Solution sensitivity-based scenario reduction for stochastic unit commitment

Yonghan Feng () and Sarah Ryan ()

Computational Management Science, 2016, vol. 13, issue 1, 29-62

Abstract: A two-stage stochastic program is formulated for day-ahead commitment of thermal generating units to minimize total expected cost considering uncertainties in the day-ahead load and the availability of variable generation resources. Commitments of thermal units in the stochastic reliability unit commitment are viewed as first-stage decisions, and dispatch is relegated to the second stage. It is challenging to solve such a stochastic program if many scenarios are incorporated. A heuristic scenario reduction method termed forward selection in recourse clusters (FSRC), which selects scenarios based on their cost and reliability impacts, is presented to alleviate the computational burden. In instances down-sampled from data for an Independent System Operator in the US, FSRC results in more reliable commitment schedules having similar costs, compared to those from a scenario reduction method based on probability metrics. Moreover, in a rolling horizon study, FSRC preserves solution quality even if the reduction is substantial. Copyright Springer-Verlag Berlin Heidelberg 2016

Keywords: Stochastic programming; Scenario reduction; Unit commitment; Variable generation (search for similar items in EconPapers)
Date: 2016
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DOI: 10.1007/s10287-014-0220-z

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