Research On Optimization Of Hybrid Energy Storage Capacity Configuration For Isolated DC Microgrid

In insulated DC micro-grids,hybrid energy storage systems(HESS)have significant advantages in smoothing power fluctuations in the grid compared to single type energy storage systems,Maintaining the energy balance of the power grid and improving the operational reliability of the system,the rationality of its power configuration has a significant impact on the operational performance and system economy of hybrid energy storage systems.Therefore,in-depth research on the power configuration optimization of insulated hybrid energy storage systems is of great significance.This research report indicates that:This paper first introduces the structure of a micro grid power system,analyzes the principles of wind and photovoltaic energy,and establishes a power output model.On this basis,mathematical models of lithium batteries and supercapacitors are established,taking into account the impact of cycle charging and discharging times and depth on the life of lithium batteries,Using rainwater counting technology,a quantitative model of battery life was established,and the concept of average life decay was proposedSecondly,for the allocation of hybrid energy storage capacity,a hybrid energy storage adaptive energy management strategy is developed.The VMD-SE method is used to decompose the total command of hybrid energy storage capacity once.And on this basis,the working state of SOC is considered.Two fuzzy controllers are used to dynamically adjust initial power instructions and establish operational standards for energy coordination between hybrid memories.At the same time,the impact of the selection of K decomposition scale in VMD-SE on the power decomposition results is analyzed.By introducing a lithium battery life decay index into the energy management strategy,adaptive power decomposition is achieved.Simulation and comparative analysis on MATLAB show that the proposed energy strategy optimizes the overall operating state of energy storage.Provide overload protection and analyze the impact of different capacity configurations on energy management strategies.Finally,considering the relationship between energy management strategies and capacity allocation in hybrid energy storage systems,this paper considers a power allocation method based on energy management strategies.A multipurpose optimization model for comprehensive calculation of annual cost of hybrid storage energy and lithium battery life cycle is established based on system reliability indicators and system energy balance.For traditional MOPSO search algorithms,adaptive nonlinear inertia weights based on global optimal distances are utilized and the selection of two learning factors is optimized to easily transition to local optimization.On this basis,cross variation operations are introduced to increase population diversity in the iterative solution process.Update the free solution set using the dynamic overcrowding distance method,using a combination of order preference and information entropy to select the optimal value.This method can improve the economy of hybrid energy storage and optimize operation status by meeting system reliability indicators.