A De-aggregation strategy based optimal co-scheduling of heterogeneous flexible resources in virtual power plant

Zixuan Zheng, Jie Li, Xiaoming Liu, Chunjun Huang, Wenxi Hu*, Xianyong Xiao, Shu Zhang, Yongjun Zhou, Song Yue, Yi Zong

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

Abstract

Virtual power plant (VPP) serves as an effective solution for maintaining internal power balance and participating in external peak shaving auxiliary services within grid-connected microgrid involved in multi-type flexible resources (FRs). However, with increasing prominence of the feature heterogeneity in response behaviors of diverse FRs and their coupling in peak shaving poses challenges in the accurate decomposition of VPP scheduling commands. This paper proposes a de-aggregation strategy, utilizing discrete choice model and feature matching methods, to dynamically sequence FRs responses while optimizing VPP's peak shaving capability. Initially, heterogeneous features are refined and modeled to characterize the response capability of multi-type FRs in meeting the scheduled demand of grid-connected microgrid (SDGM). Subsequently, a feature difference quantification model and matching priority criterion are formulated to describe the feature mapping relationship and guide dynamic decision-making process. On this basis, the multi-type FRs are co-scheduled in the considered VPP to form a dynamic response sequence achieving peak shaving objectives. Case studies based on real data from a region-connected microgrid demonstrate the proposed strategy's performance in improving return on investment by 6.1 %, reducing peak shaving deviation and power exchange with main grid by 70 % and 13.1 %, respectively, and effectively improve the ability of grid-connected microgrid to balance the power and participate in peaking auxiliary services.

Original languageEnglish
Article number125404
JournalApplied Energy
Volume383
DOIs
Publication statusPublished - 2025

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • Discrete choice model
  • Feature matching
  • Flexible resources
  • Virtual power plant
  • VPP de-aggregation

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