基于SP/A理论的发电商报价决策模型

在电力市场中,发电商的报价决策是一个风险决策过程.目前,一般使用效用函数描述发电商对风险的偏好程度.然而事实证明,效用函数关于决策者风险偏好始终一致的假设并不符合一般决策者心理.为此,使用价值函数代替效用函数来描述发电商变化的风险偏好,并借鉴SP/A(安全、潜力和期望)理论的决策思想,建立了发电商报价决策模型.该模型计及了安全概率和达到预期利润目标概率对发电商决策结果的影响,因而使得所选报价方案更符合发电商的心理愿望.最后通过算例验证了所建决策模型的有效性.     

基于SP/A理论的发电商报价决策模型

在电力市场中,发电商的报价决策是一个风险决策过程。目前,一般使用效用函数描述发电商对风险的偏好程度。然而事实证明,效用函数关于决策者风险偏好始终一致的假设并不符合一般决策者心理。为此,使用价值函数代替效用函数来描述发电商变化的风险偏好,并借鉴SP/A（安全、潜力和期望）理论的决策思想,建立了发电商报价决策模型。该模型计及了安全概率和达到预期利润目标概率对发电商决策结果的影响,因而使得所选报价方案更符合发电商的心理愿望。最后通过算例验证了所建决策模型的有效性。     

电力市场中考虑水头约束的抽水蓄能电站竞价模型

结合抽水蓄能电站水库水头与储能之间的关联关系,以及抽水蓄能机组出力的最高、最低限制,确定了机组最优的发电出力投标;在能够预测批发电力市场出清价格的基础上,构建了日前市场、双边合约市场以及辅助服务市场组合模式下的机组参与市场竞价的约束条件;同时引入了市场风险因素,建立了抽水蓄能机组在组合市场模式下的竞价决策模型;引入混沌变量对蚁群算法局部搜索部分进行了改进,并对决策模型进行求解。算例分析表明,在电力市场环境下,抽水蓄能电站通过合理安排发电计划和竞价决策能够获得更大的经济效益。     

电力市场下基于实物期权理论的电源投资动态决策模型研究

传统的电源投资模型基于净现值(NPV)分析工具,它没有考虑市场的不确定性,而电力市场环境下需要建立动态投资模型,以研究投资者如何利用投资选择权规避不确定性带来的风险。为此,该文基于实物期权理论研究提出电源投资动态决策模型。首先依据电源投资特点并结合等待投资期权理论,研究给出模型的数值求解过程,然后结合我国南方区域电力市场电源结构特点,通过对发电容量投资案例的仿真计算,研究了投资者面对市场不确定性获取等待型期权的动态决策,分析了价格上限和投资许可证有效期对投资决策的影响。该文的研究不仅能为电源投资者提供新的决策方法,而且也能为政策制定者制定有序吸引电源投资的产业政策提供理论参考。     

基于相对鲁棒CVaR的高不确定性机组日前竞价申报优化

日前电力市场中,机组需提前一天申报竞价信息,高不确定性机组次日实际出力与日前申报出力存在偏差,从而产生弃能及偏差惩罚费用。考虑预测出力存在多种概率分布时的不可比问题和日前竞价的风险决策问题,基于相对鲁棒条件风险价值(relativelyrobustconditionalvalueatrisk,RRCVa R)构建了高不确定性机组日前竞价申报优化模型,并对比了风险中性决策模型和条件风险价值(conditionalvalue at risk,CVa R)决策模型的决策情况。算例分析结果证明了所构建模型的有效性和合理性,并表明在多概率分布不可比时,RRCVa R模型的竞价决策优化结果具有相对较好的利润表现及风险规避能力,竞价决策的CVa R均不高于最大预期尾部损失,且当决策者风险态度趋向保守时,竞价决策的CVa R与风险价值趋于持平,即无超额损失。     

