A hybrid evolutionary algorithm for economic load dispatch problem considering transmission losses and various operational constraints

Optimization is a mathematical technique that concerns the finding of maxima or minima of functions in some feasible region. There is no business or industry which is not involved in solving optimization problems. A variety of optimization techniques compete for the best solution. Economic Dispatch (ED) is also one of the optimization problem. ED is the process of determining optimal output of available number of electric power generating stations in order to meet total system load, at a minimum possible cost while serving power to the public in a robust and reliable manner satisfying physical and operational constraints. Scarcity of energy resources, ever growing production cost of generation and increased load demand, there is a need to optimize the economic dispatch problem. In this research work, a hybrid technique proposed to solve non-linear ED problem named as Hybrid Particle Swarm Optimization with Gravitational Search Algorithm (HPSO-GSA) considering/neglecting valve point effects, prohibited operating zones, ramp rate limits and transmission losses. In order to evaluate the performance of the proposed Hybrid PSO-GSA algorithm has been tested on different generating unit test systems with different constraints and defined load demands. The simulation results of proposed algorithm are in comparison with the techniques in literature proves the efficiency and effectiveness of the proposed algorithm.