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Novel wind resource assessment and demand flexibility analysis for community resilience: A remote microgrid case study

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  • Her, Chong
  • Sambor, Daniel J.
  • Whitney, Erin
  • Wies, Richard

Abstract

With the increasing effects of climate change and high costs of energy, many rural Alaska communities are working to implement local alternative energy solutions to improve energy security. Integrating renewable energy systems can reduce reliance on fossil fuels and subsequently improve food, energy, and water (FEW) security. In this study, wind energy modeling techniques using local airport meteorological data were convolved with community loads to determine the most cost-effective combinations of wind turbine technology and dispatchable loads for improving FEW security in a southwestern Alaska village. This approach is different from wind assessments that exclusively analyze wind resources. A 100 kW wind turbine was determined to be suitable for the community, resulting in a capacity factor of 16.7% and levelized cost of energy (LCOE) of $1.15/kWh, with diminishing returns for higher wind turbine capacity. The results from the dispatchability study indicated that dispatchable loads could handle the intermittency of the wind resource with up to 86% of their annual load met. More work is needed to understand the impact of integrating and scheduling dispatchable loads into the grid in practice.

Suggested Citation

  • Her, Chong & Sambor, Daniel J. & Whitney, Erin & Wies, Richard, 2021. "Novel wind resource assessment and demand flexibility analysis for community resilience: A remote microgrid case study," Renewable Energy, Elsevier, vol. 179(C), pages 1472-1486.
    • Handle: RePEc:eee:renene:v:179:y:2021:i:c:p:1472-1486
    DOI: 10.1016/j.renene.2021.07.099
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    References listed on IDEAS

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    1. Zhang, Heng & Zhang, Shenxi & Cheng, Haozhong & Li, Zheng & Gu, Qingfa & Tian, Xueqin, 2022. "Boosting the power grid resilience under typhoon disasters by coordinated scheduling of wind energy and conventional generators," Renewable Energy, Elsevier, vol. 200(C), pages 303-319.
    2. Grace Bolt & Michelle Wilber & Daisy Huang & Daniel J. Sambor & Srijan Aggarwal & Erin Whitney, 2022. "Modeling and Evaluating Beneficial Matches between Excess Renewable Power Generation and Non-Electric Heat Loads in Remote Alaska Microgrids," Sustainability, MDPI, vol. 14(7), pages 1-11, March.
    3. Sima, Catalina Alexandra & Popescu, Claudia Laurenta & Popescu, Mihai Octavian & Roscia, Mariacristina & Seritan, George & Panait, Cornel, 2022. "Techno-economic assessment of university energy communities with on/off microgrid," Renewable Energy, Elsevier, vol. 193(C), pages 538-553.

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