Open Access
Issue
MATEC Web Conf.
Volume 277, 2019
2018 International Joint Conference on Metallurgical and Materials Engineering (JCMME 2018)
Article Number 03006
Number of page(s) 9
Section Material and Mechanics
DOI https://doi.org/10.1051/matecconf/201927703006
Published online 02 April 2019
  1. Chuan Ping Cheng, Chih Wen Liu, and Chun Chang Liu. Unit commitment by lagrangian relaxation and genetic algorithms. IEEE Transactions on Power Systems, 15(2):707-714, 2000. [Google Scholar]
  2. Arthur I Cohen and S. H Wan. A method for solving the fuel constrained unit commitment problem. IEEE Transactions on Power Systems, PER-7(8):39-39, 1987. [Google Scholar]
  3. X. Ma, A. A. El-Keib, R. E. Smith, and H. Ma. A genetic algorithm based approach to thermal unit commitment of electric power systems. Electric Power Systems Research, 34(1):29-36, 1995. [Google Scholar]
  4. Ioannis G Damousis, Anastasios G Bakirtzis, and Petros S Dokopoulos. A solution to the unit-commitment problem using integer-coded genetic algorithm. IEEE Transactions on Power Systems, 19(2):1165-1172, 2004. [Google Scholar]
  5. M. Carrion and J. M. Arroyo. A computationally efficient mixed-integer linear formulation for the thermal unit commitment problem. IEEE Transactions on Power Systems, 21(3):1371-1378, 2006. [Google Scholar]
  6. Xuejiao Lei, Xiaohong Guan, and Qiaozhu Zhai. Constructing Valid Inequalities by Analytical Feasibility Conditions on Unit Commitment with Transmission Constraints. IEEE Transactions on Power Systems, 31(5):3484-3494, 2016. [Google Scholar]
  7. Kai Pan, Yongpei Guan, Jean Paul Watson, and Jianhui Wang. Strengthened MILP Formulation for Certain Gas Turbine Unit Commitment Problems. IEEE Transactions on Power Systems, 31(2):1440-1448, 2016. [Google Scholar]
  8. Raca Todosijevic, Marko Mladenovic, Said Hanafi, Nenad Mladenovic, and Igor Crevits. Adaptive general variable neighborhood search heuristics for solving the unit commitment problem. International Journal of Electrical Power & Energy Systems, 78:873-883, 2016. [Google Scholar]
  9. Chunheng Wang and Yong Fu. Fully parallel stochastic security-constrained unit commitment. IEEE Transactions on Power Systems, 31(5):3561-3571, 2016. [Google Scholar]
  10. Susanne Albers, Stefan Eilts, Eyal Even-Dar, Yishay Mansour, and Liam Roditty. On nash equilibria for a network creation game. Acm Transactions on Economics& Computation, 2(1):1-27, 2014. [Google Scholar]
  11. Dimitri P Bertsekas, Dimitri P Bertsekas, Dimitri P Bertsekas, and Dimitri P Bertsekas. Dynamic programming and optimal control, volume 1. Athena Scientific Belmont, MA, 1995. [Google Scholar]
  12. S. Virmani, E. C. Adrian, K. Imhof, and S. Mukherjee. Implementation of a lagrangian relaxation based unit commitment problem. IEEE Transactions on Power Systems, 4(4):1373-1380, 1989. [Google Scholar]
  13. CHEN Xing-ying ZHANG Xiao-hua, ZHAO Jin-quan. Unit commitment by enhanced adaptive lagrangian relaxation. Proceedings of the CSEE, 30(22):71-76, 2010. [Google Scholar]
  14. Haiti Ma and SM Shahidehpour. Unit commitment with transmission security and voltage constraints. IEEE transactions on power systems, 14(2):757-764, 1999. [Google Scholar]
  15. Rickard Nilsson. organisation, history, products and roles in the deregulated Nordic Market, 2007. [Google Scholar]

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