@inproceedings{a9e89d96110e401d8887ad4dbc2efbe7,
title = "A heuristic to generate initial feasible solutions for the Unit Commitment problem",
abstract = "This paper presents a heuristic approach to generate initial feasible solutions for the Unit Commitment (UC) problem in electric power generation. The Chemical Reaction Optimization (CRO) algorithm is implemented to solve this problem. Multiple generator constraints and system constraints are considered. We also program the binary PSO and the Elite PSO (EPSO) for comparison. The proposed heuristic approach is combined with the three optimization algorithms to form H-CRO, H-PSO and H-EPSO. We test the performance of all algorithms on the standard 10-unit system. Simulation results show that the heuristic can improve the performance and CRO provides better convergence than the two PSO algorithms. H-CRO is also tested on a 20-unit and 100-unit system to show its capability. The results provided in this paper suggest that the proposed heuristic approach is a better alternative for solving the UC problem. CRO also has its advantage in optimizing UC problems.",
keywords = "Chemical reaction optimization, heuristic, power grid, unit commitment",
author = "Yi Sun and LAM, {Yun Sang Albert} and Li, {Victor O.K.}",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE. Copyright: Copyright 2015 Elsevier B.V., All rights reserved.; 2014 International Joint Conference on Neural Networks, IJCNN 2014 ; Conference date: 06-07-2014 Through 11-07-2014",
year = "2014",
month = sep,
day = "3",
doi = "10.1109/IJCNN.2014.6889548",
language = "English",
series = "Proceedings of the International Joint Conference on Neural Networks",
publisher = "IEEE",
pages = "913--920",
booktitle = "Proceedings of the International Joint Conference on Neural Networks",
address = "United States",
}