Recent Methodology-Based Gradient-Based Optimizer for Economic Load Dispatch Problem

Economic load dispatch (ELD) in power system problems involves scheduling the generating units to minimize cost and satisfy constraints. Although previous works propose solutions reduce CO2 emission production cost, an optimal allocation needs be considered on both emission-leading combined economic (CEED). Metaheuristic optimization algorithms perform relatively well ELD problems. The gradient-based optimizer (GBO) is a new metaheuristic algorithm inspired by Newton's method that integrates gradient search rule local escaping operator. GBO maintains good balance between exploration exploitation. Also, possibility of getting stuck optima premature convergence rare. This paper tests performance solving CEED We test for various scenarios such as with transmission losses, valve point effect. experimental results revealed has been obtained better compared eight other Slime mould (SMA), Elephant herding (EHO), Monarch butterfly (MBO), Moth (MSA), Earthworm (EWA), Artificial Bee Colony (ABC) Algorithm, Tunicate Swarm Algorithm (TSA) Chimp Optimization (ChOA). Therefore, simulation showed competitive benchmark algorithms.