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

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

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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)
      • E.B. Dahlin , D.N.C. Shen . Optimal solution to the hydro steam dispatch problem for certainpractical systems. IEEE Trans. , 437 - 458
    2. 2)
      • 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
    3. 3)
      • J.H. Drake , L.K. Kirchmayer , R.B. Mayall , W. Wood . Optimum operation of a hydrothermal system. AIEE Trans. PAS , 242 - 250
    4. 4)
      • S. Chang , C. Chen , I. Fong , P.B. Luh . Hydroelectric generation scheduling with an effectivedifferential dynamic programming. IEEE Trans. , 3 , 737 - 743
    5. 5)
      • A. Turgeon . Optimal operation of multi-reservoir power systems with stochastic inflows. Water Resour. Res. , 2 , 275 - 283
    6. 6)
      • J.S. Yang , N. Chen . Short-term hydrothermal co-ordination using multipass dynamic programming. IEEE Trans. , 3 , 1050 - 1056
    7. 7)
      • W.W.-G. Yeh . Optimization of real time hydrothermal system operation. J. Water Resour. Plan. Manage. , 6 , 636 - 653
    8. 8)
      • A.J. Wood , B.F. Wollenberg . (1996) Power generation operation and control.
    9. 9)
      • 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
    10. 10)
      • 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
    11. 11)
      • F. Wakamore , S. Masui , K. Morita . Layered network model approach to optimal daily hydro scheduling. IEEE Trans. , 9 , 3310 - 3314
    12. 12)
      • 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
    13. 13)
      • T.N. Saha , S.A. Khapade . An application of a direct method for the optimal scheduling ofhydrothermal power systems. IEEE Trans. , 3 , 977 - 985
    14. 14)
      • 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
    15. 15)
      • 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
    16. 16)
      • S. Soares , C. Lyra , H. Tavares . Optimal generation scheduling of hydrothermal power systems. IEEE Trans. , 3 , 1106 - 1114
    17. 17)
      • S. Kumar , J. Sharma , L.M. Ray . A nonlinear programming algorithm for hydro-thermalgeneration scheduling. Comput. Elect. Engng. , 221 - 229
    18. 18)
      • R.H. Liang , Y.Y. Hsu . Scheduling of hydroelectric generation units using artificial neuralnetworks. Proc. IEE, Pt. C , 5 , 452 - 458
    19. 19)
      • R.H. Liang , Y.Y. Hsu . Short-term hydro scheduling using hopfield neural network. Proc. IEE, Pt. C , 3
    20. 20)
      • K.P. Wong , Y.N. Wong . Short-term hydro scheduling Part 1: simulated annealing approach. Proc. IEE, Pt. C , 5 , 497 - 501
    21. 21)
      • P.C. Yang , H.T. Yang , C.L. Huang . Scheduling short term hydrothermal generation usingevolutionary programming techniques. IEE Proc. Pt. C , 4
    22. 22)
      • S.O. Orero , M.R. Irving . A genetic algorithm modelling framework and solution technique forshort term optimal hydrothermal scheduling. IEEE Trans. , 2 , 501 - 518
    23. 23)
      • C.Y. Maa , M.A. Shanblatt . A two-phase optimization neural network. IEEE Trans. Neural Netw. , 6 , 1003 - 1009
    24. 24)
      • 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
    25. 25)
      • M. Kennedy , L. Chua . Neural networks for nonlinear programming. IEEE Trans. , 554 - 562
    26. 26)
      • D.P. Bertsekas . (1982) Constrained optimization and Lagrange multiplier methods.
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