电网技术2017，Vol.41Issue(11)：3590-3597,8.DOI:10.13335/j.1000-3673.pst.2016.3379
计及不确定性和需求响应的风光燃储集成虚拟电厂随机调度优化模型
Stochastic Scheduling Optimization Model for Virtual Power Plant of Integrated Wind-Photovoltaic-Energy Storage System Considering Uncertainty and Demand Response
摘要
Abstract
In order to promote grid connection of distributed energy generation, represented by wind and photovoltaic powers, this paper introduces condition value at risk (CVaR) theory and confidence method to describe the uncertainties of virtual power plant (VPP) operation and construct a CVaR model for VPP scheduling considering wind power, photovoltaic power, gas turbine, energy storage systems (ESSs) and incentive-based demand response (IBDR). Firstly, a basic optimization model for VPP scheduling is established to determine threshold value of VPP operating profit with maximized operating profit as objective function. Secondly, CVaR theory and confidence method are used to describe the uncertainty factors in the objective function and constraints. Meanwhile, a stochastic scheduling model for VPP scheduling is established considering operational risks. Finally, the improved IEEE 30-node system is taken as simulation system. Result shows that price-based demand response (PBDR) could smooth load demand curve and ESSs and IBDR can increase VPP operating profit. In VPP's basic scheduling, the revenue and generation of wind power and PV are￥9550.19 and 12.49MW?h. In VPP's risk avoidance scheduling, the revenue and generation of wind power and PV are￥8995.34 and 11.31MW?h. This means CVaR theory and confidence method can be used to describe VPP operation risk by setting thresholds and confidence levels, providing effective risk-control tool for decision-makers.关键词
虚拟电厂/CVaR/不确定性/需求响应Key words
virtual power plant/CVaR/uncertainty/demand response分类
信息技术与安全科学引用本文复制引用
徐辉,焦扬,蒲雷,何楠,王尧,谭忠富..计及不确定性和需求响应的风光燃储集成虚拟电厂随机调度优化模型[J].电网技术,2017,41(11):3590-3597,8.基金项目
国家自然科学基金项目(71573084) （71573084）
北京市社会科学基金项目(16JDYJB044). Project Supported by National Natural Science Foundation of China (71573084) （16JDYJB044）
Beijing Municipal Social Science Foundation (16JDYJB044). （16JDYJB044）
