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Field-Ready Implementation of Linear Economic Model Predictive Control for Microgrid Dispatch in Small and Medium Enterprises

Author

Listed:
  • Tobias Kull

    (Chair of Measurement and Control Systems, Center of Energy Technology (ZET), University of Bayreuth, Universitätsstraße 30, 95447 Bayreuth, Germany)

  • Bernd Zeilmann

    (Richter R&W Steuerungstechnik GmbH, 95491 Ahorntal, Germany)

  • Gerhard Fischerauer

    (Chair of Measurement and Control Systems, Center of Energy Technology (ZET), University of Bayreuth, Universitätsstraße 30, 95447 Bayreuth, Germany)

Abstract

The increasing share of distributed renewable energy resources (DER) in the grid entails a paradigm shift in energy system operation demanding more flexibility on the prosumer side. In this work we show an implementation of linear economic model predictive control (MPC) for flexible microgrid dispatch based on time-variable electricity prices. We focus on small and medium enterprises (SME) where information and communications technology (ICT) is available on an industrial level. Our implementation uses field devices and is evaluated in a hardware-in-the-loop (HiL) test bench to achieve high technological maturity. We use available forecasting techniques for power demand and renewable energy generation and evaluate their influence on energy system operation compared to optimal operation under perfect knowledge of the future and compared to a status-quo operation strategy without control. The evaluation scenarios are based on an extensive electricity price analysis to increase representativeness of the simulation results and are based on the use of historic real-world measurements in an existing production facility. Due to real-world restrictions (imperfect forecast knowledge, implementation on field hardware, power fluctuations), between 72.2% and 85.5% of the economic optimum (rather than 100%) is reached. Together with reduced operation cost, the economic MPC implementation on field-typical industrial ICT leads to an increased share of renewable energy demand.

Suggested Citation

  • Tobias Kull & Bernd Zeilmann & Gerhard Fischerauer, 2021. "Field-Ready Implementation of Linear Economic Model Predictive Control for Microgrid Dispatch in Small and Medium Enterprises," Energies, MDPI, vol. 14(13), pages 1-23, June.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:13:p:3921-:d:585663
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    References listed on IDEAS

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    1. Alphonsus, Ephrem Ryan & Abdullah, Mohammad Omar, 2016. "A review on the applications of programmable logic controllers (PLCs)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1185-1205.
    2. Auer, Hans & Haas, Reinhard, 2016. "On integrating large shares of variable renewables into the electricity system," Energy, Elsevier, vol. 115(P3), pages 1592-1601.
    3. Matteo Moncecchi & Claudio Brivio & Stefano Mandelli & Marco Merlo, 2020. "Battery Energy Storage Systems in Microgrids: Modeling and Design Criteria," Energies, MDPI, vol. 13(8), pages 1-18, April.
    4. Felix Garcia-Torres & Ascension Zafra-Cabeza & Carlos Silva & Stephane Grieu & Tejaswinee Darure & Ana Estanqueiro, 2021. "Model Predictive Control for Microgrid Functionalities: Review and Future Challenges," Energies, MDPI, vol. 14(5), pages 1-26, February.
    5. Lund, Peter D. & Lindgren, Juuso & Mikkola, Jani & Salpakari, Jyri, 2015. "Review of energy system flexibility measures to enable high levels of variable renewable electricity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 785-807.
    6. De Lorenzi, Andrea & Gambarotta, Agostino & Morini, Mirko & Rossi, Michele & Saletti, Costanza, 2020. "Setup and testing of smart controllers for small-scale district heating networks: An integrated framework," Energy, Elsevier, vol. 205(C).
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