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An MPC-based Energy Management System for Multiple Residential Microgrids
KTH, School of Electrical Engineering (EES), Automatic Control.
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2015 (English)In: 2015 INTERNATIONAL CONFERENCE ON AUTOMATION SCIENCE AND ENGINEERING (CASE), 2015, 7-14 p.Conference paper (Refereed)Text
Abstract [en]

In this study we present a Model Predictive Control (MPC) approach to Energy Management Systems (EMSs) for multiple residential microgrids. The EMS is responsible for optimally scheduling end-user smart appliances, heating systems and local generation devices at the residential level, based on end-user preferences, weather-dependent generation and demand forecasts, electric pricing, technical and operative constraints. The core of the proposed framework is a mixed integer linear programming (MILP) model aiming at minimizing the overall costs of each residential microgrid. At each time step, the computed optimal decision is adjusted according to the actual values of weather-dependent local generation and heating requirements; then, corrective actions and their corresponding costs are accounted for in order to cope with imbalances. At the next time step, the optimization problem is re-computed based on updated forecasts and initial conditions. The proposed method is evaluated in a virtual testing environment that integrates accurate simulators of the energy systems forming the residential microgrids, including electric and thermal generation units, energy storage devices and flexible loads. The testing environment also emulates real-word network medium conditions on standard network interfaces. Numerical results show the feasibility and the effectiveness of the proposed approach.

Place, publisher, year, edition, pages
2015. 7-14 p.
National Category
Control Engineering
URN: urn:nbn:se:kth:diva-191069DOI: 10.1109/CoASE.2015.7294033ISI: 000380453000002ScopusID: 2-s2.0-84952765730ISBN: 978-1-4673-8183-3OAI: diva2:955457
IEEE International Conference on Automation Science and Engineering (CASE), AUG 24-28, 2015, Gothenburg, SWEDEN

QC 20160825

Available from: 2016-08-25 Created: 2016-08-23 Last updated: 2016-08-25Bibliographically approved

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Parisio, AlessandraJohansson, Karl Henrik
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