Optimal Sizing Of Battery Energy Storage System In Smart Microgrid Considering Virtual Energy Storage System

With the increase of distributed photovoltaic penetration and air-conditioning load,the stable operation of the distribution network faces many challenges.On one hand,it is an effective mitigation way to configure battery energy storage system（BESS）on the user side to form the microgrid.However,the net profit of energy storage under high cost is still the main obstacle to configure BESS in the system,although the peak-to-valley price difference continues to widen.On the other hand,combined with virtual energy storage system（VESS）based on the thermal inertial of air-conditioned houses,demand response technology is an effective way to reduce air-conditioning load and share the operating pressure of BESS.This thesis takes the regional users with a large number of distributed photovoltaic and air-conditioning load as the research object,and intends to form a smart microgrid in the region.With the aim of operator optimizing the size of BESS to maximize the net profit of energy storage,this thesis based on the time-of-use tariff and risk aversion carries out the optimal sizing of BESS in smart microgrid considering VESS.The main contents are as follows:（1）On the basis of clarifying the composition and business model of smart microgrid,considering the visibility of netload of users with behind the meter photovoltaic system and its impact on the sizing of battery energy storage system,a data-driven netload disaggregation model is proposed to provide historical data processing method for energy storage sizing research.The relationship between load demand and ambient temperature is briefly analyzed in the basic case,which provides a data basis for subsequent research.（2）Based on the one-parameter thermal model and the two-parameter thermal model,the mixed integer linear programming models for air-conditioning load control are built.The superiority and necessity of the two-parameter thermal model in the modeling of airconditioning load control are verified by the case study.Using the two-parameter thermal model,the mathematical model of virtual energy storage system based on air-conditioning load and its quantitative characteristic indicators are proposed.Combined with the demand response schemes,the virtual energy storage system control strategies are given,and the effectiveness of the proposed virtual energy storage system model and its demand response control strategies are verified by case studies,which provide a model basis for subsequent battery energy storage system sizing research.（3）The models for optimal sizing of battery energy storage system based on full-scenario and typical-scenario are introduced in detail.Considering the risk of changes in the net profit of operator caused by the uncertainties of photovoltaics and load,Markowitz mean-variance theory and value at risk are introduced,and net profit-risk trade-off model for optimal sizing of battery energy storage system is proposed.Taking further virtual energy storage system and its demand response control strategies into account,the net profit-risk trade-off model for optimal sizing of battery energy storage system considering virtual energy storage system is proposed,and the model solution method is given.（4）The effectiveness and superiority of the proposed battery energy storage system optimal sizing model are verified by the case studies.The results demonstrate that considering virtual energy storage system in the process of battery energy storage system optimal sizing is beneficial to increase the net profit for operator.The sensitivity analysis of battery energy storage system sizing shows that the expected net profit of operators during the project lifetime is mainly affected by changes in the ratio of photovoltaics and the comprehensive electricity price index considering the time-of-use tariff and the solar feed-in tariff.However,the optimal size of battery energy storage system is mainly affected by changes in the ratio of load and the peak-to-valley price difference.In addition,according to the degree of risk aversion and its expected net profit,the energy storage operator can determine the risk aversion coefficient,and then obtain the appropriate optimal size of battery energy storage system through the proposed model.