Open AccessUnit commitment problem solution using Local Attracting Quantum PSO algorithm
Author(s) -
Ali A. İsmail,
Ali Nasser Hussain
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/745/1/012008
Subject(s) - particle swarm optimization , power system simulation , algorithm , computer science , power (physics) , electric power system , mathematical optimization , local optimum , rotation (mathematics) , quantum , mathematics , artificial intelligence , physics , quantum mechanics
In power systems, the demand is time-varying throughout the day, week and month. For that reason, the generators have to be scheduled optimally to increase the saving in the power system by applying the Unit Commitment (UC) to the power system. UC is the operation of turning the generators ON and OFF to supply the demand power. This paper suggests Local Attracting Quantum Particle Swarm Algorithm (LAQPSO) to solve the unit commitment dilemma in power systems. The local attractor in the LAQPSO algorithm is utilized to obtain the rotation angle direction and magnitude in order to update the quantum angle by the quantum rotation gate. The proposed algorithm is applied to solve the UC problem for a 10-units power system. A comparison with different techniques in the literature was implemented to validate 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 to the literature works.