Enhancing smart grid resilience and prosumer profitability using a novel Hunter–Prey optimization-based inter-microgrid energy trading strategy

Abstract

This work presents a comprehensive framework for enhancing the resilience of smart power distribution systems vulnerable to natural disasters, ensuring physical service continuity and cybersecurity protection. By creating supporting microgrid clusters and facilitating secure and market-controlled energy trading between them, the distribution network is dynamically reconfigured. Distributed renewable generation resources, including on-site wind generators, rooftop solar systems, battery storage units, and electric vehicles with bidirectional charging, are planned using a nature-inspired Hunter‒Prey optimization algorithm that protects cyber-physical operations malicious data disruptions. The three operating scenarios modeled are a fault-tolerant system without microgrids, isolated microgrids during faults, and interconnected microgrids with adaptive tie-line transmission. In order to ensure optimal system performance during disruptions, a cyber-integrated multi-objective function is also developed to maximize the cyber-resilient resilience index while minimising cyber-operation cost and outage-related financial losses. The proposed approach reduces the total energy not delivered by more than 60% and increases the resilience index 0 to 46.99 during critical disturbances, as evaluated on two representative networks: a realistic 28-bus feeder India and a standard IEEE 34-bus benchmark. By achieving a maximum of US$50.65 per hour, the secure trading system also increases the economic benefit to the consumer. According to comparative studies, the developed method provides 30–45% faster convergence and 7–15% higher optimization accuracy than particle swarm, genetic, and gray-wolf-based optimization techniques. Overall, the findings show that intelligent energy sharing, cyber-aware control, and integrated network reconstruction all work together to improve long-term operational stability, reduce the severity of disturbances, and enhance disaster recovery in future smart distribution networks.