Distribution Network Planning Based On The Ordinal Optimization Theory

Distribution network is the last link to the users in power system, it sensitively reflects the request of the users in the security, quality and economic aspects. The reliability and quality of the power supply of the distribution network are directly related to the development of the national economy and people's daily life, so that an optimal distribution network which satisfying the economic and reliability requirements has a very important significance. This paper concentrates on the distribution network planning modeling and its solution method. The main contents are as follows:Firstly, the study status of the distribution network planning are summed up, based on different periods of development, both in terms of planning models and algorithms are reviewed, and the features and difference of the models and algorithms are analyzed.A model on distribution network is presented, and the objective of the model is to minimize the total cost including the fixed investment, maintenance costs and feeder resistive loss, while the node voltage and feeder and transformer capacities are kept within the specified limits. In view of structural features of the distribution network, used the distflow method to calculate the power flow to avoid the matrix operation, this method is simple and can get a high efficiency.Ordinal Optimization theory is used to solve the model, it can overcome the dimension problems and can guarantee to get good enough planning schemes with high probability, so that the final outcome of the planning merits can be quantified, and the result has a high practical value.Furthermore, the ordinal optimization theory was combined with the genetic algorithm optimization (GOO) to solve the limitations of each single algorithm. Use the idea of ordinal optimization to guide the evolutionary operators of genetic algorithm. This method can overcome the troubles of the GA such as premature convergence,the hardness to determine stopping criterion, and it guarantees to get the global optimal solution with a high probability.