Methodology to Incorporate Backup Generator Sizing Using the Microgrid Design Toolkit

Backup generation sizing is crucial in the design of power systems such as microgrids. This paper presents a backup generator sizing methodology for use in the optimization tool Microgrid Design Toolkit (MDT). A microgrid design that considers solar generation, energy storage in the form of batteries and a backup diesel generator is evaluated in event-based Monte Carlo simulations. Optimization metrics including diesel fuel cost and usage, and parameters such as spinning reserve are leveraged to conduct proper sizing. This paper also presents an expected microgrid configuration based on calculations for the PV, storage and diesel generator to provide context, and results from various stages of the methodology.

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Published
2025-06-08
DOI
https://doi.org/10.1109/pvsc59419.2025.11132807
Primary Topic
Microgrid Control and Optimization
Type
article
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article

Methodology to Incorporate Backup Generator Sizing Using the Microgrid Design Toolkit

Rachid Darbali-Zamora, Erick E. Aponte-Bezares, Rolando J. Tremont-Brito, John Eddy
Microgrid Control and Optimization
article

Methodology to Incorporate Backup Generator Sizing Using the Microgrid Design Toolkit

Rachid Darbali-Zamora, Erick E. Aponte-Bezares, Rolando J. Tremont-Brito, John Eddy
article en

Abstract

Backup generation sizing is crucial in the design of power systems such as microgrids. This paper presents a backup generator sizing methodology for use in the optimization tool Microgrid Design Toolkit (MDT). A microgrid design that considers solar generation, energy storage in the form of batteries and a backup diesel generator is evaluated in event-based Monte Carlo simulations. Optimization metrics including diesel fuel cost and usage, and parameters such as spinning reserve are leveraged to conduct proper sizing. This paper also presents an expected microgrid configuration based on calculations for the PV, storage and diesel generator to provide context, and results from various stages of the methodology.

Sandia National Laboratories (US), University of Puerto Rico-Mayaguez (PR)
Openalex Percentile: Top 72%
Microgrid Control and Optimization
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