Research On Optimization Of Distribution Network Maintenance Plan Based On Partition

With the development of power system and the construction of smart grid, the expanding of power grid scale and the emergence of new technologies such as condition-based maintenance and distributed generation, has put forward a new challenge to the development of distribution network maintenance scheduling. Network equipment maintenance scheduling is one of the important tasks of intelligent dispatching. Network equipment maintenance scheduling is directly related to the vital interests of power supply enterprises and power users, and has a great impact on the reliability and economy of the whole system. In China, the distribution network maintenance scheduling is still mainly rely on manual experience to complete. A large amount of calculation, low working efficiency and subjective bias bring hidden trouble to the power grid operation.According to the status of distribution network maintenance scheduling, considering effects of climate, load and distributed power supply, this dissertation puts forward the model of distribution network maintenance division and decision model based on comprehensive risk assessment. The genetic algorithm is used to solve the model. The rationality and validity of the model and the algorithm are verified by the example of Jiangyan Taizhou power distribution network. In the view of the current situation of the power distribution network expanding, the number of equipment is increase. In response to this situation, a partition method of distribution network maintenance based on improved flame propagation model is proposed. In this method, a large scale distribution network is divided into a number of relatively small maintenance areas. On the one hand it can reduce the dimension and reduce the difficulty of solving the problem, on the other hand it can reflect the differences of load type, reliability requirements and equipment health level in different maintenance areas.In recent years, the global environment, continuous high temperature, winter freezing, snow storms and other bad weather, all of these cause great trouble to the safe operation of the distribution network. At present, most equipment failure rate evaluation model ignores the impact of climatic factors. In this thesis, the influence of temperature on transformer fault rate and the influence of bad weather on the impact of the failure rate of overhead line are analyzed. The mode of the influence of weather factors on the failure rate of distribution network equipment is established to improve the accuracy of equipment failure rate assessment.Based on the accurate calculation of the equipment failure rate, considering the influence of the load fluctuation and the distributed power supply, the optimization model of distribution network maintenance decision on comprehensive risk assessment is established. The comprehensive risk in the model is composed of the grid fault risk and the risk of power grid maintenance. The optimization model objective is to minimize the comprehensive risk of power grid operation. The model constraints include power grid security constraints, maintenance constraints, and maintenance resource constraints. A genetic algorithm is used to solve the optimal maintenance schedule. The push-pull driver is used to resolve the constraints of maintenance resource in the inter-partition collaborative maintenance problem. And the elastic dynamic resource scheduling model is used to coordinate accident maintenance and the planned maintenance.