Abstract:
Optimal active–reactive power dispatch problems (OARPD) are considered large scale optimization problems with a high nonlinear complexity. Usually, in OARPD the objective...Show MoreMetadata
Abstract:
Optimal active–reactive power dispatch problems (OARPD) are considered large scale optimization problems with a high nonlinear complexity. Usually, in OARPD the objective is to minimize the cost of the system operation. In 2018, the IEEE PES committee proposed a competition, the “Operational planning of sustainable power systems”, in which a test bed relating the OARPD and a renewable energy generation challenge within a smart grid was proposed. In this work we consider three test scenarios proposed in that competition. Specifically, we present a hybrid meta-heuristic optimization approach applied to the OARPD, the Canonical Differential Evolutionary Particle Swarm Optimization (C-DEEPSO), to tackle these test scenarios. Comparative results with other algorithms such as CMA-ES, EPSO, and CEEPSO indicate that C-DEEPSO shows a competitive performance when solving the OARPD problems.
Published in: 2022 IEEE Congress on Evolutionary Computation (CEC)
Date of Conference: 18-23 July 2022
Date Added to IEEE Xplore: 06 September 2022
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