Multi-objective particle swarm optimization for optimal power flow in a deregulated environment of power systems

Multi-objective particle swarm optimization for optimal power flow in a deregulated environment of power systems

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 cos...

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Hauptverfasser: Zaro, F. R., Abido, M. A.
Format: Tagungsbericht
Sprache:eng
Schlagworte:
Fuel cos
Fuels
Generators
Load flow
Multi-objective optimization Optimal power flow
Pareto optimization
Particle swarm optimization
Reactive power
Wheeling cost
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description 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.
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A.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Zaro, F. R.</au><au>Abido, M. 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subjects Fuel cos
Fuels
Generators
Load flow
Multi-objective optimization Optimal power flow
Pareto optimization
Particle swarm optimization
Reactive power
Wheeling cost
title Multi-objective particle swarm optimization for optimal power flow in a deregulated environment of power systems
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