Research On Optimal Dispatching For Active Distribution Network Considering High Proportion Distributed Photovoltaic Stochastic Characteristics

With the increasing penetration of distributed photovoltaic in the distribution system,its decentralized and random characteristics make the safe and economic operation of the distribution system face serious challenges.On the one hand,the distributed photovoltaic is difficult to predict accurately,and the errors brought by it aggravate the uncertainty of power flow distribution in the system,affecting the economy and reliability of the system power supply;on the other hand,when dealing with uncertainty,the huge amount of adjustable resources with different characteristics increases the difficulty of regulation and makes the operation efficiency of distribution system low.In order to cope with the above challenges,this paper studies the optimal dispatching for active distribution network considering high proportion distributed photovoltaic stochastic characteristics from three dimensions:improving the coordinated optimization effect,dealing with random characteristics and promoting efficient utilization of resources.The main works are summarized as follows:(1)In order to exploit the coordination ability of various active and reactive power resources in improving the operation economy of distribution network,an active and reactive power coordinated optimal dispatch method for active distribution network with distributed photovoltaic considering conservation voltage reduction is proposed.Firstly,a variety of distributed resource mathematical models including micro gas turbine(GT),energy storage system(ESS),on-load tap changer(OLTC)and reactive Var compensation(SVC)as well as the operation model of active distribution based on branch power flow are established.The second order cone relaxation method is used to convert the original model to achieve efficient solution.Secondly,based on the above model,an active and reactive power coordinated optimal dispatch method for active distribution network considering conservation voltage reduction is proposed.The stochastic characteristics of distributed photovoltaic are described by opportunity constraint,and considering the regulating ability of various distributed resources,the active and reactive power coordinated optimal scheduling model is established.Then,according to the exponential polynomial model of load power,the sensitivity relationship between load power and feeder voltage is constructed,and the method of conservation voltage reduction(CVR)is introduced.Through the coordination of on-load tap changer and other reactive voltage regulating resources,the energy-saving purpose is realized with reasonable operation strategy of voltage reducing.Finally,case studies show that the proposed method can effectively reduce the network loss and realize the energy-saving operation of the system by coordinating the active and reactive power regulation resources.(2)In order to accurately grasp the random characteristics of distributed photovoltaic,an optimal scheduling method of active distribution network based on time-space-power three-dimensional modeling of distributed photovoltaic prediction error is established.Firstly,the mathematical model of distributed photovoltaic prediction error is established from the perspective of time-space-power,considering the temporal correlation of prediction errors in adjacent prediction periods,the spatial correlation of multiple distributed photovoltaic prediction errors in the same region,and the influence of absolute power value on the correlation of prediction errors.This model can provide more accurate error analysis results for dispatching.Secondly,based on the established prediction error model,a two-stage scheduling method is proposed:in the day-ahead stage,the operation state of slow-response resources is optimized and determined.In the intra-day stage,power sequence fluctuation information is identified and matched based on the latest photovoltaic prediction information,the prediction error distribution is updated,and the output of the fast-response resources is adjusted.Finally,case studies show that the proposed error modeling method has a good tracking effect on photovoltaic power and the application of this model to optimal scheduling can reduce the influence of error randomness on scheduling decisions,and improve the safety and economy of system operation.(3)In order to realize accurate and efficient utilization of energy storagy resources,a multi-time scale optimization scheduling method of active distribution network considering cycle life of energy storage system is proposed.First,a cycle life evaluation model of energy storage system based on depth of charge and discharge and operation model of energy storage system considering over-charge and over-discharge are established.By balancing benefits and loss of life brought by over-charge and over-discharge,the capacity of energy storage system can be efficiently utilized.Secondly,based on the above energy storage system operation model and stochastic model predictive control(SMPC)theory,a multi-time scale optimization framework is established,which expands the optimal scheduling into three sub-stage optimization problems of day-ahead,intra-day and real-time to coordinate the economic cost and operational risk of the scheduling.In the day-ahead stage and intra-day stage,the economic optimal scheduling is carried out.Through the operation decision of over-charge and over-discharge of the energy storage system and the coordination of resources with fast and slow response characteristics in short and long time scales,the output reference track of slow-response and fast-response resources is determined to ensure the economic operation of the system.In the real-time stage,a feedback mechanism is introduced based on ultra-short-term prediction information,and the plans of fast-response resources output are modified in real time.The capacity of the micro-gas turbine,static reactive Var compensation and other fast-response resources are adjusted to cope with the fluctuations of photovoltaic output.Finally,case studies verify that the proposed method can significantly improve the utilization of equipment capacity,improve the utilization efficiency of resources,and improve the economy and reliablity of the system operation.