Application of Improved PSO Technique for Short Term Hydrothermal Generation Scheduling of Power System

  • S. Padmini
  • C. Christober Asir Rajan
  • Pallavi Murthy
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7076)


This paper addresses short-term scheduling of hydrothermal systems by using Particle Swarm Optimization (PSO) algorithm. Particle Swarm Optimization is applied to determine the optimal hourly schedule of power generation in a hydrothermal power system. The developed algorithm is illustrated for a test system consisting of one hydro and one thermal plant respectively. The effectiveness and stochastic nature of proposed algorithm has been tested with standard test case and the results have been compared with earlier works. It is found that convergence characteristic is excellent and the results obtained by the proposed method are superior in terms of fuel cost.


Hydrothermal Scheduling Particle Swarm Optimization 


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  1. 1.
    Wood, A.J., Wollenberg, B.F.: Power Generation, Operation and Control. Operation and Control. John Wiley and Sons, New York (1984)Google Scholar
  2. 2.
    Umayal, S.P., Kamaraj, N.: Stochastic Multi Objective Short term Hydrothermal Scheduling Using Particle Swarm Optimization (2005)Google Scholar
  3. 3.
    Ferrero, R.W., Rivera, J.F., Shahidehpour, S.M.: A dynamicprogramming two-stage algorithm for long-termhydrothermal scheduling of multireservoir systems. IEEE Transactions on Power Systems 13(4), 1534–1540 (1998)CrossRefGoogle Scholar
  4. 4.
    Chang, W.: Optimal Scheduling of Hydrothermal System Based on Improved Particle Swarm OptimizationGoogle Scholar
  5. 5.
    Samudi, C., Das, G.P., Ojha, P.C., Sreeni, T.S., Cherian, S.: Hydro thernal Scheduling using Particle Swarm Optimization (2008)Google Scholar
  6. 6.
    Wong, K.P., Wong, Y.W.: Short-term hydrothermal scheduling, part-I: Simulated. annealing approach. IEE Proc., Part- C 141(5), 497–501 (1994)Google Scholar
  7. 7.
    Sinha, N., Chakrabarti, R.: Fast Evolutionary Programming Techniques For Short-Term Hydrothermal Scheduling. IEEE Trans. PWRS 18(1), 214–219 (2003)Google Scholar
  8. 8.
    Suman, D.S., Nallasivan, C., Henry, J., Ravichandran, S.: A Novel Approach for Short-Term Hydrothermal Scheduling Using Hybrid Technique. In: IEEE Power India Conference, April 10-12 (2006) Google Scholar
  9. 9.
    Sinha, N., Lai, L.-L.: Meta Heuristic Search Algorithms for Short-Term Hydrothermal Scheduling. In: International Conference on Machine Learning and Cybernetics, Dalian (2006)Google Scholar
  10. 10.
    Hotaa, P.K., Barisala, A.K., Chakrabarti, R.: An improved PSO technique for short-term optimal hydrothermal scheduling. Electric Power Systems Research 79(7), 1047–1053 (2009)CrossRefGoogle Scholar
  11. 11.
    Liang, J.J., Qin, A.K., Suganthan, P.N., Baskar, S.: Comprehensive Learning Particle Swarm Optimizer for Global Optimization of Multimodal Functions. IEEE T. on Evolutionary Computation 10(3), 281–295 (2006)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • S. Padmini
    • 1
  • C. Christober Asir Rajan
    • 2
  • Pallavi Murthy
    • 1
  1. 1.Department of Electrical and Electronics EngineeringSRM UniversityChennaiIndia
  2. 2.Department of Electrical and Electronics EngineeringPondichery UniversityChennaiIndia

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