Research On Reactive Power Optimization Of Distribution Network Based On Multiple Scenarios With Wind Turbines

With the increasing shortage of globalized stone energy and the growing problem of environmental pollution,the realization of clean energy replacement on the power generation side has great and urgent practical significance.Among them,the development and utilization technology of wind turbines is relatively mature,and it has received people's attention and vigorous development.When the wind turbines are connected to the distribution network,not only the structure of the distribution network becomes more complicated,but also the wind turbines are connected to the distribution network to change the power flow.In addition,the active power loss,the node voltage,and the distribution system will be given.The stability of the system has a certain impact.The reactive power optimization of the power system plays an important role in the safe and stable operation of the system,reducing network losses and improving voltage quality.However,the wind turbines output has the characteristics of randomness and correlation,which makes the traditional reactive power optimization method no longer applicable.Therefore,this paper studies the reactive power optimization of distribution network considering the uncertainty of wind turbines output.Firstly,for the randomness of the wind turbine scene,the initial scene is obtained by Latin hypercube sampling and Nataf transform,and the corresponding probability model is established,then the probabilistic power flow calculation of the distribution network is carried out.Obtaining the statistical law of system output variables,The influence of wind turbines grid connection on the system is analyzed.Secondly,A hybrid H-K clustering algorithm based on the HAC algorithm and K-means clusteringit is said that the traditional H-K composite clustering algorithm can't get the best number of disadvantage.So the optimal clustering number is obtained based on the clustering effectiveness index of density.Some representative scenes are obtained by the method of scenario reduction.Then the corresponding wind turbine output is established.Finally,the objective function reactive power optimization model is established that contains the minimum expected value of the active power loss of the sy stem and the minimum expected value of the node voltage deviation by the typical scenario.At the same time,there is the differential evolution algorithm to improve the fast non-dominated sorting genetic algorithm.To sum up,there is reactive power optimization on the distribution network of wind turbines by improved NSGA-? performs.It proves that the reactive power optimization model can effectively reduce the network loss,improve the voltage quality and the stability of the system to ensure the safe and economic operation of the system through the example analysis of IEEE 33-bus.