Heating with wind: Economics of heat pumps and variable renewables

With the growth of wind and solar energy in electricity supply, the electrification of space and water heating is becoming a promising decarbonization option. In turn, such electrification may help the power system integration of variable renewables, for two reasons: thermal storage could provide low-cost flexibility, and heat demand is seasonally correlated with wind power. However, temporal fluctuations in heat demand may also imply new challenges for the power system. This study assesses the economic characteristics of electric heat pumps and wind energy and studies their interaction on wholesale electricity markets. Using a numerical electricity market model, we estimate the economic value of wind energy and the economic cost of powering heat pumps. We find that, just as expanding wind energy depresses its €/MWh_el value, adopting heat pumps increases their €/MWh_el cost. This rise can be mitigated by synergistic effects with wind power, “system-friendly” heat pump technology, and thermal storage. Furthermore, heat pumps raise the wind market value, but this effect vanishes if accounting for the additional wind energy needed to serve the heat pump load. Thermal storage facilitates the system integration of wind power but competes with other flexibility options. For an efficient adoption of heat pumps and thermal storage, we argue that retail tariffs for heat pump customers should reflect their underlying economic cost.     

Boosting UK renewables: The market way

Why, after all these years of grants, subsidies and central government planning does Britain still have only 3% of electricity from renewable sources? Could it be that government policy is not working? Are there better market driven ways to do it? Dan Lewis provides his perspective on the current UK situation.     

Analyzing major challenges of wind and solar variability in power systems

Ambitious policy targets together with current and projected high growth rates indicate that future power systems will likely show substantially increased generation from renewable energy sources. A large share will come from the variable renewable energy (VRE) sources wind and solar photovoltaics (PV); however, integrating wind and solar causes challenges for existing power systems. In this paper we analyze three major integration challenges related to the structural matching of demand with the supply of wind and solar power: low capacity credit, reduced utilization of dispatchable plants, and over-produced generation. Based on residual load duration curves we define corresponding challenge variables and estimate their dependence on region (US Indiana and Germany), penetration and mix of wind and solar generation. Results show that the impacts of increasing wind and solar shares can become substantial, and increase with penetration, independently of mix and region. Solar PV at low penetrations is much easier to integrate in many areas of the US than in Germany; however, some impacts (e.g. over-production) increase significantly with higher shares. For wind power, the impacts increase rather moderately and are fairly similar in US Indiana and Germany.     

The effect of variable renewable energy sources on electricity price volatility: the case of the Iberian market

The relationship between variable renewable energy supply (V-RES) and electricity price volatility is a controversial issue in the economic literature. In general, the literature has been inconclusive about the sign of the impact of installed capacity of these technologies on price volatility. This paper investigates the impact of V-RES on price volatility for the Iberian Market of Electricity (MIBEL), in the period ranging from 2010 to 2015. Using regression analysis and EGARCH models, we conclude that V-RES, and more specifically wind power supply, heightens price volatility. Likewise, greater intraday variability of V-RES also induces higher price volatility. Finally, following an analysis of the connection with the French market, we find that market coupling could help alleviate the sensitivity of price volatility to wind power supply variability.     

The cannibalization effect of wind and solar in the California wholesale electricity market

Increasing penetration of zero marginal cost variable renewable technologies cause the decline of wholesale electricity prices due to the merit-order effect. This causes a “cannibalization effect” through which increasing renewable technologies’ penetration undermines their own value. We calculate solar and wind daily unit revenues (generation weighted electricity prices) and value factors (unit revenues divided by average electricity prices) from hourly data of the day-ahead California wholesale electricity market (CAISO) for the period January 2013 to June 2017. We then perform a time series econometric analysis to test the absolute (unit revenues) and relative (value factors) cannibalization effect of solar and wind technologies, as well as the cross-cannibalization effects between technologies. We find both absolute and relative cannibalization effect for both solar and wind, but while wind penetration reduces the value factor of solar, solar penetration increases wind value factor, at least at high penetration and low consumption levels. We explore non-linearities and also find that the cannibalization effect is stronger at low consumption and high wind/solar penetration levels. This entails that wind and (mainly) solar competitiveness could be jeopardized unless additional mitigation measures such as storage, demand management or intercontinental interconnections are taken.     

