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考虑多重不确定性的虚拟电厂可信备用评估

田富豪 包铭磊 惠恒宇 裘愉涛 丁一

电力系统保护与控制2025,Vol.53Issue(10):45-56,12.
电力系统保护与控制2025,Vol.53Issue(10):45-56,12.DOI:10.19783/j.cnki.pspc.240932

考虑多重不确定性的虚拟电厂可信备用评估

Reserve credit evaluation of virtual power plants considering multiple uncertainties

田富豪 1包铭磊 2惠恒宇 2裘愉涛 3丁一2

作者信息

  • 1. 浙江大学工程师学院,浙江 杭州 310015
  • 2. 浙江大学电气工程学院,浙江 杭州 310027
  • 3. 浙江大学电气工程学院,浙江 杭州 310027||国网浙江省电力有限公司,浙江 杭州 310007
  • 折叠

摘要

Abstract

Virtual power plants(VPP)can provide considerable reserve capacity for power grid operation.Accurately evaluating and quantifying the reserve capacity of VPP is key to their participating in power grid regulation.However,the strong uncertainties associated with distributed renewable energy output,load consumption,electricity price,and other factors can lead to unreliable results when using traditional deterministic methods for reserve evaluation.To address this,a definition and evaluation method for reserve credit under multiple uncertainties is proposed based on the characteristics of VPP.First,the framework of VPP and the definition of reserve credit are introduced.Then,a VPP reserve provision model is constructed considering various resource aggregation.By applying Monte Carlo to model multiple uncertainties and using kernel density estimation,a set of reserve credit with different confidence levels is derived,effectively quantifying the reserve credit of VPP.Finally,a case study on a typical VPP is conducted.It demonstrates that the proposed method can effectively reflect the probability characteristics of the reserves that VPP can provide considering multiple uncertainties,providing dispatch agencies with more comprehensive and reliable reserve information.

关键词

可信备用/虚拟电厂/不确定性/蒙特卡洛/核密度估计

Key words

reserve credit/virtual power plant(VPP)/uncertainty/Monte Carlo/kernel density estimation

引用本文复制引用

田富豪,包铭磊,惠恒宇,裘愉涛,丁一..考虑多重不确定性的虚拟电厂可信备用评估[J].电力系统保护与控制,2025,53(10):45-56,12.

基金项目

This work is supported by the Natural Science Foundation of Jiangsu Province(No.BK20232026). 江苏省自然科学基金项目资助(BK20232026) (No.BK20232026)

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