中国电机工程学报2024，Vol.44Issue(19)：7543-7554,中插5,13.DOI:10.13334/j.0258-8013.pcsee.230306
计及同步机惯性与储能虚拟惯性价值的电能、惯性及一次调频联合优化出清模型
Joint Optimal Clearing Model for Electric Energy,Inertia and Primary Frequency Response Considering Synchronous Inertia and Energy Storage Virtual Inertia Values
摘要
Abstract
The high proportion of new energy generation to the grid leads to the reduction of synchronous inertia and frequency response resources of the power system,thereby emphasizing the frequency security issue under large disturbances.Currently,the spot markets lack mechanisms to incentivize the supply of inertial resources.Given the significant value of both synchronous inertia and virtual inertia from energy storage systems,their inclusion in the spot market for efficient clearing could contribute to maintaining the stability of system frequency.Therefore,the differences of inertia and primary frequency response provided by synchronous generator and energy storage are firstly discussed.Then the frequency safety constraints of the two-stage response process based on the energy storage virtual inertia's delay are derived.Secondly,an electric energy,inertia and primary frequency response day-ahead clearing model is proposed,which takes synchronous inertia's"lumpy"characteristic and energy storage reservation factor into account,to obtain the synchronous inertia and virtual inertia values.Finally,the validity of the proposed model is verified based on an example,and the effects of different parameter settings on the clearing results are discussed.关键词
同步机惯性/虚拟惯性/频率安全约束/惯性辅助服务市场/储能Key words
synchronous inertia/virtual inertia/frequency safety constraints/inertia ancillary service market/energy storage分类
信息技术与安全科学引用本文复制引用
朱兰,董凯旋,唐陇军,李振坤,余家乐..计及同步机惯性与储能虚拟惯性价值的电能、惯性及一次调频联合优化出清模型[J].中国电机工程学报,2024,44(19):7543-7554,中插5,13.基金项目
国家自然科学基金(面上项目)(52177098) （面上项目）
上海电力人工智能工程技术研究中心项目(19DZ2252800). Project Supported by National Natural Science Foundation of China(General Program)(52177098) （19DZ2252800）
Research Project of Shanghai Electric Power Artificial Intelligence Engineering Technology Research Center(19DZ2252800). （19DZ2252800）
