Optimization of Wind Thermal Coordination Dispatch using Flower Pollination Algorithm

Authors

  • K. Dhayalini Professor, K. Ramakrishnan College of Engineering, Thiruchirappalli, Tamilnadu, India

DOI:

https://doi.org/10.24297/jac.v12i16.978

Keywords:

Fuel cost, Flower Pollination Algorithm, Economic Dispatch, wind power

Abstract

Non conventional energy sources have turned the attention of power system experts due to the environmental and economic issues. Among the different renewable energy sources wind energy is considered to be remarkable because it can be obtained at free of cost. Normally power generation is carried out using thermal generators. In this paper the integration of thermal generators with wind units are considered and the solution of wind thermal dispatch problem using Flower Pollination Algorithm (FPA) is implemented. This algorithm is implemented to find the minimum production cost with valve effects of thermal units included.  The effectiveness of the proposed approach is validated using two IEEE test systems consisting of six and thirteen units with a wind farm of 100MW capacity. The analysis is carried out neglecting the transmission losses. Simulation results predict the inclusion of wind power reduces the overall production cost.

Downloads

Download data is not yet available.

Author Biography

K. Dhayalini, Professor, K. Ramakrishnan College of Engineering, Thiruchirappalli, Tamilnadu, India

Department of Electrical and Electronics Engineering,

References

1. Wu, J., Zhang, B., Wang, K., Shao, J., Yao, J., Zeng, D., Ge, T., 2015 ‘Optimal economic dispatch model based on risk management for wind-integrated power system’ Gener. Transm. Distrib. IET 9(15), 2152—2158
2. Hetzer, J., Yu, D.C., Bhattarai, K., 2008, ‘An economic dispatchmodel incorporating wind power’, IEEE Trans. Energy Convers.23 (2), 603—611.
3. Jadoun, V.K., Gupta, N., Niazi, K.R., Swarnkar, A., 2015, ‘Modulatedparticle swarm optimization for economic emission dispatch’, Int.J. Electr. Power Energy Syst. 73, 80—88.
4. Dhayalini.K, Sathiyamoorthy.S, Christober Asir Rajan.C ‘Genetic Algorithm for the coordination of wind thermal dispatch’, Przegland Electrotechnizy, vol.4, 2014, pp.45-48.
5. Kirkpatrick, S, Elatt, CD & Vecchi, MP 1983, ‘Optimization by Simulated Annealing’, Science, vol.220, pp.671-680.
6. Wong, KP, Fung, CC 1993, ‘Simulated annealing based economic dispatch algorithm’, IEE Proceeding, vol.140, no.6, pp.509-515.
7. Goldberg, DE 1989, Genetic Algorithm in Search: Optimization and Machine Learning, Addison- Wesley.

8. Chen, PH & Chang, HC 1995, ‘Large scale economic dispatch by genetic algorithm’, IEEE Transaction on Power Systems,vol.10, no.4, pp.1919-1926.
9. Jasper, J, Sivakumar, RS, Victoire, T, & Deepa, SN 2012, ‘Cost Optimization of Power Generation Using a Differential Evolution Algorithm Enhanced with Neighbourhood Search Operation’, International Review of Electrical Engineering,vol.7,no.5,pp.5854-5865.
10. Jeyakumar, DN, Jayabarathi, T & Raghunathan, T 2006, ‘Particle swarm optimization for various types of economic
dispatch problems’, International Journal of Electrical Power & Energy Systems, vol.28, no.1, pp.36–42.
11. Wong, KP & Yuryevich, J 1998, ‘Evolutionary-programming-based algorithm for environmentally-constrained
economic dispatch’, IEEE Transaction on Power Systems, vol.13, no.2, pp.301-306.
12. Yang, X.-S., 2012. Flower Pollination Algorithm for Global Optimiza-tion. Unconventional Computation and Natural
Computation.Springer, Berlin Heidelberg, pp. 240—249.
13. Dhayalini.K, Sathiyamoorthy.s, Christober Asir Rajan.C ‘Particle Swarm Optimization for the coordination of optimal wind and thermal generation dispatch’, International Review of Electrical Engineering, vol.8, no.6, 2013, pp.1843-1849.
14. Juliana, CR & Sauer, IL 2013, ‘An assessment of wind power prospects in the Brazilian hydrothermal system’,
Renewable and Sustainable Energy Reviews, vol.19, pp.742–753.
15. Wood, AJ & Wollenberg, BF 1996, ‘Power generation operation and control, 2nd edition. New York: Wiley.
16. Yao, DL, Choi, S, Tseng, KJ & Lie, TT 2012, ‘Determination of Short-Term Power Dispatch Schedule for a Wind
Farm Incorporated With Dual-Battery Energy Storage Scheme’, IEEE Transaction on Sustainable energy, vol.3,
no.1, pp.74- 84.
17 Jiejin, C, Xiaoqian, M, Lixiang, L & Haipeng, P 2007, ‘Chaotic particle swarm optimization for economic dispatch
considering the generator constraints’, Energy Conversion Management, vol.48, pp. 645-653.
18. Nidul Sinha, B & Purkayastha 2004, ‘PSO embedded evolutionary programming technique for non-convex economic
load dispatch’, Power Systems Conference and Exposition, IEEE PES.
A

Downloads

Published

2016-12-16

How to Cite

Dhayalini, K. (2016). Optimization of Wind Thermal Coordination Dispatch using Flower Pollination Algorithm. JOURNAL OF ADVANCES IN CHEMISTRY, 12(16), 4963–4970. https://doi.org/10.24297/jac.v12i16.978

Issue

Vol. 12 No. 16 (2016)

Section

Articles

License

Creative Commons License All articles published in Journal of Advances in Linguistics are licensed under a Creative Commons Attribution 4.0 International License.