Trading wind power through physically settled options and short‐term electricity markets

Wind power producers participating in today's electricity markets face significant variability in revenue streams, with potential high losses mostly due to wind's limited predictability and the intermittent nature of the generated electricity. In order to further expand wind power generation despite such challenges, it is important to maximize its market value and move decisively towards economically sustainable and financially viable asset management. In this paper, we introduce a decision‐making framework based on stochastic optimization that allows wind power producers to hedge their position in the market by trading physically settled options in futures markets in conjunction with their participation in the short‐term electricity markets. The proposed framework relies on a series of two‐stage stochastic optimization models that identify a combined trading strategy for wind power producers actively participating in both financial and day‐ahead electricity markets. The proposed models take into consideration penalties from potential deviations between day‐ahead market offers and real‐time operation and incorporates different preferences of risk aversion, enabling a trade‐off between the expected profit and its variability. Empirical analysis based on data from the Nordic region illustrates high efficiency of the stochastic model and reveals increased revenues for both risk neutral and risk averse wind producers opting for combined strategies.     

Potential of trading wind power as regulation services in the California short-term electricity market

A short-term electricity market is usually composed of the energy market and ancillary service market. However, wind power is not allowed to be traded in ancillary service markets although it has been proven technically feasible to be regulation services. This paper aims to explore the market potential of trading wind power as regulation services in the California electricity market. A model for wind power trade in the day-ahead (DA) market is established considering the uncertainties of market prices and wind power. An optimal trading strategy for wind power producers is derived by using an analytical algorithm. Trading wind power as regulation is tested by using actual data and the impacts of market control on the market outcome are discussed. The results show that, based on the current framework of the California electricity market, wind power producers can earn much more money if they bid in the DA energy and regulation markets than if they only bid in the DA energy market. The results also show that the potential to enhance profit for wind power producers is larger in the regulation down market than in the regulation up market.     

偏差电量考核下风光储混合发电商的市场均衡博弈研究

为了更直观地分析风光储混合发电商对市场均衡博弈结果和市场力的影响,在偏差电量考核衡量风光储混合发电出力随机波动性的基础上,综合考虑各发电商的出力限制和储能系统的运行约束,建立以风光储混合发电商和传统发电商收益最大化为目标的市场均衡博弈模型,调用CPLEX软件求解利用非线性互补函数处理得到的混合整数规划模型,并对比分析了风光储混合发电商作为价格接受者和影响者参与电力市场竞争对均衡博弈电价和投标出力的影响。结果表明,风光储混合发电商参与电力市场竞争可抑制传统发电商的市场力,对电价有显著的"削峰填谷"作用;当风光储混合发电商作为价格影响者时,对电价的影响会减弱,但其收益有所增加。     

Where the wind blows: Assessing the effect of fixed and premium based feed-in tariffs on the spatial diversification of wind turbines

Feed-in tariffs (FIT) are among the most important policy instruments to promote renewable electricity production. The fixed-price FIT (FFIT), which guarantee a fixed price for every unit of produced electricity and the premium based FIT (PFIT), which pay a premium on top of the market price are commonly implemented in the EU. Costs for balancing intermittent electricity production may be significantly higher with FFIT than with PFIT, and FFIT do not provide any incentive to produce electricity when marginal production costs are high. In contrast, PFIT do provide strong incentives to better match renewable power output with marginal production costs in the system. The purpose of this article is to assess the effects of the two tariff schemes on the choice of wind turbine locations. In an analytical model, we show that both the covariance between wind power supply and demand as well as between the different wind power locations matter for investors in a PFIT scheme. High covariance with other intermittent producers causes a decrease in market prices and consequently in revenues for wind power investors. They are therefore incentivized to diversify the locations of wind turbines to decrease the covariance between different wind power production locations. In an empirical optimization model, we analyze the effects of these two different schemes in a policy experiment for Austria. The numerical results show that under a PFIT scheme, (1) spatial diversification is incentivized, (2) the covariance of wind power production with marginal electricity production costs increases, and (3) the variances of the wind power output and of residual load decrease if wind power deployment attains 10% of total national electricity consumption.     

