Optimal short-term hydrothermal generation scheduling using modified seeker optimisation algorithm

This paper presents a new evolutionary optimisation algorithm to solve the short-term hydrothermal generation problem with operational constraints using the modified seeker optimisation algorithm. Seeker optimisation algorithm is a recently developed empirical gradient based, meta-heuristic optimisation algorithm, which draws inspiration from the random process of human search strategy. In this paper, we improvise the step length determination strategy in the classical seeker optimisation method by considering an optimistically contracting step length calculation. The proposed methodology easily takes care of solving non-linear hydrothermal generation problem along with different constraints like power balance, capacity limits, valve-point loading and prohibited operating zones. Simulations were performed over various standard test cases and a comparative study is carried out with other existing relevant approaches. The result obtained reveals the robustness and ability of the proposed methodology over other existing techniques.

[1]  P. K. Chattopadhyay,et al.  Fast evolutionary programming techniques for short-term hydrothermal scheduling , 2003 .

[2]  T. S. Chung,et al.  Hybrid PSO and DE approach for dynamic economic dispatch with non-smooth cost functions , 2009, Int. J. Model. Identif. Control..

[3]  Peter B. Luh,et al.  Hydroelectric generation scheduling with an effective differential dynamic programming algorithm , 1990 .

[4]  Girish Kumar Singh,et al.  Modified PSO and wavelet transform-based fault classification on transmission systems , 2010, Int. J. Bio Inspired Comput..

[5]  Yong-Gang Wu,et al.  A diploid genetic approach to short-term scheduling of hydro-thermal system , 2000 .

[6]  Yue Shi,et al.  A modified particle swarm optimizer , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[7]  Malcolm Irving,et al.  A genetic algorithm modelling framework and solution technique for short term optimal hydrothermal scheduling , 1998 .

[8]  R. Chakrabarti,et al.  An improved PSO technique for short-term optimal hydrothermal scheduling , 2009 .

[9]  Chaohua Dai,et al.  Reactive power dispatch considering voltage stability with seeker optimization algorithm , 2009 .

[10]  Chaohua Dai,et al.  Seeker Optimization Algorithm , 2006, 2006 International Conference on Computational Intelligence and Security.

[11]  Q. Henry Wu,et al.  Distributed optimal power flow using bacterial swarming algorithm , 2010, Int. J. Model. Identif. Control..

[12]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[13]  Y. W. Wong,et al.  Short-term hydrothermal scheduling Part II: parallel simulated annealing approach , 1994 .

[14]  Allen J. Wood,et al.  Power Generation, Operation, and Control , 1984 .

[15]  Xia Qing,et al.  Optimal daily scheduling of cascaded plants using a new algorithm of nonlinear minimum cost network flow , 1988 .