A blockchain-enabled digital twin energy management framework for distributed optimization and secure peer-to-peer trading in DER-integrated microgrids

This study proposes a Blockchain-Enabled Digital Twin Energy Management System (BTEMS) for secure, scalable, and physically feasible peer-to-peer (P2P) energy trading in distributed energy resource (DER)–integrated microgrids. The framework synergistically integrates Digital Twin (DT) validation, blockchain-based smart contracts, and an adaptive multi-objective Cheeta Optimization Algorithm (COA) to jointly optimize economic efficiency, grid reliability, and cybersecurity resilience. The DT continuously mirrors the operational states of photovoltaic (PV) systems, wind turbines (WT), battery energy storage systems (BESS), and electric vehicles (EVs), enabling real-time feasibility validation of energy trades under voltage, state-of-charge (SoC), and network constraints prior to blockchain commitment. The permissioned blockchain offers a convenient method for the smart contracts to automatically manage market closure, pricing, and settlement. This ensures that everything is transparent, immutable, and trustworthy without the need for third-party intermediaries. The proposed BTEMS was tested on both the IEEE 15-bus test system (14 houses) and the IEEE 85-bus test system (84 houses), and it was able to show its capability to work in both small microgrids and large residential areas. Based on the stochastic process analysis of renewable energy and load demand, three practical scenarios of surplus (peak PV), deficit (evening peak), and EV-dominated stress are presented. The results indicate that the convergence was correct 98.75%, 95.97%, and 93.87% of the time, and that both systems had a settlement success rate of over 96%. The trade rejection rate is below 12%, and the time required to perform a smart contract and the response time of a blockchain are below 1.8 s and 0.36 s, respectively. Compared with the benchmark algorithms (PSO, GWO), COA requires less time to converge, has smaller variance, and is more robust under stress conditions. The economic performance indicates that consumers can save up to 21.5% of costs, and prosumers can earn up to 24.5% more money. The cybersecurity analysis indicates that the attack detection rates are above 90%. The Pareto frontier analysis verifies that different levels of stress can cause a trade-off between social welfare and system reliability. In conclusion, the proposed BTEMS is a scalable, open, and cyber-resilient platform for decentralized energy markets. It is a practical solution that will facilitate the secure, real-time, and optimal control of smart microgrids in the future.