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Estimating photovoltaic energy potential from a minimal set of randomly sampled data

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  • Bocca, Alberto
  • Bottaccioli, Lorenzo
  • Chiavazzo, Eliodoro
  • Fasano, Matteo
  • Macii, Alberto
  • Asinari, Pietro

Abstract

The remarkable rise of photovoltaics in the world over the past years testifies of the great improvement in the use of solar energy. Opportunities for further new PV installations are being sought, especially power plants in areas with as yet little exploited solar energy potential. In this paper, we describe a methodology for generating estimation models of PV electricity for installations in large regions where only a few scattered data or measurement stations are available. For validation only, application of this methodology was performed considering Italy, where estimations can be benchmarked using the Photovoltaic Geographical Information System (PVGIS) by the Joint Research Centre of the European Commission. The results show that the mean absolute errors were usually lower than 4%, compared to the PVGIS data, for about 90% of the estimates of PV electricity, and about 6% for the greatest mean error.

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  • Bocca, Alberto & Bottaccioli, Lorenzo & Chiavazzo, Eliodoro & Fasano, Matteo & Macii, Alberto & Asinari, Pietro, 2016. "Estimating photovoltaic energy potential from a minimal set of randomly sampled data," Renewable Energy, Elsevier, vol. 97(C), pages 457-467.
    • Handle: RePEc:eee:renene:v:97:y:2016:i:c:p:457-467
    DOI: 10.1016/j.renene.2016.06.001
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    1. Halder, P.K. & Paul, N. & Joardder, M.U.H. & Sarker, M., 2015. "Energy scarcity and potential of renewable energy in Bangladesh," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1636-1649.
    2. Kisi, Ozgur, 2014. "Modeling solar radiation of Mediterranean region in Turkey by using fuzzy genetic approach," Energy, Elsevier, vol. 64(C), pages 429-436.
    3. Linares-Rodriguez, Alvaro & Ruiz-Arias, José Antonio & Pozo-Vazquez, David & Tovar-Pescador, Joaquin, 2013. "An artificial neural network ensemble model for estimating global solar radiation from Meteosat satellite images," Energy, Elsevier, vol. 61(C), pages 636-645.
    4. Bocca, Alberto & Chiavazzo, Eliodoro & Macii, Alberto & Asinari, Pietro, 2015. "Solar energy potential assessment: An overview and a fast modeling approach with application to Italy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 291-296.
    5. Angelis-Dimakis, Athanasios & Biberacher, Markus & Dominguez, Javier & Fiorese, Giulia & Gadocha, Sabine & Gnansounou, Edgard & Guariso, Giorgio & Kartalidis, Avraam & Panichelli, Luis & Pinedo, Irene, 2011. "Methods and tools to evaluate the availability of renewable energy sources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(2), pages 1182-1200, February.
    6. Ondraczek, Janosch, 2014. "Are we there yet? Improving solar PV economics and power planning in developing countries: The case of Kenya," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 604-615.
    7. Olav H. Hohmeyer & Sönke Bohm, 2015. "Trends toward 100% renewable electricity supply in Germany and Europe: a paradigm shift in energy policies," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 4(1), pages 74-97, January.
    8. Dornan, M., 2011. "Solar-based rural electrification policy design: The Renewable Energy Service Company (RESCO) model in Fiji," Renewable Energy, Elsevier, vol. 36(2), pages 797-803.
    9. Cellura, M. & Di Gangi, A. & Longo, S. & Orioli, A., 2012. "Photovoltaic electricity scenario analysis in urban contests: An Italian case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(4), pages 2041-2052.
    10. Gyamfi, Samuel & Modjinou, Mawufemo & Djordjevic, Sinisa, 2015. "Improving electricity supply security in Ghana—The potential of renewable energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 1035-1045.
    11. Monforti, F. & Huld, T. & Bódis, K. & Vitali, L. & D'Isidoro, M. & Lacal-Arántegui, R., 2014. "Assessing complementarity of wind and solar resources for energy production in Italy. A Monte Carlo approach," Renewable Energy, Elsevier, vol. 63(C), pages 576-586.
    12. Najafi, G. & Ghobadian, B. & Mamat, R. & Yusaf, T. & Azmi, W.H., 2015. "Solar energy in Iran: Current state and outlook," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 931-942.
    13. Villicaña-Ortiz, Eunice & Gutiérrez-Trashorras, Antonio J. & Paredes-Sánchez, José Pablo & Xiberta-Bernat, Jorge, 2015. "Solar energy potential in the coastal zone of the Gulf of Mexico," Renewable Energy, Elsevier, vol. 81(C), pages 534-542.
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    4. 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).

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