Optimizing The Allocation Of PMU Based Improving The Accuracy Of State Estimation

Along with the rapid development of power industry, the structure and operating mode are growing complexity. So modern scheduling system require rapid, accurate and comprehensive grasp of the operating state of the power system, forcasting and trend analysis of the operation system, running on the various issues put forward countermeasures. Guarantee the quality of the real-time datebase is to enhance the level of critical on line appplicatons.The synchronous phasor measurement technology is one of the most important technologies in modern electric power industry. Satellite, computer and communication technology's development, lays a foundation for the development of phasor measurement. Especially, since the 1993, the global position system (GPS) becomes popular. Because of its high accuracy, high reliability and high accuracy on timing, the technoloty of synchronous phasor measurement plays a major role in dynamic monitoring, security stability analysis and control and state estimation (SE) in power system. SE is the signify partition of energy management system (EMS). The other high lever application software of EMS are influenced by the performance of the SE.However, in priactical application, the power system is vast in area, if we have all substation installation of PMU, the system will greatly increase the one-time investment. Therefore, from the economic point of view, should adopt a phased investment approach, that is phase angle measuring device should be installed in a phased manner. This stage should be used in determining what areas should be installed phase angle measureing device, that is a optimization problem of the number and sits of installation.Combinatorial optimization has many ways, but the traditional search optimization method are heavy workload, can not gurantee that the optinal solution is the best or global solution. Genetic algorithm is the theory of natural selection and genetic basis of the process of the biological evolution, it is an efficient global optimization algorithm which combinate the survival of fittest rules of and the internal gropus of random chromosome information exchange mechanism. GA abandon the traditional the search, simulated the process of evolution in nature, using artificial evolution methods on the target space stochastic optimization search. Genetic algorithm is a broad search optimization method.On the basis of the traditional state estimation, this paper established a fixed state estimation model. Based on the model, the relation between the number and sits of PMU and error of the state estimation can be annlyzed quantitatively. Then, based in the research, Genetic algorithm is proposed to opitimize the phase angle measurement unit placement in order to improve the accuracy of state estimate and minimize the amount of phase angle measurement. The feasibility of the method was verified by using IEEE14 node networks.