计及网络阻塞影响的发电公司最优报价策略

在电力市场环境下发电公司要竞价上网，其最关心的问题是如何构造最优的报价策略以获取最大利润。输电系统容量不足所引起的阻塞问题可以起到分割市场的作用，从而改变发电公司在电力市场中所处的竞争位置，进而影响发电公司的最优报价策略。文中研究了计及输电网络阻塞影响情况下的发电公司的最优报价策略，在假设可用概率分布函数来描述竞争对手报价行为的基础上，系统地构造了描述这一问题的随机优化模型，并提出了基于蒙特卡罗仿真和遗传算法的求解方法。最后，用修改过的IEEEl4节点系统说明了所提出的方法的基本特征。     

Security constrained optimal bidding strategy of GenCos in day ahead oligopolistic power markets: a Cournot-based model

Restructured electricity markets may provide opportunities for producers to exercise market power, maintaining prices in excess of competitive levels. In this paper a Cournot equilibrium model is proposed to obtain generation companies’ (GenCos’) optimal bidding strategies in a day ahead oligopoly market, considering elasticity of demand, market power and transmission security constraints. In order to consider network constraints, a multiperiod auction framework is addressed to simulate market clearing mechanism by means of social welfare maximization, in which the behaviors of market participants are modeled through piecewise block curves. Impact of transmission security constraints on participants’ market power is presented. A mixed integer linear programming is employed to solve the problem, resulting supply-demand satisfaction as well as market clearing prices at each hour. A novel methodology is presented for security constrained optimal bidding strategy of GenCos through introducing heuristic effective-supply curves. Subsequently, impact of GenCos’ power exertion on market characteristics and corresponding payoffs is studied. A 9-bus IEEE test system is used to implement the proposed methodology while simulation results demonstrate the effectiveness of the framework.     

基于模糊集理论的发电公司分段报价策略研究

在电力市场环境下，发电公司竞价上网的目标是最大化利润。显然，发电公司采用的报价策略对其获得的利润会有相当大的影响。文章针对运行不久、历史数据尚不充分、采用分段报价和统一市场清除价的电力市场，提出了一种为发电公司构造最优报价策略的方法。文中在历史报价数据尚不充分和获取其他相关信息的基础上，采用模糊集理论描述了发电市场中竞争对手的报价行为，并建立了报价策略的模糊优化模型，然后采用遗传算法求解得到发电公司的最优报价策略。最后用算例说明了该方法的主要特征。     

Energy bidding strategies for restructured electricity market

Many countries around the world have changed the economics of their electricity markets from monopolies to oligopolies in an effort to increase competition. The restructured electricity markets have introduced risk and uncertainty into a sector of the economy that was traditionally state-owned. Suppliers and customers use financial methods to manage the risk from market prices. The maximization of profit for power companies is highly associated with the bidding strategies. In order to maximize the profit, participants need suitable bidding models. In an open access electricity market, the bidding problem is a complicated task because of producer’s uncertain behaviors and demand fluctuation. Therefore, developing bidding strategy is extremely important for electricity market participants to achieve the maximum profit. This paper analyses a comprehensive literature on the state of the art research of bidding strategies in restructured electric power market.     

Price-taker在两个电力市场中的交易决策(一)购电商的策略

多市场交易量分配问题是电力市场参与者竞标决策中的重要问题之一.研究了考虑电价风险的情况下,Price-taker购电商在两个市场之间的交易量优化问题.讨论了购电商在两市场中优化分配问题的建模及解析解,引入风险因子概念,并用条件概率模型反映电价的不确定性,目标是总费用及风险均较低.用美国加州电力市场的实际数据进行了仿真.     

