Multiobjective Scheduling of Hybrid Renewable Energy System Using Equilibrium Optimization

Due to increasing concern over global warming, the penetration of renewable energy in power systems is day by day. Gencos that traditionally focused only on maximizing their profit competitive market are now also focusing operation with minimum pollution level. The paper proposes a multiobjective model capable finding set trade-off solutions for joint optimization problem, considering cost reserve and curtailment from sources. Managing hybrid system challenging task due its stochastic nature mixed objective function complex practical constraints associated it. A novel metaheuristic Equilibrium Optimizer (EO) algorithm incepted year 2020 utilizes concept control volume mass balance equilibrium state proposed here computing optimal schedule impact integration emission different objectives. In this paper, EO has shown dominant performance well-established algorithms such as particle swarm optimizer (PSO) artificial bee colony (ABC). addition, produces well-distributed Pareto-optimal fuzzy min-ranking used decision maker acquire best compromise solution.