The California generation fleet manages the existing variability and uncertainty in the demand for electric power (load). When wind power is added, the dispatchable generators manage the variability and uncertainty of the net load (load minus wind power). The variability and uncertainty of the load and the net load are compared when 8790 MW of wind power are added to the California power system, a level expected when California achieves its 33% renewable portfolio standard, using a data set of 26,296 h of synchronous historic load and modeled historic wind power output. Variability was calculated as the rate of change in power generated by wind farms or consumed by the load from 1 h to the next (MW/h). Uncertainty was calculated as the 1 h ahead forecast error [MW] of the wind power or of the load. The data show that wind power adds no additional variability than is already present in the load variability. However, wind power adds additional uncertainty through increased forecast errors in the net load compared with the load. Forecast errors in the net load increase 18.7% for negative forecast errors (actual less than forecast) and 5.4% for positive forecast errors (actual greater than forecast). The increase in negative forecast errors occurs only during the afternoon hours when negative load forecasts and positive wind forecasts are strongly correlated. Managing the integration of wind power in the California power system should focus on reducing wind power forecast uncertainty for wind ramp ups during the afternoon hours. Copyright © 2013 John Wiley & Sons, Ltd.     

Estimation of wind energy production in various sites in Australia for different wind turbine classes: A comparative technical and economic assessment

This study examines the effect of different wind turbine classes on the electricity production of wind farms in three areas of Australia, which present low, low to medium, and medium to high wind potential: Gingin, Armidale, and Gold Coast Seaway. Wind turbine classes determine the suitability of installing a wind turbine in a particulate site. Wind turbine data from six different manufacturers have been used. For each manufacturer, at lest two wind turbines with identical rated power (in the range of 1.5 MW–3 MW) and different wind turbine classes (IEC I, IEC II and/or IEC III) are compared. The results show the superiority of wind turbines that are designed for lower wind speeds (higher IEC class) in all three locations, in terms of energy production. This improvement is higher for the locations with lower and medium wind potential (Gingin and Armidale), and varies from 5% to 55%. Moreover, this study investigates the economical feasibility of a 30 MW wind farm, for all combinations of site locations and wind turbine models.     

A review on scale and siting of wind farms in China

Using a wind power information system, which is based on the geographic information system (GIS), this paper presents a statistical analysis of built and approved wind farms to the end of 2008. The average capacity of wind turbine generators (WTGs) and the scale of wind farms are investigated. The geographical distribution of wind farms and the main factors affecting wind farm siting are analysed. The results show: (i) The average capacity of WTGs is increasing; MW scale WTGs have become the mainstream product in the China market. (ii) Because of the national wind project approval policy, most of the wind farms have installed capacities of just under 50 MW. (iii) When siting a wind farm, wind resource is still the predominant factor being considered, while grid connection is still the main constraint in this stage. (iv) Concerning land use, among the wind farms built by 2008, 40% use grasslands, 31% use agricultural land, 17% use desert or bare lands, while 12% use farmlands. (v) Statistics show 88.6% of the built wind farms have elevation change of less than 300 m, and 90% of the built wind farms have GIS slopes of less than 10°. (vi) The geographical distribution of wind farms reveals a highly concentrated deployment tendency, 58.7% of all the newly built wind farms in 2008 are within 10 km of existing wind farms. Copyright © 2010 John Wiley & Sons, Ltd.     

Wind energy assessment and wind farm simulation in Triunfo – Pernambuco,Brazil

This paper presents a wind energy assessment and a wind farm simulation in the city of Triunfo in the state of Pernambuco in the northeast region of Brazil. The wind data were obtained from the SONDA (Sistema de Organização Nacional de Dados Ambientais) project’s meteor station (wind speed, wind direction and temperature) at both heights of 50 m during a period of time of 30 months. The Triunfo wind characterization and wind power potential assessment study shows an average wind speed (V) of 11.27 m/s (predominant Southeast wind direction), an average wind power density (P/A_T) of 1.672 W/m² and Weibull parameters shape (K) and scale (A) respectively equal to 2.0 and 12.7 m/s. Those values demonstrate an important wind potential in this region for future wind farm prospection. The wind farm (TRI) was simulated by using 850 kW wind turbines given a total of 20 MW installed. The simulated results show(s) an AEP (annual energy produced) of 111.4 GWh, a capacity factor (C_f) of 62% and a total of 5.462 h of operation by year (full load hours). The economical simulated results show(s) a Pay-back of 3 years Internal Rate of Return (IRR) of 47% and Net Present Value (NPV) of 85.506 k€ (both in a period of time of 20 years).     