电力市场环境下计及风险的发电公司中期运行规划

在电力市场环境下,发电公司需要对中期运行进行合理规划,以最大化其售电收益.在进行中期规划时,需要综合考虑其在现货市场和合约市场的售电策略,以及检修计划的合理安排,并采用适当方法管理风险.通过采用条件风险价值(CVaR)模型度量售电收益风险,并在计及输电阻塞对合约交易的影响下,为发电公司构造了一种兼顾期望利润最大化和CVaR风险值最小化的中期运行规划模型.将年度发电计划转化为计及机组物理约束的日发电计划,并提出了结合遗传算法和蒙特卡罗方法的求解方法.最后用算例说明了该方法的基本特征,并分析了合约参数、置信度等相关因素对发电公司决策效用的影响.     

市场机制下考虑节能环保的日计划新方式

在国家节能环保的政策下,新的发电调度方式如何与竞价上网的电力市场机制有机结合起来,是一个值得研究的问题.文中提出了市场机制下考虑节能与环保多目标的日计划新方式,定义了多目标决策模型的满意度与贴近度概念,从而将多目标模型转化为基于目标满意度的单目标决策模型.决策者可以调整目标满意度与贴近度进行交互式求解,得到各方面均衡的满意结果.算例仿真表明,该文的模型与方法能够主动协调市场公平竞争与环境保护,简便可行,可用于工程实践.     

基于展望理论的发电厂商最优报价

在电力市场中,发电商的报价决策是一个风险决策过程。展望理论描述人们在经济活动中对于风险偏好与其预期利润目标相互关系的理论：当利润大于其预期目标时,大多数倾向于回避风险,而当利润小于其预期目标时,则倾向于追求风险以尽可能实现预期目标。该文将展望理论用于制定发电厂商的报价策略,提出了基于展望理论的计及风险的发电厂商的最优报价策略。由于该模型同时考虑竞价失败风险和预期利润目标在报价决策过程中对发电商决策思想的影响,使得所选报价方案更符合发电商的心理愿望。算例证明了所提出的方法的可行性和有效性。     

发电公司的不完全信息竞价博弈模型

运用博弈论中的第一价格暗标拍卖原理，研究发电公司的不完全信息竞价博弈模型。该模型考虑了发电公司的单位成本、竞价成功的可能性概率及预期的市场清除价格等因素，通过求解模型得出发电公司报价的一般表达式。最后用算例说明了该方法的合理性和可操作性。     

可再生能源配额制下售电公司多市场交易决策

可再生能源配额制实施后,售电公司面临着电力交易市场和绿证市场的多市场组合交易决策问题。基于配额制下售电公司市场交易框架及模式,考虑售电公司多种购电渠道的购电成本、柔性合约成本、绿证交易成本及售电收入,以条件风险价值法度量相关不确定因素带来的风险值,构建多市场组合交易决策模型。运用多场景法对风电出力、集中竞价市场出清价格、绿证价格等不确定因素生成典型场景集,以售电公司收益最大、市场交易风险最低为决策目标,采用GAMS软件对决策模型进行编程求解。算例仿真分析了风险规避系数、风电出力不确定性、可再生能源配额比例等因素变化对售电公司收益的影响,对模型的有效性进行了验证,为配额制下售电公司参与多市场交易决策提供理论指导。     

Security-constrained optimal generation scheduling for GENCOs

This paper presents an approach for maximizing a GENCO's profit in a constrained power market. The proposed approach considers the Interior Point Method (IPM) and Benders decomposition for solving the security-constrained optimal generation scheduling (SC-GS) problem. The master problem represents the economic dispatch problem for a GENCO which intends to optimize its profit. The formulation of the master problem does not bear any transmission network constraints. The subproblem will be used by the same GENCO to check the viability of its proposed bidding strategy in the presence of transmission network constraints. In this case if the subproblem does not yield a certain level of financial return for the GENCO or if the subproblem results in an infeasible solution of the GENCO's proposed bidding strategy, the GENCO will modify its proposed solution according to the Benders cuts that stem out of the subproblem. The study shows a more flexible scheduling paradigm for a GENCO in a competitive arena. The proposed approach proves practical for modeling the impact of transmission congestion on a GENCO's expected profit in a competitive environment.     

