Auction design in day-ahead electricity markets

Competition in day-ahead electricity markets has been established through auctions where generators and loads bid prices and quantities. Different approaches have been discussed regarding the market auction design. Multi-round auctions, despite its implementation complexity, allow market participants to adapt their successive bids to market prices considering their operational and economic constraints. However, most of the day-ahead electricity market implementations use noniterative single-round auctions. This paper presents a market simulator to compare both auction models. Different auction alternatives, such as the Spanish single-round auction that takes into account special conditions included in the generator bids, and multi-round auctions with different stopping rules, are analyzed. The results and acquired experience in the simulation of the Spanish market, started in January 1998, are presented. Hourly market prices, average daily price, price/demand correlation and several economic efficiency indicators, such as generator surplus, consumer surplus and social welfare, are compared to derive conclusions regarding the performance of the auction alternatives     

Auction design in day-ahead electricity markets

Competition in day-ahead electricity markets has been established through auctions where generators and loads bid prices and quantities. Different approaches have been discussed regarding the market auction design. Multi-round auctions, despite its implementation complexity, allow market participants to adapt their successive bids to market prices considering their operational and economic constraints. However, most of the day-ahead electricity market implementations use noniterative single-round auctions. This paper presents a market simulator to compare both auction models. Different auction alternatives, such as the Spanish single-round auction that takes into account special conditions included in the generator bids, and multi-round auctions with different stopping rules, are analyzed. The results and acquired experience in the simulation of the Spanish market, started in January 1998, are presented. Hourly market prices, average daily price, price/demand correlation and several economic efficiency indicators, such as generator surplus, consumer surplus and social welfare, are compared to derive conclusions regarding the performance of the auction alternatives     

Extended ARMA models for estimating price developments on day-ahead electricity markets

In this paper extended models for estimating price developments on electricity markets are presented. The models consider deviations from the normality hypothesis of the prices. Based on an ARMA model combination with GARCH, Gaussian-mixture and switching-regime approaches are comparatively discussed. The comparison is based on historic electricity prices of the spot and two reserve markets in Germany. It is shown that the proposed extended models lead to significantly improved representations of the considered stochastic price processes. It is inferred that these models may be preferred for estimating price developments on electricity markets.     

Hydrothermal self-scheduling problem in a day-ahead electricity market

This paper addresses the self-scheduling problem of determining the unit commitment status for power generation companies before submitting the hourly bids in a day-ahead market. The hydrothermal model is formulated as a deterministic optimization problem where expected profit is maximized using the 0/1 mixed-integer linear programming technique. This approach allows precise modelling of non-convex variable cost functions and non-linear start-up cost functions of thermal units, non-concave power-discharge characteristics of hydro units, ramp rate limits of thermal units and minimum up and down time constraints for both hydro and thermal units. Model incorporates long-term bilateral contracts with contracted power and price patterns, as well as forecasted market hourly prices for day-ahead auction. Solution is achieved using the homogeneous interior point method for linear programming as state of the art technique, with a branch and bound optimizer for integer programming. The effectiveness of the proposed model in optimizing the generation schedule is demonstrated through the case studies and their analysis.     

Combined hydro-wind generation bids in a pool-based electricity market

Present regulatory trends are promoting the direct participation of wind energy in electricity markets. The final result of these markets sets the production scheduling for the operation time, including a power commitment from the wind generators. However, wind resources are uncertain, and the final power delivered usually differs from the initial power committed. This imbalance produces an overcost in the system, which must be paid by those who produce it, e.g., wind generators among others. As a result, wind farm revenue decreases, but it could increase by allowing wind farms to submit their bids to the markets together with a hydro generating unit, which may easily modify its production according to the expected imbalance. This paper presents a stochastic optimization technique that maximizes the joint profit of hydro and wind generators in a pool-based electricity market, taking into account the uncertainty of wind power prediction.     

