Hybrid particle swarm optimization with biased mutation applied to load flow computation in electrical power systems

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Abstract

This paper presents the implementation of a Hybrid Particle Swarm Optimization with Biased Mutation (HPSOBM) algorithm to solve the load flow computation in electrical power systems. The load flow study obtains the system status in the steady-state and it is widely used in the power system operation, planning and control. The proposed methodology is applied in a different computational model, which is based on the minimization of the power mismatches in the system buses. This new model searches for a greater convergence, and also a larger application in comparison with traditional numerical methods. In order to illustrate the proposed algorithm some simulations were conducted using the IEEE 14 bus system. © 2011 Springer-Verlag.

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Salomon, C. P., Coutinho, M. P., Lambert-Torres, G., & Ferreira, C. (2011). Hybrid particle swarm optimization with biased mutation applied to load flow computation in electrical power systems. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6728 LNCS, pp. 595–605). https://doi.org/10.1007/978-3-642-21515-5_70

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