GENCO's Risk-Based Maintenance Outage Scheduling

This paper presents a stochastic model for the optimal risk-based generation maintenance outage scheduling based on hourly price-based unit commitment in a generation company (GENCO). Such maintenance outage schedules will be submitted by GENCOs to the ISO for approval before implementation. The objective of a GENCO is to consider financial risks when scheduling its midterm maintenance outages. The GENCO also coordinates its proposed outage scheduling with short-term unit commitment for maximizing payoffs. The proposed model is a stochastic mixed integer linear program in which random hourly prices of energy, ancillary services, and fuel are modeled as scenarios in the Monte Carlo method. Financial risks associated with price uncertainty are considered by applying expected downside risks which are incorporated explicitly as constraints. This paper shows that GENCOs could decrease financial risks by adjusting expected payoffs. Illustrative examples show the calculation of GENCO's midterm generation maintenance schedule, risk level, hourly unit commitment, and hourly dispatch for bidding into energy and ancillary services markets.     

Analysis of equilibrium-oriented bidding strategies with inaccurate electricity market models

In order to make competitive electricity markets effective, bidding generation companies (GENCOs) need to estimate market demand models according to information available to each of them. However, many stochastic factors (e.g. weather, demand side features) make it very hard for GENCOs to accurately capture the actual market demand in a model. Each GENCO might hold an estimated model deviating, from the real market model as well as from its peers’. Little work has been done in discussing the impacts of model deviations towards the design of GENCO’s bidding strategies.In this paper, the effects of model deviations upon the equilibrium-oriented bidding methods (EOBMs), more specifically conjectural variation (CV) based methods, are studied. We relax the strong assumptions that one uniform and accurate market demand model is employed by all GENCOs in the basic CV-based learning bidding algorithm (CVBA). In this work, the market demand model utilized for bidding by each GENCO is different from each other and from the actual market model as well. The impacts of such model deviations are analyzed from both theoretical and simulation perspective. Theoretical analyses point out that as a consequence of the model deviations it is possible that the basic CVBA algorithm will bring the bidding process into an unstable state. In order to eliminate the effects from inaccurate modeling, a CV-based learning bidding method with data filtering capabilities is proposed. Several sets of simulations have been done to test the impact of the model deviations. The simulation results confirm the theoretical analyses. The feasibility and effectiveness of the proposed bidding methods are also verified. The proposed algorithm can bring systems into stable state even when model deviations exist.     

考虑需求响应和储能的微电网市场竞价策略

由于可再生能源出力的间歇性、负荷用电量和市场电价的不确定性这两方面因素,使得微电网内的竞价策略存在较大的风险和和较高的计算难度.为应对这些问题,设计采用三阶段混合随机/区间优化(Hybrid Stochastic/Interval Optimization,HSIO)模型来构建微电网内部的竞价问题,通过微电网内潜在灵活资源和实时市场支撑这两种方式来处理上述波动.其中,采用经济有效的随机规划来实现日前市场决策中的微电网利益最大化,从而解决日前市场价格的不确定性.此外,设计了一种基于快速鲁棒区间优化的灵活方法来实现实时阶段微电网的平衡成本最小化,从而应对可再生能源能出力的间歇性和实时市场电价的不确定性.算例综合比较分析了所提出方法的有效性、鲁棒性和计算复杂度.结果 表明HSIO模型能够同时兼具随机规划模型的成本效益性和区间优化模型计算简单和鲁棒性的特点.     

