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Day-Ahead MPC Energy Management System for an Island Wind/Storage Hybrid Power Plant

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  • Rubén López-Rodríguez

    (ESTIA Institute of Technology, Technopole Izarbel, 64210 Bidart, France
    Grenoble INP (Institute of Engineering University Grenoble Alpes), Université Grenoble Alpes, CNRS , G2Elab, F-38000 Grenoble, France)

  • Adriana Aguilera-González

    (ESTIA Institute of Technology, Technopole Izarbel, 64210 Bidart, France)

  • Ionel Vechiu

    (ESTIA Institute of Technology, Technopole Izarbel, 64210 Bidart, France)

  • Seddik Bacha

    (Grenoble INP (Institute of Engineering University Grenoble Alpes), Université Grenoble Alpes, CNRS , G2Elab, F-38000 Grenoble, France)

Abstract

This paper presents a multi-objective energy management system (EMS) to manage the power dispatch of a hybrid power plant (HPP), consisting of a grid-connected wind farm and a Li-ION battery storage system on the island of Guadeloupe’s electrical grid. Via a controller based on Model Predictive Control (MPC), the EMS solves the problem of optimization by considering the production forecast data and managing several operation rules, which ensures meet energy targets considered for a sustainable power dispatching plan. The proposed strategy is tested in a PowerFactory/MATLAB co-simulation environment.

Suggested Citation

  • Rubén López-Rodríguez & Adriana Aguilera-González & Ionel Vechiu & Seddik Bacha, 2021. "Day-Ahead MPC Energy Management System for an Island Wind/Storage Hybrid Power Plant," Energies, MDPI, vol. 14(4), pages 1-33, February.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:4:p:1066-:d:501358
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    References listed on IDEAS

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    1. Bechlenberg, Alva & Luning, Egbert A. & Saltık, M. Bahadır & Szirbik, Nick B. & Jayawardhana, Bayu & Vakis, Antonis I., 2024. "Renewable energy system sizing with power generation and storage functions accounting for its optimized activity on multiple electricity markets," Applied Energy, Elsevier, vol. 360(C).
    2. Yao, Leyi & Liu, Zeyuan & Chang, Weiguang & Yang, Qiang, 2023. "Multi-level model predictive control based multi-objective optimal energy management of integrated energy systems considering uncertainty," Renewable Energy, Elsevier, vol. 212(C), pages 523-537.

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