EDP Sciences logo
Web of Conferences logo
Search
Menu
All issues Volume 209 (2020) E3S Web Conf., 209 (2020) 06006 References
Open Access
Issue
E3S Web Conf.
Volume 209, 2020
ENERGY-21 – Sustainable Development & Smart Management
Article Number 06006
Number of page(s) 6
Section Session 5. Reliability of Fuel and Energy Supply to the Consumer, Energy Security
DOI https://doi.org/10.1051/e3sconf/202020906006
Published online 23 November 2020
  1. Kulenov N.S., Khasenov Zh.H., Energy forecasting, Alma-Ata: Science (1980) (In Russian). [Google Scholar]
  2. M. Makkonen, S. Patari, A. Jantunen, S. Viljainen, Competition in the European electricity markets – outcomes of a Delphi study. Energy Policy Vol. 44, pp. 431–440, (2012). [Google Scholar]
  3. System investigations of power engineering problems / L. S. Belyaev, B. G. Saneev, S. P. Filippov, and others; Ed. N. I. Voropay. Novosibirsk: Nauka. Siberian firm of the Russian Academy of Sciences (2000) (in Russian). [Google Scholar]
  4. Systems Research in Energy: Methodology and Results / Ed. A.A. Makarov and N.I. Voropay. M.: ERI RAS (2018) (in Russian). [Google Scholar]
  5. Shapot D.V. Lessons learned from developing managerial input-output models and elaborating the methodology behind them / D.V. Shapot, V.A. Malakhov, Moscow: The Publishing House of the Moscow Power Engineering Institute (2018) (in Russian). [Google Scholar]
  6. Andrianov D.L., Naumenko D.O., Starkova G.S., Analysis of methods and models of energy consumption at the macro level. Scientific and technical statements, SPbGPU, No. 4, Economic sciences. pp. 215-219 (2012) (in Russian). [Google Scholar]
  7. Bhattacharyya, Subhes C. and Timilsina, Govinda R., Energy Demand Models for Policy Formulation: A Comparative Study of Energy Demand Models (March 1, 2009). World Bank Policy Research Working Paper No. 4866, Available at SSRN: https://ssrn.com/abstract=1368072 Accessed on: (March. 10, 2020). [Google Scholar]
  8. D. Finon, and B. Lapillonne, Long term forecasting of energy demand in developing countries. European Journal of Operations Research, 13(1), pp. 12-28 (1983). [CrossRef] [Google Scholar]
  9. L. Suganthi, Samuel A. Anand, Energy models for demand forecasting – A review. Renewable and Sustainable Energy Reviews. 16, pp. 1223-1240 (2012) [CrossRef] [Google Scholar]
  10. Filippov S.P., Energy forecasting using a complex adaptive simulation models. Bulletin of RAS. Energy Series, No. 4, pp. 41–55 (2010) (In Russian). [Google Scholar]
  11. The National Energy Modeling System: An Overview 2018. – U.S. Energy Information Administration. – Washington, DC 20585. – 75 p . [Online]. Available: www.eia.gov, Accessed on: (March. 10, 2020). [Google Scholar]
  12. Long range Energy Alternatives Planning (LEAP) System [Online]. Available: https://openei.org/wiki/Long_range_Energy_Alterna tives_Planning_(LEAP)_System Accessed on: (March. 10, 2020). [Google Scholar]
  13. POLES: Prospective Outlook on Long-term Energy Systems. [Online]. Available: https://www.enerdata.net/solutions/poles-model.html. Accessed on: (March. 10, 2020). [Google Scholar]
  14. Makarov A.A., Model information system for researching the prospects of the energy complex of Russia (SCANER). Managing the development of large-scale systems, M.: Fizmatlit (2012) (In Russian). [Google Scholar]
  15. Energy Technology Perspectives 2017. [Online]. Available: https://www.iea.org, Accessed on: (July. 24, 2019). [Google Scholar]
  16. Ph. Grunewald, M. Diakonova, Flexibility, dynamism and diversity in energy supply and demand: A critical review. Energy Research & Social Science 38, pp. 58–66 (2018). [Google Scholar]
  17. Demand Response on retail energy markets in Russia may appear as soon as in 2019. [Online]. Available:https://www.np-ace.ru/news/power_industry/1026/, Accessed on: (March. 6, 2020) (in Russian). [Google Scholar]
  18. Kuleshov M., Rychkov S., The concept of operation of distributed energy resources aggregators within the United Power System of Russia. Aggregators for electricity demand management. Developed by System Operator of the United Power System JSC, [Online]. Available: https://www.so-ups.ru/fileadmin/files/company/markets/dr/docs/dr_ agregator_concept.pdf, Accessed on: (March. 6, 2020) (in Russian). [Google Scholar]
