Research On Optimization Planning Of Energy Storage On The Power Supply Side Of Large Energy Base

In the background of “double carbon” target,clean and low-carbon energy system is the development direction,and new energy sources have entered a rapid development stage.Wind,light and other renewable energy sources are connected to the grid on a large scale,but wind and light have uncertainty and volatility,and the contradiction of consumption is becoming more and more prominent.The configuration of energy storage on the power side of new energy can effectively promote the consumption of wind and light and optimize the energy structure.In this context,this paper takes an energy base in the northwest region of a province as the research object,considers the uncertainty and correlation of wind and light output and other factors,and proposes a multi-objective energy storage optimization planning model,whose main contents are summarized as follows:Firstly,the levelized power cost model of energy storage is established based on the whole life cycle cost method.The initial investment cost and the discounted O&M cost,replacement cost and recovery cost constitute the whole life cycle cost model of energy storage,and analyze the main components and influencing factors of the electricity cost of energy storage,which provides a theoretical basis for the economic analysis of energy storage.Secondly,a scenery output uncertainty model is established based on the stochastic optimization method,and the probability distribution of scenery output is fitted using the nonparametric kernel density estimation method.At the same time,considering the correlation between wind power and PV output of the same energy base,the optimal Copula function is selected based on three metrics: Spearman rank correlation coefficient,Kendall rank correlation coefficient and squared Euclidean distance,and the joint probability distribution model of scenery output based on Copula theory is established,and a large number of scenery output scenarios with scenery output uncertainty and correlation are sampled from the model and obtained by inverse transformation.A large number of scenarios with uncertainty and correlation of scenery output are sampled from the model,and typical scenarios with correlation of scenery output are obtained by K-means clustering algorithm,which provides basic data for the study of energy storage optimization planning.Finally,the overall structure of this scenic energy base is introduced,and the optimal planning of energy storage on the power side of the energy base is studied with the premise of centralized energy storage configuration mode.For the game problem of energy storage to promote scenery consumption and enhance its own economy,the multi-objective energy storage optimization planning model is established with the minimum amount of wind and light abandonment and the whole life cycle cost of energy storage,considering the constraints of energy storage charging and discharging power constraints and load state constraints.The multi-objective particle swarm algorithm is used to solve the Pareto solution set,from which the optimal solution is determined by the entropy power method to ensure that the energy storage system can maximize the consumption of scenery while ensuring its own economy.Taking an energy base as an example,the optimal energy storage planning scheme is solved by taking into account the uncertainty and correlation of scenery output in each season,different objective function scenarios and scenarios without considering scenery correlation,and the effectiveness of the model is verified by comparative analysis.