This paper suggests a new PSOHHCalgorithm for solving the economic dispatch (ED). Thisalgorithm was created by integrating two algorithms: PSO(particle swarm optimization) algorithm, an evolutionaryalgorithm based on collective intelligence, and a newsearch algorithm for HHC (Hybrid Hill Climbing) whichis based on searching. The aim of presenting thisalgorithm is to improve the performance of the PSOalgorithm in terms of convergence to achieve the bestpossible solution with the required accuracy. This newalgorithm is able to improve the responses obtained fromthe PSO algorithm with a controllable local search. Themost important goal of economic dispatch is the optimalallocation of each generator's contribution to provide theload and reduce the costs of active units in the powersystem. This is generally due to the nonlinear factors andlimitations, such as: the effect of steam inlet valve (valvepoint effect (VPE)), the balance between the productionand consumption of the system, the prohibited operatingzones (POZS), production limits, slope rate, and lines’losses. This algorithm is implemented on 3 test systems of13 units, 31 units and 40 units with different operatingconditions, independently and also in combination withthe PSO evolutionary algorithm, and simulation resultsillustrate the efficiency of this algorithm in solving EDproblems.
