Optimal Scheduling of Storage Devices in Smart Buildings Including Battery Cycling

Abstract : This paper presents an optimization model for energy management in smart buildings, when electrochemical and thermal storage are considered as flexibilities to achieve minimum operation costs. The optimization problem takes into account the battery’s cycling cost and the possibility of storing energy in the electric water heater. To deal with the cycling aging process, the problem is decomposed into two subproblems that are iteratively solved, in which a Particle Swarm Optimization decides the battery’s State of Charge and then a day-ahead dispatch takes place to determine the total operation cost. This approach allows us to deal with the non-linearities of battery aging in a simple an effective way. The results show that the potential presence of both storage technologies has a positive impact on the operation costs; they also show the impact on the device settings when battery’s cycling aging cost is considered. This methodology has been developed in the context of the Horizon 2020 project SENSIBLE as part of the tasks related to the use case, Flexibility and Demand Side Management in Market Participation.
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Communication dans un congrès
12th IEEE Power and Energy Society PowerTech Conference - PowerTech, Jun 2017, Manchester, United Kingdom. 〈10.1109/PTC.2017.7981199〉
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Carlos Adrian Correa Florez, Alexis Gerossier, Andrea Michiorri, Georges Kariniotakis. Optimal Scheduling of Storage Devices in Smart Buildings Including Battery Cycling. 12th IEEE Power and Energy Society PowerTech Conference - PowerTech, Jun 2017, Manchester, United Kingdom. 〈10.1109/PTC.2017.7981199〉. 〈hal-01520365〉

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