Two-phase neural network based solution technique for short term hydrothermal scheduling

Author(s): R. Naresh and J. Sharma
DOI: 10.1049/ip-gtd:19990855

For access to this article, please select a purchase option:

Buy article PDF

Buy Knowledge Pack

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership

Recommend Title Publication to library

IEE Proceedings - Generation, Transmission and Distribution — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

Author(s): R. Naresh ¹ and J. Sharma ²
- Affiliations: 1: Department of Electrical Engineering, Regional Engineering College, Hamirpur, India
  2: Department of Electrical Engineering, University of Roorkee, Roorkee, India
Source: Volume 146, Issue 6, November 1999, p. 657 – 663
DOI: 10.1049/ip-gtd:19990855 , Print ISSN 1350-2360, Online ISSN 1359-7051

A two-phase neural network based optimisation method for short-term scheduling of a hydrothermal power system is proposed. The method is based on the solution of a set of differential equations obtained from transformation of an augmented lagrangian energy function. A multireservoir cascaded hydroelectric system with a nonlinear power generation function of water discharge rate and storage volume is considered for implementation. The water transportation delay between cascaded reservoirs is taken into account. Results from this method are compared with those obtained from the augmented lagrangian method. It is shown that the proposed solution technique is capable of yielding good optimal solution with proper selection of control parameters.

References

1. 1)
  - S.A. Soliman , G.S. Christensen . Application of functional analysis to optimisation of variablehead multi-reservoir power system for long term regulation. Water Resour. Res. , 60 , 852 - 858
2. 2)
  - P.C. Yang , H.T. Yang , C.L. Huang . Scheduling short term hydrothermal generation usingevolutionary programming techniques. IEE Proc. Pt. C , 4
3. 3)
  - S. Soares , C. Lyra , H. Tavares . Optimal generation scheduling of hydrothermal power systems. IEEE Trans. , 3 , 1106 - 1114
4. 4)
  - C. Wang , S.M. Shahidehpour . Power generation scheduling for multi-area hydrothermal powersystem with tie line constraints, cascaded reservoirs and uncertain data. IEEE Trans. , 3 , 1333 - 1340
5. 5)
  - S.O. Orero , M.R. Irving . A genetic algorithm modelling framework and solution technique forshort term optimal hydrothermal scheduling. IEEE Trans. , 2 , 501 - 518
6. 6)
  - Q. Xia , N. Xiang , S. Wang , B. Zhang , M. Huang . Optimal daily scheduling of cascaded plantsusing a new algorithm of nonlinear minimum cost network flow concept. IEEE Trans. , 3 , 929 - 935
7. 7)
  - W.W.-G. Yeh . Optimization of real time hydrothermal system operation. J. Water Resour. Plan. Manage. , 6 , 636 - 653
8. 8)
  - S. Kumar , J. Sharma , L.M. Ray . A nonlinear programming algorithm for hydro-thermalgeneration scheduling. Comput. Elect. Engng. , 221 - 229
9. 9)
  - R.H. Liang , Y.Y. Hsu . Short-term hydro scheduling using hopfield neural network. Proc. IEE, Pt. C , 3
10. 10)
  - J.S. Yang , N. Chen . Short-term hydrothermal co-ordination using multipass dynamic programming. IEEE Trans. , 3 , 1050 - 1056
11. 11)
  - K.P. Wong , Y.N. Wong . Short-term hydro scheduling Part 1: simulated annealing approach. Proc. IEE, Pt. C , 5 , 497 - 501
12. 12)
  - A.J. Wood , B.F. Wollenberg . (1996) Power generation operation and control.
13. 13)
  - R.H. Liang , Y.Y. Hsu . Scheduling of hydroelectric generation units using artificial neuralnetworks. Proc. IEE, Pt. C , 5 , 452 - 458
14. 14)
  - A. Turgeon . Optimal operation of multi-reservoir power systems with stochastic inflows. Water Resour. Res. , 2 , 275 - 283
15. 15)
  - H. Brannud , J.A. Bubenko , D. Sjelvgren . Optimal short term operation of a large hydrothermalpower system based on a nonlinear network flow concept. IEEE Trans. , 4 , 75 - 82
16. 16)
  - D.P. Bertsekas . (1982) Constrained optimization and Lagrange multiplier methods.
17. 17)
  - D.W. Tank , J.J. Hopfield . Simple neural optimization networks: An A/D converter, signaldecision circuit, and a linear programming circuit. IEEE Trans. , 533 - 541
18. 18)
  - C.Y. Maa , M.A. Shanblatt . A two-phase optimization neural network. IEEE Trans. Neural Netw. , 6 , 1003 - 1009
19. 19)
  - J.H. Drake , L.K. Kirchmayer , R.B. Mayall , W. Wood . Optimum operation of a hydrothermal system. AIEE Trans. PAS , 242 - 250
20. 20)
  - M.V.F. Pereira , L.M.V.G. Pinto . Application of decomposition techniques to the mid andshort term scheduling of hydro thermal systems. IEEE Trans. , 11 , 3611 - 3618
21. 21)
  - W.G. Chandler , P.L. Dandeno , A.F. Glimn , L.K. Kirchmayer . Short range economicoperation of a combined thermal and hydroelectric power system. AIEE Trans. PAS , 1057 - 1065
22. 22)
  - F. Wakamore , S. Masui , K. Morita . Layered network model approach to optimal daily hydro scheduling. IEEE Trans. , 9 , 3310 - 3314
23. 23)
  - M. Kennedy , L. Chua . Neural networks for nonlinear programming. IEEE Trans. , 554 - 562
24. 24)
  - E.B. Dahlin , D.N.C. Shen . Optimal solution to the hydro steam dispatch problem for certainpractical systems. IEEE Trans. , 437 - 458
25. 25)
  - S. Chang , C. Chen , I. Fong , P.B. Luh . Hydroelectric generation scheduling with an effectivedifferential dynamic programming. IEEE Trans. , 3 , 737 - 743
26. 26)
  - T.N. Saha , S.A. Khapade . An application of a direct method for the optimal scheduling ofhydrothermal power systems. IEEE Trans. , 3 , 977 - 985

Two-phase neural network based solution technique for short term hydrothermal scheduling

Two-phase neural network based solution technique for short term hydrothermal scheduling

Buy article PDF

Buy Knowledge Pack

Thank you

References

Related content