Optimal bidding strategies in oligopoly markets considering bilateral contracts and transmission constraints

In electricity industry with transmission constraints and limited number of producers, Generation Companies (GenCos) are facing an oligopoly market rather than a perfect competition one. Under oligopoly market environment, each GenCo may increase its own profit through a favorable bidding strategy. This paper investigates the problem of developing optimal bidding strategies of GenCos, considering bilateral contracts and transmission constraints. The problem is modeled with a bi-level optimization algorithm, where in the first level each GenCo maximizes its payoff and in the second level a system dispatch will be accomplished through an OPF problem in which transmission constraints are taken into account. It is assumed that each GenCo has information about initial bidding strategies of other competitors. Impacts of exercising market power due to transmission constraints as well as irrational biddings of the some generators are studied and the interactions of different bidding strategies on participants’ corresponding payoffs are presented. Furthermore, a risk management-based method to obtain GenCos’ optimal bilateral contracts is proposed and the impacts of these contracts on GenCos’ optimal biddings and obtained payoffs are investigated. At the end, IEEE 30-bus test system is used for the case study in order to demonstrate the simulation results and support the effectiveness of the proposed model.     

Market power implication on congested power system: A case study of financial withheld strategy

Market power refers to the ability of generators in influencing the energy prices above competitive level to obtain more profits. It may be the cause of transmission congestion that limits transfer capability in an interconnected area. Hence an independent system operator (ISO) must be able to detect the conditions in which market power has been practiced to guarantee a secure competition and economical operation of the electricity market. To cope up with transmission congestion to assess market power, an optimal power flow (OPF) based on shift-factor methodology to find out a new indicator, called congestion-based dynamic dispatch index has been proposed. One of the beneficial feature of the proposed method is the ability to recognise accurately the most potential generator to exercise the market power. A generator bidding scheme represented by financial withheld strategy is then utilised to investigate the dynamic condition of power market. An analysis on the power market performance to identify potential generators in exercising market power is also presented. The results show that transmission congestion condition may be created unnaturally by this particular bidding strategy. It prevents some cheap generators to supply their outputs and allows all more expensive generators within the congested zone to gain more profits at the cost of other market participants.     

基于效用分析方法的发电企业最优报价策略

不完全竞争的电力市场中,发电企业可以通过策略性报价来最大化利润。然而,在不完全信息的条件下,提出的报价策略一般都存在着一定的风险,如由于报价过高而没有被调度或被调度的容量明显小于期望值等。因此,对发电企业而言,需要对报价策略的风险和利润进行评估,构造兼顾利润最大和风险最小这2个矛盾目标的折中报价策略。文中针对这一问题进行了研究,提出了基于预测边际清算电价的计及风险的发电企业机组报价模型,将风险管理中的概率分析方法及效用分析理论引入报价方案的利润和风险评估中,并给出了求解方法,为解决计及风险的情况下构造发电企业的报价策略问题提供了新的途径。最后以一算例证明了该模型的可行性。     

Markov过程理论在发电商报价策略选择中的应用

在电力市场的环境下,发电商在报价策略选择的过程中将面临许多不确定性因素,如各时段的系统负荷、市场边际价格、对手的报价策略、自身发电成本等,本文从发电商的角度出发对竞价策略的选择问题进行研究,将竞价策略选择的过程设计成为Markov决策过程--一种抽象的随机优化方法,先将每个时段的报价简化为报价参数的选择,利用Markov过程理论对不确定性因素的出现进行概率估计,将发电商报价策略的选择问题表示为离散的随机优化过程--Markov决策过程;通过使期望收益最大来计算最优策略,从而确定了每个时段发电商报价参数的最优选择,并将报价参数还原成为报价结果.     

实时电力市场运营模式

随着电力市场改革的深入，实时电力市场将成为我国电力市场改革的重要内容，也是保证电网在市场环境下安全运行的关键。文中对实时电力市场运营中的报价、交易、阻塞管理等环节的模型和算法进行了分析和研究。设计了基于容量报价和调整报价两种实时报价方法，给出了将区域电价和实时电价相结合的阻塞管理方法以适应我国未来的多级电力市场模式。据此设计了相应的实时电力市场运营模式，根据该模式设计实现了实时电力市场技术支持系统。     

Congestion management impacts on bilateral electricity markets under strategic negotiation

