首页    期刊浏览 2024年11月28日 星期四
登录注册

文章基本信息

  • 标题:The Day-ahead Energy Market Forecasting in Russian Federation: a Case Study of Siberia
  • 本地全文:下载
  • 作者:Alexander Filatov ; Evgeny Lisin ; Evgenya Smirnova
  • 期刊名称:Montenegrin Journal of Economics
  • 印刷版ISSN:1800-5845
  • 电子版ISSN:1800-6698
  • 出版年度:2015
  • 卷号:11
  • 期号:2
  • 页码:125-135
  • DOI:10.14254/1800-5845.2015/11-2/8
  • 出版社:Economic Laboratory for Transition Research Podgorica
  • 摘要:Recent reforms in Russian power industry and the wholesale electric power and capacity market construction put energy companies into the new competitive conditions. Due to these reforms, the issues of price and quantity forecasting at the day- ahead market (DAM) gain special importance. Particularly, the extrapolated values of the prices and quantities at DAM are necessary for the regulator, and also for energy companies to work out the best market strategy. The current Russian wholesale electricity market represents a fundamentally new model of the electric power industry that functions on a competitive basis. The key role in the structure of the wholesale energy trading sector is played by the day-ahead electricity sector that provides up to the 80% of total electricity sales in the country. As a result of the auction clearing, the market price for all points in the supply of electricity is formed and the volume of the market is determined. There is also a need for forecasting the equilibrium price and quantity of elec- tricity sales, which largely determine the strategies of generation companies from the perspective of the use of free electric pow- ers. This paper proposes a method of construction of medium and long-term forecasting of the DAM's main characteristics. Our results that stem from the mathematical model and statisti- cal data reveal the most significant factors and quantified their nature, their extent as well as their effect on the energy market of Siberia.
  • 关键词:Energy; ; Wholesale electricity market; ; Power; ; Day-ahead energy market; ; Marginal pricing; ; Generator strategy ; Time series; ; Russian Federation
国家哲学社会科学文献中心版权所有