Low-carbon distribution system planning considering flexible support of zero-carbon energy station

Shuaijia He, Hongjun Gao*, Zhe Chen, Junyong Liu, Liang Zhao, Gang Wu, Song Xu

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

7 Citations (Scopus)

Abstract

Zero-carbon energy stations (ZCESs) have a promising prospect in reducing carbon emission, which also results in great impacts on the planning scheme of low-carbon distribution system (DS). In this context, this paper carries out the low-carbon DS planning considering the flexible support of ZCES. Firstly, a low-carbon DS planning model is established, where the material carbon emission and operational carbon emission are both considered. Then, for achieving the low-carbon goal of DS, the flexible support of ZCES is considered during the low-carbon DS planning process. Especially, ZCES is supplied by zero-carbon renewable energy (e.g., photovoltaics and wind power). Meanwhile, DS and ZCES are regarded as different stakeholders, which is addressed by the analytical target cascading (ATC) algorithm. In addition, a distributionally robust optimization method is proposed to cope with the probability distribution (PD) uncertainty of renewable energy and loads. Moreover, a tractable low-carbon planning model for DS considering the flexible support of ZCES is reformulated based on the duality method. Finally, the proposed planning model is tested on a modified IEEE 33-node and a practical 99-node distribution system with ZCES. Numerical results show that the proposed low-carbon planning model is effective in managing PD uncertainties, and improving the low-carbon and economic performance of DS while the ATC algorithm also exhibits good convergence performance.

Original languageEnglish
Article number123079
JournalEnergy
Volume244
ISSN0360-5442
DOIs
Publication statusPublished - 1 Apr 2022

Bibliographical note

Publisher Copyright:
© 2022 Elsevier Ltd

Keywords

  • Analytical target cascading algorithm
  • Distribution systems
  • Distributionally robust optimization
  • Low-carbon
  • Zero-carbon energy station

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