Modeling and Evaluating Beneficial Matches between Excess Renewable Power Generation and Non-Electric Heat Loads in Remote Alaska Microgrids

Grace Bolt, Michelle Wilber, Daisy Huang, Daniel J. Sambor, Srijan Aggarwal and Erin Whitney
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Grace Bolt: Alaska Center for Energy and Power, University of Alaska Fairbanks, Fairbanks, AK 99775, USA
Michelle Wilber: Alaska Center for Energy and Power, University of Alaska Fairbanks, Fairbanks, AK 99775, USA
Daisy Huang: Alaska Center for Energy and Power, University of Alaska Fairbanks, Fairbanks, AK 99775, USA
Daniel J. Sambor: Department of Civil and Environmental Engineering, Stanford University, Stanford, CA 94305, USA
Srijan Aggarwal: Department of Civil, Geological and Environmental Engineering, College of Engineering and Mines, University of Alaska Fairbanks, Fairbanks, AK 99775, USA
Erin Whitney: Alaska Center for Energy and Power, University of Alaska Fairbanks, Fairbanks, AK 99775, USA

Sustainability, 2022, vol. 14, issue 7, 1-11

Abstract: Many Alaska communities rely on heating oil for heat and diesel fuel for electricity. For remote communities, fuel must be barged or flown in, leading to high costs. While renewable energy resources may be available, the variability of wind and solar energy limits the amount that can be used coincidentally without adequate storage. This study developed a decision-making method to evaluate beneficial matches between excess renewable generation and non-electric dispatchable loads, specifically heat loads such as space heating, water heating and treatment, and clothes drying in three partner communities. Hybrid Optimization Model for Multiple Electric Renewables (HOMER) Pro was used to model potential excess renewable generation based on current generation infrastructure, renewable resource data, and community load. The method then used these excess generation profiles to quantify how closely they align with modeled or actual heat loads, which have inherent thermal storage capacity. Of 236 possible combinations of solar and wind capacity investigated in the three communities, the best matches were seen between excess electricity from high-penetration wind generation and heat loads for clothes drying and space heating. The worst matches from this study were from low penetrations of solar (25% of peak load) with all heat loads.

Keywords: microgrids; renewable energy; thermal storage; heating; dispatchability (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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