The effect of timescales on wind farm power variability with nonlinear model predictive control

Model predictive control techniques enable operators to balance multiple objectives in large wind farms, but the controller design depends on modeling effects that propagate at different timescales. This paper uses nonlinear model predictive control to investigate how wind farm power variability can be reduced both by varying ratios of three timescales impacting the system control and by inclusion of a power variability minimization measure in the controller objective function. Tests were conducted to assess how different timescale ratios affect the average farm power and power variability. Power variability measures are shown to be sensitive to the ratio of the incident wind period and the turbine time delay, particularly for cases with dominant incident wind frequencies. The average farm power increases in a series of steps as the controller time horizon increases, which corresponds to time horizon values required for wakes disturbances to propagate to downstream turbines. A second set of tests was conducted in which various measures of power variability were incorporated into the controller objective function and shown to yield significant reductions in farm power variability without significant reductions in farm power output. The controller was found to utilize two different approaches for achieving power variability reduction depending on the formulation of the controller objective function. These results have important implications for the design and operation of wind power plants, including the importance of considering the frequency components of wind during turbine siting and the potential to reduce power variability through the use of farm‐level coordinated control. Copyright © 2017 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 dark side of the sun: How solar power production affects the market value of solar and gas sources

Using daily data for the Italian wholesale day-ahead power market over the period 2008–2013, we assess the impact of solar production on the market value of solar and gas sources, defined using the concepts of value factor and unit revenues. We find that, on average, solar generation negatively affects the solar source market value, causing a departure from the grid parity condition and mining their competitiveness once public incentives are removed. This negative relation is not constant over time and becomes stronger for increasing solar penetration in the energy mix. Interestingly, the opposite is found when looking at gas. While the relation between solar production and the gas market value is negative or not significant when the former is low, it turns positive for higher levels of solar production. This is the result of a change in gas producers' bidding strategies. Indeed, in the Italian power market the highest hourly price has shifted from the peak daytime, when solar production is concentrated, to the off-peak nighttime, when solar is absent from the market and gas can exploit temporary market power.     

Supporting solar power in renewables portfolio standards: Experience from the United States

Renewables portfolio standards (RPS) have become an increasingly popular option for encouraging the deployment of renewable electricity. It is a relatively new policy mechanism, however, and experience with its use is only beginning to emerge. One key concern is whether RPS policies offer adequate support to a wide range of renewable energy technologies and applications or whether, alternatively, they will favor a small number of the currently least-cost forms of renewable energy. This article documents the design of and early experience with state-level RPS programs in the United States that have been specifically tailored to encourage a wider diversity of renewable energy technologies, and solar energy in particular. As shown here, state-level RPS programs specifically designed to support solar have already proven to be an important driver for solar energy deployment, and those impacts are projected to build in the coming years. State experience in supporting solar energy with RPS programs is mixed, however, and full compliance with existing requirements has not been achieved. The comparative experiences described herein highlight the opportunities and challenges of applying an RPS to specifically support solar energy, as well as the importance of policy design details to ensuring that program goals are achieved.     

风力发电的环境价值

风能资源是无污染的清洁能源.文章对风电的环境影响进行了评价;相对于煤电评估了风电的减排污染物的环境价值;通过风电环境价值评价,认为风力发电具有减排污染物0.28元/kWh的环境价值.发展风电有显著的环境效益和经济效益.     

我国风电项目的投资与电价初探

一引言我国的并网型风电经过了科研、示范、小规模商业运营三个阶段,近二十年发展历程,目前正进入一个大规模开发时期。为鼓励和规范可再生能源的开发利用,国家发     

Simulating subhourly variability of wind power output

As installed wind power capacity grows, subhourly variability in wind power output becomes increasingly important for determining the system flexibility needs, operating reserve requirements, and cost associated with wind integration. This paper presents a new methodology for simulating subhourly wind power output based on hourly average time series, which are often produced for system planning analyses, for both existing wind plants and expanded, hypothetical portfolios of wind plants. The subhourly model has an AR(p)‐ARCH(q) structure with exogenous input in the heteroskedasticity term. Model coefficients may be fit directly to high‐pass filtered historical data if it exists; for sets of wind plants containing hypothetical plants for which there are no historical data, this paper presents a method to determine model coefficients based on wind plant capacities, capacity factors, and pairwise distances. Unlike predecessors, the model presented in this paper is independent of wind speed data, captures explicitly the high variability associated with intermediate levels of power output, and captures distance‐dependent correlation between the power output of wind plants across subhourly frequencies. The model is parameterized with 1‐minute 2014 plant‐level wind power data from Electric Reliability Council of Texas (ERCOT) and validated out‐of‐sample against analogous 2015 data. The expanded‐capacity model, fit to 2014 data, produces accurate subhourly time series for the 2015 wind fleet (a 49% capacity expansion) based only on the 2015 system's wind plant capacities, capacity factors, and pairwise distances. This supports its use in simulating subhourly fleet aggregate wind power variability for future high‐wind scenarios.     

