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A blockchain-based optimal peer-to-peer energy trading framework for decentralized energy management with in a virtual power plant: Lab scale studies and large scale proposal

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  • Alam, Khandoker Shahjahan
  • Kaif, A.M.A. Daiyan
  • Das, Sajal K.

Abstract

The integration of distributed energy resources (DERs) such as wind, solar, batteries, etc. into the grid presents opportunities as well as challenges with regard to efficient coordination and trading. Virtual power plants (VPPs) have emerged as an important paradigm for aggregating and managing numerous DERs. This paper proposes a decentralized blockchain-based peer-to-peer (P2P) multilayer energy trading framework to facilitate optimized coordination of DERs within a VPP context. A control center, prosumers, and service operators constitute the model’s multi-layered architecture. Profits from feed-in tariffs, ancillary services, and P2P sales are optimized for revenue while expenses are minimized using a mixed-integer linear programming formulation. Smart contracts enable prosumers to trade energy units in the Ethereum blockchain with ease via a participatory web platform. The effectiveness of the framework in synchronizing power supply and demand within the VPP by coordinating the charging and discharging of storage systems in accordance with consumption patterns is demonstrated through performance evaluation. In contrast to conventional centralized architectures, the proposed framework utilized decentralized architecture efficiently consolidates and optimizes distributed energy resources (DERs) to improve grid stability and renewable energy utilization.

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  • Alam, Khandoker Shahjahan & Kaif, A.M.A. Daiyan & Das, Sajal K., 2024. "A blockchain-based optimal peer-to-peer energy trading framework for decentralized energy management with in a virtual power plant: Lab scale studies and large scale proposal," Applied Energy, Elsevier, vol. 365(C).
    • Handle: RePEc:eee:appene:v:365:y:2024:i:c:s0306261924006263
    DOI: 10.1016/j.apenergy.2024.123243
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    7. Wei Huang & Chao Zheng & Xuehao He & Xiaojie Liu & Suwei Zhai & Guobiao Lin & Shi Su & Chenyang Zhao & Qian Ai, 2025. "A Trusted Sharing Strategy for Electricity in Multi-Virtual Power Plants Based on Dual-Chain Blockchain," Energies, MDPI, vol. 18(11), pages 1-22, May.
    8. Lefeng Cheng & Xin Wei & Manling Li & Can Tan & Meng Yin & Teng Shen & Tao Zou, 2024. "Integrating Evolutionary Game-Theoretical Methods and Deep Reinforcement Learning for Adaptive Strategy Optimization in User-Side Electricity Markets: A Comprehensive Review," Mathematics, MDPI, vol. 12(20), pages 1-56, October.

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