An integrated approach for optimal coordination of wind power and hydro pumping storage

The increasing wind power penetration in power systems represents a techno‐economic challenge for power producers and system operators. Because of the variability and uncertainty of wind power, system operators require new solutions to increase the controllability of wind farm output. On the other hand, producers that include wind farms in their portfolio need to find new ways to boost their profits in electricity markets. This can be done by optimizing the combination of wind farms and storage so as to make larger profits when selling power (trading) and reduce penalties from imbalances in the operation. The present work describes a new integrated approach for analysing wind‐storage solutions that make use of probabilistic forecasts and optimization techniques to aid decision making on operating such systems. The approach includes a set of three complementary functions suitable for use in current systems. A real‐life system is studied, comprising two wind farms and a large hydro station with pumping capacity. Economic profits and better operational features can be obtained from the proposed cooperation between the wind farms and storage. The revenues are function of the type of hydro storage used and the market characteristics, and several options are compared in this study. The results show that the use of a storage device can lead to a significant increase in revenue, up to 11% (2010 data, Iberian market). Also, the coordinated action improves the operational features of the integrated system. Copyright © 2013 John Wiley & Sons, Ltd.     

Optimizing hybrid offshore wind farms for cost-competitive hydrogen production in Germany

Nearly 96% of the world's current hydrogen production comes from fossil-fuel-based sources, contributing to global greenhouse gas emissions. Hydrogen is often discussed as a critical lever in decarbonizing future power systems. Producing hydrogen using unsold offshore wind electricity may offer a low-carbon production pathway and emerging business model. This study investigates whether participating in an ancillary service market is cost competitive for offshore wind-based hydrogen production. It also determines the optimal size of a hydrogen electrolyser relative to an offshore wind farm. Two flexibility strategies for offshore wind farms are developed in this study: an optimal bidding strategy into ancillary service markets for offshore wind farms that build hydrogen production facilities and optimal sizing of Power-to-Hydrogen (PtH) facilities at wind farms. Using empirical European power market and wind generation data, the study finds that offshore-wind based hydrogen must participate in ancillary service markets to generate net positive revenues at current levels of wind generation to become cost competitive in Germany. The estimated carbon abatement cost of “green” hydrogen ranges between 187 EUR/tonCO₂e and 265 EUR/tonCO₂e. Allowing hydrogen producers to receive similar subsidies as offshore wind farms that produce only electricity could facilitate further cost reduction. Utilizing excess and intermittent offshore wind highlights one possible pathway that could achieve increasing returns on greenhouse gas emission reductions due to technological learning in hydrogen production, even under conditions where low power prices make offshore wind less competitive in the European electricity market.     

Economic analysis of electrical heating with heat storage using grid integrated wind power

针对冬季供热期我国北方地区因电网风电接纳能力不足导致的严重弃风问题,研究了电力市场背景下采用蓄热式电采暖提高电网风电消纳规模的经济性评估问题,考虑弃风电量、弃风电价等因素影响,建立了弃风蓄热式电采暖系统的经济性评估模型,分析了影响蓄热式电采暖系统经济性的关键因素。结合某清洁供暖示范工程进行算例分析,分析了协定弃风电价对系统经济性的影响,对所提出的经济性评估模型的有效性进行验证,为蓄热式电采暖可行性分析奠定了理论基础。     

The impact of European balancing rules on wind power economics and on short-term bidding strategies

Wind power represents a significant percentage of the European generation mix and this will increase to fulfill the renewable energy targets. Different balancing rules are applied to wind power among the countries; for instance, to what extent wind power producers (WPPs) are responsible for the energy imbalances and how those imbalances are penalized. This paper discusses those different rules and evaluates their effects on WPP bidding strategies. To do so, a quantitative analysis is presented for an offshore wind farm, considering the differences in the balancing rules and prices of Belgium, Denmark, Germany and the Netherlands. The quantitative approach consists of a stochastic optimization model that maximizes the profits of a WPP by trading in different markets (day-ahead and intraday) and computes the final energy delivered. The model considers uncertainties of most important parameters such as wind energy forecasts and prices at different time frames. The results show that the imbalance pricing design and the allocation of balance responsibility significantly affect WPP’ revenues. Additionally, WPPs deviate differently from the expected energy depending on the balancing rules, which can impact the system. Furthermore, these balancing rules should be considered with other market regulations, such as the design of support schemes.     

