Stochastic Security-Constrained Unit Commitment

By Lei Wu, Mohammad Shahidehpour, Tao Li. IEEE Transactions on Power Systems, 2007

854 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/c39c425256ca60d6a584a7d583b043aec182427a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Electrical and Electronic Engineering

1. Mohammad Shahidehpour
2. Wei Wei
3. ShengWei Mei
4. Feng Liu
5. Zuyi Li
6. Lei Wu
7. Amin Khodaei
8. Shmuel S. Oren

Citations in the corpus

• Data-driven Affinely Adjustable Distributionally Robust Unit Commitment (2018, methodology): “Monte Carlo simulation based method is usually employed to generate scenarios [3], [7].”
• Hourly Coordination of Electric Vehicle Operation and Volatile Wind Power Generation in SCUC (2012, background): “Hence, the stochastic solution would lower the operating cost by $5243.276 (i.e., ), which is the value of stochastic programming.”
• Uncertainty Management in the Unit Commitment Problem (2009, background): “After these initial implementations, others have extended these efforts to incorporate the uncertainty in the wind generation [14], market outcomes [15], fuel cost [16], network aspects [17]–[19], and longer-term production costing [20].”
• Chance-Constrained Two-Stage Unit Commitment Under Uncertain Load and Wind Power Output Using Bilinear Benders Decomposition (2016, background): “, wind power generation [7], and introduce a recourse decision problem for every scenario.”
• Hourly Electricity Demand Response in the Stochastic Day-Ahead Scheduling of Coordinated Electricity and Natural Gas Networks (2016, background): “the computation efficiency and the modeling accuracy [19].”
• Chance-Constrained Day-Ahead Scheduling in Stochastic Power System Operation (2014, methodology): “Random outages of generators and transmission lines are simulated based on forced outage rates and repair rates by a sampling method [13], which determines the component availability in each scenario.”
• Uncertainty-Aware Household Appliance Scheduling Considering Dynamic Electricity Pricing in Smart Home (2013, background): “In [21], the authors proposed a three-step control methodology to manage the cooperation between technologies of energy production, consumption, and storage.”
• Adaptive Robust Optimization With Dynamic Uncertainty Sets for Multi-Period Economic Dispatch Under Significant Wind (2014, background): “[30], [32] propose security constrained UC models and consider stochastic wind power generation.”
• Large-Scale Integration of Deferrable Demand and Renewable Energy Sources (2014, positive): “The use of a stochastic unit commitment model for the purpose of simulating the operations of a dayahead market introduces computational challenges that can be addressed by using an appropriate scenario selection technique to discretize the uncertainty space of the problem [5], [22]–[24] and exploit”
• Distributionally Robust Co-Optimization of Energy and Reserve Dispatch (2016, methodology): “Provided with the PDFs of wind power, the unit commitment, economic dispatch and spinning reserve can be scheduled in the framework of stochastic optimization (SO), including the scenario based models [13]–[17] and the chance-constraints based models [18]–[21].”