@inproceedings{44868eceddf747cb800528b8ba94a687,
title = "Comparative study of bat & flower pollination optimization algorithms in highly stressed large power system",
abstract = "Optimal power flow is an important non-linear optimization task in power systems. In this process, the total power demand is distributed amongst the generating units such that each unit satisfies its generation limit constraints and the cost of power production is minimized. This paper presents a comparative study of new meta-heuristic optimization techniques namely bat and flower pollination algorithm for the optimal solution of optimal power flow problem such as minimizing the fuel cost of a thermal power plant. In this paper PSO is also taken just as a reference for measure the performance of the above two techniques. The numerical results clearly show that the bat algorithm gives better results than flower pollination algorithm in terms of fuel cost value and time required to reach global best solution. In order to illustrate the effectiveness of the proposed algorithm, it has been tested on highly stressed modified IEEE 300-bus test system.",
keywords = "Bat Algorithm (BA), Flower Pollination Algorithm (FPA), Optimal Power Flow (OPF), Particle Swarm Optimization (PSO)",
author = "Pandya, {K. S.} and Dabhi, {D. A.} and Joshi, {S. K.}",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 2015 Clemson University Power Systems Conference, PSC 2015 ; Conference date: 10-03-2015 Through 13-03-2015",
year = "2015",
month = may,
day = "4",
doi = "10.1109/PSC.2015.7101677",
language = "English",
series = "2015 Clemson University Power Systems Conference, PSC 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2015 Clemson University Power Systems Conference, PSC 2015",
address = "United States",
}