Optimal electricity market for wind power

This paper is about electricity market operation when looking from the wind power producers’ point of view. The focus in on market time horizons: how many hours there is between the closing and delivering the bids. The case is for the Nordic countries, the Nordpool electricity market and the Danish wind power production. Real data from year 2001 was used to study the benefits of a more flexible market to wind power producer. As a result of reduced regulating market costs from better hourly predictions to the market, wind power producer would gain up to 8% more if the time between market bids and delivery was shortened from the day ahead Elspot market (hourly bids by noon for 12–36 h ahead). An after sales market where surplus or deficit production could be traded 2 h before delivery could benefit the producer almost as much, gaining 7%.     

Joint price and volumetric risk in wind power trading: A copula approach

This paper examines the dependence between wind power production and electricity prices and discusses its implications for the pricing and the risk distributions associated with contracts that are exposed to joint price and volumetric risk. We propose a copula model for the joint behavior of prices and wind power production, which is estimated to data from the Danish power market. We find that the marginal behavior of the individual variables is best described by ARMA–GARCH models with non-Gaussian error distributions, and the preferred copula model is a time-varying Gaussian copula. As an application of our joint model, we consider the case of an energy trading company entering into longer-term agreements with wind power producers, where the fluctuating future wind power production is bought at a predetermined fixed price. We find that assuming independence between prices and wind power production leads to an underestimation of risk, as the profit distribution becomes left-skewed when the negative dependence that we find in the data is accounted for. By performing a simple static hedge in the forward market, we show that the risk can be significantly reduced. Furthermore, an out-of-sample study shows that the choice of copula influences the price of correlation risk, and that time-varying copulas are superior to the constant ones when comparing actual profits generated with different models.     

Dynamic model for market-based capacity investment decision considering stochastic characteristic of wind power

This paper proposes a decentralized market-based model for long-term capacity investment decisions in a liberalized electricity market with significant wind power generation. In such an environment, investment and construction decisions are based on price signal feedbacks and imperfect foresight of future conditions in electricity market. System dynamics concepts are used to model structural characteristics of power market such as, long-term firms’ behavior and relationships between variables, feedbacks and time delays. For conventional generation units, short-term price feedback for generation dispatching of forward market is implemented as well as long-term price expectation for profitability assessment in capacity investment. For wind power generation, a special framework is proposed in which generation firms are committed depending on the statistical nature of wind power. The method is based on the time series stochastic simulation process for prediction of wind speed using historical and probabilistic data. The auto-correlation nature of wind speed and the correlation with demand fluctuations are modeled appropriately. The Monte Carlo simulation technique is employed to assess the effect of demand growth rate and wind power uncertainties. Such a decision model enables the companies to find out the possible consequences of their different investment decisions. Different regulatory policies and market conditions can also be assessed by ISOs and regulators to check the performance of market rules. A case study is presented exhibiting the effectiveness of the proposed model for capacity expansion of electricity markets in which the market prices and the generation capacities are fluctuating due to uncertainty of wind power generation.     

Economic and environmental implications of different approaches to hedge against wind production uncertainty in two-settlement electricity markets: A PJM case study

This paper examines the economic and environmental outcomes of four two-settlement electricity market clearing designs. The first design corresponds to a Deterministic Market Clearing (DMC) similar to the mechanism currently used in organized wholesale electricity markets in the United States. The other three designs account for the day-ahead (DA) wind power production uncertainty into the DA market mechanisms either implicitly or explicitly. An Augmented Deterministic Market Clearing (ADMC) design introduces DA ramp-capability products. These products ensure adequate and ramp-feasible electricity generation capacity commitments in the DA stage to cope with the real-time realization of wind power generation. A Hybrid Deterministic Market clearing (HDMC) design augments ADMC by explicitly integrating a characterization of wind power production uncertainty into the residual unit commitment (RUC) process, which is run after the DA market is closed, using stochastic programming. The last design, referred to as stochastic market clearing (SMC), uses stochastic optimization to explicitly account for wind power production uncertainty in the DA market clearing mechanisms (i.e. DA unit commitment and economic dispatch).The four market clearing designs are assessed by simulating the electricity market operations of a test system and comparing their results in terms of operating costs, prices, costs and revenues of different types of producers, consumer's payments, integration of wind power, and air emissions. The test system has 12% of the capacity of PJM's fossil-fired power generation fleet, and uses data on coincident demand and wind power production from the Bonneville Power Administration (BPA) system during years 2010–2014. The simulations are performed hourly for a whole year.Results show that SMC is superior as its costs reductions are more than two times the improvements attained by ADMC and HDMC. Also, SMC results in electricity prices that are better aligned with operation costs, cuts the spread between the day-ahead and real-time prices by >40%, reduces out-of-market short-term revenue sufficiency payments by 58%, reduces CO₂ emissions by 3.52%, and decreases power plants' cycling. HDMC is a distant second-best market design. Relative to DMC, it achieves a reduction in total costs that is less than half the reduction achieved by SMC, a reduction in out-of-market payments that is 80% of the reduction attained by SMC, and an increase in wind power integration that is <10% the improvement obtained under SMC.     