Congestion management design is key to a fair and efficient use of transmission facilities and an improvement of market efficiency. Emergence of bilateral electricity markets provides a more flexible, private and decentralized decision-making scenario, in which the self-interested players autonomously search for counterparts to negotiate profitable transactions. In competitive bilateral markets of imperfect and incomplete information and explicit consideration of the network constraints, which make the markets significantly complex, more sophisticated bargaining strategies and market evaluation tools are imperative to both players and regulators.In this paper, under an assumption of imperfect and incomplete information, evolutionary bipartite complex network theory is employed to develop quantities bidding strategies through a dynamic game, in which the players drive the evolution of the network while maximizing their own utilities with explicitly considering the congestion management results. Resorting to adjustment bids, two congestion management schemes, with and without balancing bilateral transactions, are considered.The approach is illustrated with an application to the IEEE30 test system, assessing the impact of different congestion management schemes on the negotiations, market equilibria, market performance and gaming opportunities for the market participants in congestion managements.     

A Reinforcement Learning Model to Assess Market Power Under Auction-Based Energy Pricing

Auctions serve as a primary pricing mechanism in various market segments of a deregulated power industry. In day-ahead (DA) energy markets, strategies such as uniform price, discriminatory, and second-price uniform auctions result in different price settlements and thus offer different levels of market power. In this paper, we present a nonzero sum stochastic game theoretic model and a reinforcement learning (RL)-based solution framework that allow assessment of market power in DA markets. Since there are no available methods to obtain exact analytical solutions of stochastic games, an RL-based approach is utilized, which offers a computationally viable tool to obtain approximate solutions. These solutions provide effective bidding strategies for the DA market participants. The market powers associated with the bidding strategies are calculated using well-known indexes like Herfindahl-Hirschmann index and Lerner index and two new indices, quantity modulated price index (QMPI) and revenue-based market power index (RMPI), which are developed in this paper. The proposed RL-based methodology is tested on a sample network     

有限信息环境下基于学习自动机的发电商竞价策略

电力市场是典型的不完全竞争市场,发电商可以通过策略性报价以提高自身收益。现有的发电商报价策略研究通常假设发电商能利用充分的市场信息,但这种假设在市场启动初期往往不成立。为解决发电商在有限信息环境下的报价策略问题,文中提出了一种改进的强化学习自动机算法,该方法对外部信息量要求较低,且计算复杂度小,易于实现。此外,将发电商报价和市场出清的过程建模为重复博弈而非广泛使用的马尔可夫博弈,避免了马尔可夫博弈要求系统状态具有时间相关性这一强假设。最后,算例验证了该算法的有效性。     

Supplier's optimal bidding strategy in electricity pay-as-bid auction: Comparison of the Q-learning and a model-based approach

In this paper, the bidding decision making problem in electricity pay-as-bid auction is studied from a supplier's point of view. The bidding problem is a complicated task, because of suppliers’ uncertain behaviors and demand fluctuation. In a specific case, in which, the market clearing price (MCP) is considered as a continuous random variable with a known probability distribution function (PDF), an analytic solution is proposed. The suggested solution is generalized to consider the effect of supplier market power due to transmission congestion. As a result, an algebraic equation is developed to compute optimal offering price. The basic assumption in this approach is to take the known probabilistic model for the MCP.     

基于双人博弈且参数估计下的发电商报价策略研究

在竞争性电力市场下，发电商之间的竞价可以描述成一个不完全信息下的非合作博弈过程。该文在对发电商的策略性报价现有研究基础上,提出了发电商基于双人博弈、参数估计下的最优策略性报价，建立了数学模型并给出了其求解方法，从而较好地解决了现实情况中难以解决的多人博弈以及不完全信息的处理问题。其结论是：当对竞争对手的报价参数估计正确的情况下，其最佳策略收敛于纳什(Nash)均衡点。该文最后通过算例验证了该方法的有效性。     

