An optimized decentralized peer-to-peer energy trading system for smart grids incorporating uncertain renewable energy sources through fuzzy optimization

• Published in: Electric power systems research 2025-01, Vol.238, p.111154, Article 111154
• Main Authors: Uddin, Nesar, Wu, Yingjun, Islam, Md Saiful, Zakaria, Khan Md
• Format: Article
• Language: English
• Subjects: Decentralized P2P energy trading network; Demand response; Energy stability; Fuzzy optimization; Real-time pricing strategy
• ISSN: 0378-7796
• DOI: 10.1016/j.epsr.2024.111154

•P2P allows demand response pricing strategy among prosumers and grid.•P2P allow direct energy exchanged between P2P, P2G or G2P without third party.•P2P optimized based on fuzzy logic controller.•P2P promotes environmental sustainability and entrepreneurial engagement. The significant issue in today's world is that the power system is undergoing on account of unafforded power generation and distribution. Consequently, improper utilization of renewable energy, as well as its pricing mechanism of electrical energy, is also a vital issue in transmission and distribution systems (TDS). In addition, in the context of upcoming power systems, ensuring energy stability and effective energy management have become paramount. This paper introduces a novel approach to address these challenges by proposing an optimal demand response grid-connected decentralized peer-to-peer (P2P) energy trading system. This system efficiently manages energy transactions among prosumers, the grid, and renewable energy sources (RES) under uncertain conditions. Fuzzy optimization (FO) is employed to facilitate interconnections between these entities. A fuzzy logic controller with intelligent rules governs the overall strategy and pricing mechanism based on prosumer power deviation (PPD). Inspired by human thinking, these rules prioritize P2P transactions, with surplus energy exported to the main grid (MG) and energy imported from the MG when necessary. Pricing adjusts dynamically with load demand. Simulation results demonstrate the effectiveness of the fuzzy rules across various conditions, ensuring proper system operation. The proposed model also proves that the P2P energy trading system has reduced power consumption by balancing the generated power and the load demand. The proposed system is environmentally friendly, emitting no harmful gases.