Uncertainty Management in the Unit Commitment Problem

By P. Ruiz, C. Russ Philbrick, E. Zak, K. Cheung, P. Sauer. IEEE Transactions on Power Systems, 2009

432 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Safety, Risk, Reliability and Quality

View Paper: https://www.semanticscholar.org/paper/c7da0f0f57b7ad5d7b5a93639e7788380f64a74a

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Citations in the corpus

The future of the European electricity system and the impact of fluctuating renewable energy – A scenario analysis (2014, background): “4 been developed to determine unit commitment and dispatch, taking into account the stochastic behavior of wind generators (i.a. Pappala et al., 2009; Ruiz et al., 2009; Garcia-Gonzalez et al., 2008), but these models are not designed for assessing long-term developments with endogenous investments,”
Chance-Constrained Two-Stage Unit Commitment Under Uncertain Load and Wind Power Output Using Bilinear Benders Decomposition (2016, neutral): “Compared with deterministic UC (DUC) models, SUC models have advantages of high reliability, as shown in [3] and [11].”
Multi-Stage Robust Unit Commitment Considering Wind and Demand Response Uncertainties (2013, background): “Related research can also be found in [9]–[11].”
Two-Stage Minimax Regret Robust Unit Commitment (2013, methodology): “, see [47] and [13], among others), we apply the sample average approximation (SAA) algorithm”
Multi-Area Energy and Reserve Dispatch Under Wind Uncertainty and Equipment Failures (2013, neutral): “The conclusions drawn from this study are provided in Section IV.”
A Chance-Constrained Two-Stage Stochastic Program for Unit Commitment With Uncertain Wind Power Output (2012, background): “[6] proposed a stochastic formulation to manage uncertainty in the unit commitment problem and extended the model to consider uncertainty and variability in wind power by using the same stochastic framework [7].”
Multiarea Stochastic Unit Commitment for High Wind Penetration in a Transmission Constrained Network (2013, methodology): “As a result, we are capable of simulating a total of 8,000 days (1,000 days for each day type), by contrast to Sioshansi and Short (2009), Ruiz et al. (2009a), and Tuohy et al. (2009), who only simulate one year of operations on a rolling horizon basis.”
Wind power forecasting : state-of-the-art 2009. (2009, background): “In [339]–[343], [347], and [352], the stochastic unit commitment is repeatedly discussed, which shows a promising generation scheduling alternative to the deterministic one.”
Spinning Reserve Estimation in Microgrids (2009, methodology): “References [35, 36] try to get a better accuracy by combining stochastic UC with the SR requirement.”