Portfolio optimization in electricity markets

In a competitive electricity market, Generation companies (Gencos) face price risk and delivery risk that affect their profitability. Risk management is an important and essential part in the Genco's decision making. In this paper, risk management through diversification is considered. The problem of energy allocation between spot markets and bilateral contracts is formulated as a general portfolio optimization problem with a risk-free asset and n risky assets. Historical data of the PJM electricity market are used to demonstrate the approach.     

应用动态学习改进对竞争对手微增响应猜测的发电公司投标策略

该文应用微增响应猜测(Conjcctural Variation，CV)方法构造一种在不完全信息情况下的寡头竞争电力现货市场中发电公司通过动态学习改进对竞争对手的微增响应猜测的新投标策略，指出当各发电公司采用该文提出的投标策略进行不断重复的投标竞争后，市场所达到的均衡点为：Nash均衡点。算例计算结果说明各发电公司具有进行动态学习的动力，但是当所有公司进行学习时将会降低市场结清电价从而提高电力市场的社会总效益。算例计算结果还说明了电力需求弹性对学习过程的收敛性具有积极作用。     

Distributed resources and re-regulated electricity markets

This paper briefly defines distributed resources (DR) and discusses the current status of DR. The main focus is on discussing the value DR can provide to re-regulated electricity markets. DR can, under certain circumstances, help to significantly reduce the main problem of re-regulation, i.e. market power. Distributed generation and demand-side resources may, even if only small quantities in terms of size of the entire market are utilised, be able to help to significantly reduce market power. This results in a significantly more efficient market. To achieve such benefits, however, DR must be in operation during times when market power issues are likely to arise. To a certain extent this is the case as demand-side resources are usually independent of established generation companies. In addition, many business cases for DG require DG to actually operate to capture the second revenue.     

解除管制的电力零售市场实时电价研究

零售侧打破垄断引入竞争是电力市场发展的趋势,制定合理的零售电价是市场开放的关键.根据电力零售市场的特点,基于负荷价格响应的定义以及边际成本定价理论,推导出了考虑负荷价格响应的有功实时电价的表达式.以社会成本最大化为目标函数,建立了考虑负荷价格响应特性的最优潮流模型,从而求解出未来引入竞争的电力零售市场中电力库交易模式下的实时电价.采用32节点配电系统对所提方法进行仿真,结果证明为促进零售市场竞争、引导用户合理用电提供了合理有效的定价方法.     

Influence of TCSC on congestion and spot price in electricity market with bilateral contract

This paper presents a quantitative analysis of the effect of TCSC on congestion and spot price in deregulated electricity markets. The paper could also be considered as a comprehensive tutorial on the influence of TCSC in electricity market. A voluntary pool market, where the market participants can trade electricity either via a pool or through bilateral contracts is considered. The electricity market is modeled in an optimal power flow framework with the objective of maximizing the social welfare. In such formulation, the Lagrange operators associated with the equality constraints associated with real power balance give the spot prices of energy at each bus of the system. Studies are carried out with and without TCSC at peak and low loading conditions to capture the influence and to see the effectiveness of TCSC at different loading conditions. The paper further explores the effect of TCSC compensation level on the spot prices and the congestion under varying pool and bilateral loading conditions. A 5-bus test system is used for numerical studies and to showcase the influence of TCSC in an electricity market environment.     

A game theory simulator for assessing the performances of competitive electricity markets

In the last years, electricity markets were created all over the world following different basis concepts. Market structure, market rules, demand levels, market concentration and energy sources to produce electricity have a strong influence on market performances. Modifications on these aspects may significantly affect market outcomes. Sensitivity analyses need proper simulation tools. In this paper a medium run electricity market simulator (MREMS) based on game theory is presented. This simulator incorporates two different games, one for the unit commitment of thermal units and one for strategic bidding and hourly market clearing. Either a Forchheimer (one leader) or Bertrand (all player are leaders) or even intermediate model with a whatever number of leaders can be selected, in dependence on the strategic behavior of the producers, allowing for the simulation of markets with different levels of concentration. The simulator was applied to analyse producers’ behavior during the first operative year of the Italian power exchange. A comparison between simulation and true market results was carried out in order to test the simulator and validate its simplifying hypotheses. MREMS, yet capable to be used stand-alone, was conceived as the heart of a long-term market simulator (LREMS) allowing to simulate the long-run evolution of the generation park (investments in new plants, refurbishment and dismission of older ones). LREMS is a hierarchic simulator: a long-term “outer” game takes yearly investment decisions based on mid-term price projections provided by MREMS. Although this paper is mainly devoted to describe MREMS, one specific section will provide an overview of the “outer” game implemented by LREMS.     

