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Diesel genset optimization in remote microgrids

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  • Lambert, Mathieu
  • Hassani, Rachid

Abstract

In this paper, a new model is proposed for the real-time diesel genset optimal dispatch and unit commitment in remote microgrids. The objective is to reduce fuel consumption, while taking into account several constraints, such as maintenance considerations and prime power ratings, specific to gensets. The model described in this work is deterministic in nature and is a mixed-integer linear programming optimization problem. In order to demonstrate the correct behavior of the model, four case studies were chosen to illustrate the activation of different constraints under certain conditions. The results show that the model properly reproduces the intended behavior, and that it could have permitted to reduce fuel consumption by 4.3 % when compared to the actual dispatch during those 2 days. Finally, it was shown that the performance of the model solved with CPLEX and Gurobi is adequate for real-time optimization in remote microgrids, and that the economic gain of using a baseload strategy instead of a load sharing strategy is negligible compared to the increase of complexity in implementing this baseload strategy.

Suggested Citation

  • Lambert, Mathieu & Hassani, Rachid, 2023. "Diesel genset optimization in remote microgrids," Applied Energy, Elsevier, vol. 340(C).
    • Handle: RePEc:eee:appene:v:340:y:2023:i:c:s0306261923004002
    DOI: 10.1016/j.apenergy.2023.121036
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    References listed on IDEAS

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    1. Steffen Rebennack, 2016. "Computing tight bounds via piecewise linear functions through the example of circle cutting problems," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 84(1), pages 3-57, August.
    2. Husted, Mark A. & Suthar, Bharatkumar & Goodall, Gavin H. & Newman, Alexandra M. & Kohl, Paul A., 2018. "Coordinating microgrid procurement decisions with a dispatch strategy featuring a concentration gradient," Applied Energy, Elsevier, vol. 219(C), pages 394-407.
    3. Morais, Hugo & Kádár, Péter & Faria, Pedro & Vale, Zita A. & Khodr, H.M., 2010. "Optimal scheduling of a renewable micro-grid in an isolated load area using mixed-integer linear programming," Renewable Energy, Elsevier, vol. 35(1), pages 151-156.
    4. Stringer, Thomas & Joanis, Marcelin, 2023. "Decarbonizing Canada's remote microgrids," Energy, Elsevier, vol. 264(C).
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    1. Reza Nadimi & Masahito Takahashi & Koji Tokimatsu & Mika Goto, 2024. "The Reliability and Profitability of Virtual Power Plant with Short-Term Power Market Trading and Non-Spinning Reserve Diesel Generator," Energies, MDPI, vol. 17(9), pages 1-19, April.

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