Toward sustainable microgrids with blockchain technology-based peer-to-peer energy trading mechanism: A fuzzy meta-heuristic approach

Microgrids with renewable distributed generation units are a promising solution for reducing investment cost and greenhouse gas emissions in the face of rapidly rising energy demand and recent organizational concerns regarding social and environmental issues. However, microgrids closely located to demand areas cannot easily balance power supply and demand owing to the intermittency of renewable energy generation and the barriers to connecting with the main electricity grid. To overcome this problem, this study addresses a sustainable microgrid design problem, where blockchain technology is used for peer-to-peer energy trading in the microgrid. The adoption of the blockchain technology in peer-to-peer energy trading ensures the security and sustainability for participants in the microgrid. It enables the participants to take control of the energy system without the need for a central regulatory authority. The problem entails decisions regarding not only the power flow among entities in the grid and the number, location, and capacity of renewable distributed generation units but also the price mechanism for peer-to-peer trading. A sustainable network microgrid is modeled by considering economic and environmental objectives with social constraints related to maximizing demand satisfaction of consumers. A fuzzy multi-objective programming model is proposed to tackle the variability in the capacity of renewable distributed generation units and demand load. The proposed model is solved by a genetic algorithm. Numerical experiments are conducted to evaluate the feasibility of the proposed model in decision-making regarding microgrid design, the impact of peer-to-peer trading on the total profit of the microgrid, and the applicability of the developed solution approach. •This study addresses a sustainable microgrid design problem.•Blockchain technology is used for peer-to-peer energy trading in the microgrid.•A sustainable microgrid is modeled by considering economic and environmental objectives.•A fuzzy multi-objective programming model is proposed to tackle the variability and uncertainty.•The proposed model is solved by a genetic algorithm.