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.     

A spatial and temporal correlation analysis of aggregate wind power in an ideally interconnected Europe

Studies have shown that a large geographic spread of installed capacity can reduce wind power variability and smooth production. This could be achieved by using electricity interconnections and storage systems. However, interconnections and storage are not totally flexible, so it is essential to understand the wind power correlation in order to address power system constraints in systems with large and growing wind power penetrations. In this study, the spatial and temporal correlation of wind power generation across several European Union countries was examined to understand how wind ‘travels’ across Europe. Three years of historical hourly wind power generation data from 10 countries were analysed. The results of the analysis were then compared with two other studies focused on the Nordic region and the USA. The findings show that similar general correlation characteristics do exist between European country pairs. This is of particular importance when planning and operating interconnector flows, storage optimization and cross‐border power trading. Copyright © 2017 The Authors Wind Energy Published by John Wiley & Sons Ltd     

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.     

Characteristics of day‐ahead wind power forecast errors in Nordic countries and benefits of aggregation

The growing proportion of wind power in the Nordic power system increases day‐ahead forecasting errors, which have a link to the rising need for balancing power. However, having a large interconnected synchronous power system has its benefits, because it enables to aggregate imbalances from large geographical areas. In this paper, day‐ahead forecast errors from four Nordic countries and the impacts of wind power plant dispersion on forecast errors in areas of different sizes are studied. The forecast accuracy in different regions depends on the amount of the total wind power capacity in the region, how dispersed the capacity is and the forecast model applied. Further, there is a saturation effect involved, after which the reduction in the relative forecast error is not very large anymore. The correlations of day‐ahead forecast errors between areas decline rapidly when the distance increases. All error statistics show a strong decreasing trend up to the area sizes of 50,000 km². The average mean absolute error (MAE) in different regions is 5.7% of installed capacity. However, MAE of a smaller area can be over 8% of the capacity, but when all the Nordic regions are aggregated together, the capacity‐normalized MAE decreases to 2.5%. The average of the largest errors for different regions is 39.8% and when looking at the largest forecast errors for smaller areas, the largest errors can exceed 80% of the installed capacity, whereas at the Nordic level, the maximum forecast error is only 13.5% of the installed capacity. Copyright © 2016 John Wiley & Sons, Ltd.     

Nordic hydropower flexibility and transmission expansion to support integration of North European wind power

The expected increase of wind power production in the North and Baltic Seas will substantially increase the variability of the generation portfolio in Northern Europe. Access to available resources of flexible power production will be necessary to support the power system against this variability. Since the Nordic hydro‐based power system can provide such resources, a stronger interconnection between continental Europe and the Nordic region seems to be beneficial. This paper assesses the challenges related to wind power production variability, especially offshore, in the North and Baltic Seas. Assessment on the transmission grid needed for both harvesting the available wind production located far away from load centres and to enable the optimal use of hydropower flexibility is studied in a long‐term cost‐benefit analysis. Special focus is devoted to the role of an offshore grid structure and the impact of onshore grid constraints. The analysis includes two interrelated simulation steps. The first step focuses on the strategic use of hydro energy in the day‐ahead market, where detailed modelling of water courses and hydro production in the Nordic region is considered. Then, in a second step, flow‐based simulations are conducted on a detailed grid model for the whole European system. The results show that long‐term strategies for the expansion of offshore and onshore grids must be defined in a coordinated way to ensure optimal developments. Copyright © 2014 John Wiley & Sons, Ltd.     

Correlation and statistical characteristics of aggregate wind power in large transcontinental systems

Studies have shown that the unpredictability and variability of wind power is reduced in systems with large numbers of geographically diverse wind plants. These effects are caused by the decreased correlation of power output between wind plants as their separation and diversity in terrain increases. One way that system operators have increased geographic diversity is by enlarging balancing areas through the physical or administrative connection of adjacent systems. This strategy can be extended from the regional level to the transcontinental level. As such, it is important to study the correlation and statistical characteristics of aggregate wind power between large, distant systems. This paper analyzes multi‐year historical data from four North American system operators—Bonneville Power Administration, Electric Reliability Council of Texas, Midwest Independent Transmission System Operator and PJM—to see how effective transcontinental interconnection of systems is at enabling wind plant integration. The effects of separation and timescale on correlations of instantaneous and hourly variations are analyzed. The analysis is complemented by a study of a hypothetical transcontinental connection of the systems across yearly, monthly, daily and hourly timescales. The results show that correlations between large systems exhibit similar characteristics as the correlations between individual wind plants, but are somewhat larger in magnitude. The transcontinental system exhibits a close to normal distribution of power output and decreased variability, but there is still appreciable and statistically significant correlation at the longer timescales driven by seasonal and diurnal forcing, as well as synoptic weather systems. Copyright © 2013 John Wiley & Sons, Ltd.     

