【作者】 黄大为；

【导师】 郭志忠； 韩学山；

【作者基本信息】 哈尔滨工业大学 ， 电力系统及其自动化， 2008， 博士

【摘要】 电力工业的市场化改革已经成为我国电力工业发展的必然趋势。我国电力市场的发展还处于初级阶段,仅在发电侧引入竞争,火电厂作为电力市场的竞争主体,通过参与市场竞争来获得经济效益。如何建立符合电力市场交易情况的竞价决策模型,制定优化的竞价策略来实现电厂竞价利润的最大化,已成为火电厂急须解决的问题。本文从指导火电厂参与电力市场竞价交易、提高电厂经济效益的角度出发,对火电厂竞价决策问题进行了研究。目前我国电力市场的竞价交易以电能交易为主。火电厂的竞价交易主要在中长期交易市场和日前交易市场中进行。本文结合火电厂的生产特点和我国电力市场发展的实际情况,针对火电厂竞价交易中所面临的主要问题,构建了火电厂竞价决策的整体框架。该框架主要对三个层面的问题进行分析:中长期交易中的发电量优化分配问题,日前交易市场中的多时段竞价问题,峰荷交易时段输电网络约束对火电厂竞价决策的影响。我国电力市场的电能交易需要通过年度、月度以及日前交易多个交易市场来完成。由于受发电成本、各交易市场电价以及供需关系等因素的影响,按不同比例将有限的发电量分配到各交易市场,所获得的风险和收益会有很大差异。为了协调火电厂的竞价利润和风险,本文提出了基于满意度的发电量优化分配决策模型。该模型借鉴模糊投资组合理论,结合决策者经验和对待风险的态度,将反映利润和风险的各项指标进行模糊化处理,通过模糊优化确定符合决策者满意度的电量优化分配策略。该模型较适合我国电力市场历史数据不足的实际情况,可以为电厂制定月度竞价策略提供理论依据。在日前交易市场中,发电厂主要解决的问题是,如何合理安排次日各交易时段的竞价电量,使发电机组在满足合同电量的前提下,获得更多利润。本文通过对历史交易数据的分析处理,给出反映市场电价与电厂中标容量之间量化关系的电价模糊回归模型,在此基础上建立了基于模糊机会约束规划的多时段竞价决策模型。该模型考虑了市场电价不确定所引起的风险问题,通过选择置信水平和悲观利润与乐观利润的折中系数,体现决策者对待风险的态度。根据优化模型的特点,提出了改进的离散二进制粒子群优化算法和遗传算法相结合的求解方法。分别针对目标函数和约束条件的特点,给出适应求解该模型的启发式规则和粒子生成策略,保证新生粒子为该优化问题的可行解,提高了离散二进制粒子群算法的性能。在峰荷时段,输电元件上的传输功率往往会达到其输电容量的限值,输电容量约束的存在将直接影响电力市场的出清结果,进而影响到发电厂的竞价利润。本文采用考虑合同电力的线性供给函数均衡模型,分析在峰荷时段输电网络约束对火电厂竞价决策的影响。对无约束和计及网络约束情况下,电厂的Nash均衡策略进行了比较研究,并针对峰荷时段发电厂竞价所特有的现实条件,提出了一种改进的循环迭代方法,用来求解Nash均衡。该方法可以在一定程度上避免由于初始值选择不当导致的迭代不收敛,而且迭代过程可以保证网络阻塞状况不发生变化,有利于得到符合现实意义的Nash均衡。为了根据自身特点和外部市场环境制定合理的竞价策略,发电厂需要对自身以及竞争对手的在电力市场中的竞争地位进行分析和评估。本文建立了面向发电厂的市场力评估指标体系。该评估指标体系分为预评估指标和后评估指标。重点分析了预评估指标的构成。在分析发电厂的必发容量的基础上,运用潮流追踪方法从微观层面分析了发电厂对节点和支路的影响,提出了发电厂供电控制区域的概念,由此构成了反映发电厂对节点、支路、区域乃至系统影响的预评估指标。预评估指标用于比较评价各电厂的位置优势,后评估指标则用于评价电厂自身市场力水平和竞价策略的优劣。本文研究工作得到了国家自然科学基金项目(项目编号:50377021)的资助,部分研究成果在烟台发电厂运营决策支持系统中得到应用,该项目获得山东省科技进步二等奖。更多还原

