Research On Optimal Configuration And Scheduling Of Distributed Power Supply With Energy Storage

Since entering the 21st century,new energy has always been developing at an extremely fast rate and high efficiency.Since the Chinese government put forward the strategic goals of"2030 carbon peak" and "2060 carbon neutral" at the United Nations General Assembly in 2020,the proportion of new energy as distributed power in the grid has gradually increased,and it is imperative to study the consumption of new energy.The development of Distributed Generation(DG)in China,which is represented by photovoltaic,wind power and hydropower,has made significant breakthroughs in distribution network.However,the fluctuations caused by the grid connection of distributed power cannot be solved under the existing conditions,so it is always necessary to adopt certain abandonment of new energy output,resulting in a waste of resources.The energy storage system can perform charging and discharging actions according to the real-time demand of the power grid,reduce the voltage fluctuation of the system,narrow the peak-valley load difference,and improve the stability of the system operation.But,for the research on optimal configuration and scheduling of distributed power supply with energy storage,the problem of energy storage location and capacity should be analyzed,and the scheduling optimization should also be considered to ensure the stable operation of the power system.Therefore,the thesis on distributed power supply with energy storage has important practical significance.This article conducts research from the following aspects:First of all,this paper takes the output prediction of distributed power supply as the research basis,establishes the output model of new energy and makes output prediction based on the actual operation data of Eastern Power Grid of Inner Mongolia,and conducts detailed analysis and research for the purpose of ensuring the accuracy and integrity of the data.The outlier detection based on isolated forest algorithm is used to preprocess the historical output data of distributed power supply.A long and short term memory neural network optimized by particle swarm optimization algorithm was used to construct the output prediction model.According to the above problems and processing methods,a complete data set of distributed power output prediction is obtained,which provides a rigorous and complete data set for the research.Secondly,aiming at the problem of energy storage optimization configuration,an energy storage optimization configuration model based on mixed integer second-order cone programming is established to optimize energy storage location and capacity configuration.The IEEE-33 node system is used to conduct simulation and example analysis.The energy storage configuration of the example is used to analyze the comprehensive influence of energy storage types,configuration nodes and number of configurations on the model.The results of energy storage configuration under different requirements and standards are obtained.Finally,aiming at the optimal dispatching problem of the "wind-photovoltaic-hydropowerstorage" joint system,under the condition of meeting the load demand of the system in recent years and the demand of future load forecast,various constraints such as power construction and investment constraints,power output constraints,power grid operation requirements,etc.,are considered.Based on the column and constraint generation algorithm,a two-stage robust optimal distribution network scheduling model is proposed to find an optimal network scheduling operation scheme,which maximizes the influence of uncertainty on the solution results.Finally,the IEEE-33 node system was used for simulation and example analysis to obtain dispatching results such as output conditions of various power sources and working conditions of various energy storage devices under this scheduling method,so as to verify that the optimization model established in this paper can ensure stable operation of the system considering the uncertainty of wind power and photovoltaic output,and has good robustness.