Energy Storage Capacity Allocation Optimization Model Considering Wind Power Generation And User Demand

With the increasing energy crisis,the demand for environmental protection continues to heat up,and the clean energy represented by wind power has become one of the most important types of power generation.However,due to the volatility and intermittency of wind power generation,it is difficult to guarantee power quality and there are problems such as wind curtailment.The development and application of energy storage charging and discharging technology has brought an opportunity to solve the problem of wind curtailment,and the joint operation of wind storage has become a general trend.And,with the continuous improvement of people’s living standards,users have put forward higher demand for electricity comfort and economy.Based on this,this paper studies the optimization problem of mixed energy storage capacity configuration,considering both the demand for wind power generation and the demand for user electricity.By selecting appropriate energy storage technologies and configuring reasonable energy storage capacity,the complementary and rapid adjustment performance of mixed energy storage can be fully utilized to effectively meet the dual demands of wind power merchants and users.The paper first constructs a wind-storage joint system in the blockchain environment,analyzes its technical support,value demands,method applications,and key issues,laying a theoretical foundation for subsequent research.Secondly,based on the classification and characteristic analysis of energy storage technology and the analysis of its necessity,a mixed energy storage combination optimal selection index system is constructed following principles of scientific rationality,comprehensiveness,and inclusivity.The comprehensive weight is determined using the interval type-2 fuzzy hierarchy analysis method and entropy weight method,and the mixed energy storage combination is evaluated using the interval type-2 fuzzy TOPSIS method to select the mixed energy storage with the best adjustment capacity,providing a prerequisite for mixed energy storage capacity configuration.Furthermore,to meet the demand for wind power generation,an intelligent contract-based wind power and energy storage,battery,and supercapacitor energy collaborative management strategy is developed,which considers the energy storage cost,wind curtailment penalty cost,and government subsidy cost.A capacity configuration model is established with the goal of minimizing the system’s total cost,and particle swarm optimization algorithm and improved Shapley value method are used to solve it.Through example analysis,result analysis and sensitivity analysis,the validity and reliability of the model are verified.Moreover,to meet the user’s electricity demand,a demand response basic model is constructed,analyzing the wind-storage joint system’s structure and operation strategies under user demand.A multi-objective capacity configuration model is established with the goal of minimizing the energy storage and user subsidy costs,minimizing wind curtailment,and maximizing user satisfaction.The multi-objective particle swarm algorithm is used to solve the model,and the effectiveness and practicality of the model are analyzed through case studies and result verification.Finally,wind-storage collaborative operation recommendations are proposed for the dual demands of wind power and users.Selecting the appropriate mix of energy storage and planning the capacity of hybrid energy storage while considering the needs of wind power generation and user electricity consumption is the primary step and key issue in optimizing the wind-storage joint system.This paper aims to promote wind power integration,improve user satisfaction,and further advance the development of wind power and energy storage technology by addressing the aforementioned issues.The ultimate goal is to achieve increased value of the wind-storage joint system.