Optimal Allocation Of Energy Storage In Active Distribution Network Considering Demand Side Response

As the non-renewable energy gradually goes to exhaustion,green energy is more and more widely used in the field of power supply for the strong support of the governments in various countries.Full and reasonable use of renewable energy sources such as wind and Solar energy can effectively solve the energy crisis and reduce environmental pollution.Due to the intermittent and random nature of renewable energy,it impacts the power system and increases the difficulty of distribution network dispatching,so the traditional distribution network has been unable to deal with it effectively.Therefore,the active distribution network technology arises at the historic moment.Energy storage,as an important part of the active distribution network,can smooth the intermittent energy power fluctuations,achieve load peak clipping and valley filling,and increase the flexibility of the distribution network dispatch,which has great practical significance for the research on the energy storage optimization of the active distribution network.At the same time,the installation location,rated power and capacity of energy storage will have a certain impact on the power flow distribution and economic operation of the distribution network.Therefore,this paper studies the optimal allocation of energy storage in active distribution network.Firstly,this paper briefly analyzes the power generation characteristics and operation characteristics of wind power,solar power and energy storage,and establishes the corresponding mathematical model,which serves as the basis for the optimal allocation of energy storage in active distribution network.And based on the time-of-use electricity price,considering the elastic relationship between user power load and electricity price,with the goal of peak-cutting and valley-filling,and smoothing load fluctuations,a demand-side controllable load response model was established to enhance the interaction,and realize the energy storage system with controllable load optimization,and the source-net-storage-charge equipment coordinated operation.Then,in order to solve the uncertainty of wind power and solar power output and the difficulty of energy storage planning and scheduling,a large-scale scene reduction method based on k-means clustering algorithm was proposed.Typical wind power and solar power output curves were obtained by scene division of historical data.Besides the average value method is used to reduce the scene of the measured daily load data and the typical daily load curve is obtained.Then,the typical scene curve is applied to the energy storage planning,and a two-layer multi-objective optimal configuration model of energy storage considering wind power and solar power grid-connected is established.The optimization goal is to maximize the investment benefit of energy storage,take into account the operation cost of distribution network,and consider the load fluctuation and voltage deviation.In addition,a multi-objective evolutionary algorithm based on decomposition is applied to the solving process,and the inner Pareto optimal frontier and optimal solution set are obtained by MOEA/D algorithm.A satisfaction evaluation mechanism based on fuzzy function is proposed to select the optimal compromise solution and transfer it to the outer layer.In this way,the configure of energy storage takes into account the later operation,and at the same time,the latter operation guides the planning,so as to configure the energy storage more reasonably.Finally,the four selected scenarios are simulated and compared by IEEE-33 node distribution network system,and calculated by Matlab software programming.This paper analyzes the results of the program from the perspectives of economic benefit,peak-filling effect and improving voltage quality,and verifies the effectiveness and superiority of the two-layer optimal configuration model of energy storage and the corresponding solving method.