Efficient control and multi-criteria energy scheduling of renewable-based utility grid via pareto-metaheuristic optimizers

Being a renewable influenced utility grid, the wind integrated hydrothermal system (WHTS) is considered as a future-proof and contemporary energy system to reduce the dependency on depleting fossil fuels. However, due to intermittent nature of wind energy and complex operational constraints, offering the day-ahead operation schedule of WHTS with joint awareness of fuel economy and emissions is classified as a complicated multi-objective optimization problem. The major challenge is to maximize the utilization of clean hydro power to accommodate uncertain wind energy together with reduced dependency on fossils based thermal power. In this context, the paper devises an efficient control and multi-criteria energy scheduling method, essentially comprised of adaptive repair and volume restriction to maximize the utilization of available hydro power. The pareto-metaheuristic optimizer based on non-dominated sorting is exploited for the day-ahead scheduling of WHTS based utility grid. The most appropriate solution from pareto-optimal archive is selected using fuzzy-ranking index. The expected reductions in fuel cost and emissions are reflected using a significant probability scheme. The effectiveness of the proposed approach based on pareto-metaheuristic is appraised by various case studies. The simulation results provide a suitable day-ahead generation schedule of WHTS based grid, considering both economics and environmental aspects.