An MPC-based Energy Management System for multiple residential microgrids

Alessandra Parisio, Christian Wiezorek, Timo Kyntaja, Joonas Elo, Karl Henrik Johansson

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


    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.

    Original languageEnglish
    Title of host publication2015 IEEE Conference on Automation Science and Engineering: Automation for a Sustainable Future, CASE 2015
    PublisherIEEE Computer Society
    Number of pages8
    ISBN (Electronic)9781467381833
    Publication statusPublished - 7 Oct 2015
    Event11th IEEE International Conference on Automation Science and Engineering, CASE 2015 - Gothenburg, Sweden
    Duration: 24 Aug 201528 Aug 2015


    Conference11th IEEE International Conference on Automation Science and Engineering, CASE 2015


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