南方电网技术2025，Vol.19Issue(9)：117-130,14.DOI:10.13648/j.cnki.issn1674-0629.2025.09.011
智慧楼宇型虚拟电厂辅助电网调频的优化方法
Optimization Method for Auxiliary Power Grid Frequency Regulation of Smart Building-Type Virtual Power Plant
摘要
Abstract
To address the issue of insufficient frequency regulation resources in power systems caused by high penetration of renew-able energy,a two-stage optimization method is proposed based on virtual power plant(VPP)technology.This method aggregates flexible resources within buildings to jointly participate in multi-energy markets and frequency regulation ancillary service markets.Firstly,a gas-electric VPP model is constructed with smart buildings as units.Secondly,considering the high-quality frequency regulation potential of electric energy storage and electric vehicles within buildings,a day-ahead and real-time two-stage optimization strategy is designed for VPP-assisted grid frequency regulation.In the day-ahead stage,based on forecasts such as wind and solar generation,the mixed-integer linear programming method is applied to obtain the global optimal day-ahead scheduling scheme,aim-ing to minimize the total operating cost of the VPP.In the real-time stage,model predictive control combined with mixed-integer quadratic programming is used for rolling optimization based on real-time measurements such as frequency regulation signals,reduc-ing prediction errors.Finally,simulation results under different scenarios demonstrate that the proposed method enables the VPP to fully exploit the flexibility potential of electric energy storage and electric vehicles for grid frequency regulation,achieving optimal resource allocation in both energy and frequency regulation markets while significantly improving the overall operational efficiency of the VPP.关键词
虚拟电厂/智慧楼宇/优化运行/调频/辅助服务Key words
virtual power plant/smart buildings/optimizing operation/frequency regulation/ancillary service分类
信息技术与安全科学引用本文复制引用
范宏,罗昊,陈舒阳,徐涛,徐勇杰..智慧楼宇型虚拟电厂辅助电网调频的优化方法[J].南方电网技术,2025,19(9):117-130,14.基金项目
国家重点研发计划资助项目(2022YFA1004600). Supported by the National Key Research and Development Program of China(2022YFA1004600). （2022YFA1004600）
