Optimization Of Distributed Power Distribution Network Based On Probabilistic Load Flow

Distributed power control is more flexible,less polluting to the environment,and it can dissipate energy locally,so its role in the power system is increasingly important.After the distributed power supply in the distribution network is gradually increased,it will cause large interference to the initial structure and even the operation mode of the distribution network,among which the more intuitive changes in power flow,fluctuations in node voltage,and increase or decrease of network loss.Therefore,with the increasing popularity of wind power and photovoltaic power generation in distribution networks,new challenges have been brought to the optimal operation of distribution networks.In addition to the random volatility of wind power and solar power output,there is a certain correlation between wind speed,illumination and load.The impact of these correlations on grid operation is the same as the impact of randomness and volatility.Can not be ignored.Based on the correlation between wind speed,illumination and load,this paper studies the optimization of distribution network with distributed power supply by means of probabilistic power flow calculation of distribution network.Firstly,the influence of distributed power supply distribution network is briefly described.The research status of the domestic and international research on the optimization of distribution network with probabilistic currents and distributed power supply is analyzed.After the artificial intelligence optimization algorithm is comprehensively compared,it is determined that the particle swarm optimization algorithm is used to solve the final optimization model.Secondly,considering that the Latin hypercube Monte Carlo simulation method has higher computational efficiency and less computational error than other probabilistic power flow algorithms,the Monte Carlo simulation of Latin hypercube sampling is introduced to make detailed probability for the distribution network.Trend calculation.By analyzing the wind speed,illumination and load probability models,and using the Spearman rank correlation coeffiicient matrix to describe the correlation between the three,the acquisition process of the correlation sample matrix is given and added to the calculation process of the probabilistic power flow.A double-layer optimization model of distribution network is established.The upper layer optimizes the distribution network structure with the lowest network loss as the target.The lower layer carries out multi-objective planning of distributed power with the goal of minimum annual cost and minimum average voltage deviation of nodes.Finally,the improved particle swarm optimization algorithm is used to optimize the iterative model of the upper layer model,and the optimal result of the iteration is used to solve the lower layer model by using the multi-objective particle swarm optimization algorithm,and the optimal non-dominated solution set is used to make the decision.Get the final optimization plan.Based on the IEEE33 node distribution network system,the corresponding example analysis is carried out.The analysis proves that the importance of the correlation between uncertain factors is considered when optimizing the distribution network with distributed power supply.The optimization scheme is relatively good in terms of economic applicability and reliability,and can more effectively make the distribution network connected to the distributed power source maintain safe,economical and stable operation.