Modified Worst-Case Excess Minimization for Value Sharing in Energy Communities

Amir Safdarian, Poria Hasanpor Divshali, Marius Baranauskas, Antti Keski-Koukkari, Anna Kulmala

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

1 Citation (Scopus)

Abstract

Worst-case excess minimization provides a stabilizing value sharing mechanism for energy communities (ECs). It, however, takes much time to solve the problem especially in larger ECs with tens of prosumers. To alleviate the issue, this paper proposes a modified worst-case excess minimization problem which is faster to solve. In this paper, the problem is formulated for individual time slots, e.g., hour by hour, instead of solving the problem for the whole study horizon. This enables modifying the problem by defining new constraints as well as removing unnecessary variables and constraints. By doing so, the minimization problem can be solved faster without sacrificing the accuracy of the simulation. The proposed method is simulated, and the achieved results are compared with the original worst-case excess minimization problem. Based on the results, the proposed method performed significantly better than the original.

Original languageEnglish
Title of host publicationPESGRE 2022 - IEEE International Conference on "Power Electronics, Smart Grid, and Renewable Energy"
PublisherIEEE
ISBN (Electronic)978-1-6654-4837-6
DOIs
Publication statusPublished - 2022
MoE publication typeA4 Conference publication
EventIEEE International Conference on Power Electronics, Smart Grid, and Renewable Energy - Virtual, Trivandrum, India
Duration: 2 Jan 20225 Jan 2022

Conference

ConferenceIEEE International Conference on Power Electronics, Smart Grid, and Renewable Energy
Abbreviated titlePESGRE
Country/TerritoryIndia
CityTrivandrum
Period02/01/202205/01/2022

Keywords

  • energy community
  • minimization
  • optimization
  • payoff allocation
  • prosumer
  • value sharing
  • worst-case excess minimization

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