  19. Khokhlov A., Veselov F., Internet of Energy: how distributed energy will influence safety, electricity prices, and the environment. [Online]. Available: http://www.forbes.ru/biznes/351485-internet-energy-kak-raspredelennaya-energetika-povliyaet-na-bezopasnost-ceny-na, Accessed on: (March. 6, 2020) (in Russian). [Google Scholar]
  20. Distributed energy is undergoing rapid development in Russia. Yet is it heading in the right direction? [Online]. Available: http://www.ranepa.ru/sdsn/arkhiv-novostej/v-rossii-idet-bystroe-razvitie-raspredelennoj-energetiki-no-tuda-li-2, Accessed on: (February 2, 2018) (in Russian). [Google Scholar]
  21. Distributed generation: a consumer trend during the crisis of trust in large-scale energy systems?. [Online]. Available: https://www.eprussia.ru/epr/307-308/2223659.htm, Accessed on: (January 30, 2018) (in Russian). [Google Scholar]
  22. Andronov M., Distributed generation: the future of energy or a dead end?. Online Business Magazine ‘Invest Foresight’ [Online]. Available: https://www.if24.ru/budushhee-energetiki/, Accessed on: (February 28, 2018) (in Russian). [Google Scholar]
  23. Digitalization & Energy. International Energy Agency OECD/IEA (2017) [Online]. Available: www.iea.org [Google Scholar]
  24. P. O’Connor, M. Jacobs, Charging Smart. Drivers and Utilities Can Both Benefit from Well-Integrated Electric Vehicles and Clean Energy. (May 2017). [Online]. Available: https://www.ucsusa.org/sites/default/files/attach/2017/05/Charging-Smart-full-report.pdf, Accessed on: (February 6, 2020). [Google Scholar]
  25. IRENA, Innovation landscape brief: Electric-vehicle smart charging, International Renewable. Energy Agency, Abu Dhabi (2019). [Google Scholar]
  26. Daim T.U., Wang X., Cowan K., Shott T. Technology roadmap for smart electric vehicle-to-grid (V2G) of residential chargers // Daim et al. Journal of Innovation and Entrepreneurship (2016) 5:15 DOI 10.1186/s13731-016-0043-y [Google Scholar]
  27. R. Yusufov, E. Chalenko, A. Perdero, E. Krivosheya, Blockchain in the electric power industry: the landscape of projects and investors, Skolkovo (2019) [Online]. Available: https://energy.skolkovo.ru/downloads/documents/SEneC/Research/SKOLKOVO_EneC_RU_MINDSMITH_blockchain_investment_landscape2019.pdf , Accessed on: (February 3, 2020) (in Russian). [Google Scholar]
  28. Sorokin P., Blockchain in energy: a future or a reality? [Online]. Available: http://digitalsubstation.com/blog/2018/12/11/blokchejn-v-nbsp-energetike-budushhee-ili-nbsp-realnost/, Accessed on: (February 3, 2020) (in Russian). [Google Scholar]
  29. Blockchain technology in energy. [Online]. Available: https://aiz.com/documentation/articles/blockchain-energy/, Accessed on: (February 3, 2020) (in Russian). [Google Scholar]
  30. Kalinina A., Blockchain in energy: how to sell electricity in a new way [Online]. Available: https://decenter.org/ru/blokcheyn-v-energetike-kak- po-novomu-prodavat-elektrichestvo, Accessed on: (February 3, 2020) (in Russian). [Google Scholar]
  31. Blockchain: new opportunities for electricity producers and consumers? 2016. PwC., [Online]. Available:www.pwc.com/utilities , Accessed on: (February 3, 2020) (in Russian). [Google Scholar]
  32. Gal’perova E.V., Gal’perov V.I., Modeling the Active Consumer Behavior Based on the Agent Approach. 3rd Russian-Pacific Conference on Computer Technology and Applications (RPC-2018). DOI: 10.1109/RPC.2018.8482157 [Google Scholar]
  33. Galperova E.V., Galperov V.I., Loktionov V.I., Semantic Approach and Agent-based Modeling for Electricity Demand Forecasting in the Regional Market. Advances in Intelligent Systems Research, vol.158. pp.56-61 doi:10.2991/iwci-18.2018.10 [Google Scholar]
  34. Buildeconomic, [Online]. Available: http://www.buildeconomic.ru/hankips-56-1.html, Accessed on: (February 3, 2020) (in Russian). [Google Scholar]
  35. Russell S., Norvig P., Artificial Intelligence: A Modern Approach, 2nd ed: Transl. from English Moscow: Williams Publishing House (2006) (in Russian) [Google Scholar]
  36. Sidorenko V.N., Krasnoselsky A.V., Simulation modeling in science and business: approaches, tools and applications. Business Informatics. No.2 (08), pp. 52-57 (2008) (in Russian). [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.