Mitigating wind exposure with zero-cost collar insurance

Renewable energy generation worldwide has relied increasingly on wind farms where wind energy is transformed into electricity. On the other hand, electricity prices are uncertain and wind speeds are highly variable, which exposes the producer to risks. Typically wind power producers enter into long term fixed price contracts in order to hedge against energy price risk, but these contracts expose the wind farm to energy volume risk, as they require delivery of the full amount of energy contracted, even if energy production falls short due to low wind speeds. To mitigate this risk, wind producers can purchase insurance. This article proposes a zero-cost collar insurance and develop a stochastic model to determine the feasible range of wind strikes for both the wind farm and the insurer. The results indicate there is a set of possible strike combinations that meets the objectives of both parties.     

Electrolysers for mitigating wind curtailment and producing ‘green’ merchant hydrogen

The implementation electrolysis plant in combination with wind power plant is proposed, to absorb wind generation otherwise curtailed while generating ‘green’ hydrogen for the merchant hydrogen market. The objective are to (i) achieve exceptionally high wind power penetrations in future power systems, and (ii) derive hydrogen for sale in the existing merchant industrial market from surplus (zero cost) renewable electricity. The economic rationale is investigated for an isolated power system as a function wind penetration, wind curtailment target, electrolyser cost, hydrogen system efficiency and hydrogen sales price. The main outputs are the total annualized cost of wind power plant with electrolysis plant, net annual revenues and discounted pay-back periods. Unprecedented low values of pay-back period are attainable, relative to the implementation of wind power plant at low wind penetrations (Φ_W). For example, at Φ_W = 50%, a wind curtailment target of 80% allows the investment to be recovered after 4-7 years, provided the hydrogen system efficiency is ≥50% and the hydrogen sales price is 20-30 $/kg. Making use of some non-curtailed wind electricity to boost the utilization of the electrolyser stock is also investigated as a means for improving the return on investment.     

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.     

Optimal operation of a wind-electrolytic hydrogen storage system in the electricity/hydrogen markets

Wind power, the most promising renewable energy source in the world, plays an important role in the electricity markets. Wind power curtailment cannot be avoided in some countries due to its output has a special feature of randomness and volatility. Since the excess wind power being converted into hydrogen and sold to the hydrogen market will be the future trend. This study proposes a wind-electrolytic hydrogen storage system to participate in the electricity/hydrogen markets for selling electricity and hydrogen, which can help to improve the benefits of wind power in the electricity markets and addree the wind power curtailment effectively. With considering the uncertainties of wind power outputs and electricity prices, the optimal operation strategy is proposed with the objective of maximizing profits. The scenario-based stochastic method is adopted to describe the uncertainties, and the financial risk is evaluated using conditional value-at-risk. The operational problem of the proposed system is formulated into a mixed-integer linear programming model. Finally, the feasibility of the proposed operational strategy is validated by a case study. The results show that the expected revenue increases with the increase of the hydrogen selling price, indicating that investors can obtain profits by converting electricity into hydrogen. The optimal expected revenue increases by 33.42% when hydrogen price increases from 1.2 DKK/kWh to 1.8 DKK/kWh and the risk factor is equal to 0. Based on the analysis of the results, the importance of hydrogen can be proven.     

