This paper presents a comparison of swarm intelligence and evolutionary techniques based approaches for minimization of system losses and improvement of voltage profiles in a power network. Efficient distribution of reactive power in an electric network can be achieved by adjusting the excitation on generators, the on-load tap changer positions of transformers, and proper switching of discrete portions of inductors or capacitors. This is a mixed integer non-linear optimization problem where metaheuristics techniques have proven suitable for providing optimal solutions. Four algorithms explored in this paper include differential evolution (DE), particle swarm optimization (PSO), a hybrid combination of DE and PSO, and a mutated PSO (MPSO) algorithm. The effectiveness of these algorithms is evaluated based on their solution quality and convergence characteristic. Simulation studies on the Nigerian power system show that a PSO based solution is more effective than a DE approach in reducing real power losses while keeping the voltage profiles within acceptable limits. The results also show that MPSO allows for further reduction of the real power losses while maintaining a satisfactory voltage profile.
G. K. Venayagamoorthy et al., "Swarm Intelligence and Evolutionary Approaches for Reactive Power and Voltage Control," Proceedings of the 2008 IEEE Swarm Intelligence Symposium (2008, St. Louis, MO), Institute of Electrical and Electronics Engineers (IEEE), Sep 2008.
The definitive version is available at http://dx.doi.org/10.1109/SIS.2008.4668314
2008 IEEE Swarm Intelligence Symposium (2008, St. Louis, MO)
Electrical and Computer Engineering
National Science Foundation (U.S.)
United States. Department of Education
Keywords and Phrases
Minimisation; Optimal Control; Particle Swarm Optimisation; Power System Control; Power System Stability; Power Transformers; Reactive Power Control; Voltage Control; Convergence; Evolutionary computation; Integer programming; Nonlinear programming
Article - Conference proceedings
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