电力市场中市场力的评估与发电竞标策略

提出发电公司竞标价格函数，并构建了在不健全市场下发电公司的竞标模型，在这种竞标模型和竞标价格函数的基础上对市场力加以评估。市场力的评估主要针对供不应求而且具有价格限制的市场。当市场经常出现供不应求的局面时，具有装机容量非常大或市场中主要的市场垄断者或所在地理位置可容易地造成输电阻塞等特性的发电公司，可利用其对市场需求的准确预测，来行使市场力，控制市场价格，从而获取高额的利润。数字仿真结果表明，在市场供不应求和市场供求均衡等2种情况下发电公司实现利润最大化的竞标策略完全不相同，从另一方面看也证实了市场力的存在和表现。     

基于纳什均衡理论的电力市场动态投标分析

为准确模拟电力市场参与者的动态决策过程,基于供给函数和纳什(Nash)均衡理论,考虑输电网固有的特性,提出计及输电网约束的电力市场动态供应函数模型。新模型由一差分动态系统和由非线性互补函数转换的半光滑方程系统构成,参与者策略报价的决策变量考虑为供应函数的线性和二次项系数。基于此两参数投标模型,以3个节点组成的电力市场为例,分析在不同市场参数和不同输电网运行状态(阻塞和不阻塞)下,市场的Nash均衡状况和均衡点的局部稳定性;通过数值仿真探讨不同市场参数对市场的动态行为及局部稳定性的影响;并与古诺(Cournot)模型进行仿真比较,仿真结果显示了供应函数模型更符合电力市场的运营情况。     

线路传输容量约束对电力市场均衡的影响

电力市场中最优竞标可描述成一个两层优化问题,其中在下层优化中ISO通过求解最优潮流(OPF)问题来最大化社会效益,而在上层优化中,电力供应商(发电商)通过线性供应函数竞标来最大化各自利润。线路传输容量约束将导致电力供应商决策空间分成不同区域,在任一决策区域内约束状态严格不变(或为严格等式,或为严格不等式)。而不同决策区域内约束状态不同又导致电力供应商在不同区域内有相应不同的最优策略。从市场均衡定义出发,通过在不同决策区域中搜索发电供应商最优响应曲线的交点来定位市场均衡点。文中首先研究一个简单的3节点系统,发现线路传输容量约束的引入导致市场可能有一段连续的均衡点,或是不存在均衡点;且如果均衡点存在,那么只能在约束边界式上发现,即不存在节点电价差或不存在网络拥塞费用。通过分析上述结论的内在因素,将其推广到复杂系统中。算例检验表明了文中分析的正确性。     

完全开放的双边电力市场中供需双方叫价拍卖的贝叶斯博弈模型

随着我国进行电力体制改革和建立发电侧竞争市场，需求方很快也会引入竞争，并建立完全开放的双边电力市场。研究供给侧和需求侧如何建立有效的报价策略具有十分重要的理论和实践价值。作者将所有发电公司看成供给方，把所有买电代理商看成需求方，将供给方和需求方的报价问题看成是他们向市场的投标问题，并根据市场确定的规则，总需求电量将在某一价格下完成交易，因而它是供给方和需求方的双方叫价拍卖问题。通过对双方叫价拍卖的交易规则进行描述，针对供给方的生产成本和需求方的估价是私有信息的情况，建立了完全开放的双边电力市场中供给和需求双方叫价拍卖的不完全信息贝叶斯博弈模型，并求解贝叶斯纳什均衡，给出供给方和需求方的均衡报价策略。     

计及输电约束的线性供应函数激励显示机制

基于博弈论中的机制设计理论和线性供应函数均衡(LSFE)理论,设计了一种激励相容的线性供应函数激励显示机制。依据该机制,所有发电商的最优报价策略为呈报其真实的边际成本曲线;所有用户的最优报价策略为呈报其真实的边际效用曲线;而且参与者(发电商和用户)是否披露其真实的经济信息与输电约束及其他所有参与者的报价策略无关,即所有参与者披露其真实的经济信息为市场惟一的纳什均衡,且该均衡为占优战略均衡。从而,独立系统运行员(ISO)根据参与者的报价曲线实施经济调度,以实现电力资源的优化配置和社会福利的最大化。不仅从理论上论证了所提出的激励机制的合理性,而且以IEEE3机9节点电力系统为例进一步验证了该机制在限制市场势力和提高电力系统运行效率方面的有效性。