Optimal offering and allocation policies for wind power in energy and reserve markets

Proliferation of wind power generation is increasingly making this power source an important asset in designs of energy and reserve markets. Intuitively, wind power producers will require the development of new offering strategies that maximize the expected profit in both energy and reserve markets while fulfilling the market rules and its operational limits. In this paper, we implement and exploit the controllability of the proportional control strategy. This strategy allows the splitting of potentially available wind power generation in energy and reserve markets. In addition, we take advantage of better forecast information from the different day‐ahead and balancing stages, allowing different shares of energy and reserve in both stages. Under these assumptions, different mathematical methods able to deal with the uncertain nature of wind power generation, namely, stochastic programming, with McCormick relaxation and piecewise linear decision rules are adapted and tested aiming to maximize the expected revenue for participating in both energy and reserve markets, while accounting for estimated balancing costs for failing to provide energy and reserve. A set of numerical examples, as well as a case study based on real data, allow the analysis and evaluation of the performance and behavior of such techniques. An important conclusion is that the use of the proposed approaches offers a degree of freedom in terms of minimizing balancing costs for the wind power producer strategically to participate in both energy and reserve markets. Copyright © 2017 John Wiley & Sons, Ltd.     

Risk-averse based optimal operational strategy of grid-connected photovoltaic/wind/battery/diesel hybrid energy system in the electricity/hydrogen markets

The techno-economic advantages of grid-connected hybrid energy system (HES) exploit synergies to improve reliability and economic efficiency while maintaining grid stability. Therefore, this paper proposes a risk-averse optimal operational strategy of grid-connected photovoltaic/wind/battery/diesel HES to participate into two energy markets including electricity and hydrogen markets. The grid company can flexibly trade power into two markets to maximally achieve profits based on price arbitrage. The risk influences of the uncertainties, i.e., photovoltaic/wind generation, and electricity prices on the expected revenue are evaluated with CVaR model. For a better exhibition of seasonal variability effects on HES optimal operation strategy, two typical Spring/Summer days are chosen. The proposed risk-averse optimal operational strategy is formulated as a two-stage mixed-integer linear programming (MILP) model. The results in a Spring day simulation under non-risk situation indicate that the overall expected revenue can be improved 2.74 times larger if considering hydrogen market. Moreover, the optimal operational strategy of hydrogen production is considerably affected by unpredictable wind farm. Sensitivity analysis also validates that the changes of PV/WT curtailment penalty have a profound influence than battery degradation coefficient on the HES expected revenue.     

A combined modeling approach for wind power feed-in and electricity spot prices

Wind power generation and its impacts on electricity prices has strongly increased in the EU. Therefore, appropriate mark-to-market evaluation of new investments in wind power and energy storage plants should consider the fluctuant generation of wind power and uncertain electricity prices, which are affected by wind power feed-in (WPF). To gain the input data for WPF and electricity prices, simulation models, such as econometric models, can serve as a data basis.This paper describes a combined modeling approach for the simulation of WPF series and electricity prices considering the impacts of WPF on prices based on an autoregressive approach. Thereby WPF series are firstly simulated for each hour of the year and integrated in the electricity price model to generate an hourly resolved price series for a year. The model results demonstrate that the WPF model delivers satisfying WPF series and that the extended electricity price model considering WPF leads to a significant improvement of the electricity price simulation compared to a model version without WPF effects. As the simulated series of WPF and electricity prices also contain the correlation between both series, market evaluation of wind power technologies can be accurately done based on these series.     

A market‐oriented wind power dispatch strategy using adaptive price thresholds and battery energy storage

In this paper, an adaptive dispatch strategy is presented to maximize the revenue for grid‐tied wind power plant coupled with a battery energy storage system (BESS). The proposed idea is mainly based on time‐varying market‐price thresholds, which are varied according to the proposed algorithm in an adaptive manner. The variable nature of wind power and market price signals leads to the idea of storing energy at low price periods and consequently selling it at high prices. In fact, the wind farm operators can take advantage of the price variability to earn additional income and to maximize the operational profit based on the choice of best price thresholds at each instant of time. This research study proposes an efficient strategy for intermittent power dispatch along with the optimal operation of a BESS in the presence of physical limits and constraints. The strategy is tested and validated with different BESSs, and the percentage improvement of income is calculated. The simulation results, based on actual wind farm and market‐price data, depict the proficiency of the proposed methodology over standard linear programming methods.