Dampening variations in wind power generation—the effect of optimizing geographic location of generating sites

This paper presents a method to dampen the variations in the output of aggregated wind power through geographic allocation of wind power generation sites. The method, which is based on the sequential optimization of site localization, is applied to the Nordic countries and Germany, using meteorologic wind speed data as the input. The results show that the variability in aggregated wind power output mitigates by applying sequential optimization. For the data used in this work, the coefficient of variation (standard deviation/mean) was 0.54 for the optimized aggregation of sites, as compared with 0.91 for the present day installation. An optimal allocation of wind power generation site reduces the need for dispatch and other measures to deal with the intermittent nature of wind power. Copyright © 2013 John Wiley & Sons, Ltd.     

Integration of wind power in the liberalized Dutch electricity market

Wind power is becoming a large‐scale electricity generation technology in a number of European countries, including the Netherlands. Owing to the variability and unpredictability of wind power production, large‐scale wind power can be foreseen to have large consequences for balancing generation and demand in power systems. As an essential aspect of the Dutch market design, participants are encouraged to act according to their energy programs, as submitted day‐ahead to the system operator. This program responsibility shifts the burden of balancing wind power away from the system operator to the market. However, the system operator remains the responsible party for balancing any generation/load imbalances that may still be arising in real time. In this article, features that are unique for the Dutch market design are presented and their implications on the system integration of wind power are investigated. It is shown that the Dutch market design penalizes the intermittent nature of wind power. A discussion of opportunities and threats of balancing wind power by use of market forces is provided. Last, an outline is given of future work. Copyright © 2006 John Wiley &Sons, Ltd.     

Assessment of offshore wind farm characteristics with the cloud resolving storm simulator: A case study in Japan

Wind conditions and output power characteristics of a wind farm in Japan are evaluated with highly resolved weather predictions from the so‐called cloud resolving storm simulator. One year of 30‐hour‐ahead predictions with 2‐km spatial resolution and 1‐hour time resolution are evaluated against 10‐minute averaged measurements (averaged to hourly data) from the wind farm. Also, extremely detailed shorter‐term predictions with 200‐m spatial resolution and 1‐second time resolution are evaluated against 1‐Hz measurements. For the hourly data, wind speeds are predicted with an RMSE of 3.0 to 3.5 m/s, and wind power with about 0.3 per unit. Wind direction is predicted with a standard deviation of errors of 16° to 28° for hourly data, and generally below 10° for the 1‐Hz data. We show that wind power variability—here in terms of increments—can be assessed on the timescale of several hours. The measured and predicted wind spectra are found similar on both short and long timescales.     

A statistical model for comparing future wind power scenarios with varying geographical distribution of installed generation capacity

As installed wind generation capacity increases, understanding the effect of wind power on the electric power system is becoming more important. This paper introduces a statistical model that can be used to estimate the variability in wind generation and assess the risk of wind generation contingencies over a large geographical area. The analysis of the installed wind generation capacities is separated from the analysis of the spatial and temporal dependency structures. This enables the study of different future wind power scenarios with varying generation capacities. The model is built on measured hourly wind generation data from Denmark, Estonia, Finland and Sweden. Three scenarios with different geographical distributions of wind power are compared to show the applicability of the model for power system planning. A method for finding the scenario with the minimum variance of the aggregate wind generation is introduced. As the geographical distribution of wind power can be affected by subsidies and other incentives, the presented results can have policy implications. Copyright © 2015 John Wiley & Sons, Ltd.     

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.     

Comparison of potential power production at on‐ and offshore sites

This article presents analyses of the potential power production from turbines located in the near‐shore and offshore environment relative to an onshore location, using half‐hourly average wind speed data from four sites in the Danish wind monitoring network. These measurement sites are located in a relatively high wind speed environment, and data from these sites indicate a high degree of spatial coherence. For these sites and representative turbine specifications (rated power 1·3–2 W) the fraction of time with power output in excess of 500 kW is twice as high for the offshore location as for the land site. Also, the fraction of time with negligible power production (defined as <100 kW output from the turbines described herein) is less than 20% for the offshore site and twice as high at the land‐based location. Capacity factors are higher for coastal sites than for the land site, and the annual capacity factor for the offshore location is twice that of the land site. Potential power output at the offshore site exhibits approximately the same seasonal variation as at the land site but little diurnal variation. Copyright © 2001 John Wiley & Sons, Ltd.     

