A Novel Combined Economic and Emission Dispatch Control by Hybrid Particle Swarm Optimization Technique

Jothi Swaroopan, N.M

doi:10.1234/mjee.v4i2.238

Document Type : Review Article

Author

N.M Jothi Swaroopan

https://doi.org/10.1234/mjee.v4i2.238

Abstract

The problem of Economic Dispatch (ED) in electric power systems is to schedule the power output for each committed generator unit such that the operating cost is minimized and simultaneously, the customer load demand is matched and the generator operating limits are met. Nowadays with increasing awareness of environmental pollution caused by burning of fossil fuels, emission of pollutants is also a criterion for economic dispatch of the plants. The environmental objective of generation dispatch is to minimize the total environmental cost or the total pollutant emission. This paper presents an efficient and simple approach for solving the emission constrained economic dispatch problem using the proposed Hybrid Particle Swarm Optimization Technique (HPSO). The convergence and usefulness of the proposed HPSO is demonstrated through its application to a test system. The computational results reveal that the proposed algorithm has an excellent convergence characteristic and has the potential to apply to other power system problems.

Keywords

References

[1] Chowdhury B.H. and Rahman S.; “A Review of Recent Advances in Economic Dispatch”, IEEE Trans.on power systems, Vol. 5, No. 4, pp.1248 -1259, (1990)

[2] Singh S.N. and Erlich I.; “Particle Swarm Based Optimal Estimation of Block Incremental Cost Curve”, The 14th International Conference on Intelligent System Application to Power System, Kaohsiung Taiwan, pp. 257-263, (November 2007)

[3] Thanushkodi Vinodh R.; “An Efficient Particle Swarm Optimization for Economic Dispatch with Valve-Point Effect” Applied Computing Conference, Istanbul Turkey, pp. 182-187, (May 2008)

[4] Park Jong-Bae and Jeong Yun-Won; “An Improved Particle Swarm Optimization for Economic Dispatch with Valve-Point Effect”, International journal of Innovation in Energy Systems and Power, Vol. 1, No. 1, pp. 1-7, (November 2006)

[5] Al-Hamouz Z. and Al-Sharif S.; “Application of Particle Swarm Optimization Algorithm for Optimal Reactive Power Planning, Control and Intelligent System”, Control and Intelligent Systems, Vol. 35, No. 2, pp. 66-72, (2007)

[6] Talaq J.H., El Hawary F. and Hawray M.E. El; “A Summary of Environmental/Economic Dispatch Algorithms”, IEEE Trans. on Power systems, Vol. 9, No. 3, pp.1508-1516, (1994)

[7] Eberhart R.C. and J. Kennedy; “Particle Swarm Optimization”. Proc. IEEE Int. Conf. Neural Netw., Vol. 4, pp. 1942–1948, (1995)

[8] Eberhart R. C. and Shi Y.; “Comparison Between Genetic Algorithms and Particle Swarm Optimization”, IEEE Int. Conf. Evolutionary Compututation, pp 611–616, (1998)

[9] Shi Y. and Eberhart R. C.; “Empirical Study of Particle Swarm Optimization”, Proc. IEEE Int. Congr. Evolutionary Computation, Vol. 3, pp. 101–106, (1999)

[10] Mendes R., Kennedy J. and Neves J.; “The Fully Informed Particle Swarm: Simpler, May Be Better”, IEEE Trans. Evol. Comput., Vol. 8, No. 3, pp. 204–210, (2004)

[11] Van Den Bergh F. and Engel Brecht A. P.; “A Cooperative Approach to Particle Swarm Optimization”, IEEE Trans. Evol. Comput., Vol. 8, No. 3, pp. 225–239, (2004)

[12] Gaing Z. L.; “Particle Swarm Optimization to Solving The Economic Dispatch Considering The Generator Constraints”, IEEE Trans. Power Syst., Vol. 18, No. 3, pp. 1187–1195, (2003)

[13] Abido M.A; “Optimal Power Flow Using Particle Swarm Optimization”, Electrical Power and Energy Systems, Vol. 24, pp. 563-571, (2002)

[14] Ahmed A.A.E, Germano L.T. and Antonio Z.C; “A Hybrid Particle Swarm Optimization To Loss Power Minimization”, IEEE Transaction of power system, Vol. 20, No. 2, pp.859-866, (may 2005)

[15] Park J.B., Lee K.S., Shin J.R. and Lee K.Y.; “A Particle Swarm Optimization For Economic Dispatch With Non Smooth Cost Functions”, IEEE Trans. Power Syst., Vol. 20, No. 1, pp. 34–42, (2005)

[16] Yang H.T., Yang P.C. and Huang C.L; “Evolutionary Programming Based Economic Dispatch for Units With Non-Smooth Fuel Cost Functions”, IEEE Trans. Power Systems, Vol. 11, No. 1, pp. 112-118, (February 1996)

Majlesi Journal of Electrical Engineering

A Novel Combined Economic and Emission Dispatch Control by Hybrid Particle Swarm Optimization Technique

References

References

Volume 4, Issue 2 - Serial Number 2
June 2010
Pages 19-24

A Novel Combined Economic and Emission Dispatch Control by Hybrid Particle Swarm Optimization Technique

References

References

Volume 4, Issue 2 - Serial Number 2June 2010Pages 19-24

Volume 4, Issue 2 - Serial Number 2
June 2010
Pages 19-24