As the energy management undergoes rapid transformations, there's an imperative need for innovative energy management frameworks. Responding to this, our research introduces an advanced energy management framework, synergistically combining quantum computing advancements with a robust trust management system. At the core of our proposition is the utilization of Quantum Annealing (QA) and Quantum-inspired Genetic Algorithm (QGA) for energy distribution, offering marked improvements in speed, accuracy, and scalability. Complementing this, multi-objective decision-making algorithms are integrated, optimizing trade-offs in intricate scenarios. Central to ensuring system reliability, the trust management system ensures improved regulation and compliance adherence. Our approach's potency is further evidenced by its wide applicability, demonstrated through diverse case studies ranging from solar power plant management to smart city energy distribution. Experimental simulations underscore the framework's efficacy, establishing its relevance in today's dynamic energy ecosystems.
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Awan et al. (2024) studied this question.
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