Imperial College London
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DrMingyangSun

Faculty of Engineering, Department of Electrical and Electronic Engineering

Honorary Lecturer
 
 
 
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Contact

 

mingyang.sun11

 
 
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Location

 

Electrical EngineeringSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@inproceedings{Sun:2016,
author = {Sun, M and Konstantelos, I and Tindemans, S and Strbac, G},
title = {Evaluating composite approaches to modelling high-dimensional stochastic variables in power systems},
url = {http://hdl.handle.net/10044/1/30488},
year = {2016}
}
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RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - The  large-scale  integration  of  intermittent  energy  sources,  the  introduction  of  shiftable  load  elements  and  the  growing  interconnection  that  characterizes  electricity  systems  worldwide  have  led  to  a  significant  increase  of  operational  uncertainty.  The  construction  of  suitable  statistical  models  is  a  fundamental   step   towards   building   Monte   Carlo   analysis   frameworks to be used for exploring the uncertainty state-space and     supporting     real-time     decision-making.     The     main     contribution  of  the  present  paper  is  the  development  of  novel  composite   modelling   approaches   that   employ   dimensionality   reduction, clustering and parametric modelling techniques with a particular focus on the use of pair copula construction schemes. Large   power   system   datasets   are   modelled   using   different   combinations  of  the  aforementioned  techniques,  and  detailed  comparisons  are  drawn  on  the  basis  of  Kolmogorov-Smirnov  tests,   multivariate   two-sample   energy   tests   and   visual   data   comparisons. The proposed methods are shown to be superior to alternative high-dimensional modelling approaches.
AU  - Sun,M
AU  - Konstantelos,I
AU  - Tindemans,S
AU  - Strbac,G
PY  - 2016///
TI  - Evaluating composite approaches to modelling high-dimensional stochastic variables in power systems
UR  - http://hdl.handle.net/10044/1/30488
ER  -
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