Hybrid neural network and simulated annealing approach to the unit commitment problem

Computers and Electrical Engineering

Volumn 26, Issue 6, 2000, Pages 461-477

  Nayak, R ^a   Sharma, J D ^b  

^a QUEENSLAND UNIVERSITY OF TECHNOLOGY   (Australia)

^b INDIAN INSTITUTE OF TECHNOLOGY ROORKEE   (India)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; BACKPROPAGATION; COMBINATORIAL MATHEMATICS; LEARNING SYSTEMS; MULTILAYER NEURAL NETWORKS; PROBLEM SOLVING; SIMULATED ANNEALING;

UNIT COMMITMENT;

ELECTRIC POWER SYSTEMS;

EID: 0034246501     PISSN: 00457906     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0045-7906(99)00037-3     Document Type: Article

References (18)

1. Akoi K., Itoh M., Satoh T., Nara K., Kanezashi M. Optimal long term unit-commitment in large scale systems including fuel constrained thermal and pumped storage hydro. IEEE Transactions on PS. 4:(8):1989;1065-1073.
2. Baum Eric B., Haussle D. What size net gives valid generalization. Neural Computation. 1:1989;149-157.
3. Chowdhury N., Billinton R. Unit commitment in interconnected system using a probabilistic technique. IEEE Transactions on PS. 5:(11):1990;1231-1237.
4. Cohen A.I., Yoshimura M. A branch and bound algorithm for unit commitment. IEEE Transactions on PAS. 103:(2):1983;445-451.
5. Gibbs J.W. Elementary principles in statistical mechanics. 1960;Dover, New York.
6. Hornik K., Stinchcomble M., White H. Multi-layer feedforward neural networks are universal approximators. Neural Networks. 2:1989;359-363.
7. Lippman RP. An Introduction to computing with neural nets. IEEE ASSP Magazine 1987;(April):4-21.
8. Metropolis N., Rosenbluth A., Rosenbluth M., Teller A. Equation of state calculations by fast computing machines. Journal of Chemical Physics. 21:1953;1087-1092.
9. Mohan C., Shanker K. Computational algorithm based on random search for solving global optimisation problem. Asia Pacific Journal of Operation Research. 11:1994;99-101.
10. Nayak R. Neural network approach to unit commitment problem. M.E. dissertation, Department of Electrical Engineering, University of Roorkee, India, 1995.
11. Ouyang Z., Shahidehpour S.M. A hybrid artificial neural network-dynamic programming approach to unit commitment. IEEE Transactions on PS. 7:(2):1992;236-242.
12. Sasaki H., Fujii Y., Watanbe M., Kubokawa J., Yorino N. A solution method using neural network for the generator commitment problem. Electrical Eng. in Japan. 112:1992;55-61.
13. Sheble' G., Fahd G. Unit commitment literature synopsis. IEEE Transactions on PS. 9:(2):1994;128-135.
14. Sheble' G., Grigsby L. Decision analysis solution of the unit commitment problem. Electric Power System Research. 10:(11):1986;85-93.
15. Shoults A.A., Chang S.K., Helmick S., Grady W.M. A practical approach to unit commitment, economic dispatch and saving allocation for multiple-area pool operation with import/export constraints. IEEE Transactions on PAS. 99:(3/4):1980;625-635.
16. Turgeon A. Optimal scheduling of thermal generating units. IEEE Transactions on AC. 23:(12):1978;1000-1005.
17. Vankayala V.S.S., Nutakki D. Artificial neural network and their applications to power systems - a bibliographical survey. Electric Power System Research. 28:(5):1993;67-79.
18. Zhuang F., Galiana F.D. Unit commitment by simulated annealing. IEEE Transactions on PS. 5:(2):1990;311-317.