Research On Probabilistic Power Flow Algorithm For Flexible Interconnected Distribution Network

With the rapid development of new power electronic technologies,flexible interconnected distribution networks composed of flexible DC devices or flexible DC distribution networks combined with AC distribution networks have become a current research hotspot.In response to climate change,the Chinese government has put forward the mid-to-long-term goal of "carbon peak and carbon neutrality".Distributed generation represented by green and sustainable power sources such as wind power and photovoltaics will develop rapidly.Distributed generation has the characteristics of intermittent and randomness.Its access to a flexible interconnected distribution network of a certain scale makes the originally uncertain system more complicated,which will affect the power flow control,loss,and operation protection of the system..Traditional power flow analysis methods are no longer able to analyze this highly complex uncertain system.Probabilistic load flow analysis methods are needed.However,there are currently few literatures on probabilistic load flow research on flexible interconnected power distribution systems.In view of this situation,this paper carries out research on the probability power flow calculation of flexible interconnected distribution network.Interconnected Distribution Network.Due to the many uncertain factors in the system,this article focuses on the study of the probabilistic load flow algorithm for flexible interconnected distribution systems with uncertain wind power,photovoltaics,and loads.The specific content is as follows:First of all,the probability model of wind power,photovoltaic and load in distributed generation is modeled and the point estimate method of probability power flow calculation method is explained.Based on the conventional three point estimate method,an improved three point estimate method calculation method is proposed.In view of the insufficiency of the traditional point estimate method that cannot handle dependent input variables,the probability density model and the cumulative distribution model,the correlation processing of wind power,photovoltaics,and load is carried out,and the probability density model and accumulation are fitted by the Cornish-Fisher series expansion method.The distribution model,and the analysis of calculation examples,verify the calculation accuracy,efficiency and scope of application of the proposed method,and prove that it has practical application value.Secondly,the common topology types of the DC part in the flexible interconnected distribution network are introduced,the DC power flow solution method based on the unified model is introduced,and the improved three-point estimate method based on the unified model is given for the calculation method and steps of the probability power flow of the DC distribution network.,The correctness of the proposed algorithm is verified through the analysis of a calculation example,which provides method support for the subsequent further research.Finally,the improved alternating iterative power flow calculation method for flexible interconnected distribution network is derived,and the probabilistic load flow calculation method and steps of flexible interconnected distribution network are given.Finally,the flexible interconnected distribution network containing only flexible DC devices and the DC distribution network are adopted.Two calculation examples of flexible interconnected distribution network are verified,and the results show that the improved three-point estimate method and the three-point estimate method can be used as the probabilistic load flow algorithm of flexible interconnected distribution network.Specifically,the improved three-point estimate method is suitable for the calculation of the probabilistic load flow of the flexible interconnected distribution network of small-scale systems,and the three-point estimate method is more suitable for the calculation of the probabilistic load flow of the flexible interconnected distribution network of the large-scale system.