IDEAS home Printed from https://ideas.repec.org/r/eee/appene/v217y2018icp189-211.html
   My bibliography  Save this item

Large-scale rooftop solar photovoltaic technical potential estimation using Random Forests

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Luka Martin Tomažič & Niko Lukač & Gorazd Štumberger, 2021. "A New Regulatory Approach for PV-Based Self-Supply, Validated by a Techno-Economic Assessment: A Case Study for Slovenia," Sustainability, MDPI, vol. 13(3), pages 1-14, January.
  2. Elham Fakhraian & Marc Alier & Francesc Valls Dalmau & Alireza Nameni & Maria José Casañ Guerrero, 2021. "The Urban Rooftop Photovoltaic Potential Determination," Sustainability, MDPI, vol. 13(13), pages 1-18, July.
  3. Ding, Feng & Yang, Jianping & Zhou, Zan, 2023. "Economic profits and carbon reduction potential of photovoltaic power generation for China's high-speed railway infrastructure," Renewable and Sustainable Energy Reviews, Elsevier, vol. 178(C).
  4. Honglu Zhu & Tingting Jiang & Yahui Sun & Shuang Sun, 2022. "A New Regional Distributed Photovoltaic Power Calculation Method Based on FCM-mRMR and nELM Model," Sustainability, MDPI, vol. 14(21), pages 1-20, October.
  5. Shaban R. S. Aldhshan & Khairul Nizam Abdul Maulud & Wan Shafrina Wan Mohd Jaafar & Othman A. Karim & Biswajeet Pradhan, 2021. "Energy Consumption and Spatial Assessment of Renewable Energy Penetration and Building Energy Efficiency in Malaysia: A Review," Sustainability, MDPI, vol. 13(16), pages 1-26, August.
  6. Cesar de Lima Nogueira, Silvio & Och, Stephan Hennings & Moura, Luis Mauro & Domingues, Eric & Coelho, Leandro dos Santos & Mariani, Viviana Cocco, 2023. "Prediction of the NOx and CO2 emissions from an experimental dual fuel engine using optimized random forest combined with feature engineering," Energy, Elsevier, vol. 280(C).
  7. Sredenšek, Klemen & Štumberger, Bojan & Hadžiselimović, Miralem & Mavsar, Primož & Seme, Sebastijan, 2022. "Physical, geographical, technical, and economic potential for the optimal configuration of photovoltaic systems using a digital surface model and optimization method," Energy, Elsevier, vol. 242(C).
  8. Mohajeri, N. & Gudmundsson, A. & Kunckler, T. & Upadhyay, G. & Assouline, D. & Kämpf, J.H & Scartezzini, J.L., 2019. "A solar-based sustainable urban design: The effects of city-scale street-canyon geometry on solar access in Geneva, Switzerland," Applied Energy, Elsevier, vol. 240(C), pages 173-190.
  9. Khan, Waqas & Walker, Shalika & Zeiler, Wim, 2022. "Improved solar photovoltaic energy generation forecast using deep learning-based ensemble stacking approach," Energy, Elsevier, vol. 240(C).
  10. Dupré la Tour, Marie-Alix, 2023. "Photovoltaic and wind energy potential in Europe – A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 179(C).
  11. Job Taminiau & John Byrne & Jongkyu Kim & Min‐Hwi Kim & Jeongseok Seo, 2022. "Inferential‐ and measurement‐based methods to estimate rooftop “solar city” potential in megacity Seoul, South Korea," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 11(5), September.
  12. Peng, Jieyang & Kimmig, Andreas & Niu, Zhibin & Wang, Jiahai & Liu, Xiufeng & Ovtcharova, Jivka, 2021. "A flexible potential-flow model based high resolution spatiotemporal energy demand forecasting framework," Applied Energy, Elsevier, vol. 299(C).
  13. Wu, Xianguo & Li, Xinyi & Qin, Yawei & Xu, Wen & Liu, Yang, 2023. "Intelligent multiobjective optimization design for NZEBs in China: Four climatic regions," Applied Energy, Elsevier, vol. 339(C).
  14. Suntiti Yoomak & Theerasak Patcharoen & Atthapol Ngaopitakkul, 2019. "Performance and Economic Evaluation of Solar Rooftop Systems in Different Regions of Thailand," Sustainability, MDPI, vol. 11(23), pages 1-20, November.
  15. Bienvenido-Huertas, David & Rubio-Bellido, Carlos & Solís-Guzmán, Jaime & Oliveira, Miguel José, 2020. "Experimental characterisation of the periodic thermal properties of walls using artificial intelligence," Energy, Elsevier, vol. 203(C).
  16. Mohajeri, Nahid & Perera, A.T.D. & Coccolo, Silvia & Mosca, Lucas & Le Guen, Morgane & Scartezzini, Jean-Louis, 2019. "Integrating urban form and distributed energy systems: Assessment of sustainable development scenarios for a Swiss village to 2050," Renewable Energy, Elsevier, vol. 143(C), pages 810-826.
  17. Yu-Sheng Kao & Kazumitsu Nawata & Chi-Yo Huang, 2019. "Systemic Functions Evaluation based Technological Innovation System for the Sustainability of IoT in the Manufacturing Industry," Sustainability, MDPI, vol. 11(8), pages 1-34, April.
  18. Sebastian Krapf & Nils Kemmerzell & Syed Khawaja Haseeb Uddin & Manuel Hack Vázquez & Fabian Netzler & Markus Lienkamp, 2021. "Towards Scalable Economic Photovoltaic Potential Analysis Using Aerial Images and Deep Learning," Energies, MDPI, vol. 14(13), pages 1-22, June.
