Open AccessA novel bat algorithm for solving optimal power flow problem
Author(s) -
Hardiansyah Hardiansyah
Publication year - 2020
Publication title -
engineering review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.198
H-Index - 11
eISSN - 1849-0433
pISSN - 1330-9587
DOI - 10.30765/er.1465
Subject(s) - bat algorithm , power flow , selection (genetic algorithm) , heuristic , mathematical optimization , compensation (psychology) , computer science , power (physics) , algorithm , electric power system , mathematics , artificial intelligence , psychology , physics , quantum mechanics , particle swarm optimization , psychoanalysis
This paper presents an application of a novel bat algorithm (NBA) for solving optimal power flow (OPF) problems in power systems. The proposed algorithm combines a bat habitat selection and their self-adaptive compensation for the Doppler effects in echoes into the basic bat algorithm (BA). The selection of the bat habitat is modeled as a selection between their quantum behavior and mechanical behavior. The objective of this paper is to minimize the total generation costs by considering equality and inequality constraints. To validate the proposed algorithm, the standard IEEE 30-bus and 57-bus test systems are applied. The results show that the proposed technique provides a better solution than other heuristic techniques reported in the literature.