SOC State Evaluation Of Battery Energy Storage System Based On AGC FM In Thermal Power Plant

Advanced large scale energy storage system has the ability to accurately control the charging and discharging power,and it has been applied to the power grid frequency modulation has incomparable advantages compared with the traditional fm.Energy storage,as a high performance FM resource,will increase the level of energy saving and emission reduction of power generation side,and improve the acceptance of renewable energy from the grid side.In this paper,the SOC state evaluation is analyzedbased on the energy storage system of the AGC power plant,and the battery energy storage system state evaluation model is established.The research content is as follows:1、The thermal power plant AGC FM was introuduced,we analyzed the necessity and significance of the thermal power plant AGC FM.The control scheme of energy storage system of power plant auxiliary AGC FM were introduced,respectively introduces the system output control.2、 For the operating conditions of power plant with energy storage system,the coordinated control logic between the unit and the energy storage system and the combined response of the unit and the energy storage system are analyzed.From the two aspects of the output control precision and the response speed of the energy storage system,the closed-loop operation of ACE and the performance test results are analyzed.3、PSO-BP neural network is used to realize SOC evaluation of energy storage system.Taking the battery current and voltage as the input of the neural network,and the SOC state estimation as the output of the neural network,the PSO-BP neural network SOC state evaluation model is established.Compared with the traditional BP neural network,the PSO-BP state evaluation model has higher accuracy for the SOC state assessment.