Distributed Generation Hosting Capacity Assessment Method For Distribution Systems

With the rapid development of economy and technology,the demand for electrical energy is increasing.Under the background of the shortage of traditional fossil energy and the aggravation of ecological deterioration,the full utilization of renewable energy has become a global consensus.Therefore,the distributed generation has developed rapidly,and its large-scale penetration has become an unstoppable development trend of the new distribution network.However,the high permeability of the distributed generation brings many problems to the operation of the distribution network,such as voltage rise,reverse power flow and worse power quality.In addition,since the distributed generation is greatly affected by the external environment,its power output has significant uncertainty.Hence,there are intrinsic motivations to evaluate the capacity limit of distributed generation access to distribution networks.On the other hand,DG is developing rapidly in some areas,resulting in serious consumption problems.Therefore,the configuration of energy storage systems is indispensable,which can deal with the flexibility changes of distributed generation output,decline the electricity abandoned and increase capacity of DG into the network.The paper mainly focuses on the research of hosting capacity and consumption of distributed generation.Firstly,it analyzes the influence of distributed generation on the operating voltage of distribution network,and then based on the voltage sensitivity,the relevant indicators are established to guide the access of distributed generation and energy storage.Secondly,a distributed generation hosting capacity evaluation model based on robust optimization is established,which provides a reference for evaluating the access capacity of distributed generation in the distribution network.In addition,a dual-layer energy storage configuration model for distributed generation consumption is promoted,which provides theoretical guidance for energy storage allocation in distribution networks with large-scale solar and wind power sources.The main contents of this article are as follows:(1)From the optimization of the voltage of the distribution network as the starting point to study the most preferable location of distributed generation and energy storage,and the calculation method of timing sensitivity index of distributed generation and energy storage is proposed.Firstly,the offset of the node voltage is used as the weighting factor to improve the sensitivity index,secondly,the adjustment direction of different nodes is considered.Finally,the operating state of the system is different in different time periods,and the importance of the indexes in each period is different.Based on the time series model,a timing sensitivity index is proposed.(2)In the problem of determining the maximum hosting capacity of distributed generation in distribution network,considering the fluctuation of DG output and the uncertainty of load demand,a robust model of DG hosting capacity is established,which is constrained by the safe operation of the system.In order to coordinate the contradiction between the security of the system and the admission capacity of DG,a robust index is established to realize the uncertain interval adjustable robust optimization,which makes up for the excessive conservation of the traditional robust optimization.At the same time,in order to adapt to the new distribution network,the model considering the robust optimal operation of on load tap changers and static var compensators in the uncertain context of DG power outputs and load consumptions.Finally,the uncertain model is transformed into a determined mixed integer linear programming by robust linear optimization method.An effective method is proposed to evaluate the maximum admission capacity of DG in distribution network.(3)To improve DG consumption through energy storage configuration,a two-layer energy storage configuration model is proposed with the objective of minimizing the net present value of the economic cost.The upper objective function includes the installation cost of energy storage,replacement cost,energy storage arbitrage gain,and the reduction in active power loss.The decision variables are energy storage capacity and power.In this layer,energy storage cycle life model is established to calculate the actual service life for energy storage replacement cost.The lower layer determines the energy storage day operation strategy by considering the active power loss reduction and the energy storage arbitrage gain.A model solution scheme combining elite genetic algorithm and second-order cone optimization is proposed.