Creation of a Synthetic Rural Alaskan Microgrid Model

Power system models of electric systems are crucial in system planning for operations, economics, and expansion analyses. However, as these models contain critical infrastructure data, they are not publicly available. This poses challenges in future expansion scenarios and evaluating technological advancements in an electric grid. Synthetic models are realistic power system models, both topologically and operationally. However, since the electrical network is typically produced using statistical data and often uses machine learning, it does not contain propriety information. This allows researchers to evaluate system behavior under various operating conditions and as test cases for emerging technologies. These test cases are particularly important in highly evolving electric grids and areas of high renewable energy integration such as Alaska. Currently, no publicly available benchmark power system models of rural Alaskan island microgrids exist. This paper presents a rural Alaskan microgrid synthetic power system model and the methodology adopted to develop the model. The performance of the developed synthetic grid was assessed through steady state and positive-sequence dynamic simulations under various operating conditions.

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Publication Details

Journal
Energies
Published
2025-09-04
DOI
https://doi.org/10.3390/en18174715
Primary Topic
Microgrid Control and Optimization
Type
article
Field-Weighted Citation Impact
0.00

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Creation of a Synthetic Rural Alaskan Microgrid Model

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Creation of a Synthetic Rural Alaskan Microgrid Model

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article en

Abstract

Power system models of electric systems are crucial in system planning for operations, economics, and expansion analyses. However, as these models contain critical infrastructure data, they are not publicly available. This poses challenges in future expansion scenarios and evaluating technological advancements in an electric grid. Synthetic models are realistic power system models, both topologically and operationally. However, since the electrical network is typically produced using statistical data and often uses machine learning, it does not contain propriety information. This allows researchers to evaluate system behavior under various operating conditions and as test cases for emerging technologies. These test cases are particularly important in highly evolving electric grids and areas of high renewable energy integration such as Alaska. Currently, no publicly available benchmark power system models of rural Alaskan island microgrids exist. This paper presents a rural Alaskan microgrid synthetic power system model and the methodology adopted to develop the model. The performance of the developed synthetic grid was assessed through steady state and positive-sequence dynamic simulations under various operating conditions.

EnergiesVol. 18(17)
University of Alaska Fairbanks (US)
National Science Foundation, U.S. Department of Energy, Electric Power Research Institute, American College of Emergency Physicians, Università degli Studi di Firenze, Office of Energy Efficiency and Renewable Energy, Office of Energy Efficiency
Openalex Percentile: Top 71%
Microgrid Control and Optimization
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