Optimal demand-side response to electricity spot prices forstorage-type customers

The customer response to spot prices is discussed. The factors that allow flexible customer response without service curtailments are identified. An overview of a fast, optimal, nonsimplex algorithm applicable to single storage electricity consuming processes is presented. A case study involving an air compression company demonstrates the application of the algorithm and shows the economic effects of industrial customer response to the spot pricing of electricity     

Strategic bidding for electricity supply in a day-ahead energy market

The problem of building optimal bidding strategies for competitive suppliers in a day-ahead energy market is addressed in this paper. It is assumed that each supplier bids 24 linear energy supply functions, one for each hour, into the day-ahead energy market, and the market is cleared separately and simultaneously for all the delivery hours. Each supplier makes decisions on unit commitment and chooses the coefficients in the linear energy supply functions to maximize total benefits in the schedule day, subject to expectations about how rival suppliers will bid. Two different bidding schemes, namely ‘maximum hourly-benefit bidding strategies’ and ‘minimum stable output bidding strategies’, have been suggested for each hour, and based on these two schemes an overall bidding strategy in the day-ahead market can then be developed. Stochastic optimization models are first developed to describe these two different bidding schemes and a genetic algorithm based method is then presented to develop an overall bidding strategy for the day-ahead market. A numerical example is utilized to illustrate the essential features of the method.     

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.     

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.     

电力市场中高可靠性电价的设计研究

在电力市场环境下,电价的制定应遵循优质优价的经济原则.对国内外实施高可靠性电价案例及收取方式进行了分析研究;基于边际成本理论和马尔科夫过程理论,研究给出了高可靠性电价的计算模型;提出高可靠性电价的实施方案建议.     

基于深度信念网络的日前电价预测

随着我国电力体制改革的不断深入,电力市场建设取得重大进展。电价是电力市场的关键影响因素,每个参与者都基于电价进行电力交易。因此,提高电价预测的精度对于电力市场中每个参与者而言都十分重要。采用单层神经网络预测的预测精度有限。为此,根据机器学习在预测方面展示出的精准度,采用深度信念网络的方法对日前电价进行预测。在算例部分,采用美国PJM电力市场的真实数据进行仿真预测,并与其他神经网络的预测模型进行比较。算例结果表明,采用的深度信念网络模型的预测精度更高,使用深度信念网络可以为我国售电公司进行电价预测提供一种有效的方法。     

激励性含柔性负荷日前市场出清电价机制的建模

对于电力市场而言,发电竞争只是电力改革的初级阶段,进一步让柔性负荷参与市场竞价是电力市场化的必经之路。传统上采用节点边际电价的日前市场出清电价机制,理论与实践均证明,该机制难以同时实现个体理性、激励相容和社会福利最大化等要求。考虑到电力市场成员之间的信息不对称性,为克服电力市场中市场成员的策略性报价行为,实现市场的高效运行及社会福利最大化,基于VCG的机制设计理论,给出了一种考虑发电机组和柔性负荷参与日前市场出清的电价机制,该机制同时满足激励相容、个体理性以及社会福利最大化要求。最后,采用某2节点系统和修改的IEEE14节点系统为例说明了该日前市场出清电价机制的基本特征。     

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。     

Optimal energy exchange of an industrial cogeneration in a day-ahead electricity market

This paper addresses an optimal strategy for the daily energy exchange of a 22-MW combined-cycle cogeneration plant of an industrial factory operating in a liberalized electricity market. The optimization problem is formulated as a Mixed-Integer Linear Programming Problem (MILP) that maximizes the profit from energy exchange of the cogeneration, and is subject to the technical constraints and the industrial demand profile. The integer variables are associated with export or import of electricity whereas the real variables relate to the power output of gas and steam turbines, and to the electricity purchased from or sold to the market. The proposal is applied to a real cogeneration plant in Spain where the detailed cost function of the process is obtained. The problem is solved using a large-scale commercial package and the results are discussed and compared with different predefined scheduling strategies.     

