Research On Optimal Configuration Of Distributed Generation Considering Uncertainty

Under the background that the disadvantages of large power grid operation are increasingly prominent,the access of Distributed Generation(DG)can effectively alleviate the power supply shortage of distribution network,and the access of Distributed Generation relying on renewable clean energy generation also plays a positive role in solving energy crisis and environmental problems.However,with the increase of intermittent wind power and photovoltaic grid-connected capacity,the fluctuation of grid load and voltage is aggravated,and many uncontrollable factors are brought at the same time.Therefore,aiming at the uncertainty of wind turbine and photovoltaic output and load demand,this paper studies the optimal configuration of DG grid-connected,and realizes the location and capacity planning of distributed generation through intelligent optimization algorithm.Firstly,the power generation principle and grid-connected node types of common distributed generation are analyzed,and the power flow calculation of distribution network with DG is carried out by using the forward-backward generation method,and the influence of distributed generation access on distribution network operation is analyzed.The influence of distributed generation access on distribution network loss and voltage distribution is mainly studied through IEEE 33-node example.Secondly,aiming at the uncertainty of source load,the probability model of wind speed,light intensity and load is constructed Introducing multi-scenario analysis and adopting importance sampling to optimize Latin super-force sampling method to generate initial planning scenarios;The idea of density peak clustering and elbow method are used to improve the basic K-means clustering algorithm.The local density and relative distance in density peak clustering algorithm are used to determine the initial clustering center of K-means clustering algorithm,and the elbow method is used to determine the optimal cluster number K value.The improved K-means clustering algorithm is applied to scene reduction.Thirdly,considering the environmental benefit into the distribution network operation economy,taking the basic investment and construction cost,recovery benefit and environmental cost generated by DG grid connection as objective functions,the optimal allocation model of distributed generation based on multi-scenario analysis is constructed.The basic particle swarm optimization algorithm is improved,and the adaptive inertia weight factor is used to increase the optimization speed and efficiency in the iterative process of the algorithm;At the same time,the crossover mutation operation of genetic algorithm is used in iterative updating of particles to increase the diversity of particle population;Adopt elite retention strategy to avoid the loss of optimal particles;The test function proves that the improved particle swarm optimization algorithm can improve the convergence speed and accuracy,and has the ability to jump out of the local optimal solution.Finally,the simulation results of IEEE 33-bus system show that distributed generation access is beneficial to improve the distribution network loss and voltage distribution;Considering the uncertainty of source load,the distributed generation planning result is the best in economy;In addition,this paper also verifies the superiority of the improved particle swarm optimization algorithm in solving the optimal configuration problem of distributed generation.