DocumentCode :
648431
Title :
Toward scalable, parallel progressive hedging for stochastic unit commitment
Author :
Ryan, Sarah M. ; Wets, Roger J.-B ; Woodruff, David L. ; Silva-Monroy, Cesar ; Watson, Jean-Paul
Author_Institution :
Iowa State Univ., Ames, IA, USA
fYear :
2013
fDate :
21-25 July 2013
Firstpage :
1
Lastpage :
5
Abstract :
Given increasing penetration of variable generation units, there is significant interest in the power systems research community concerning the development of solution techniques that directly address the stochasticity of these sources in the unit commitment problem. Unfortunately, despite significant attention from the research community, stochastic unit commitment solvers have not made their way into practice, due in large part to the computational difficulty of the problem. In this paper, we address this issue, and focus on the development of a decomposition scheme based on the progressive hedging algorithm of Rockafellar and Wets. Our focus is on achieving solve times that are consistent with the requirements of ISO and utilities, on modest-scale instances, using reasonable numbers of scenarios. Further, we make use of modest-scale parallel computing, representing capabilities either presently deployed, or easily deployed in the near future. We demonstrate our progress to date on a test instance representing a simplified version of the US western interconnect (WECC-240).
Keywords :
power generation dispatch; power generation scheduling; stochastic processes; ISO; US western interconnect; WECC-240; decomposition scheme; modest-scale parallel computing; parallel progressive hedging; power systems research community; research community; stochastic unit commitment; test instance; variable generation units; Computational modeling; Context; Convergence; Parallel processing; Reliability; Stochastic processes; Uncertainty; Computation time; Optimization methods; Parallel algorithms; Power generation scheduling; Wind energy;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Power and Energy Society General Meeting (PES), 2013 IEEE
Conference_Location :
Vancouver, BC
ISSN :
1944-9925
Type :
conf
DOI :
10.1109/PESMG.2013.6673013
Filename :
6673013
Link To Document :
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