Hybrid Evolutionary Algorithm for Residential Demand Side Management with a Photovoltaic Panel and a Battery

Abstract : Residential demand side management (DSM) is one of the most challenging topics in smart grids. In this paper, a multiobjective model for the residential DSM over a 24-hour horizon is presented. This model consists of appliances, a battery and a photovoltaic panel. The resolution of this model is based on combining a multiobjective evolutionary algorithm (NSGA-II) and an exact solver (CPLEX). Solutions in this hybrid approach are incompletely represented, and optimally the exact solver determines the missing parts of the encoding. In our case, hybridization involves solving a MILP sub-problem by CPLEX to manage the battery and the photovoltaic panel constraints. Through case studies, It is shown that the coordination between the photovoltaic panel and the battery is effective to reduce the total electricity cost, the discomfort and the standard deviation of power consumed especially in summer conditions.
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Communication dans un congrès
ICCAIRO 2017 - International Conference on Control, Artificial Intelligence, Robotics & Optimization, May 2017, Prague, Czech Republic. IEEE, Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO), 2017 International Conference on, pp.4-10, 〈10.1109/ICCAIRO.2017.10〉
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https://hal.inria.fr/hal-01654829
Contributeur : Talbi El-Ghazali <>
Soumis le : lundi 4 décembre 2017 - 14:19:04
Dernière modification le : mardi 3 juillet 2018 - 11:23:47

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Zineb Garroussi, Rachid Ellaia, El-Ghazali Talbi, Jean-Yves Lucas. Hybrid Evolutionary Algorithm for Residential Demand Side Management with a Photovoltaic Panel and a Battery. ICCAIRO 2017 - International Conference on Control, Artificial Intelligence, Robotics & Optimization, May 2017, Prague, Czech Republic. IEEE, Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO), 2017 International Conference on, pp.4-10, 〈10.1109/ICCAIRO.2017.10〉. 〈hal-01654829〉

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