Publisher : The Korean Institute of Electrical Engineers
DOI : 10.5370/JEET.2012.7.1.17
Title & Authors
Evaluation of Two Lagrangian Dual Optimization Algorithms for Large-Scale Unit Commitment Problems Fan, Wen; Liao, Yuan; Lee, Jong-Beom; Kim, Yong-Kab;
Lagrangian relaxation is the most widely adopted method for solving unit commitment (UC) problems. It consists of two steps: dual optimization and primal feasible solution construction. The dual optimization step is crucial in determining the overall performance of the solution. This paper intends to evaluate two dual optimization methods - one based on subgradient (SG) and the other based on the cutting plane. Large-scale UC problems with hundreds of thousands of variables and constraints have been generated for evaluation purposes. It is found that the evaluated SG method yields very promising results.
A hybrid biased random key genetic algorithm approach for the unit commitment problem, Journal of Combinatorial Optimization, 2014, 28, 1, 140
Benjamin F. Hobbs, et al, The Next Generation of Electric Power Unit Commitment Models, Kluwer's International Series, 2001.
X Feng and Yuan Liao, "A new Lagrangian multiplier update approach for Lagrangian relaxation based unit commitment", Electric Power Components & Systems, 34 (2006), pp. 857-866.
N. J. Redondo, A. J. Conejo, "Short-term hydrothermal coordination by Lagrangian relaxation: solution of the dual problem", IEEE Transactions on Power Systems, 14 (1999), pp. 89-95.
C. P. Cheng, C. W. Liu, C. C. Liu, "Unit commitment by Lagrangian relaxation and genetic algorithms", IEEE Transactions on Power Systems, 15(2000), pp. 707-714.
R. T. Rockafellar, "Lagrange multipliers and optimality", SIAM Rev., 35 (1993), pp. 183-238.
Mokhtar S. Bazaraa, Hanif D. Sherali, C. M. Shetty, Nonlinear Programming, Theory and Algorithms, John Wiley & Sons, Inc. 1993.
C. A. Kaskavelis, M. C. Caramanis, "Efficient Lagrangian relaxation algorithm for industry size jobshop scheduling problems", IIE Transactions, 30 (1998), pp 1085-1097.
W. Ongsakul, N. Petcharaks, "Unit commitment by enhanced adaptive Lagrangian relaxation", IEEE Transactions on Power Systems, 19 (2004), pp. 620-628.
A. Borghetti, A. Frangioni, F. Lacalandra, C.A. Nucci, "Lagrangian Heuristics Based on Disaggregated Bundle Methods for Hydrothermal Unit Commitment", IEEE Transactions on Power Systems, 18 (2003), pp. 313-323.
H.P. Williams, Model Building in Mathematical Programming, John Wiley & Sons Ltd.,West Sussex, England, 1999.
Yuan Liao, "Development of a generation resource scheduling case library", 38th Southeastern Symposium on System Theory, Tennessee Technological University, Cookeville, TN, USA, March 5-7, 2006.
Yuan Liao, X Feng and J Pan, "Impact of emission compliance program on competitive power market", invited paper, The 2nd International Conference on Electric Utility Deregulation, Restructuring and Power Technologies, Hong Kong, April 5-8, 2004.
Yuan Liao, X Feng and J Pan, "Analysis of interaction between ancillary service markets and energy market using power market simulator", invited paper, The 2nd International Conference on Electric Utility Deregulation, Restructuring and Power Technologies, Hong Kong, April 5-8, 2004.
K. Chandram, N. Subrahmanyam and M. Sydulu, "Improved pre-prepared power demand table and muller's method to solve the profit based unit commitment problem", Journal of Electrical Engineering & Technology, 4 (2009), pp. 159-167.
Yun-Won Jeong, Woo-Nam Lee, Hyun-Houng Kim, Jong-Bae Park and Joong-Rin Shin, "Thermal unit commitment using binary differential evolution", Journal of Electrical Engineering & Technology, 4 (2009), pp. 323-329.