Dmitriy O. Afanasyev, Elena A. Fedorova, Popov U. Viktor, 2015
Energy Economics 51, 215-226
Article on ScienceDirect
Preprint available for download on Munich Personal RePEc Archive
In this research we investigate the problems of dynamic relationship between electricity price and demand over different time scales for two largest price zones of Russian wholesale electricity market. We use multi-scale correlation analysis based on a modified method of time-dependent intrinsic correlation and the complete ensemble empirical mode decomposition with adaptive noise for this purpose. Three hypotheses on the type and strength of correlations in the short-, medium- and long-runs was tested. It is shown that price zones significantly differ in internal price-demand correlation structure over the comparable time scales, and not each of the theoretically formulated hypotheses is true for each of them. We can conclude that the answer to the question whether it is necessary to take into account the influence of demand-side on electricity spot prices over different time scales, is significantly dependent on the structure of electricity generation and consumption on the corresponding market.
electricity spot price; electricity demand; price-demand correlation; empirical mode decomposition; time-dependent intrinsic correlation; trend estimation
The authors are grateful to Evgenii V. Gilenko (PhD, St. Petersburg State University, Russia) for his fruitful comments on the text of paper and Igor Y. Lukasevich (PhD, Financial University under the Government of Russian Federation, Russia) for his support during this research. This paper also greatly benefited from the helpful and stimulating comments of two anonymous reviewers. Dmitriy O. Afanasyev would like to thank also his lovely wife Tatyana whose love and support has been invaluable. Responsibility for all errors and inaccuracies made by the authors rests solely on the part of the authors. Please read the disclaimer.
Source code used for article is available in the program library of adaptive data analysis ADAnalysis for Matlab™.