IDEAS home Printed from https://ideas.repec.org/r/eee/appene/v250y2019icp283-291.html
   My bibliography  Save this item

Urban solar utilization potential mapping via deep learning technology: A case study of Wuhan, China

Citations

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


Cited by:

  1. Zhenqiang Han & Weidong Zhou & Aimin Sha & Liqun Hu & Runjie Wei, 2023. "Assessing the Photovoltaic Power Generation Potential of Highway Slopes," Sustainability, MDPI, vol. 15(16), pages 1-26, August.
  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. Dalibor Dobrilovic & Jasmina Pekez & Eleonora Desnica & Ljiljana Radovanovic & Ivan Palinkas & Milica Mazalica & Luka Djordjević & Sinisa Mihajlovic, 2023. "Data Acquisition for Estimating Energy-Efficient Solar-Powered Sensor Node Performance for Usage in Industrial IoT," Sustainability, MDPI, vol. 15(9), pages 1-22, April.
  4. Liu, Guanjun & Qin, Hui & Shen, Qin & Lyv, Hao & Qu, Yuhua & Fu, Jialong & Liu, Yongqi & Zhou, Jianzhong, 2021. "Probabilistic spatiotemporal solar irradiation forecasting using deep ensembles convolutional shared weight long short-term memory network," Applied Energy, Elsevier, vol. 300(C).
  5. Özdemir, Samed & Yavuzdoğan, Ahmet & Bilgilioğlu, Burhan Baha & Akbulut, Zeynep, 2023. "SPAN: An open-source plugin for photovoltaic potential estimation of individual roof segments using point cloud data," Renewable Energy, Elsevier, vol. 216(C).
  6. Wenbo Cui & Xiangang Peng & Jinhao Yang & Haoliang Yuan & Loi Lei Lai, 2023. "Evaluation of Rooftop Photovoltaic Power Generation Potential Based on Deep Learning and High-Definition Map Image," Energies, MDPI, vol. 16(18), pages 1-17, September.
  7. Ren, Simiao & Hu, Wayne & Bradbury, Kyle & Harrison-Atlas, Dylan & Malaguzzi Valeri, Laura & Murray, Brian & Malof, Jordan M., 2022. "Automated Extraction of Energy Systems Information from Remotely Sensed Data: A Review and Analysis," Applied Energy, Elsevier, vol. 326(C).
  8. Zhong, Teng & Zhang, Kai & Chen, Min & Wang, Yijie & Zhu, Rui & Zhang, Zhixin & Zhou, Zixuan & Qian, Zhen & Lv, Guonian & Yan, Jinyue, 2021. "Assessment of solar photovoltaic potentials on urban noise barriers using street-view imagery," Renewable Energy, Elsevier, vol. 168(C), pages 181-194.
  9. Mao, Hongzhi & Chen, Xie & Luo, Yongqiang & Deng, Jie & Tian, Zhiyong & Yu, Jinghua & Xiao, Yimin & Fan, Jianhua, 2023. "Advances and prospects on estimating solar photovoltaic installation capacity and potential based on satellite and aerial images," Renewable and Sustainable Energy Reviews, Elsevier, vol. 179(C).
  10. Zhong, Teng & Zhang, Zhixin & Chen, Min & Zhang, Kai & Zhou, Zixuan & Zhu, Rui & Wang, Yijie & Lü, Guonian & Yan, Jinyue, 2021. "A city-scale estimation of rooftop solar photovoltaic potential based on deep learning," Applied Energy, Elsevier, vol. 298(C).
  11. Arias-Rosales, Andrés & LeDuc, Philip R., 2020. "Modeling the transmittance of anisotropic diffuse radiation towards estimating energy losses in solar panel coverings," Applied Energy, Elsevier, vol. 268(C).
  12. Jiang, Hou & Zhang, Xiaotong & Yao, Ling & Lu, Ning & Qin, Jun & Liu, Tang & Zhou, Chenghu, 2023. "High-resolution analysis of rooftop photovoltaic potential based on hourly generation simulations and load profiles," Applied Energy, Elsevier, vol. 348(C).
  13. Mendis, Thushini & Huang, Zhaojian & Xu, Shen & Zhang, Weirong, 2020. "Economic potential analysis of photovoltaic integrated shading strategies on commercial building facades in urban blocks: A case study of Colombo, Sri Lanka," Energy, Elsevier, vol. 194(C).
