Security-constrained unit commitment for simultaneous clearing of energy and ancillary services markets

By Zuyi Li, Mohammad Shahidehpour. IEEE Transactions on Power Systems, 2005

156 citations recorded by the source corpus.

How researchers see this paper

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

Market-clearing with stochastic security-part I: formulation (2005, methodology): “Solution techniques based on Benders’ decomposition [35], [39]–[41] are promising strategies to deal with large systems by keeping the size of the constraint set to a more reasonable level and by taking advantage of the parallelism offered by this decomposition technique.”
Market-clearing with stochastic security-part II: case studies (2005, methodology): “In addition, as mentioned in the companion paper, the use of scenario reduction techniques [15]–[17] is promising, as are decomposition techniques based on Benders’ decomposition [18]–[21] and “branch-and-price” decomposition [22]–[24].”
Contingency-Constrained Reserve Requirements in Joint Energy and Ancillary Services Auction (2009, background): “However, the pricing algorithm in [12] and [18] considers a pre-defined ancillary services margin, which is usually a certain percentage of the system load or the largest unit capacity in the system.”
MIP Reformulation for Max-Min Problems in Two-Stage Robust SCUC (2017, background): “The unit-wise constraints are normally composed of generation capacity limits, ramping rate limits, and minimum on/off time limits [2], [3].”