电力系统自动化2024，Vol.48Issue(14)：16-27,12.DOI:10.7500/AEPS20230909001
考虑灵活爬坡产品的虚拟电厂两阶段分布鲁棒优化运营策略
Two-stage Distributionally Robust Optimization Operation Strategy of Virtual Power Plants Considering Flexible Ramping Products
摘要
Abstract
With the proposed goal of"carbon emission peak and carbon neutrality",large-scale integration of renewable energy into the power system puts forward higher demands for the flexibile operation of power systems.The operation revenue of virtual power plant(VPP)is enhanced by aggregating distributed resources,incorporating flexible ramping products(FRPs)into its operation strategy and participating in multiple types of electricity markets.On this basis,a two-stage distributionally robust optimization(DRO)operation strategy of VPPs considering FRPs is proposed.Firstly,considering the FRP market under high penetration of renewable energy and combining the operation characteristics of multiple types of distributed resources,an optimization operation framework for VPP participating in multiple types of electricity markets is proposed.Secondly,integrating the uncertainty set of renewable energy output based on the Wasserstein distance and the typical scenario set of electricity market prices based on scenario analysis,a two-stage DRO model for VPP day-ahead bidding and intra-day dispatch considering FRP is constructed.Finally,the effectiveness of the proposed model is validated by taking a VPP as a case.The results of the case demonstrate that the proposed VPP operation strategy has good dispatching economic efficiency and risk robustness,and can maximize the operation revenue in multiple types of electricity market transactions.关键词
虚拟电厂/灵活爬坡产品/电力市场/运营策略/不确定性/分布鲁棒优化Key words
virtual power plant(VPP)/flexible ramping product(FRP)/electricity market/operation strategy/uncertainty/distributionally robust optimization(DRO)引用本文复制引用
俞鸿飞,王韵楚,吕瑞扬,金骆松,林振智,杨莉..考虑灵活爬坡产品的虚拟电厂两阶段分布鲁棒优化运营策略[J].电力系统自动化,2024,48(14):16-27,12.基金项目
国家重点研发计划资助项目(2022YFB2403100).本文研究得到国网浙江省电力有限公司科技项目(B311DJ220003)的资助,特此感谢! This work is supported by National Key R&D Program of China(No.2022YFB2403100). （2022YFB2403100）