Long-term Nash equilibria in electricity markets

In competitive electricity markets, companies simultaneously offer their productions to obtain the maximum profits on a daily basis. In the long run, the strategies utilized by the electric companies lead to various long-term equilibria that can be analyzed with the appropriate tools. We present a methodology to find plausible long-term Nash equilibria in pool-based electricity markets. The methodology is based on an iterative market Nash equilibrium model in which the companies can decide upon their offer strategies. An exponential smoothing of the bids submitted by the companies is applied to facilitate the convergence of the iterative procedure. In each iteration of the model the companies face residual demand curves that are accurately modeled by Hermite interpolating polynomials. We introduce the concept of meta-game equilibrium strategies to allow companies to have a range of offer strategies where several pure and mixed meta-game Nash equilibria are possible. With our model it is also possible to model uncertainty or to generate price scenarios for financial models that assess the value of a generating unit by real options analysis. The application of the proposed methodology is illustrated with several realistic case studies.     

Short-term operation scheduling of a hydropower plant in the day-ahead electricity market

This paper presents a novel approach to solve the short-term operation scheduling problem of a hydropower plant that sells energy in a deregulated electricity market with the objective of maximizing its revenue. This paper proposes a nonlinear programming based scheduling model that determines both the optimal unit commitment (start-ups and shut-downs scheduling) and the generation dispatch of the committed units (hourly power output). The power generated by each hydro unit is considered as a nonlinear function of the water discharge and the volume of the associated reservoir. The dependence of the units’ operating limits (maximum and minimum water flows) on the actual gross head has been also taken into account in this model. The results from a case study are also presented to illustrate the application of the proposed approach in a real hydro plant.     

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。     

激励性含风电竞标日前市场出清电价机制的建模

在日前市场出清电价机制中,为同时实现发电机组个体理性和激励相容以及市场出清总成本最小化的要求,应用基于VCG (Vickrey-Clarke-Groves)的机制设计理论,给出了一种含风力机组竞标的日前市场出清电价机制。建立了含风电竞标日前市场出清模型,采用抽样平均逼近法求解该市场出清模型。基于VCG机制设计理论,定义发电机组(常规/风电)获得的支付为该机组参与日前市场出清前后,日前市场出清总成本的变化量。采用某2节点系统和修改的IEEE14节点系统为例说明了该含风电竞标日前市场出清电价机制的基本特征。仿真结果表明,所提电价机制满足市场出清总成本最小化、激励相容以及个体理性等要求。     

Demand-side view of electricity markets

This tutorial paper discusses some aspects of electricity markets from the perspective of the demand-side. It argues that increasing the short-run price elasticity of the demand for electrical energy would improve the operation of these markets. It shows, however, that enhancing this elasticity is not an easy task. The tools that consumers and retailers of electrical energy need to participate more actively and effectively in electricity markets are discussed. The paper also describes how consumers of electricity can take part in the provision of power system security.     

Wind generation imbalances penalties in day-ahead energy markets: The Italian case

Today there is a lot of interest in wind energy exploitation. It has been emphasized by adopted incentive mechanisms and by the possibility to sell energy to the electrical market in different ways. The rise of wind installed power requires more energy for ancillary services. Moreover, imbalance costs have to be sustained by the Transmission System Operator (TSO) which could charge them to all the consumers where wind power producers are not penalized for their imbalances. To solve this problem some solutions can be adopted depending on market rules that are different from one country to another. In particular referring to the current Italian market framework and taking into account to the state-of-the-art wind power forecasting, an economic assessment of imbalance for some wind farms have been compared to balancing costs of the TSO. Different stochastic approaches have been adopted, using available historical data, in the analysis of various scenarios both for the TSO and for wind plant owners. Also possible mechanisms for imbalance settlements have been proposed in order to maintain grid safety costs within a reasonable level for electricity consumers, and to avoid an excessively penalizing treatment for wind energy source investments in order to satisfy environmental targets of the European Community.