【Abstract】 Power market is the trend of Chinese power industry. Chinese power market is in the original period which there is competition only in the supply side. Power plant gets profit through competition as the main part in the market competition. How to built bidding decision model according with the market trade condition, establish optimal bidding strategy to maximize bidding profit of the plant is in urgent need for the power plant. In this thesis the power plant bidding strategy problem is studied from point of power plant taking part in power market bidding trade and increasing the profit of power plant.At present the main trade is for energy in Chinese power market. The bidding trade of the power plants is going on mainly in the medium and long trade and day-head market. In this thesis aiming at the main problem that will be met in the power plant bidding trade combined the power plant’s producing characteristics and real condition in Chinese power plant developing, the power plant bidding decision framework is built. In this framework three aspects of problems are analyzed which are optimal generation allocation in medium and long trade market, multi-periods bidding in day-ahead trade market and the influence of transmission constraints on power plant bidding decision in peak load trade period.The energy trade in Chinese power market should be accomplished in year market, month market and day-ahead market. Influenced by the generation cost, different prices in market and relationship between supply and demand the limited generation allocated in each market according to different proportion will lead to different risk and profit. To harmonize the profit and risk of the power plant in this thesis an optimal allocation decision model based on satisfaction is proposed. In this model the fuzzy investment portfolio theory is used for reference. Combined with the experience of the decision-maker and his attitude to risk, the indexes reflecting risks and profits are expressed by fuzzy sets. The optimal generation allocation strategy accord with decision-maker satisfaction is decided by fuzzy optimization.In day-ahead trade market the main problem should be solved is arrange next day bidding generation in each trade period reasonably to get more profit in premise of satisfy the contract generation. In this thesis the historic trade data is analyzed, the fuzzy regression model which reflect the relationship between the market price and generator allocated generation is given. On this basis the multi-period bidding decision model based on fuzzy chance-constrained program model is built. In this model the risk problem caused by uncertainty of market power price is considered, the decision-maker’s attitude to risk is reflected by selecting confidence level and tradeoff coefficient of pessimism profit and optimism profit. Considering the characteristic of this model the BPSO and GA are united to solve this problem. Aiming at the characteristics of the object and constraint condition, the heuristic rules and particle generation strategy to solve this model is given to assure the new particle is the feasible solve for the optimization problem and the performance of BPSO is improved.In the peak load period, the transmission power in the transmission equipment will reach the transmission capacity limit which can affect the clearing result of the power market and the bidding profit of the power plant. In this thesis the linear supply function equilibrium model of contracted power is considered, the power bidding decision with transmission constraints during peak load period is studied. The Nash equilibrium decisions with and without network constraints are compared. For the special real condition of power plant bidding in peak load period an advanced circulation iteration method is proposed to solve Nash equilibrium. This method prohibits iteration disconvergence by improper selection of original data. The iteration process guarantees that the congestion condition of the network will not change. And the solved Nash equilibrium has real sense.To make reasonable bidding strategy based on its characteristics and market environment outside, the power plant need to analyze and evaluate the position of itself and competing rival. In this thesis the market power evaluation index system for power plant is built. The evaluation index system is separated into pre-evaluation and post-evaluation index. The composition of the pre-evaluation is analyzed for emphasis. On the basis of analyzing must-run capacity the power flow tracing method is used to analyze influence of plant on node and branch from the point of microcosmic. The power plant serving control area is proposed. And on this basis the pre-evaluation index reflecting influences of power plant on node, branch, area and the system is formed. The pre-evaluation index is to compare the advantage of power plant position and the post-evaluation index is to evaluate self-market power and the bidding strategy.This research work is supported by National Nature Science Foundation (50377021). Part of the research results has been applied in Operation Decision Supporting System of Yantai Power Plant. This project achieved the Shandong Province Science and Technology Advancement Award.更多还原