A Novel Gradient Based Optimizer for Solving Unit Commitment Problem

Secure and economic operation of the power system is one prime concerns for engineers 21st century. Unit Commitment (UC) represents an enhancement problem controlling operating schedule units in each hour interval with different loads at various technical environmental constraints. UC complex optimization tasks performed by plant regular planning system. Researchers have used a number metaheuristics (MH) solving this demanding problem. This work aims to test Gradient Based Optimizer (GBO) performance treating The evaluation GBO applied on five cases study, first case network 4-unit second 10-unit, then 20 units, 40 100-unit Simulation results establish efficacy robustness as compared other such Differential Evolution, Enhanced Genetic Algorithm, Lagrangian Relaxation, Ionic Bond-direct Particle Swarm Optimization, Bacteria Foraging Algorithm Grey Wolf Algorithm. method achieve lowest average run time than competitor methods. best cost function all systems achieved technique.