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Challenges estimating distributed solar potential with utilization factors: California universities case study

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  • Thai, Clinton
  • Brouwer, Jack

Abstract

Utilization factors are a popular method to identify distributed solar photovoltaic potential in many scopes. Though not the most accurate method, it is computationally inexpensive. In this work, Google’s Project Sunroof is reverse engineered to produce an image analysis model capable of predicting photovoltaic capacity for user-defined volumes. The developed model is tuned with a set of reference zip codes and applied to an adjacent set of zip codes, resulting in an error range from as small as 1% to as great as 30%. This analysis guides an investigation of how rooftop utilization factors vary across adjacent zip codes and building types. The findings provide the basis to question the accuracy of similar current and future analyses that extrapolate using fixed utilization factors to identify distributed solar photovoltaic potential between similar settings (e.g. one residential area to another). Sensitivity of these results are established by referring to actual and modeled installations’ utilization factors ranging from 0.28 to 0.89. Such variance suggests upmost caution or necessitates strong justification when assuming a utilization factor for distributed solar potential quantification. The range of utilization factors can be effectively reduced when considering multiple similar samples (e.g. several multi-functional higher education campuses). The results from the model are used to guide the justification of a utilization factor to determine the combined distributed photovoltaic capacities of University of California campuses. A total of 471 MW when liberally installing solar parking canopies and 345 MW when conservatively anticipating building development on parking lots is found.

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  • Thai, Clinton & Brouwer, Jack, 2021. "Challenges estimating distributed solar potential with utilization factors: California universities case study," Applied Energy, Elsevier, vol. 282(PB).
    • Handle: RePEc:eee:appene:v:282:y:2021:i:pb:s0306261920316056
    DOI: 10.1016/j.apenergy.2020.116209
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    1. Lobaccaro, G. & Croce, S. & Lindkvist, C. & Munari Probst, M.C. & Scognamiglio, A. & Dahlberg, J. & Lundgren, M. & Wall, M., 2019. "A cross-country perspective on solar energy in urban planning: Lessons learned from international case studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 209-237.
    2. Byrne, John & Taminiau, Job & Kurdgelashvili, Lado & Kim, Kyung Nam, 2015. "A review of the solar city concept and methods to assess rooftop solar electric potential, with an illustrative application to the city of Seoul," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 830-844.
    3. Zhang, Ji & Xu, Le & Shabunko, Veronika & Tay, Stephen En Rong & Sun, Huixuan & Lau, Stephen Siu Yu & Reindl, Thomas, 2019. "Impact of urban block typology on building solar potential and energy use efficiency in tropical high-density city," Applied Energy, Elsevier, vol. 240(C), pages 513-533.
    4. Vardimon, Ran, 2011. "Assessment of the potential for distributed photovoltaic electricity production in Israel," Renewable Energy, Elsevier, vol. 36(2), pages 591-594.
    5. Kanters, Jouri & Wall, Maria, 2016. "A planning process map for solar buildings in urban environments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 173-185.
    6. Freitas, S. & Catita, C. & Redweik, P. & Brito, M.C., 2015. "Modelling solar potential in the urban environment: State-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 915-931.
    7. Kabir, Md. Humayun & Endlicher, Wilfried & Jägermeyr, Jonas, 2010. "Calculation of bright roof-tops for solar PV applications in Dhaka Megacity, Bangladesh," Renewable Energy, Elsevier, vol. 35(8), pages 1760-1764.
    8. Kucuksari, Sadik & Khaleghi, Amirreza M. & Hamidi, Maryam & Zhang, Ye & Szidarovszky, Ferenc & Bayraksan, Guzin & Son, Young-Jun, 2014. "An Integrated GIS, optimization and simulation framework for optimal PV size and location in campus area environments," Applied Energy, Elsevier, vol. 113(C), pages 1601-1613.
    9. Hofierka, Jaroslav & Kaňuk, Ján, 2009. "Assessment of photovoltaic potential in urban areas using open-source solar radiation tools," Renewable Energy, Elsevier, vol. 34(10), pages 2206-2214.
    10. Strzalka, Aneta & Alam, Nazmul & Duminil, Eric & Coors, Volker & Eicker, Ursula, 2012. "Large scale integration of photovoltaics in cities," Applied Energy, Elsevier, vol. 93(C), pages 413-421.
    11. Peng, Jinqing & Lu, Lin, 2013. "Investigation on the development potential of rooftop PV system in Hong Kong and its environmental benefits," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 149-162.
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    2. Aslani, Mohammad & Seipel, Stefan, 2022. "Automatic identification of utilizable rooftop areas in digital surface models for photovoltaics potential assessment," Applied Energy, Elsevier, vol. 306(PA).
    3. Thebault, Martin & Desthieux, Gilles & Castello, Roberto & Berrah, Lamia, 2022. "Large-scale evaluation of the suitability of buildings for photovoltaic integration: Case study in Greater Geneva," Applied Energy, Elsevier, vol. 316(C).
    4. Ren, Haoshan & Xu, Chengliang & Ma, Zhenjun & Sun, Yongjun, 2022. "A novel 3D-geographic information system and deep learning integrated approach for high-accuracy building rooftop solar energy potential characterization of high-density cities," Applied Energy, Elsevier, vol. 306(PA).
    5. Joel Alpízar-Castillo & Laura Ramirez-Elizondo & Pavol Bauer, 2022. "Assessing the Role of Energy Storage in Multiple Energy Carriers toward Providing Ancillary Services: A Review," Energies, MDPI, vol. 16(1), pages 1-31, December.
    6. Gassar, Abdo Abdullah Ahmed & Cha, Seung Hyun, 2021. "Review of geographic information systems-based rooftop solar photovoltaic potential estimation approaches at urban scales," Applied Energy, Elsevier, vol. 291(C).
    7. Xingyu Zhu & Yuexia Lv & Jinpeng Bi & Mingkun Jiang & Yancai Su & Tingting Du, 2023. "Techno-Economic Analysis of Rooftop Photovoltaic System under Different Scenarios in China University Campuses," Energies, MDPI, vol. 16(7), pages 1-18, March.

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