California offshore wind energy potential

This study combines multi-year mesoscale modeling results, validated using offshore buoys with high-resolution bathymetry to create a wind energy resource assessment for offshore California (CA). The siting of an offshore wind farm is limited by water depth, with shallow water being generally preferable economically. Acceptable depths for offshore wind farms are divided into three categories: ≤20 m depth for monopile turbine foundations, ≤50 m depth for multi-leg turbine foundations, and ≤200 m depth for deep water floating turbines. The CA coast was further divided into three logical areas for analysis: Northern, Central, and Southern CA. A mesoscale meteorological model was then used at high horizontal resolution (5 and 1.67 km) to calculate annual 80 m wind speeds (turbine hub height) for each area, based on the average of the seasonal months January, April, July, and October of 2005/2006 and the entirety of 2007 (12 months). A 5 MW offshore wind turbine was used to create a preliminary resource assessment for offshore CA. Each geographical region was then characterized by its coastal transmission access, water depth, wind turbine development potential, and average 80 m wind speed. Initial estimates show that 1.4–2.3 GW, 4.4–8.3 GW, and 52.8–64.9 GW of deliverable power could be harnessed from offshore CA using monopile, multi-leg, and floating turbine foundations, respectively. A single proposed wind farm near Cape Mendocino could deliver an average 800 MW of gross renewable power and reduce CA's current carbon emitting electricity generation 4% on an energy basis. Unlike most of California's land based wind farms which peak at night, the offshore winds near Cape Mendocino are consistently fast throughout the day and night during all four seasons.     

The world's largest all-vanadium redox flow battery energy storage system for a wind farm

风力发电具有明显的随机性,间歇性,不可控性和反调峰特性,风力发电的大规模并网给电网调峰和稳定,安全运行带来了巨大压力,造成弃风限电现象愈加严重,严重影响了风力资源的有效利用和经济效益.全钒液流电池储能电站在能量管理系统的调度下,对风力发电输出功率进行平滑,配合风电场功率预报系统,提高风电场跟踪计划发电能力,改善了风电场并网电能质量,降低了对电网的冲击与影响,同时也提高了风电场输出功率可控性,有利于提高电网对风电的接纳能力.国电龙源卧牛石风电场配套的5 MW/10 MW∙h全钒液流电池储能系统为目前世界上最大规模的全钒液流电池储能系统.本文介绍了该全钒液流电池技术特点和储能系统的设计,成组方案及功能,并对储能技术在可再生能源发展中的作用进行了展望.     

Variability in large‐scale wind power generation

The paper demonstrates the characteristics of wind power variability and net load variability in multiple power systems based on real data from multiple years. Demonstrated characteristics include probability distribution for different ramp durations, seasonal and diurnal variability and low net load events. The comparison shows regions with low variability (Sweden, Spain and Germany), medium variability (Portugal, Ireland, Finland and Denmark) and regions with higher variability (Quebec, Bonneville Power Administration and Electric Reliability Council of Texas in North America; Gansu, Jilin and Liaoning in China; and Norway and offshore wind power in Denmark). For regions with low variability, the maximum 1 h wind ramps are below 10% of nominal capacity, and for regions with high variability, they may be close to 30%. Wind power variability is mainly explained by the extent of geographical spread, but also higher capacity factor causes higher variability. It was also shown how wind power ramps are autocorrelated and dependent on the operating output level. When wind power was concentrated in smaller area, there were outliers with high changes in wind output, which were not present in large areas with well‐dispersed wind power. Copyright © 2015 John Wiley & Sons, Ltd.     

Guest Editorial: Introduction to the Special Issue on Wind Power

The twenty-seven papers in this special issue focus on wind power. The special issue highlights wind electricity's rapidly evolving influx into conventional power systems on a global scale. Some of the topics covered include farm case studies, failure surveys, and experience with wind power's integration into, and impact on, thermal generation. Other topics include wind power's environmental impact, novel generator design, and spinning reserve requirements. Voltage and reactive power control as well as maintenance management issues are also addressed.     

Generating wind time series as a hybrid of measured and simulated data

Certain applications, such as analysing the effect of a wind farm on grid frequency regulation, require several years of wind power data measured at intervals of a few seconds. We have developed a method to generate days to years of non‐stationary wind speed time series sampled at high rates by combining measured and simulated data. Measured wind speed data, typically 10–15 min averages, capture the non‐stationary characteristics of wind speed variation: diurnal variations, the passing of weather fronts, and seasonal variations. Simulated wind speed data, generated from spectral models, add realistic turbulence between the empirical data. The wind speed time series generated with this method agree very well with measured time series, both qualitatively and quantitatively. The power output of a wind turbine simulated with wind data generated by this method demonstrates energy production, ramp rates and reserve requirements that closely match the power output of a turbine simulated turbine with measured wind data. Copyright © 2011 John Wiley & Sons, Ltd.     

Assessing the economic wind power potential in Austria

In the European Union, electricity production from wind energy is projected to increase by approximately 16% until 2020. The Austrian energy plan aims at increasing the currently installed wind power capacity from approximately 1 GW to 3 GW until 2020 including an additional capacity of 700 MW until 2015. The aim of this analysis is to assess economically viable wind turbine sites under current feed-in tariffs considering constraints imposed by infrastructure, the natural environment and ecological preservation zones in Austria. We analyze whether the policy target of installing an additional wind power capacity of 700 MW until 2015 is attainable under current legislation and developed a GIS based decision system for wind turbine site selection.Results show that the current feed-in tariff of 9.7 ct kW h⁻¹ may trigger an additional installation of 3544 MW. The current feed-in tariff can therefore be considered too high as wind power deployment would exceed the target by far. Our results indicate that the targets may be attained more cost-effectively by applying a lower feed-in tariff of 9.1 ct kW h⁻¹. Thus, windfall profits at favorable sites and deadweight losses of policy intervention can be minimized while still guaranteeing the deployment of additional wind power capacities.