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

Nicolo Gionfra 1 Guillaume Sandou 1, 2 Houria Siguerdidjane 1 Philippe Loevenbruck 3 Damien Faille 4
1 L2S - Laboratoire des signaux et systèmes
2 DISCO - Dynamical Interconnected Systems in COmplex Environments
L2S - Laboratoire des signaux et systèmes, Inria Saclay - Ile de France
3 EDF - EDF
4 EDF R&D STEP - Simulation et Traitement de l'information pour l'Exploitation des systèmes de Production
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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CENTRALESUPELEC | SUP_LSS | SUP_SYSTEMES | CNRS | TDS-MACS | L2S | UNIV-PARIS-SACLAY | INRIA | EDF

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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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