Optimization of the Design and Control System of a Backup Power System Based on Batteries and Generator Set

Iñigo Aramendia, Ekaitz Zulueta, Jose Manuel Lopez-Guede (), Daniel Teso-Fz-Betoño and Unai Fernandez-Gamiz
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Iñigo Aramendia: Electrical Engineering Department, University of the Basque Country (UPV/EHU), Nieves Cano 12, 01006 Vitoria-Gasteiz, Araba, Spain
Ekaitz Zulueta: Automatic Control and System Engineering Department, University of the Basque Country (UPV/EHU), Nieves Cano 12, 01006 Vitoria-Gasteiz, Araba, Spain
Jose Manuel Lopez-Guede: Automatic Control and System Engineering Department, University of the Basque Country (UPV/EHU), Nieves Cano 12, 01006 Vitoria-Gasteiz, Araba, Spain
Daniel Teso-Fz-Betoño: Electrical Engineering Department, University of the Basque Country (UPV/EHU), Nieves Cano 12, 01006 Vitoria-Gasteiz, Araba, Spain
Unai Fernandez-Gamiz: Nuclear Engineering and Fluid Mechanics Department, University of the Basque Country (UPV/EHU), Nieves Cano 12, 01006 Vitoria-Gasteiz, Araba, Spain

Sustainability, 2025, vol. 17, issue 5, 1-19

Abstract: Grid complexity is expected to increase in the near future, and therefore, research on it is highly increasing due to the interest in optimizing power distribution along with the implementation of renewable energy sources. The grid presented in the current work uses a hybrid storage system with batteries and a generator set. A supervisor is also added to the model in order to distribute the load between the batteries and the generator when a power grid outage is detected. The main objective of this study is to find optimal supervisor operating values and battery capacity sizing. To that end, a recently developed intelligent algorithm, called Basque optimization (BO), is applied to model the battery capacity sizing and its depth of discharge. The results obtained provided an optimum value of 0.7267, which implies a battery sizing of 72.67% of the maximum battery capacity proposed in the optimization algorithm. Additionally, an optimal state of charge ( SoC_lim ) of the battery of 3.87% is obtained, corresponding to a depth of discharge ( DoD_lim ) of 96.13%. A sensitivity analysis is also performed to evaluate different time horizons and load profiles. The results showed that longer simulation horizons reduce the DoD , preserving battery life, while battery utilization increases in longer time horizons and variable load conditions, ensuring energy availability.

Keywords: smart grid; intelligent optimization; supervisor; battery management; battery sizing (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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