Cooperative Behaviors and Multienergy Coupling through Distributed Energy Storage in the Peer-to-Peer Market Mechanism


Tanis Z., Durusu A.

IEEE ACCESS, cilt.13, ss.1-22, 2025 (SCI-Expanded)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 13
  • Basım Tarihi: 2025
  • Doi Numarası: 10.1109/access.2025.3529205
  • Dergi Adı: IEEE ACCESS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Compendex, INSPEC, Directory of Open Access Journals
  • Sayfa Sayıları: ss.1-22
  • Yıldız Teknik Üniversitesi Adresli: Evet

Özet

The integration of distributed energy storage systems into multienergy systems has garnered significant attention due to the increased use of renewable energy sources and the demand for improved energy management. This study explores the concept of multienergy coupling by facilitating energy storage through a peer-to-peer marketplace. An innovative peer-to-peer market structure is proposed, supported by advanced algorithms, to enable direct energy trading among prosumers. Key challenges are addressed through a systematic methodology, encompassing user registration, multienergy systems involving electricity, heat, and gas, storage cost optimization, multienergy trading, and blockchain-based transactions. A consortium blockchain-based framework ensures secure and private registration. A peer-to-peer network facilitates multienergy trading, enabling efficient energy generation and storage. A storage virtualization model is developed to minimize storage costs, and a nonlinear programming multiobjective model optimizes battery energy storage. For multienergy trading, Nash bargaining under uncertainty is introduced, allowing participants to negotiate based on their contributions. The proposed model’s performance is benchmarked against conventional peer-to-peer energy trading and the Q-learning algorithm. Transactions are secured using blockchain-based payment systems. The implementation is carried out using Matlab-R2023b Network Simulator, and the results are evaluated using various performance metrics.