构造发电公司投标策略的一种新方法-微增响应猜测法初探

介绍了微增响应猜测法(Conjectural Variation，CV)的基本概念，提出了基于这种方法构造发电公司在不完全信息情况下的最优投标策略。通过理论分析和算例计算，结果表明基于经典博弈理论构造的发电公司的最优投标策略是该方法的一种特例。采用该方法进行市场模拟时，对各发电公司不同的微增响应猜测进行组合，可以得到不同的市场均衡点，且均为Nash均衡点。     

Conjectural variation based learning model of strategic bidding in spot market

In actual electricity market, which operates repeatedly on the basis of one hour or half hour, each firm might learn or estimate other competitors' strategic behaviors from available historical market operation data, and rationally aims at its maximum profit in the repeated biddings. A conjectural variation based learning method is proposed in this paper for generation firm to improve its strategic bidding performance. In the method, each firm learns and dynamically regulates its conjecture upon the reactions of its rivals to its bidding according to available information published in the electricity market, and then makes its optimal generation decision based on the updated conjectural variation of its rivals. Through such learning process, the equilibrium reached in the market is proven a Nash equilibrium. Motivation of generation firm to learn in the changing market environment and consequence of learning behavior in the market are also discussed through computer tests.     

Slack-bus independent penalty factor for regional spot pricing under deregulation

Recently, the deregulation has been a hot issue in electric power industries with the introduction of the bidding system to electric power markets. One of the main topics associated with the deregulation is spot pricing where the exact analysis of transmission loss and the method of calculating reliable penalty factor play an important role. Penalty factors calculated with conventional methods are highly dependent on the location of the slack bus, which brings about unfair competition to Independent Power Producers (IPPs). This paper presents a new method of calculating the exact and reliable penalty factor independent of the change of the slack bus. The proposed method is tested on IEEE 14 bus system, New England 39 bus system and OH-145 bus system. The test results show that the proposed method can give more reliable information of the penalty factors for the regional spot pricing.     

A summary of demand response in electricity markets

This paper presents a summary of Demand Response (DR) in deregulated electricity markets. The definition and the classification of DR as well as potential benefits and associated cost components are presented. In addition, the most common indices used for DR measurement and evaluation are highlighted, and some utilities’ experiences with different demand response programs are discussed. Finally, the effect of demand response in electricity prices is highlighted using a simulated case study.     

The effect of wind generation and weekday on Spanish electricity spot price forecasting

This paper empirically compares the predictive accuracy of a set of methods for day-ahead spot price forecasting in the Spanish electricity market. The methods come from time series analysis and artificial intelligence disciplines, and include univariate, multivariate, linear and nonlinear. Within the univariate methods, the double seasonal ARIMA and the recently proposed exponential smoothing for double seasonality are compared and used as benchmarks. They allow us to quantify the improvement on price forecasting when including explanatory variables or using more complex models. Dynamic regression models including the electricity load forecast are then considered. Their good performance in price forecasting has been pointed out by many authors. However, we find evidences of their predictive accuracy can be significantly outperformed by accounting the wind generation forecast provided by the System Operator. Moreover, these forecasts can be even more accurate if changes of price's behavior according with the day of the week are taken into account by means of periodic models. The last of the tested methods are feed-forward neural networks used as multivariate nonlinear regression methods with universal function approximation capabilities. The influence of the wind generation forecast on price prediction is also proved with this approach. Detailed out-of-sample results of the tested methods are given.     

