Sustainable microgrids design with uncertainties and blockchain-based peer-to-peer energy trading

Vincent F. Yu, Thi Huynh Anh Le and Jatinder N.D. Gupta

Renewable and Sustainable Energy Reviews, 2025, vol. 216, issue C

Abstract: A sustainable microgrid based on renewable energy (RNE) sources is a useful solution to reduce the environmental impact and meet customer demand as it offers advantages on the goals related to the economy, environment, and society. Several previous studies have applied peer-to-peer energy trading (P2P-ET) as a feasible solution to reduce the power loss during power supply over long distances. Due to the intermittent nature of RNE sources and demand load, it is challenging to control and manage the operation and distribution of microgrids in P2P-ET. However, the availability and the number of other nearby microgrids needed to connect to microgrids through electric cables in P2P-ET and the mechanisms to manage and balance the power between supply and demand have not been investigated in the current literature. Therefore, this paper examines the sustainable microgrid design problem with P2P-ET under blockchain application, time value of money, elasticity coefficient of demand, and uncertainties to maximize overall earnings and minimize the collective environmental expenses while meeting customer demand. The two-phase stochastic programming is integrated with fuzzy probabilistic programming to determine the quantity, site, type of RNE, and capacity of renewable distributed generation units, the quantity of other nearby microgrids and electric cables required for connection in the P2P-ET, the electricity flows, and dynamic pricing mechanisms. The results demonstrate that the use of the blockchain application in the suggested model increases overall earnings by 14. 75% and reduces collective environmental expenses by 13.25% compared to the case without the blockchain application.

Keywords: Blockchain technology; Smart contract; Sustainable microgrid design; P2P energy trading; Uncertainties; Fuzzy probabilistic-two phase stochastic programming (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1016/j.rser.2025.115600

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