Time series modelling of power output for large‐scale wind fleets

Simulations of power systems with high wind penetration need to represent the stochastic output of the wind farms. Many studies use historic wind data directly in the simulation. However, even if historic data are used to drive the realized wind output in scheduling simulations, a model of the wind's statistical properties may be needed to inform the commitment decisions for the dispatchable units. There are very few published studies that fit models to the power output of nation‐sized wind fleets rather than the output at a single location. We fitted a time series model to hourly, time‐averaged, aggregated wind power data from New Zealand, Denmark and Germany, based on univariate, second‐order autoregressive drivers. Our model is designed to reproduce the asymptotic distribution of power output, the diurnal variation and the volatility of power output over timescales up to several hours. For the cases examined here, it was also found to provide a generally good representation of the overall distribution of power output changes and the variation of volatility with power output level, as well as an acceptable representation of the distribution of calm periods. Copyright © 2011 John Wiley & Sons, Ltd.     

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.     

Simulating intra‐hourly wind power fluctuations on a power system level

In wind integration studies, sub‐hourly, load synchronous wind data are often preferable. These datasets can be generated by a hybrid approach, combining hourly measurements or output from meteorological models with a stochastic simulation of the high‐frequency fluctuations. This paper presents a method for simulating aggregated intra‐hourly wind power fluctuations for a power system, taking into account the time‐varying volatility seen in measurements. Some key elements in the modelling were transformations to stationarity, the use of frequency domain techniques including a search for appropriate phase angles and an adjustment of the resulting time series in order to get correct hourly means. Generation data from Denmark and Germany with 5 and 15 min temporal resolution were used for training models. It is shown that the distribution and non‐stationarity of simulated deviations from hourly means closely follow those of measurements. Power spectral densities and step change distributions agree well. Of particular importance is that the results are good also when the training and objective power systems are not the same. The computational cost is low in comparison with other approaches for generating high‐frequency data. Copyright © 2016 John Wiley & Sons, Ltd.     

Power smoothing in large wind farms using optimal control of rotating kinetic energy reserves

In large wind farms, self‐induced turbulence levels significantly increase the variability of generated power in a range of time scales from a few seconds to several minutes. In the current study, we investigate the potential for reducing this type of variability by dynamically controlling the rotating kinetic energy reserves that are present in the farm's wind turbines. To this end, we reduce the burden of frequency regulation on remaining conventional units when they are displaced in favor of wind turbines. We focus on the development of a theoretical benchmark framework in which we explore the trade‐off between high energy extraction and low variability using optimal coordinated control of multiple turbines subject to a turbulent wind field. This wind field is obtained from a large‐eddy simulation of a fully developed wind farm boundary layer. The controls that are optimized are the electric torque and the pitch angles of the individual turbines as function of time so that turbines are accelerated or decelerated to optimally extract or store energy in the turbines' rotating inertia. Results are presented in terms of Pareto fronts (i.e., curves with optimal trade‐offs), and we find that power variations can be significantly reduced with limited loss of extracted energy. For a one‐turbine case, such an optimal control leads to large potential reductions of variability but mainly for time scales below 10 s if we limit power losses to a few percent. Variability over longer time scales (10–100 s) is reduced considerably more for coordinated control. For instance, restricting the energy‐loss incurred with smoothing to 1%, and looking at time scales of 50 s, we manage to reduce variability with a factor of 6 for a coordinated case with 24 turbines, compared with a factor of 1.4 for an uncoordinated case. Copyright © 2014 John Wiley & Sons, Ltd.     

