Peer-to-Peer Energy Trading through Swarm Intelligent Stackelberg Game - Chathurangi Edussuriya; Umar Marikkar; Subash Wickramasinghe; Upul Jayasinghe; Janaka Alawatugoda (Energies, 2023)
The development of smart grids has paved the way for sustainable energy infrastructure to transition towards decentralized energy trading. As intelligent agents, energy sources engage in energy trading based on their energy surplus or deficit. Buyers and sellers (participants) should achieve maximum payoffs in which buyers cut costs and sellers improve their utilities, and the security of sensitive information of smart agents must be guaranteed. This paper provides a blockchain-based energy trading network where intelligent agents can exchange energy in a secure manner, without the intervention of third parties. We model energy trading as a Stackelberg game, ensuring that the platform maximizes social welfare while participants increase their payoffs. Using the inherited characteristics of blockchain technology, a novel decentralized swarm intelligence technique is applied to solve the game while ensuring the privacy of the smart agents’ sensitive information. The numerical analysis demonstrates that the suggested method outperforms the present methods (Constant Utility Optimization, average method...) for optimizing the objectives of each agent by maximizing the sellers’ utilities and reducing the buyers’ costs. In addition, the experimental results demonstrate that it significantly reduces carbon footprint (15%) by enhancing energy exchange between intelligent agents.