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Title: Stochastic Unit Commitment: Scalable Computation and Experimental Results.


Abstract not provided.

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Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
Report Number(s):
DOE Contract Number:
Resource Type:
Resource Relation:
Conference: Proposed for presentation at the 13th International Conference on Stochastic Programming held July 8-12, 2013 in Bergamo, Italy.
Country of Publication:
United States

Citation Formats

Watson, Jean-Paul, Woodruff, David L., and Ryan, Sarah M.. Stochastic Unit Commitment: Scalable Computation and Experimental Results.. United States: N. p., 2013. Web.
Watson, Jean-Paul, Woodruff, David L., & Ryan, Sarah M.. Stochastic Unit Commitment: Scalable Computation and Experimental Results.. United States.
Watson, Jean-Paul, Woodruff, David L., and Ryan, Sarah M.. Mon . "Stochastic Unit Commitment: Scalable Computation and Experimental Results.". United States. doi:.
title = {Stochastic Unit Commitment: Scalable Computation and Experimental Results.},
author = {Watson, Jean-Paul and Woodruff, David L. and Ryan, Sarah M.},
abstractNote = {Abstract not provided.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon Jul 01 00:00:00 EDT 2013},
month = {Mon Jul 01 00:00:00 EDT 2013}

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  • Production cost models (PCMs) simulate power system operation at hourly (or higher) resolution. While computation times often extend into multiple days, the sequential nature of PCM's makes parallelism difficult. We exploit the persistence of unit commitment decisions to select partition boundaries for simulation horizon decomposition and parallel computation. Partitioned simulations are benchmarked against sequential solutions for optimality and computation time.
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  • Variable renewable generation resources are increasing their penetration on electric power grids. These resources have weather-driven fuel sources that vary on different time scales and are difficult to predict in advance. These characteristics create challenges for system operators managing the load balance on different timescales. Research is looking into new operational techniques and strategies that show great promise on facilitating greater integration of variable resources. Stochastic Security-Constrained Unit Commitment models are one strategy that has been discussed in literature and shows great benefit. However, it is rarely used outside the research community due to its computational limits and difficulties integratingmore » with electricity markets. This paper discusses how it can be integrated into day-ahead energy markets and especially on what pricing schemes should be used to ensure an efficient and fair market.« less