Study On Genetic Algorithms In The Application Of Electric Power Market Transaction Decision-Making

Electric power market is a market where electric power and other auxiliary services are exchanged fairly according to the market rules between generation suppliers, transmission service suppliers and demand service suppliers. Electric power market transaction decision-making is a core of electric power market operation and its aim is to make transmission service supplier get maximum profit through competition between generation suppliers under constrains of unit, grid and market. Specialty of electric power market leads to specialty of electric power market transaction decision-making. Some problems such as how to describe electric power market transaction decision-making using mathematic model, how to solve this model using algorithms and how to effectively solve it are very important theoretically and practically and will be useful to the construction of electric power market in China.Under comparative analysis of traditional power dispatching model and electric power market transaction model, an electricity market transaction decision-making mathematic model is constructed. This model considers unit commitment or unit fees of startup and suspension, and it also considers two clearing methods based on unified marginal cost and practical bidding price. Aimed at defects of traditional optimization methods, GA(Genetic Algorithm) is proposed to solve electric power market transaction decision-making mathematic model. Based on natural selection and genetic mechanism, GA is an algorithm with characteristics of global optimization and parallelism. It can make up defects of traditional optimization methods. So a GA based method is proposed to solve this model. Because of some defects in standard Genetic Algorithms based on binary encoding and decoding techniques, a decimal-binary hybrid coding GA is proposed and according to the specialty of the model, some critical techniques, such as coding method, constrains-handling technique, genetic operator design and algorithm efficiency optimization method, are studied. Genetic Algorithm programs based on object-oriented design and implementation are suggested to improve algorithm efficiency and to favor parallel computation. Unified Modeling Language is used to model object-orientedGenetic Algorithm program. Class diagrams, interactive diagrams and methods of classare given in the essay.Using GA and its programs proposed in the essay, electric power market transaction decision-making mathematic model with linear bidding curve is analyzed and solved, and practically useful results are given. It proves that it is effective to solve electric power market transaction decision-making mathematic model through GA and its programs.