Cost of Reliability Analysis Based on Stochastic Unit Commitment
By Lei Wu, Mohammad Shahidehpour, Tao Li. IEEE Transactions on Power Systems, 2008
211 citations recorded by the source corpus.
Subfields: Electrical and Electronic Engineering, Safety, Risk, Reliability and Quality
View Paper: https://www.semanticscholar.org/paper/c0094a07db35c6152a81e61b9abf1507a5fc03b0
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
- Mohammad Shahidehpour
- Zuyi Li
- Hongyu Wu
- Nima Amjady
- Ahmed Alabdulwahab
- Abdullah M. Abusorrah
- Xiaping Zhang
- Rafal Weron
In Safety, Risk, Reliability and Quality
- Hongyu Wu
- Zuyi Li
- Mingqiang Wang
- Hoay Beng Gooi
- Wei Tian
- Ahmed Alabdulwahab
- Xiaping Zhang
- Abdullah M. Abusorrah
Citations in the corpus
- Spinning Reserve Estimation in Microgrids (2009, methodology): “Similar to the classification of the analytical SR optimization methods, the stochastic SR optimization methods include successive iteration of stochastic UC [28], reliability constrained stochastic UC [29], and stochastic programming based on the cost/benefit analysis [11, 30-34].”
- Chance-Constrained Day-Ahead Scheduling in Stochastic Power System Operation (2014, background): “Unlike our previous studies in [12] and [13] which utilized the scenario-based MCS and a continuous distribution was approximated by a discrete distribution, the proposed model assumes continuous random variables for representing the hourly variations of loads and renewable generation profiles.”
- Stochastic Multiobjective Market Clearing of Joint Energy and Reserves Auctions Ensuring Power System Security (2009, background): “For instance, in [21] and [34], bundle constraints are proposed to avoid infeasible solutions with the expected value-based scenario aggregation.”
- Hourly Electricity Demand Response in the Stochastic Day-Ahead Scheduling of Coordinated Electricity and Natural Gas Networks (2016, methodology): “A low-discrepancyMonte Carlo simulation method Latin hypercube sampling (LHS) technique is employed to decrease the variance of simple Monte Carlo simulation [18].”