Diesel genset optimization in remote microgrids

Mathieu Lambert and Rachid Hassani

Applied Energy, 2023, vol. 340, issue C, No S0306261923004002

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.

Keywords: Real-time optimization; Mixed-integer linear programming; Deterministic unit commitment; Microgrids; Diesel gensets (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (1)

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DOI: 10.1016/j.apenergy.2023.121036

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