Cost‐optimized allocation of wind power investments: a Nordic–German perspective

Using a linear cost minimization model with a 1 h time resolution, we investigated the influence of geographic allocation of wind power on large‐scale wind power investments, taking into account wind conditions, distance to load, and the nature of the power system in place (i.e. power generation and transmission capacities). We employed a hypothetical case in which a 20% wind power share of total electricity demand is applied to the Nordic–German power system. Free, i.e. geographically unrestricted, allocation of new wind power capacity is compared with a case in which national planning frameworks impose national limitations on wind power penetration levels. Given the cost assumptions made in the present work, the prospect of increasing the wind power capacity factor from 20 to 30% could motivate investments in transmission capacity from northern Scandinavia to continental Europe. The results obtained using the model show that the distribution of wind farms between regions with favorable wind conditions is dependent upon two factors: (i) the extent to which existing lines can be used to transmit the electricity that results from the new wind power and (ii) the correlation for wind power generation between the exporting region and the wind power generation already in place. In addition, the results indicate that there is little difference, i.e. just over 1%, in total yearly cost between the free allocation of new wind power and an allocation that complies with national planning frameworks. However, on a national level, there are significant differences with respect to investments in transmission and wind power capacities and the replacement of conventional power generation. Copyright © 2012 John Wiley & Sons, Ltd.     

Area price and demand response in a market with 25% wind power

Denmark, east and west of the Great Belt are bidding areas with separate hourly area prices for the Nord Pool power exchange, covering four Nordic countries and parts of Germany. The share of wind power has now increased to 25% on an annual basis in western Denmark. This has a significant impact not only on the electricity wholesale prices, but also on the development of the market. Hourly market data are available from the website of Danish TSO from 1999. In this paper these data are analysed for the period 2004–2010. Electricity generators and customers may respond to hourly price variations, which can improve market efficiency, and a welfare gain is obtained. An important limitation for demand response is events of several consecutive hours with extreme values. The analysis in this paper is a summary and update of some of the issues covered by the EU RESPOND project. It shows that extreme events were few, and the current infrastructure and market organisation have been able to handle the amount of wind power installed so far. This recommends that geographical bidding area for the wholesale electricity market reflects external transmission constraints caused by wind power.     

The effect of spatial dispersion of wind power plants on the curtailment of wind power in the Greek power supply system

To meet the national target of 29% for electricity production from renewable energy sources by 2020 in Greece, effective implementation of massive wind power installed capacity into the power supply system is required. In such a situation, the effective absorption of wind energy production is an important issue in a relatively small and weak power system such as that of Greece, which has limited existing interconnections with neighboring countries. The curtailment of wind power is sometimes necessary in autonomous systems with large wind energy penetration. The absorption or curtailment of wind power is strongly affected by the spatial dispersion of wind power installations. In the present paper, a methodology for estimating this effect is presented and applied for the power supply system of Greece. The method is based on probability theory, and makes use of wind forecasting models to represent the wind energy potential over any candidate area for future wind farm installations in the country. Moreover, technical constraints imposed by the power supply system management, the commitment of power plants and the load dispatch strategies are taken into account to maximize the wind energy penetration levels while ensuring reliable operation of the system. Representative wind power development scenarios are studied and evaluated. Results show that the spatial dispersion of wind power plants contributes beneficially to the wind energy penetration levels that can be accepted by the power system. Copyright © 2009 John Wiley & Sons, Ltd.     

国外风电并网特点及对我国的启示

国外风电发达国家已有风电场大多装机规模较小,主要是分散接入配电网就地消纳。风电大规模并网依赖于坚强电网的支撑,同时也需要其他电源的支持和协调发展。如丹麦东部电网通过交流输电线路与挪威、瑞典、芬兰等国组成北欧电网,西部电网则通过德国电网与欧洲大陆互联电网相联,北欧电网中的大量水电为丹麦风电提供了足够的调峰支持;而美国大量具有灵活调节能力的燃气电站为风电快速发展提供了保障。国外针对未来风电大规模开发,规划通过高电压等级线路接入电网,远距离输送至负荷中心地区,并且扩展输电网以扩大风电消纳范围和规模。风电发达国家都制定了严格的并网导则且强制执行,风电收购政策根据风电发展的不同阶段不断调整,同时广泛开展了风电功率预测工作,并对风电进行有效调控。我国风电在持续快速发展中暴露出一些问题,如风电开发缺乏统一规划,配套电网建设难度较大;系统调峰能力不足;电网建设滞后于电源建设,尤其是跨大区电网的互联规模不足;风电技术和运行水平较低,相关政策有待完善等。建议我国应努力优化电源结构,增加电源装机中调峰电源和灵活调节电源的比重;建设坚强智能电网,解决风电大规模接入和输送问题;完善相关法律和政策支持体系。