GENETIC ALGORITHM MODEL FOR PROFIT MAXIMIZATION OF GENERATING COMPANIES IN DEREGULATED ELECTRICITY MARKETS

REFERENCES

• Aldridge , C. J. , S. McKee , J. R. McDonald , S. J. Galloway , K. P. Dahal , M. E. Bradley , and J. F. Macqueen . 2001 . Knowledge-based genetic algorithm for unit commitment . IEE Proceedings – Generation, Transmission and Distribution 148 ( 2 ): 146 – 152 .
   Google Scholar
• Allen , E. and M. Ilic . 1999 . Price-Based Commitment Decisions in the Electricity Market . London : Springer .
   Google Scholar
• Arroyo , J. M. and A. J. Conejo . 2000 . Optimal response of a thermal unit to an electricity spot market . IEEE Transactions on Power Systems 15 ( 3 ): 1098 – 1104 .
   Web of Science ®Google Scholar
• Arroyo , J. M. and A. J. Conejo . 2002 . Optimal response of a power generator to energy, AGC, and reserve pool-based markets . IEEE Transactions on Power Systems 17 ( 2 ): 404 – 410 .
   Google Scholar
• Baptistella , L. F. B. and J. C. Geromel . 1980. A decomposition approach to problem of unit commitment schedule for hydrothermal systems. Proc. IEE, Part C 127(6):250.
   Google Scholar
• Cohen , A. I. and M. Yoshimura . 1983 . A branch-and-bound algorithm for unit commitment . IEEE Transactions on Power Apparatus and Systems 102 ( 2 ): 444 – 451 .
   Google Scholar
• Contreras , J. , R. Espinola , F. G. Nogales , and A. J. Conejo . 2003 . ARIMA models to predict next-day electricity prices . IEEE Transactions on Power Systems 18 : 1014 – 1020 .
   Web of Science ®Google Scholar
• Correia , P. F. 2006 . Decentralised unit commitment in a market structure: problem formulation and solution advancement . IEE Proceedings – Generation, Transmission and Distribution 153 ( 1 ): 121 – 126 .
   Google Scholar
• Damousis , I. G. , A. G. Bakirtzis , and P. S. Dokopoulos . 2004 . A solution to the unit-commitment problem using integer-coded genetic algorithm . IEEE Transactions on Power Systems 19 ( 2 ): 1165 – 1172 .
   Web of Science ®Google Scholar
• de La Torre , S. , J. M. Arroyo , A. J. Conejo , and J. Contreras . 2002 . Price-maker self-scheduling in a pool-based electricity market: A mixed-integer LP approach . IEEE Transactions on Power Systems 17 ( 4 ): 1037 – 1042 .
   Web of Science ®Google Scholar
• El Desouky , A. A. , R. Aggarwal , M. M. Elkateb , and F. Li . 2001 . Advanced hybrid genetic algorithm for short-term generation scheduling . TEE Proceedings – Generation, Transmission and Distribution 148 ( 6 ): 511 – 517 .
   Google Scholar
• Georgilakis , P. S. 2007 . Artificial intelligence solution to electricity price forecasting problem . Applied Artificial Intelligence 21 ( 8 ): 707 – 727 .
   Web of Science ®Google Scholar
• Goldberg , D. E. 1989 . Genetic Algorithms in Search, Optimization, and Machine Learning . Reading : Addison-Wesley .
   Google Scholar
• Hobbs , B. F. , M. H. Rothkopf , R. P. O'Neill , and H.-P. Chao . 2001 . The Next Generation of Electric Power Unit Commitment Models . Boston : Kluwer .
   Google Scholar
• Kazarlis , S. A. , A. G. Bakirtzis , and V. Petridis . 1996 . A genetic algorithm solution to the unit commitment problem . IEEE Transactions on Power Systems 11 ( 1 ): 83 – 92 .
   Web of Science ®Google Scholar
• Li , T. and M. Shahidehpour . 2005 . Price-based unit commitment: A case of Lagrangian relaxation versus mixed integer programming . IEEE Transactions on Power Systems 20 ( 4 ): 2015 – 2025 .
   Web of Science ®Google Scholar
• Maifeld , T. T. and G. B. Sheblé . 1996 . Genetic-based unit commitment algorithm . IEEE Transactions on Power Systems 11 ( 3 ): 1359 – 1370 .
   Web of Science ®Google Scholar
• Michalewicz , Z. 1996 . Genetic Algorithms +Data Structures = Evolution Programs . Berlin : Springer-Verlag .
   Google Scholar
• Rao , S. S. 1996 . Engineering Optimization: Theory and Practice, , 3rd ed . New York : Wiley .
   Google Scholar
• Sasaki , H. , M. Watanabe , and R. Yokoyama . 1992 . A solution method of unit commitment by artificial neural networks . IEEE Transactions on Power Systems 7 : 974 – 981 .
   Web of Science ®Google Scholar
• Senjyu , T. , A. Y. Saber , T. Miyagi , K. Shimabukuro , N. Urasaki , and T. Funabashi . 2005 . Fast technique for unit commitment by genetic algorithm based on unit clustering . IEE Proceedings – Generation, Transmission and Distribution 152 ( 5 ): 705 – 713 .
   Google Scholar
• Shahidehpour , M. , H. Yamin , and Z. Li . 2002 . Market Operations in Electric Power System . New York : Wiley .
   Google Scholar
• Sheblé , G. B. and G. N. Fahd . 1994 . Unit commitment literature synopsis . IEEE Transactions on Power Systems 9 ( 1 ): 128 – 135 .
   Google Scholar
• Shrestha , G. B. , B. K. Pokharel , T. T. Lie , and S.-E. Fleten . 2007 . Price-based unit commitment for bidding under price uncertainty . IET Generation, Transmission and Distribution 1 ( 4 ): 663 – 669 .
   Google Scholar
• Snyder , W. L. , H. D. Powell Jr ., and J. C. Rayburn . 1987 . Dynamic programming approach to unit commitment . IEEE Transactions on Power Systems 2 : 339 – 350 .
   Web of Science ®Google Scholar
• Takriti , S. , B. Krasenbrink , and L. Wu . 2000 . Incorporating fuel constraints and electricity spot prices into the stochastic unit commitment problem . Oper. Res. 48 : 268 – 280 .
   Web of Science ®Google Scholar
• Wang , C. and S. M. Shahidehpour . 1992 . A decomposition approach to non-linear multi-area generation scheduling with tie-line constraints using expert systems . IEEE Transactions on Power Systems 7 : 1409 – 1418 .
   Web of Science ®Google Scholar
• Wong , K. P. and Y. W. Wong . 1995 . Thermal generator scheduling using hybrid genetic/simulated-annealing approach . IEE Proceedings – Generation, Transmission and Distribution 142 ( 4 ): 372 – 380 .
   Google Scholar
• Wood , A. J. and B. F. Wollenberg . 1996 . Power Generation, Operation and Control, , 2nd ed . New York : Wiley .
   Google Scholar
• Yao , S. J. and Y. H. Song . 2000 . Prediction of system marginal prices by wavelet transform and neural network . Elect. Mach. Power Syst. 28 : 983 – 993 .
   Web of Science ®Google Scholar
• Zhuang , F. and F. D. Galiana . 1988 . Toward a more rigorous and practical unit commitment by Lagrangian relaxation . IEEE Transactions on Power Systems 3 : 763 – 770 .
   Web of Science ®Google Scholar
• Zhuang , F. and F. D. Galiana . 1990 . Unit commitment by simulated annealing . IEEE Transactions on Power Systems 5 ( 1 ): 311 – 318 .
   Web of Science ®Google Scholar