A Novel Multi-Hierarchical Bidding Strategy for Peer-to-Peer Energy Trading Among Communities


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GÖKÇEK T. , Sengor I., ERDİNÇ O.

IEEE ACCESS, vol.10, pp.23798-23807, 2022 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 10
  • Publication Date: 2022
  • Doi Number: 10.1109/access.2022.3154393
  • Journal Name: IEEE ACCESS
  • Journal Indexes: Science Citation Index Expanded, Scopus, Compendex, INSPEC, Directory of Open Access Journals
  • Page Numbers: pp.23798-23807
  • Keywords: Pricing, Optimization, Games, Costs, Real-time systems, Peer-to-peer computing, Uncertainty, Bi-level optimization, local market, market clearing, optimal bidding strategy, peer-to-peer energy trading, SHARING FRAMEWORK, ALLOCATION, SYSTEM

Abstract

Recently, several market types and regulations have been developed in an attempt to handle the increased carbon effect. End-users can also actively participate in the existing distribution system thanks to Peer-to-Peer (P2P) energy trading, which is one of the new emerging market types. In this paper, a novel dual bidding strategy for multi-hierarchical P2P energy trading that includes both intra community and inter communities is proposed considering uncertainties in solar irradiance and temperature. While the lower-level problem consists of both optimal bids of the households to the own Local Market Operators (LMO) for intra community trades and optimal bids of the LMOs to the Central Market Operator (CMO) for inter community trades, profit of both the LMOs and CMO is maximized by clearing the market prices at the upper-level problem. To prove the validity of the devised model, a set of case studies are created. Moreover, the results suggest that the proposed bi-level model is robust, and a remarkable amount of cost savings could be provided by integrating the model.