Supplier bidding strategy based on non-cooperative game theory concepts in single auction power pools

In single auction power pools, only generators bid several energy price segments depending on the amount of energy supply, at individual generating companies’ (GENCO) own discretion, for every trading interval. Then all selected bidders are paid a uniform Market Clearing Price (MCP). In this paper, it is realized that each GENCO has the complete information on its own payoff as well as the other parties’ payoffs, corresponding to each potential combination of choices of strategies by all the players. Specifically, all the suppliers attempt to estimate the others’ bids using the concept of Nash equilibrium in the general sense of profit maximization. Under some simplified assumptions, this problem can be modeled as a simultaneous-move game confronted by the bidders. Here, the system demand forecast by competitive sellers is captured for the purpose of constructing the optimal bidding strategy. Finally, a numerical example is presented demonstrating the effectiveness of the proposed solution scheme.     

市场环境下发电厂商机组检修新策略

提出市场环境下基于单台机组弹性检修模型的发电厂商(generating company,GENCO)机组检修新策略。针对单台机组多出力运行状态,提出评估检修与否的两个经济指标：检修经济损失值Loss和运行风险损失值Loss,P,前者反映了机组检修时的经济损失,后者反映了继续运行时由于故障造成的风险损失,通过比较两者,便可确定单台机组的最优检修时段及可检修区间。根据该发电厂商中各机组的预期经济损失ELoss值确定其规划检修顺序,在单台机组的弹性检修模型基础上,依次确定各机组的检修时段。在该策略下,各机组不再按传统的固定时间间隔进行检修,确保了其安全经济运行,体现了发电厂商的市场主体地位。最后,用一个简单算例说明了该策略的合理性与有效性。     

考虑空调负荷虚拟储能的产消者鲁棒日前申报策略

在分布式可再生能源大力发展的背景下,产消者将成为新的重要利益主体参与电网运行。考虑到产消者中空调负荷具有良好的调控潜力,文中首先建立了空调负荷的虚拟储能模型,并在此基础上分析了虚拟储能与常规储能的不同之处。针对虚拟储能可参与日内调控的特点,考虑可再生能源出力不确定性,提出了产消者鲁棒日前申报策略,并进一步提出了将虚拟储能日前决策与实时调整相结合的产消者最优申报及调度策略,运用改进的列约束生成算法进行求解。最后对具体算例进行比较,证明了最优策略在产消者运行灵活性与经济性方面的优势,并分析了可再生能源出力不确定性、惩罚价格选取及室外温度对实际结果的影响。     

A hybrid approach based on IGDT–MPSO method for optimal bidding strategy of price-taker generation station in day-ahead electricity market

This paper considers a price-taker generation station producer that participates in a day-ahead market. The producer behaves as a price-taker participant in the day-ahead electricity market. In electricity market, the price-taker producer could develop bidding strategies to maximize own profits. While making optimal bidding strategy, the market price uncertainty needs to be considered as they have direct impact on the expected profit and bidding curves. In this paper, a hybrid approach based on information gap decision theory (IGDT) and modified particle swarm optimization (MPSO) is used to develop the optimal bidding strategy. Information gap decision theory is used to model the optimal bidding strategy problem. It assesses the robustness/opportunity of optimal bidding strategy in the face of the market price uncertainty while price-taker producer considers whether a decision risk-averse or risk-taking. The optimization problems to delivering IGDT approach are solved using MPSO. It is shown that risk-averse or risk-taking decisions might affect the expected profit and bidding curve to day-ahead electricity market. The IGDT–MPSO method is illustrated through a case study and compared to IGDT–MINLP method.     

基于区间规划的可用传输容量计算方法

区域间可用传输容量是保障系统安全的指标之一.在电力市场环境下,发电机报价的不确定性将给电网可用传输容量计算带来很大偏差.文中基于区间数理论,引入了广义报价的新理念,详细分析了广义报价作用下的发电序位决策方法,构建了不确定性的电网可用传输容量计算新方法.该方法可方便地求解不同市场购电期望水平下不确定性的电网可用传输容量,...