Author:
Mahmoud Marwan,Ben Slama Sami
Abstract
Peer-to-peer energy trading is an innovative idea that overcomes several technological and industrial hurdles. It allows industries and consumers, including knowledgeable prosumers, to trade excess energy with distributed generation sources, such as solar, wind, and electric vehicles, thus promoting a significant reduction in overall energy consumption. Real-Time Pricing (RTP) is increasingly essential in integrating smart home device Demand Response (DR) strategies. RTP improves energy management and enables customers to respond intelligently to price fluctuations. In this vein, this paper proves how DR and peer-to-peer (P2P) energy trading could affect energy prices by allowing producers (consumers) and smart home users to interact directly rather than through the traditional grid. The two-pronged planning approach substantially contributes to the reduction of electricity costs. DR enables P2P energy trading, while deep learning algorithms adapt smart home devices to RTP dynamics. Simulation results show that using P2P energy trading and DR in smart homes can significantly eliminate costs. This hybrid approach increases the energy efficiency of Smart Grid (SG) 2.0 technology and makes it more adaptable and cost-effective.
Publisher
Engineering, Technology & Applied Science Research