电力市场下的需求响应研究

介绍了电力市场下的需求响应,包括需求响应的概念及其分类、需求响应成本和需求响应效益.分析了需求响应的短期市场影响效益、长期市场影响效益以及系统可靠性的效益等.同时,介绍了市场下的需求响应在国外的应用情况,并给出了在我国电力市场下实施需求响应的一些想法.     

电力市场操纵力问题探析

分析电力工业改革重组后电力市场操纵力依然存在的基础，探讨测度电力市场操纵力的方向，并介绍世界主要国家电力改革后市场操纵力的实证分析结果。揭示出电力市场操纵力这个在上世纪电力监管要克服的核心问题，仅仅依靠电力工业的按环节拆分重组，并不能从根本上改变其存在与实施的基础。随着我国电力体制改革的推进和电力市场的建立，必须有针对性地制定一系列抑制和消除市场操纵力的政策措施，以全面实现电力体制改革的目标。     

Strategic bidding in electricity markets using particle swarm optimization

Profit maximization for power companies is highly related to the bidding strategies used. In order to sell electricity at high prices and maximize profit, power companies need suitable bidding models that consider power operating constraints and price uncertainty within the market. In this paper, we present two particle swarm optimization (PSO) algorithms to determine bid prices and quantities under the rules of a competitive power market. The first method uses a conventional PSO technique to find solutions. The second method uses a decomposition technique in conjunction with the PSO approach. This new decomposition-based PSO dramatically outperforms the conventional form of PSO. We show that for nonlinear cost functions PSO solutions provide higher expected profits than marginal cost-based bidding.     

Economic efficiency of coordinated multilateral trades in electricity markets

This paper presents economic efficiency evaluation of electricity markets operating on the basis of a coordinated multilateral trading concept. The evaluation accounts for the overall costs of power generation, network losses, and system and unit constraints. We assume a non-collusive oligopolistic competition. An iterative Cournot model is used to characterize the competitive behavior of suppliers. A supplier maximizes the profit of each of his generating units while taking rivals' generation as given. Time span is over multiple hours. This leads to a mixed integer non-linear programming problem. We use the augmented Lagrangian approach to solve iteratively for globally optimal schedules. An IEEE 24-bus, 8-supplier, and 17-customer test system is used for illustration. The results show that such a market at times of light demands exhibits little market power, and at times of large demands exhibits a great deal of market power. This contrasts with the PCMI and HHI concentration measures, which give fixed measurement values of market power. The results of two-year (730 round) market simulations show a range of deadweight efficiency loss between 0.9 and 6% compared to that of PoolCo which results in a range between 0.5 and 10% for the same test case.     

电力市场条件下供电公司最优购电问题研究

电力市场条件下,根据现代投资理论建立了购电公司最优购电分配模型,用以确定远期合同市场、日前市场、实时市场的购电量,利用蚁群算法对模型求解。给出具体算例,通过算例证明了模型的正确性与可行性。     

国际电力金融市场对中国电力市场建设的启示

电力期货是规避现货市场风险的有效管理工具,电力期权是有效的电力价格风险管理工具,两者均已在欧洲和美国电力市场引入。美国、英国、澳大利亚等国主要的电力市场均以合约交易为主,现货交易为辅,实现了现货价格调节功能与期货价格风险规避功能的结合,介绍了国际电力金融市场的运作和管理模式,分析了欧美各国电力市场开展和运行的经验和教训,提出先开展差价合约,远期合约,逐步过渡到实现"以合约交易为主,现货交易为辅"的全面市场化目标。     

电力市场中期货与现货电量交易比例的研究

合理的期货与现货电量交易比例是保证电力市场有效实施的一个重要环节。以市场效率最大化为目标函数,考虑发电机组的可用容量与负荷预测的误差,以及输电线路的有效传输容量等因素,推导出期货与现货市场交易比例的计算公式,此公式是以发、输、负荷三个串联系统可靠供电的概率性指标为基础的。经过一个实际系统的仿真,说明这种比例是非常合理的。