@inproceedings{3827cba4c9ac45afafc21cd73a6a5c08,
title = "Multi-objective particle swarm optimization for optimal power flow in a deregulated environment of power systems",
abstract = "In this paper, a multi-objective particle swarm optimization (MOPSO) technique is proposed for solving the optimal power flow (OPF) problem in a deregulated environment. The OPF problem is formulated as a nonlinear constrained multi-objective optimization problem where the fuel cost and wheeling cost are to be optimized simultaneously. MVA-km method is used to calculate the wheeling cost in the system. The proposed approach handles the problem as a true multi-objective optimization problem. The results demonstrate the capabilities of the proposed approach to generate true and well-distributed Pareto optimal solutions of the multi-objective OPF problem in one single run. In addition, the effectiveness of the proposed approach and its potential to solve the multi-objective OPF problem are confirmed. IEEE 30 bus system is considered to demonstrate the suitability of this algorithm.",
keywords = "Fuel cos, Multi-objective optimization Optimal power flow, Particle swarm optimization, Wheeling cost",
author = "Zaro, \{F. R.\} and Abido, \{M. A.\}",
year = "2011",
doi = "10.1109/ISDA.2011.6121809",
language = "English",
isbn = "9781457716751",
series = "International Conference on Intelligent Systems Design and Applications, ISDA",
pages = "1122--1127",
booktitle = "Proceedings of the 2011 11th International Conference on Intelligent Systems Design and Applications, ISDA'11",
}