Imperial College London
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MrAdriaanHilbers

Faculty of Natural Sciences, Department of Mathematics

Casual - Lib. Ass, Clerks & Gen. Admin Assistants
 
 
 
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Contact

 

a.hilbers17

 
 
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Location

 

667Huxley BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Hilbers:2021:10.1109/TPWRS.2020.3031187,
author = {Hilbers, AP and Brayshaw, DJ and Gandy, A},
doi = {10.1109/TPWRS.2020.3031187},
journal = {IEEE Transactions on Power Systems},
pages = {1771--1779},
title = {Efficient quantification of the impact of demand and weather uncertainty in power system models},
url = {http://dx.doi.org/10.1109/TPWRS.2020.3031187},
volume = {36},
year = {2021}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - This paper introduces a novel approach to quantify the effect of forwardpropagated demand and weather uncertainty on power system planning andoperation model outputs. Recent studies indicate that such samplinguncertainty, originating from demand and weather time series inputs, should notbe ignored. However, established uncertainty quantification approaches fail inthis context due to the computational resources and additional data requiredfor Monte Carlo-based analysis. The method introduced here quantifiesuncertainty on model outputs using a bootstrap scheme with shorter time seriesthan the original, enhancing computational efficiency and avoiding the need forany additional data. It both quantifies output uncertainty and determines thesample length required for desired confidence levels. Simulations performed ontwo generation and transmission expansion planning models and one unitcommitment and economic dispatch model illustrate the method's efficacy. A testis introduced allowing users to determine whether estimated uncertainty boundsare valid. The models, data and code applying the method are provided asopen-source software.
AU  - Hilbers,AP
AU  - Brayshaw,DJ
AU  - Gandy,A
DO  - 10.1109/TPWRS.2020.3031187
EP  - 1779
PY  - 2021///
SN  - 0885-8950
SP  - 1771
TI  - Efficient quantification of the impact of demand and weather uncertainty in power system models
T2  - IEEE Transactions on Power Systems
UR  - http://dx.doi.org/10.1109/TPWRS.2020.3031187
UR  - http://arxiv.org/abs/1912.10326v3
UR  - http://hdl.handle.net/10044/1/83272
VL  - 36
ER  -
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