  14. Islam, Md. Rabiul & Aziz, Md. Tareq & Alauddin, Mohammed & Kader, Zarjes & Islam, Md. Rakibul, 2024. "Site suitability assessment for solar power plants in Bangladesh: A GIS-based analytical hierarchy process (AHP) and multi-criteria decision analysis (MCDA) approach," Renewable Energy, Elsevier, vol. 220(C).
  15. Tian, Shuai & Yang, Guoqiang & Du, Sihong & Zhuang, Dian & Zhu, Ke & Zhou, Xin & Jin, Xing & Ye, Yu & Li, Peixian & Shi, Xing, 2024. "An innovative method for evaluating the urban roof photovoltaic potential based on open-source satellite images," Renewable Energy, Elsevier, vol. 224(C).
  16. Liu, Zhengguang & Guo, Zhiling & Song, Chenchen & Du, Ying & Chen, Qi & Chen, Yuntian & Zhang, Haoran, 2023. "Business model comparison of slum-based PV to realize low-cost and flexible power generation in city-level," Applied Energy, Elsevier, vol. 344(C).
  17. 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.
  18. Shiyu Jin & Hui Zhang & Xiaoxi Huang & Junle Yan & Haibo Yu & Ningcheng Gao & Xueying Jia & Zhengwei Wang, 2023. "Solar Energy Utilization Potential in Urban Residential Blocks: A Case Study of Wuhan, China," Sustainability, MDPI, vol. 15(22), pages 1-34, November.
  19. 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).
  20. Zhang, Yuhu & Ren, Jing & Pu, Yanru & Wang, Peng, 2020. "Solar energy potential assessment: A framework to integrate geographic, technological, and economic indices for a potential analysis," Renewable Energy, Elsevier, vol. 149(C), pages 577-586.
  21. Zhang, Chen & Li, Zhixin & Jiang, Haihua & Luo, Yongqiang & Xu, Shen, 2021. "Deep learning method for evaluating photovoltaic potential of urban land-use: A case study of Wuhan, China," Applied Energy, Elsevier, vol. 283(C).
  22. 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).
  23. Babak Ranjgar & Alessandro Niccolai, 2023. "Large-Scale Rooftop Solar Photovoltaic Power Production Potential Assessment: A Case Study for Tehran Metropolitan Area, Iran," Energies, MDPI, vol. 16(20), pages 1-14, October.
  24. Jiang, Mingkun & Qi, Lingfei & Yu, Ziyi & Wu, Dadi & Si, Pengfei & Li, Peiran & Wei, Wendong & Yu, Xinhai & Yan, Jinyue, 2021. "National level assessment of using existing airport infrastructures for photovoltaic deployment," Applied Energy, Elsevier, vol. 298(C).
  25. Wei, Tianxi & Zhang, Yi & Zhang, Yuhang & Miao, Rui & Kang, Jian & Qi, He, 2024. "City-scale roof-top photovoltaic deployment planning," Applied Energy, Elsevier, vol. 368(C).
  26. Zhixin Li & Chen Zhang & Zejun Yu & Hong Zhang & Haihua Jiang, 2023. "Deep Learning Method for Evaluating Photovoltaic Potential of Rural Land Use Types," Sustainability, MDPI, vol. 15(14), pages 1-17, July.
  27. Žalik, Mitja & Mongus, Domen & Lukač, Niko, 2024. "High-resolution spatiotemporal assessment of solar potential from remote sensing data using deep learning," Renewable Energy, Elsevier, vol. 222(C).
  28. 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).
  29. Sánchez-Aparicio, M. & Martín-Jiménez, J. & Del Pozo, S. & González-González, E. & Lagüela, S., 2021. "Ener3DMap-SolarWeb roofs: A geospatial web-based platform to compute photovoltaic potential," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
  30. Luka Djordjević & Jasmina Pekez & Borivoj Novaković & Mihalj Bakator & Mića Djurdjev & Dragan Ćoćkalo & Saša Jovanović, 2023. "Increasing Energy Efficiency of Buildings in Serbia—A Case of an Urban Neighborhood," Sustainability, MDPI, vol. 15(7), pages 1-20, April.
  31. Sun, Tao & Shan, Ming & Rong, Xing & Yang, Xudong, 2022. "Estimating the spatial distribution of solar photovoltaic power generation potential on different types of rural rooftops using a deep learning network applied to satellite images," Applied Energy, Elsevier, vol. 315(C).
  32. 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.