IDEAS home Printed from https://ideas.repec.org/a/gai/ruserr/r2380.html
   My bibliography  Save this article

Экономическая Целесообразность Развития Солнечной Энергетики В России

Author

Listed:
  • Vera A. Barinova

    (Russian Presidential Academy of National Economy and Public Administration; Gaidar Institute for Economic Policy)

  • Kseniya V. Demidova

    (Russian Presidential Academy of National Economy and Public Administration)

Abstract

В статье проведена оценка экономической целесообразности развития солнечной энергетики в городах России с населением свыше 1 млн человек, а также предложено несколько бизнес-моделей, за счет которых солнечная энергетика может быть внедрена в городских условиях. В статье используются метод оценки приведенной стоимости электроэнергии (Levelized Cost of Energy – LCOE) и метод сравнительного анализа, представлен обзор международного опыта применения солнечной энергетики в городах. Проводится анализ экономических и социальных преимуществ развития городских солнечных электростанций. Согласно результатам исследования, производство солнечной электроэнергии на крышах всех городов-миллионников России может быть экономически выгодным для потребителей электроэнергии на розничных рынках уже сейчас. При этом развитие солнечной энергетики также будет способствовать решению проблемы роста пиковых нагрузок во время волн жары, снижению потребности в кондиционировании зданий, решению проблемы энергодефицита, сокращению выбросов парниковых газов, развитию производства отечественного высокотехнологичного оборудования, повышению привлекательности российских городов. Статья подготовлена в рамках выполнения научно-исследовательской работы государственного задания РАНХиГС при Президенте Российской Федерации.

Suggested Citation

  • Vera A. Barinova & Kseniya V. Demidova, 2023. "Экономическая Целесообразность Развития Солнечной Энергетики В России," Russian Economic Development (in Russian), Gaidar Institute for Economic Policy, issue 10, pages 18-31, October.
  • Handle: RePEc:gai:ruserr:r2380
    as

    Download full text from publisher

    File URL: http://www.iep.ru/files/RePEc/gai/ruserr/r2380.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Nieto-Díaz, Balder A. & Crossland, Andrew F. & Groves, Christopher, 2021. "A levelized cost of energy approach to select and optimise emerging PV technologies: The relative impact of degradation, cost and initial efficiency," Applied Energy, Elsevier, vol. 299(C).
    2. 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).
    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. Tian, Xinyi & Wang, Jun & Yuan, Shuang & Ji, Jie & Ke, Wei & Wang, Chuyao, 2023. "Investigation on the electrical performance of a curved PV roof integrated with CIGS cells for traditional Chinese houses," Energy, Elsevier, vol. 263(PC).
    2. Xinghua Wang & Fucheng Zhong & Yilin Xu & Xixian Liu & Zezhong Li & Jianan Liu & Zhuoli Zhao, 2023. "Extraction and Joint Method of PV–Load Typical Scenes Considering Temporal and Spatial Distribution Characteristics," Energies, MDPI, vol. 16(18), pages 1-19, September.
    3. Zhixin Zhang & Min Chen & Teng Zhong & Rui Zhu & Zhen Qian & Fan Zhang & Yue Yang & Kai Zhang & Paolo Santi & Kaicun Wang & Yingxia Pu & Lixin Tian & Guonian Lü & Jinyue Yan, 2023. "Carbon mitigation potential afforded by rooftop photovoltaic in China," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    4. 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).
    5. 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).
    6. Yun, Min Ju & Sim, Yeon Hyang & Lee, Dong Yoon & Cha, Seung I., 2022. "Reliable Lego®-style assembled stretchable photovoltaic module for 3-dimensional curved surface application," Applied Energy, Elsevier, vol. 323(C).
    7. Chavid Leewiraphan & Nipon Ketjoy & Prapita Thanarak, 2023. "Business Perspectives of Distributed System Operators for Solar Rooftop-as-a-Service," Energies, MDPI, vol. 17(1), pages 1-15, December.
    8. 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).
    9. Zakariya M. Dalala & Saba Z. AlAqbani & Dima R. Khirfan & Layth H. Alhamad & Mohammad Al-Addous & Nesrine Barbana, 2022. "Analysis and Design Methodology of a Novel Integration Topology of Storageless Off-Grid PV Systems," Energies, MDPI, vol. 15(4), pages 1-18, February.
    10. 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).
    11. Yilin Xu & Jie He & Yang Liu & Zilu Li & Weicong Cai & Xiangang Peng, 2023. "Evaluation Method for Hosting Capacity of Rooftop Photovoltaic Considering Photovoltaic Potential in Distribution System," Energies, MDPI, vol. 16(22), pages 1-23, November.
    12. 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).
    13. Hou Jiang & Ning Lu & Xuecheng Wang, 2023. "Assessing Carbon Reduction Potential of Rooftop PV in China through Remote Sensing Data-Driven Simulations," Sustainability, MDPI, vol. 15(4), pages 1-16, February.
    14. Chen, Qi & Li, Xinyuan & Zhang, Zhengjia & Zhou, Chao & Guo, Zhiling & Liu, Zhengguang & Zhang, Haoran, 2023. "Remote sensing of photovoltaic scenarios: Techniques, applications and future directions," Applied Energy, Elsevier, vol. 333(C).
    15. 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.
    16. Zheng, Jianan & Liu, Wenjun & Cui, Ting & Wang, Hanchun & Chen, Fangcai & Gao, Yang & Fan, Liulu & Ali Abaker Omer, Altyeb & Ingenhoff, Jan & Zhang, Xinyu & Liu, Wen, 2023. "A novel domino-like snow removal system for roof PV arrays: Feasibility, performance, and economic benefits," Applied Energy, Elsevier, vol. 333(C).
    17. 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).
    18. Sun, Yanwei & Li, Ying & Wang, Run & Ma, Renfeng, 2022. "Measuring dynamics of solar energy resource quality: Methodology and policy implications for reducing regional energy inequality," Renewable Energy, Elsevier, vol. 197(C), pages 138-150.
    19. Li, Yue & Luo, Hao & Cai, Hua, 2023. "Photovoltaic-battery powered bike share stations are not necessarily energy self-sufficient," Applied Energy, Elsevier, vol. 348(C).
    20. Zhu, Rui & Kondor, Dániel & Cheng, Cheng & Zhang, Xiaohu & Santi, Paolo & Wong, Man Sing & Ratti, Carlo, 2022. "Solar photovoltaic generation for charging shared electric scooters," Applied Energy, Elsevier, vol. 313(C).

    More about this item

    Keywords

    выбросы парниковых газов; возобновляемая энергетика; солнечная энергетика; солнечные электростанции; приведенная стоимость электроэнергии (LCOE); сетевой паритет;
    All these keywords.

    JEL classification:

    • O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
    • R1 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics
    • M2 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics

    Statistics

    Access and download statistics

    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:gai:ruserr:r2380. 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: Olga Beloborodova (email available below). General contact details of provider: https://edirc.repec.org/data/gaidaru.html .

    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.