Smart Grid based decentralized Peer-to-Peer Energy Trading Using Whale Optimization Algorithm

Abstract

Increased penetration of distributed energy resources (DERs) in smart grids (SG) has sparked a new movement to consumer-centric structure as marketplaces based on peer-to-peer (P2P) models. Participants can directly agree bilateral power transactions in P2P markets to balance producers and consumers. The trading mechanism should be well-designed to encourage participants to operate actively in the trading activity. This article proposes a trading strategy for P2P strategy in SG. The proposed framework is modeled using the Whale optimization algorithm (WOA). In order to evaluate the proposed optimization method, particle swarm optimization (PSO) and classical optimization methods are carried out. The compared results show that the convergency of proposed method is faster than PSO algorithm.