A Proposed Improved Hybrid Hill Climbing Algorithm with the Capability of Local Search for Solving the Nonlinear Economic Load Dispatch Problem

This paper introduces a new hybrid hill-climbing algorithm (HHC) for solving the Economic Dispatch (ED) problem. This algorithm solves the ED problems with a systematic search structure with a global search. It improves the results obtained from an evolutionary algorithm with local search and converges to the best possible solution that grabs the accuracy of the problem. The most important goal of economic load dispatch is the optimal allocation of each generator's contribution to provide the load and reduce the costs of active units in the power system. This is generally due to presence of the nonlinear factors and limitations, such as the effect of the steam inlet valve (valve point effect (VPE)), the balance between the power generation and power demand of the system, the prohibited operating zones (POZS), power generation limits, ramp rate limits, and transmission losses. This algorithm is implemented on three 13-unit, 15-unit and 40-unit test systems with different operating conditions, and also for the same three test systems in combination with the evolutionary PSO algorithm. The simulation results show the efficiency of the proposed algorithm in solving ED problems.