Researche On Optimization Models And Methods Of Electric Power Industry's Value Chain In Electricity Market

The development of theory and practice of electric power market has started just now in China and require a lot of work to do. The reform of electric power market aims to improve the production efficiency of electric power industry, reduce the electricity expenses of consumers, and guarantee investors' reasonable revenue, in order to maximize the social benefits of electric power production and help the continuous and steady development of electric power industry. As a main body running independently in electric power market, it takes various actions in different conditions to make as much profit as possible. Therefore, the optimization models and methods of electric power industry value chain are of importance and difficulty, the main research and innovation to the problems in this thesis are as below:The first, combined with the reform outcome of other countries, this thesis analyzes the current electric power industry value chain in China and points out a lot of problems;studies the electric power industry value chain optimization in China by research on the economic leading of terminal rate to the consumers' response;it also researches the contents, emphases, projects based on the electric power industry value chain of generating, transmitting, distributing and using in order to propose some relevant measures for promoting the electric power industry value chain optimization.The second, in the problem of bidding strategies for the generation enterprises, the process of choosing bidding strategies is formulated as a Markov Decision Process —a discrete stochastic optimization method based on the research of part or total game models among power suppliers. This thesis simplify every period's bidding to a form of selecting bidding parameters, and utilize the Markov theory to estimate the probabilities that uncertainties factor, however, the power provider's bidding strategies choosing can be described as discrete stochastic optimization process-Markov decision process. The optimal selection of power provider's bidding parameters can be determined at every period based on the optimal strategy that maximizes the expected profit, and these parameters are converted to the bidding results.The third, regarding the risk of bidding strategy for the generation enterprises, this thesis compares its decision feature with risk decision characteristic;a risk decision method is used to solve the choosing of bidding strategy of power suppliers. Markowit portfolio theory is used to solve the multi-market distribution of annual generation capacity of power suppliers. It minimizes the risk when guaranteeing certain revenue,takes the utility function of power suppliers into bidding portfolio, and then comes to optimum portfolio taking generator utility function into consideration.The fourth, in the supplying part of electric power industry value chain, considering the existing have dispersed and continuous variables and its target function is discontinuous and non-derivative, this thesis presents a heuristic algorithm. This method is easy to calculate and converges fast, based on a dimension-reduced semi-analytical dynamic programming approach for unit commitment is presented.The fifth, in the distributing and using parts of electric power industry value chain, this thesis describes the economical significance for power suppliers and consumers, and the structure of time-of-use (TOU) rate based on peak-valley and the peak and valley time period partition approach are expounded by using price theory and economics theory. A TOU price target function is proposed based on the previous analysis, a model of the customer demand response to the TOU is thus presented from many references to a general customer demand response model. A new approach of peak-valley time-period partitioning and TOU rate setting is thus presented by optimizing the TOU price model as above of performance function in DSM. This thesis analyzes the TOU rate problem existing in China. It also discusses the questions that must be taken into account in TOUimplementing, for promoting the electric power industry development in China.