| Issue |
Renew. Energy Environ. Sustain.
Volume 1, 2016
|
|
|---|---|---|
| Article Number | 41 | |
| Number of page(s) | 5 | |
| DOI | https://doi.org/10.1051/rees/2016045 | |
| Published online | 08 September 2016 | |
Research Article
Demand and residual demand modelling using quantile regression
1
Department of Industrial Economics and Technology Management, Norwegian University of Science and Technology,
7491
Trondheim, Norway
2
Charles University, CERGE-EI (Center for Economic Research and Graduate Education – Economics Institute),
Prague, Czech Republic
⁎ e-mail: peter.molnar@iot.ntnu.no
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.
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