Renew. Energy Environ. Sustain.
Volume 1, 2016
|Number of page(s)
|08 September 2016
Demand and residual demand modelling using quantile regression
Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology,
2 Charles University, CERGE-EI (Center for Economic Research and Graduate Education – Economics Institute), Prague, Czech Republic
⁎ e-mail: firstname.lastname@example.org
Residual demand, the difference between demand and solar and wind production, is an important variable in predicting the future price and storage requirements. However, little is known about predicting the residual demand itself as well as its quantiles. Therefore, we model both demand and residual demand using both ordinary and quantile regression and compare the results for the hourly electricity consumption in Germany. We find that the residual demand is less predictable than demand. The effect is visible for all hours, and is higher for the lower than the upper quantiles.
© L.P.C. Do et al., published by EDP Sciences, 2016
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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.