  19. Liao, Xuan & Zhu, Rui & Wong, Man Sing & Heo, Joon & Chan, P.W. & Kwok, Coco Yin Tung, 2023. "Fast and accurate estimation of solar irradiation on building rooftops in Hong Kong: A machine learning-based parameterization approach," Renewable Energy, Elsevier, vol. 216(C).
  20. Enrique Fuster-Palop & Carlos Prades-Gil & Ximo Masip & J. D. Viana-Fons & Jorge Payá, 2023. "Techno-Economic Potential of Urban Photovoltaics: Comparison of Net Billing and Net Metering in a Mediterranean Municipality," Energies, MDPI, vol. 16(8), pages 1-32, April.
  21. Gupta, Rahul & Sossan, Fabrizio & Paolone, Mario, 2021. "Countrywide PV hosting capacity and energy storage requirements for distribution networks: The case of Switzerland," Applied Energy, Elsevier, vol. 281(C).
  22. Lukač, Niko & Špelič, Denis & Štumberger, Gorazd & Žalik, Borut, 2020. "Optimisation for large-scale photovoltaic arrays’ placement based on Light Detection And Ranging data," Applied Energy, Elsevier, vol. 263(C).
  23. Liu, Jiang & Wu, Qifeng & Lin, Zhipeng & Shi, Huijie & Wen, Shaoyang & Wu, Qiaoyu & Zhang, Junxue & Peng, Changhai, 2023. "A novel approach for assessing rooftop-and-facade solar photovoltaic potential in rural areas using three-dimensional (3D) building models constructed with GIS," Energy, Elsevier, vol. 282(C).
  24. Ren, Haoshan & Sun, Yongjun & Norman Tse, Chung Fai & Fan, Cheng, 2023. "Optimal packing and planning for large-scale distributed rooftop photovoltaic systems under complex shading effects and rooftop availabilities," Energy, Elsevier, vol. 274(C).
  25. Ali S. Alghamdi, 2021. "Performance Enhancement of Roof-Mounted Photovoltaic System: Artificial Neural Network Optimization of Ground Coverage Ratio," Energies, MDPI, vol. 14(6), pages 1-18, March.
  26. Ahmed Bilal Awan & Mohammed Alghassab & Muhammad Zubair & Abdul Rauf Bhatti & Muhammad Uzair & Ghulam Abbas, 2020. "Comparative Analysis of Ground-Mounted vs. Rooftop Photovoltaic Systems Optimized for Interrow Distance between Parallel Arrays," Energies, MDPI, vol. 13(14), pages 1-21, July.
  27. Moiz, Abdul & Kawasaki, Akiyuki & Koike, Toshio & Shrestha, Maheswor, 2018. "A systematic decision support tool for robust hydropower site selection in poorly gauged basins," Applied Energy, Elsevier, vol. 224(C), pages 309-321.
  28. Gomez-Exposito, Antonio & Arcos-Vargas, Angel & Gutierrez-Garcia, Francisco, 2020. "On the potential contribution of rooftop PV to a sustainable electricity mix: The case of Spain," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
  29. Nicholas Mukisa & Ramon Zamora & Tek Tjing Lie, 2022. "Energy Business Initiatives for Grid-Connected Solar Photovoltaic Systems: An Overview," Sustainability, MDPI, vol. 14(22), pages 1-26, November.
  30. Fuster-Palop, Enrique & Vargas-Salgado, Carlos & Ferri-Revert, Juan Carlos & Payá, Jorge, 2022. "Performance analysis and modelling of a 50 MW grid-connected photovoltaic plant in Spain after 12 years of operation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
  31. 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).
  32. Lee, Minhyun & Hong, Taehoon & Jeong, Kwangbok & Kim, Jimin, 2018. "A bottom-up approach for estimating the economic potential of the rooftop solar photovoltaic system considering the spatial and temporal diversity," Applied Energy, Elsevier, vol. 232(C), pages 640-656.
  33. David Bienvenido-Huertas & Jesús A. Pulido-Arcas & Carlos Rubio-Bellido & Alexis Pérez-Fargallo, 2021. "Prediction of Fuel Poverty Potential Risk Index Using Six Regression Algorithms: A Case-Study of Chilean Social Dwellings," Sustainability, MDPI, vol. 13(5), pages 1-30, February.
  34. 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).
  35. Lonergan, Katherine Emma & Sansavini, Giovanni, 2022. "Business structure of electricity distribution system operator and effect on solar photovoltaic uptake: An empirical case study for Switzerland," Energy Policy, Elsevier, vol. 160(C).
  36. Walch, Alina & Rüdisüli, Martin, 2023. "Strategic PV expansion and its impact on regional electricity self-sufficiency: Case study of Switzerland," Applied Energy, Elsevier, vol. 346(C).
  37. Walch, Alina & Castello, Roberto & Mohajeri, Nahid & Scartezzini, Jean-Louis, 2020. "Big data mining for the estimation of hourly rooftop photovoltaic potential and its uncertainty," Applied Energy, Elsevier, vol. 262(C).
  38. Primož Mavsar & Klemen Sredenšek & Bojan Štumberger & Miralem Hadžiselimović & Sebastijan Seme, 2019. "Simplified Method for Analyzing the Availability of Rooftop Photovoltaic Potential," Energies, MDPI, vol. 12(22), pages 1-17, November.
  39. 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).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.