Static/Dynamic Environmental Economic Dispatch Employing Chaotic Micro Bacterial Foraging Algorithm

  • Nicole Pandit
  • Anshul Tripathi
  • Shashikala Tapaswi
  • Manjaree Pandit
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7076)

Abstract

Environmental Economic Dispatch is carried out in the energy control center to find the optimal thermal generation schedule such that power balance criterion and unit operating limits are satisfied and the fuel cost as well as emission is minimized. Environmental economic dispatch presents a complex, dynamic, non-linear and discontinuous optimization problem for the power system operator. It is quite well known that gradient based methods cannot work for discontinuous or nonconvex functions as these functions are not continuously differentiable As a result, evolutionary methods are increasingly being proposed. This paper proposes a chaotic micro bacterial foraging algorithm (CMBFA) employing a time-varying chemotactic step size in micro BFA. The convergence characteristic, speed, and solution quality of CMBFA is found to be significantly better than classical BFA for a 3-unit system and the standard IEEE 30-bus test system.

Keywords

Particle Swarm Optimization Bacterium Count Economic Load Economic Load Dispatch Bacterial Forage Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Passino, K.M.: Biomimicry of bacterial foraging for distributed optimization and control. IEEE Control Syst. Mag. 22(3), 52–67 (2002)CrossRefGoogle Scholar
  2. 2.
    Dasgupta, S., Biswas, A., Das, S., Panigrahi, B.K., Abraham, A.: A Micro-Bacterial Foraging Algorithm for High-Dimensional Optimization. In: IEEE Congress on Evolutionary Computation, pp. 785–792 (2009)Google Scholar
  3. 3.
    Long, L.X., Jun, L.R., Ping, Y.: Bacterial Foraging Global Optimization Algorithm Based On the Particle Swarm Optimization. In: IEEE International Conference on Intelligent Computing and Intelligent Systems, pp. 22–27 (2010)Google Scholar
  4. 4.
    Talaq, J.H., El-Hawary, F., El-Hawary, M.E.: A summary of environmental and economic dispatch algorithms. IEEE Trans. Power Syst. 9(3), 1508–1516 (1994)CrossRefGoogle Scholar
  5. 5.
    Palanichamy, C., Srikrishna, K.: Economic Thermal Power Dispatch with Emission Constraint. Journal of the Institution of Engineers (India) 72, 11–18 (1991)Google Scholar
  6. 6.
    Basu, M.: Dynamic economic emission dispatch using nondominated sorting genetic algorithm-II. Electrical Power and Energy Systems 30, 140–149 (2008)CrossRefGoogle Scholar
  7. 7.
    Abido, M.A.: Multiobjective particle swarm optimization for environmental/economic dispatch problem. Electric Power Systems Research 79, 1105–1113 (2009)CrossRefGoogle Scholar
  8. 8.
    Hota, P.K., Barisal, A.K., Chakrabarti, R.: Economic emission load dispatch through fuzzy based bacterial foraging algorithm. Electrical Power and Energy Systems 32, 794–803 (2010)CrossRefGoogle Scholar
  9. 9.
    Chen, P.H., Chang, H.C.: Large scale economic dispatch approach by genetic algorithm. IEEE Transactions on Power Systems 10(4), 1919–1926 (1995)CrossRefGoogle Scholar
  10. 10.
    Panigrah, B.K., Ravikumar, P.V., Das, S.: An Adaptive Particle Swarm Optimization Approach for Static and Dynamic Economic Load Dispatch. International Journal on Energy Conversion and Management 49, 1407–1415 (2008)CrossRefGoogle Scholar
  11. 11.
    Panigrahi, B.K., Yadav, S.R., Agrawal, S., Tiwari, M.K.: A clonal algorithm to solve economic load dispatch. Electric Power System Research 77, 1381–1389 (2007)CrossRefGoogle Scholar
  12. 12.
    Bhattacharya, A., Chattopadhyay, P.K.: Hybrid differential evolution with biogeography- based optimization for solution of economic load dispatch. IEEE Transactions on Power System 25(4), 1955–1964 (2010)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Nicole Pandit
    • 1
  • Anshul Tripathi
    • 1
  • Shashikala Tapaswi
    • 1
  • Manjaree Pandit
    • 2
  1. 1.ABV-IIITMGwaliorIndia
  2. 2.Department of Electrical EngineeringMITSGwaliorIndia

Personalised recommendations