Economic environmental dispatch problem including wind farms using quantum-inspired optimization algorithms

Le résumé fourni par la source

In this paper, the Economic and Environmental Dispatch (EED) problem in wind-powered power systems is solved using the Quantum Grey Wolf Optimizer (QGWO), Quantum Particle Swarm Optimizer (QPSO), and Quantum Flower Pollination Algorithm (QFPA) metaheuristics. The EED is a multi-objective problem that aims to minimize two conflicting objectives: generation costs and pollutant emissions. The cost of wind power was modeled through the composition of three components: overestimation, underestimation, and direct costs. The quantum metaheuristics were compared using statistical indices. The simulations were carried out in an electrical system composed of 6 generators. The QFPA algorithm performed better, providing better-quality solutions compared to those obtained by the other quantum metaheuristics.

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