S. Zachary
Estimation of Joint Distribution of Demand and Available Renewables for Generation Adequacy Assessment
Zachary, S.; Dent, C.J.
Authors
C.J. Dent
Abstract
In recent years there has been a resurgence of interest in generation adequacy risk assessment, due to the need to include variable generation renewables within such calculations. This paper will describe new statistical approaches to estimating the joint distribution of demand and available VG capacity; this is required for the LOLE calculations used in many statutory adequacy studies, for example those of GB and PJM. The most popular estimation technique in the VG-integration literature is ‘hind- cast’, in which the historic joint distribution of demand and available VG is used as a predictive distribution. Through the use of bootstrap statistical analysis, this paper will show that due to extreme sparsity of data on times of high demand and low VG, hindcast results can suffer from sampling uncertainty to the extent that they have little practical meaning. An alternative estimation approach, in which a marginal distribution of available VG is rescaled according to demand level, is thus proposed. This reduces sampling uncertainty at the expense of the additional model structure assumption, and further provides a means of assessing the sensitivity of model out- puts to the VG-demand relationship by varying the function of demand by which the marginal VG distribution is rescaled.
Citation
Zachary, S., & Dent, C. (2014). Estimation of Joint Distribution of Demand and Available Renewables for Generation Adequacy Assessment. IET Generation, Transmission and Distribution, 1-16
Journal Article Type | Article |
---|---|
Publication Date | Oct 1, 2014 |
Deposit Date | Jun 26, 2014 |
Publicly Available Date | Oct 30, 2014 |
Journal | IET Generation, Transmission and Distribution |
Print ISSN | 1751-8687 |
Electronic ISSN | 1751-8695 |
Publisher | Institution of Engineering and Technology (IET) |
Peer Reviewed | Not Peer Reviewed |
Pages | 1-16 |
Keywords | Power system planning, Power system reliability, Risk analysis, Wind energy. |
Files
Submitted Journal Article
(464 Kb)
PDF
Downloadable Citations
About Durham Research Online (DRO)
Administrator e-mail: dro.admin@durham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search