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An analysis of multi objective energy scheduling in PV-BESS system under prediction uncertainty

  • Unnikrishnan Raveendrannair
  • , Monika Sandelic
  • , Ariya Sangwongwanich
  • , Tomislav Dragicevic
  • , Ramon Costa Castello
  • , Frede Blaabjerg
    • Polytechnic University of Catalonia
    • Aalborg University

    Research output: Contribution to journal › Journal article › Research › peer-review

    363 Downloads (Orbit)

    Abstract

    Energy storage systems (ESS) are being considered to overcome issues in modern grids, caused by increasing penetration of renewable generation. Nevertheless, integration of ESS should also be supplemented with an optimal energy management framework to ensure maximum benefits from ESS. Conventional energy management of battery, used with PV system, maximises self-consumption but does not mitigate grid congestion or address battery degradation. Model predictive control (MPC) can alleviate congestion, degradation while maximizing self-consumption. As such, studies will be carried out,in this work, to highlight the improvement with MPC based energy management over conventional method using simulations of one-year system behaviour. As MPC uses forecast information in decision making, the impact of forecast uncertainties will be assessed and addressing the same through constraint tightening will be presented. It is concluded that MPC provides improvement in system behaviour over multiple performance criteria.

    Original languageEnglish
    JournalIEEE Transactions on Energy Conversion
    Volume36
    Issue number3
    Pages (from-to)2276 - 2286
    ISSN0885-8969
    DOIs
    Publication statusPublished - 2021

    Bibliographical note

    Publisher Copyright:
    IEEE

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 7 - Affordable and Clean Energy
      SDG 7 Affordable and Clean Energy

    Keywords

    • Artificial neural networks
    • battery management
    • Decision making
    • Degradation
    • Energy management
    • grid congestion degradation
    • Mathematical model
    • Model predictive control
    • Predictive models
    • PV system
    • State of charge

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