Solving the unit commitment problem in large systems using hybrid PSO algorithms

Abstract

Abstract Unit Commitment (UC) is a nonlinear mixed integer-programming problem. UC is used to minimize the operational cost of the generation units in a power system by scheduling some of generators in ON state and the other generators in OFF state according to the total power outputs of generation units, load demand and the constraints of power system to increase the saving in the power system by applying the Unit Commitment (UC) to the power system. This work proposes Local Attracting Quantum Particle Swarm Algorithm (LAQPSO) to solve the unit commitment problem in power systems. The local attractor in the LAQPSO algorithm is used to obtain the rotation angle direction and magnitude for updating the quantum angle using the quantum rotation gate. The proposed algorithm is applied to solve the UC problem for a 26 units power system. A comparison with the Binary PSO (BPSO), Improved Quantum BPSO (IQBPSO) and other techniques in the literature was implemented to show the efficiency and the accuracy of the proposed algorithm. The results show the superior performance of the proposed LAQPSO algorithm to minimize the total cost when compared with BPSO, IQBPSO and the literature works.