The Study On Optimization Of Distribution Line Of Hengshui Taocheng Power Supply Company

With the high-speed development of national economy and people’s living standard is increasing day by day, electricity as a kind of the main and most widely used energy, people use electricity reliability, economy put forward higher requirements. Human demand for energy increasing at the same time, the problems in the operation of the power distribution network in the upgrade of industrial structure, improve power sales and price mechanism of some prominent problems to be solved. Main problem is lack of funding, line loss is higher and the reliability of the power not guaranteed. At the same time, between the three limit and to decrease network loss and power supply reliability guaranteed, it is necessary to increase investment, but the amount of money can bring large economic pressure to power supply company。So need the money, the network loss and reliability three aspects to find a balance way, so as to achieve the requirements of the distribution network optimization.Is described in the paper about distribution network optimization of the main method, and the line maintenance, wreck and operation cost, reliability and economical efficiency of these three aspects, analyzes the investment in the economy, on line power loss, the safety of power as the objective function under the premise of distribution network optimization mathematical model, according to current situation of taocheng district power network, through the transformation of the general model of multi-objective optimization, distribution network is established aiming at line loss, reliability, mathematical model, and define the constraints of the model, power distribution network based on genetic algorithm(ga) optimization method is presented. Finally, based on the software of MATLAB genetic algorithm toolbox and MATPOWER3.0 wrote a distribution network optimization program, hengshui taocheng district power network, for example, through the network line loss and reliability indexes before and after optimization comparison shows that the effectiveness of the proposed model and algorithm of listed in this paper.