1BALDICK R. The generalized unit commitment problem[J].IEEE Trans on Power Systems, 1995, 10(1): 465-475.
2BATH R, BRAND H, MEIBOM P, et al. A stochastic unitcommitment model for the evaluation of the impacts of the integration of large amounts of wind power[C]// Proceedings of the 9th International Conference on Probabilistic Methods Applied to Power Systems, June 11-15, 2006, Stockholm, Sweden: 8p.
3TUOHY A, MEIBOM P, OMALI.EY M. Benefits of stochastic scheduling for power system with significant installed wind power[C]// Proceedings of the 10th International Conference on Probabilistic Methods Applied to Power Systems, May 25-29, 2008, Mayagtlez, Puerto Rieo: 7p.
4TUOHY A, MEIBOM P, DENNY E, et al. Unit commitment for systems with significant wind penetration[J]. IEEE Trans on Power Systems, 2009, 24(2) : 592-601.
5RUIZ P A, PHILBRICK C R, SAUER P W. Wind power day ahead uncertainty management through stochastic unit commitment policies[C]// Proceedings of Power Systems Conference and Exhibition, March 15-18, 2009, Seattle, WA, USA: 9p.
6WANG Jianhui, SHAHIDEHPOUR M, LI Zuyi. Security constraint unit commitment with volatile wind power generation [J]. IEEETransonPowerSystems, 2008, 23(3): 1319-1327.
7WANG Jianhui, BOTTERUD A, MIRANDA V, et al. Impact of wind power forecasting on unit commitment and dispatch [C]// Proceedings of the 8th International Workshop on Largescale Integration of Wind Power into Power Systems, October 14 15, 2009, Bremen, Germany.
8PINSON P. Estimation of the uncertainty in wind power forecasting[D]. Paris, France: Ecole des Mines de Paris, 2006.
9PINSON P, JUBAN J, KARINIOTAKIS G N. On the quality and value of probabilistic forecasts of wind generation [C]// Proceedings of the 9th International Conference on Probabilistic Methods Applied to Power Systems, June 11-15, 2006, Stockholm, Sweden: 7p.
10GLASSERMAN P. Monte Carlo methods for financial engineering[M]. New York, NY, USA: Springer, 2003.
