IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i7p1684-d1368639.html
   My bibliography  Save this article

Analysis of Solar Radiation Differences for High-Voltage Transmission Lines on Micro-Terrain Areas

Author

Listed:
  • Hualong Zheng

    (Xuefeng Mountain Energy Equipment Safety National Observation and Research Station, Chongqing University, Chongqing 400044, China)

  • Yizhang Wang

    (Xuefeng Mountain Energy Equipment Safety National Observation and Research Station, Chongqing University, Chongqing 400044, China)

  • Dexin Xie

    (Chongqing Electric Power Design Institute Co., Ltd., Chongqing 404100, China)

  • Zhijin Zhang

    (Xuefeng Mountain Energy Equipment Safety National Observation and Research Station, Chongqing University, Chongqing 400044, China)

  • Xingliang Jiang

    (Xuefeng Mountain Energy Equipment Safety National Observation and Research Station, Chongqing University, Chongqing 400044, China)

Abstract

The stable operation of high-voltage transmission lines is significantly affected by atmospheric icing. Research on the physical processes of icing and de-icing of transmission lines in micro-terrain, as well as the factors affecting them, is a crucial theoretical foundation for enhancing current icing prediction capabilities and guiding the planning of transmission lines in mountainous areas. The difficulty lies in the fact that, unlike the calculation of surface radiation, the amount of radiation received by the lines is affected by a combination of terrain, environmental shading, and the orientation of the lines. Therefore, this work initially establishes a method for calculating the total amount of radiant heat received per unit length of the line throughout the day at various heights from the ground, based on the angle of solar incidence and the three-dimensional spatial position of the lines. Furthermore, a method of mapping the regional heat radiation by gridding the direction of the lines was proposed, providing the daily heat radiation and equivalent Joule heat. The proposed mapping method supports anti-icing planning for high-voltage transmission lines in micro-terrain areas.

Suggested Citation

  • Hualong Zheng & Yizhang Wang & Dexin Xie & Zhijin Zhang & Xingliang Jiang, 2024. "Analysis of Solar Radiation Differences for High-Voltage Transmission Lines on Micro-Terrain Areas," Energies, MDPI, vol. 17(7), pages 1-16, April.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:7:p:1684-:d:1368639
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/7/1684/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/17/7/1684/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Akarslan, Emre & Hocaoglu, Fatih Onur & Edizkan, Rifat, 2018. "Novel short term solar irradiance forecasting models," Renewable Energy, Elsevier, vol. 123(C), pages 58-66.
    2. Jiazheng Lu & Jun Guo & Jianping Hu & Li Yang & Tao Feng, 2017. "Analysis of ice disasters on ultra-high-voltage direct-current transmission lines," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 86(1), pages 203-217, March.
    3. Hong, Taehoon & Lee, Minhyun & Koo, Choongwan & Jeong, Kwangbok & Kim, Jimin, 2017. "Development of a method for estimating the rooftop solar photovoltaic (PV) potential by analyzing the available rooftop area using Hillshade analysis," Applied Energy, Elsevier, vol. 194(C), pages 320-332.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alhamwi, Alaa & Medjroubi, Wided & Vogt, Thomas & Agert, Carsten, 2018. "Modelling urban energy requirements using open source data and models," Applied Energy, Elsevier, vol. 231(C), pages 1100-1108.
    2. Hossein Heirani & Naser Bagheri Moghaddam & Sina Labbafi & Seyedali Sina, 2022. "A Business Model for Developing Distributed Photovoltaic Systems in Iran," Sustainability, MDPI, vol. 14(18), pages 1-21, September.
    3. Moon-Hyun Kim & Tae-Hyoung Tommy Gim, 2021. "Spatial Characteristics of the Diffusion of Residential Solar Photovoltaics in Urban Areas: A Case of Seoul, South Korea," IJERPH, MDPI, vol. 18(2), pages 1-16, January.
    4. Kumar Ganti, Praful & Naik, Hrushikesh & Kanungo Barada, Mohanty, 2022. "Environmental impact analysis and enhancement of factors affecting the photovoltaic (PV) energy utilization in mining industry by sparrow search optimization based gradient boosting decision tree appr," Energy, Elsevier, vol. 244(PA).
    5. Kong, Minjin & Ji, Changyoon & Hong, Taehoon & Kang, Hyuna, 2022. "Impact of the use of recycled materials on the energy conservation and energy transition of buildings using life cycle assessment: A case study in South Korea," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
    6. Reikard, Gordon & Hansen, Clifford, 2019. "Forecasting solar irradiance at short horizons: Frequency and time domain models," Renewable Energy, Elsevier, vol. 135(C), pages 1270-1290.
    7. Bódis, Katalin & Kougias, Ioannis & Jäger-Waldau, Arnulf & Taylor, Nigel & Szabó, Sándor, 2019. "A high-resolution geospatial assessment of the rooftop solar photovoltaic potential in the European Union," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    8. Jeongyoon Oh & Taehoon Hong & Hakpyeong Kim & Jongbaek An & Kwangbok Jeong & Choongwan Koo, 2017. "Advanced Strategies for Net-Zero Energy Building: Focused on the Early Phase and Usage Phase of a Building’s Life Cycle," Sustainability, MDPI, vol. 9(12), pages 1-52, December.
    9. Jiang, Wei & Zhang, Shuo & Wang, Teng & Zhang, Yufei & Sha, Aimin & Xiao, Jingjing & Yuan, Dongdong, 2024. "Evaluation method for the availability of solar energy resources in road areas before route corridor planning," Applied Energy, Elsevier, vol. 356(C).
    10. 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).
    11. Heydari, Azim & Astiaso Garcia, Davide & Keynia, Farshid & Bisegna, Fabio & De Santoli, Livio, 2019. "A novel composite neural network based method for wind and solar power forecasting in microgrids," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    12. 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).
    13. 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).
    14. Tao, Linwei & Hayashi, Kiichiro & Shiraki, Hiroto & Huang, Xiaoxun & Dem, Phub, 2024. "Exploration of determinants underlying regional disparity in rooftop photovoltaic adoption: A case study in Nagoya, Japan," Applied Energy, Elsevier, vol. 367(C).
    15. 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.
    16. Buffat, René & Grassi, Stefano & Raubal, Martin, 2018. "A scalable method for estimating rooftop solar irradiation potential over large regions," Applied Energy, Elsevier, vol. 216(C), pages 389-401.
    17. Wang, Yingli & Duan, Jialong & Zhao, Yuanyuan & Yuan, Haiwen & He, Benlin & Tang, Qunwei, 2018. "Film-type rain energy converters from conductive polymer/PtCo hybrids," Applied Energy, Elsevier, vol. 218(C), pages 317-324.
    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. Stavros Vigkos & Panagiotis G. Kosmopoulos, 2024. "Photovoltaics Energy Potential in the Largest Greek Cities: Atmospheric and Urban Fabric Effects, Climatic Trends Influences and Socio-Economic Benefits," Energies, MDPI, vol. 17(15), pages 1-32, August.
    20. Diana Bernasconi & Giorgio Guariso, 2021. "Rooftop PV: Potential and Impacts in a Complex Territory," Energies, MDPI, vol. 14(12), pages 1-17, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:17:y:2024:i:7:p:1684-:d:1368639. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.