Open AccessMulti-objective unit commitment problem using Cuckoo search Lagrangian method
Author(s) -
K. Chandrasekaran,
Sishaj P. Simon
Publication year - 2018
Publication title -
international journal of engineering, science and technology andb. lagos
Language(s) - English
Resource type - Journals
ISSN - 2141-2839
DOI - 10.4314/ijest.v4i2.7
Subject(s) - cuckoo search , power system simulation , mathematical optimization , fuzzy logic , harmony search , computer science , reliability (semiconductor) , operating cost , electric power system , reliability engineering , engineering , mathematics , power (physics) , artificial intelligence , physics , quantum mechanics , particle swarm optimization , waste management
Restructuring of power system changed the mechanism of reliability management in solving the unit commitment problem (UCP). In general, operating reserve capacity is predetermined either by dispatch rules or predefined by reliability index. This paper considers that the operating reserve capacity in a power system is bendable, which is based on the cost-reliability issues. In UCP, these two competing objectives such as fuel cost and reliability level of the system were optimized simultaneously, as a multi-objective unit commitment problem (MOUCP), using the proposed fuzzy integrated binary real coded cuckoo search Lagrangian (BCSL) algorithm. The ON/OFF status of the thermal power units is obtained by binary coded cuckoo search algorithm (CSA), where as the economic dispatch is obtained by Lagrangian multiplier method. The fuzzy set theory is used to pick up the best compromise solution. The proposed methodology is tested and validated for both the single and multi-objective UCP. The effectiveness of the proposed technique is demonstrated on IEEE RTS 24 bus system by comparing its performance with other methods reported in the literature.Keywords: binary coded cuckoo search algorithm, fuzzy set theory, reliability index, reserve scheduling, unit commitment problem.