Research On Multi-objective Optimal Reconfiguration Of Distribution Network Considering Wind Power Consumption

With the continuous social progress and economic development,the global demand for electricity is rising steadily,so the power grid is also growing and in the ascendant.However,the increasing shortage of traditional fossil energy and the aggravation of greenhouse effect also follow.In order to effectively alleviate these problems,new distributed power generation came into being.Among them,wind power is one of the most widely used distributed generation,which has a good development prospect.Wind power generation can effectively replace the traditional fossil energy generation,reduce energy consumption and slow down the greenhouse effect.However,wind power output is closely related to seasons and weather,and has natural randomness and volatility,which makes wind power consumption become another problem to be solved urgently.The lack of wind power consumption capacity will lead to serious wind abandonment problem.On the other hand,distribution network reconfiguration is a way to improve its reliability,reduce network loss,realize load balance and improve power quality by changing the network topology of distribution network;it is also a very important energy-saving means to improve its technology,strengthen its security and improve its economy.However,due to its inherent nature,as well as in the process of distribution network operation,it is easy to be affected by various factors,with uncertainty.Therefore,distribution network reconfiguration will be a complex and large-scale combinatorial optimization problem.After the distributed wind power energy is incorporated into the distribution network,the system is lack of energy consumption capacity,and the utilization rate of wind power is not high.In this paper,a new energy consumption mode is proposed,which combines wind power consumption with distribution network reconstruction.Considering the uncertainty of load,the fluctuation and randomness of wind power output and the number of switching operations,the objective of modeling is to minimize the proportion of wind power to be consumed and the number of switching operations,and the real number coding strategy based on independent loop is used to simplify the optimization process and improve the optimization speed.In view of the uncertainty of wind power,Weibull distribution is used to represent the wind power output,and confidence interval estimation is used to solve this problem.Compared with different mathematical methods,the shortest confidence interval fast solution method is selected to solve the confidence interval of wind power output.In view of the situation that the conventional differential algorithm is easy to precocity and fall into the local optimum,this paper intends to solve the problem from the perspective of quantum mechanics,and adopts the multi-objective quantum differential evolution algorithm,which improves the local search ability and effectively strengthens the individual diversity and search speed.Taking the ieee33 node system connected to the distributed generation as an example,the effectiveness and feasibility of the algorithm are demonstrated,and the effect of the reconstruction method used in this paper on improving the wind power consumption capacity of the distribution network is also verified.