Research On Optimal Configuration Of Hybrid Energy Storage System Based On Full Life Cycle

With the rise of smart grids,my country has placed distributed energy construction in a strategic position.However,distributed energy has the characteristics of intermittent and volatility.Adding an energy storage system to the microgrid can not only improve the reliability of the power supply,but also bring direct economic benefits to users.In this paper,Under the condition of preprocessing the Wind power and photovoltaic data,this paper establishes the comprehensive benefit model and life prediction model of hybrid energy storage for multiple scenarios,formulates different control strategies according to different power consumption regions,and uses intelligent optimization algorithms to solve the comprehensive model.Focusing on the hybrid energy storage system composed of super capacitors and batteries,the main work of this article is aimed at the following aspects1)Analyze the influence factors of wind power,photovoltaic power generation system and load data.Select wind power and photovoltaic data in a certain area of Heze City,Shandong Province.Introduce the extreme learning machine algorithm,and propose improvement strategies based on the characteristics of the extreme learning machine.Establish predictive models for differences in data characteristics and influence factors.Finally,by analyzing the revised data,it is more convenient to conduct research on the comprehensive model of the hybrid energy storage system.2)Around the comprehensive benefits of the hybrid energy storage system and the evaluation of the service life of the system,a multi-scenario mathematical model was established.In the upper-level model,first consider the establishment of different benefit models for different power consumption regions throughout the life cycle,and supplement the benefits and costs involved in the entire life cycle,that is,consider the benefits of grid connection,distribution,upgrades,subsidies,etc.And establish a comprehensive benefit model for maintenance,construction,and power generation costs.In the lower model,the life influence factor of the hybrid energy storage system is analyzed,and then for practical engineering applications,a full life cycle assessment model of the hybrid energy storage system is established.3)Considering that the control strategies of different power-using regions should be different,analyze and improve the control strategies of the hybrid energy storage system around different power-using regions.Among them,for the different charging and discharging characteristics of batteries and supercapacitors in hybrid energy storage systems,the CEEMDAN decomposition algorithm is introduced.According to the analysis,the hybrid energy storage system that introduces the decomposition strategy has certain advantages in power distribution and life optimization.Finally,in order to better operate the hybrid energy storage system,while ensuring the system reliability constraints,the system stability constraints are added.4)In order to solve the above-mentioned complex model,the Salp Swarm Algorithm(SSA)is introduced.And according to the characteristics and common characteristics of the SSA algorithm,different improvement strategies are proposed,so that compared with the original algorithm.The improved SSA algorithm not only improves the convergence accuracy,but also improves the convergence speed.5)For the improved algorithm,first combine the extreme learning machine in the first part to preprocess wind power,photovoltaic and load data.And use the processed data into the integrated model of the hybrid energy storage system for analysis.The improved SSA algorithm is used again to solve the comprehensive model.The MATLAB simulation results show that the configuration scheme designed in this paper based on the optimal configuration of the hybrid energy storage system throughout its life cycle not only ensures the stability of the energy storage system,but also effectively avoids power fluctuations and stabilizes the peak-shaving and valley-filling rate.While improving the economics of the energy storage system,it also increases the service life of the energy storage system.