Understanding the variability of wind power costs

Wind power has a significant contribution to make in efforts to abate CO₂ emissions from global energy systems. Currently, wind power generation costs are approaching parity with costs attributed to conventional, carbon-based sources of energy but the economic advantage still rests decidedly with conventional sources. Therefore, there is an imperative to ensure that wind power projects are developed in the most economically optimal fashion. For wind power project developers, shaving a few tenths of a cent off of the kilowatts per hour cost of wind power can mean the difference between a commercially viable project and a non-starter. For civic authorities who are responsible for managing municipally supported wind power projects, optimizing the economics of such projects can attenuate stakeholder opposition. This paper attempts to contribute to a better understanding of how to economically optimise wind power projects by conflating research from the fields of energy economics, wind power engineering, aerodynamics, geography and climate science to identify critical factors that influence the economic optimization of wind power projects.     

Production price of hydrogen from grid connected electrolysis in a power market with high wind penetration.

In liberalized power markets, there are significant power price fluctuations due to independently varying changes in demand and supply, the latter being substantial in systems with high wind power penetration. In such systems, hydrogen production by grid connected electrolysis can be cost optimized by operating an electrolyzer part time. This paper presents a study on the minimization of the hydrogen production price and its dependence on estimated power price fluctuations. The calculation of power price fluctuations is based on a parameterization of existing data on wind power production, power consumption and power price evolution in the West Danish power market area. The price for hydrogen is derived as a function of the optimal electrolyzer operation hours per year for four different wind penetration scenarios. It is found to amount to 0.41–0.45 €/Nm³. The study further discusses the hydrogen price sensitivity towards investment costs and the contribution from non-wind power sources.     

The advantages of using continuously variable transmissions in wind power systems

When connected to appropriate electric power generators, wind turbines may be used to produce electric energy. This may become complicated because wind speed tends to change. Traditionally, electric power was produced by electric generators connected to mechanical devices whose movement could be perfectly controlled and adapted to user's needs by special governors. This paper explores the feasibility of incorporating a continuously variable mechanical transmission between a wind turbine and an electric generator. Such a system would allow the turbine to operate at maximum efficiency levels and the generator to produce electric power at a desired frequency without using other devices. A mathematical model has been used to simulate a system formed by a wind turbine connected to an induction generator by means of a continuously variable transmission. The simulation was aimed at assessing whether the system was stable and attempted to adjust the transmission in order to ensure the required power supply.     

Persistence of low wind speed conditions and implications for wind power variability

As the penetration of wind generation increases on power systems throughout the world, the effects of wind variability on power systems are of increasing concern. This study focuses on sustained occurrences of low wind speeds over durations ranging from 1 h to 20 days. Such events have major implications for the variability of energy yields from wind farms. This, in turn, influences the accuracy of wind resource assessment. The frequency analysis techniques commonly used to study wind variability cannot represent the autocorrelation properties of wind speeds and thus provide no information on the probabilities of occurrence of such sustained, low wind events. We present two complementary methods for assessing wind variability, runs analysis and intensity–duration–frequency analysis, both with emphasis on characterising the occurrence of continuous, extended periods (up to several days) of low wind speeds. Multi‐annual time series of hourly wind speeds from meteorological stations in Ireland are analysed with both techniques. Sustained 20‐day periods corresponding to extremely low levels of wind generation are found to have return periods of around 10 years in coastal areas. Persistent, widespread low wind speed conditions across the entire country are found to occur only rarely. Copyright © 2012 John Wiley & Sons, Ltd.     

风压对太阳能热风发电系统的影响分析

根据太阳能热风发电系统的工作特征,以内蒙古乌海金沙沙漠太阳能热风发电系统为模型,模拟计算了不同形式的太阳能热风发电系统;对比不同系统内的气流分布,研究讨论了风压对气流流动和气流速度大小的影响。模拟结果表明:半圆形集热棚系统更具优势,其利用率较高,塔囱底部的平均气流速度可达24.38 m/s。该研究分析为乌海金沙沙漠太阳能热风发电站的建设提供了技术指导。     

Optimizing wind farm siting to reduce power system impacts of wind variability

We introduce and solve two variants of a biobjective optimization model to reduce the negative impact of wind variability on the power system by strategically locating wind farms. The first model variant considers average changes in wind power over time; the second captures extreme fluctuations in wind power. A complementary set of wind sites is selected with the aim of minimizing both residual demand and the variability in residual demand. Because exact optimization is computationally intensive, we develop two heuristics—forward and backward greedy algorithms—to find approximate solutions. The results are compared with the exact optimization results for a well‐selected subset of the data as well as to the results from selecting sites based on average wind alone. The two models are solved using demand data and potential wind sites for the Southwest Power Pool. Though both objectives can be improved by adding more sites, for a fixed number of sites, minimizing residual demand and variability in residual demand are competing objectives. We find an approximate efficient frontier to compare trade‐offs between the two objectives. We also vary the parameter in the heuristic that controls how the two objectives are prioritized. For the case study, the backward greedy algorithm is more effective at reducing the wind power variability than the forward greedy algorithm. Furthermore, using the backward algorithm for the full dataset is more effective than solving the exact optimization on a subset of the data when the results are evaluated using the full dataset.