A Novel Distributed Particle Swarm Optimization Algorithm for the Optimal Power Flow Problem

Abstract : The distributed optimal power flow problem is addressed. No assumptions on the problem cost function, and network topology are needed to solve the optimization problem. A distributed particle swarm optimization algorithm is proposed, based on Deb's rule to handle hard constraints. Moreover, the approach enables to treat a class of distributed optimization problems in which the agents share a common optimization variable. Under mild communication assumptions, agents are only required to know local variables, cost function, and constraints to solve a common optimization problem. A simulation example is provided, based on a 5-bus electric grid.
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Submitted on : Tuesday, December 19, 2017 - 4:05:14 PM
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Nicolo Gionfra, Guillaume Sandou, Houria Siguerdidjane, Philippe Loevenbruck, Damien Faille. A Novel Distributed Particle Swarm Optimization Algorithm for the Optimal Power Flow Problem. 1st IEEE Conference on Control Technology and Applications (CCTA 2017), Aug 2017, Kohala Coast, United States. pp.1-8, ⟨10.1109/ccta.2017.8062537 ⟩. ⟨hal-01667868⟩

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