NEW DEVELOPMENT OF ANALYSIS TOOL FOR OPTIMIZING GENERATION COST WITH GAS EMISSION VIA AN ELECTROMAGNETISM LIKE ALGORITHM

Authors

  • F.Y.C. Albert Electrical & Electronics Dept., UCSI University, Cheras, Kuala Lumpur,Malaysia
  • S.P. Koh Power Engineering Center, University Tenaga Nasional, Kajang, Selangor, Malaysia
  • C. P. Chen Center of System and Machine Intelligence, University Tenaga Nasional, Kajang, Selangor, Malaysia
  • S. K. Tiong Power Engineering Center, University Tenaga Nasional, Kajang, Selangor, Malaysia

DOI:

https://doi.org/10.11113/jt.v78.8939

Keywords:

, Generation cost, emission gas, electromagnetism-like algorithm, optimization

Abstract

This paper addresses the preliminary new development results of the evolutionary algorithm technique to optimize the formulated problems incorporating the generation cost with emission gas as objective function or constraints. The power generation cost with emission gas are a complex problem which also the major concerns in electric power generation systems in the Environmental or Economic Dispatch Problems (EDP). Thus, due to environmental concern the electrical utilities required to minimize the emission level while optimizing the thermal generating units at a minimum generating cost and hence, satisfying the load demand and the emissions. In this work the electromagnetism-Like algorithm (EML) has been employed for optimizing generation cost and emission constraints economic dispatch problem. The proposed decision analysis tool software in this work will optimize the generation cost with emission gas objective function. The best generation cost with emission gas solution are obtained from different fuel technology via the developed software.

 

References

Arya, L.D.; Chouble, S.C.; Kothari, D.P., 1997. Emission Constrained Secure Economic Dispatch, International Journal Of Electrical Power & Energy Systems.19(5): 279-285.

Liang, Zi-xiong; Duncan Glover, J., 1992. A Zoom Feature For A Dynamic Programming Solution To Economic Dispatch Including Transmission Losses. IEEE Transaction On Power Systems. 7(2): 544-550 .

Lung, Chung; Chen; Chen, Nanming, 2011. Direct Search Method For Solving Economic Dispatch Problem Considering Transmission Capacity Constraints IEEE Transanction On Power Systems. 16(4): 764-769.

Kumar, Sushil; Naresh, R., 2009. Non Convex Economic Load Dispatch Using An Efficient Real Coded Genetic Algorithm. Applied Soft Computing. 9(1): 321-329.

Orike; Corne, S.; D.W., 2012. Improved Evolutionary Algorithms For Economic Load Dispatch Optimization Problems. IEEE Conference On Computational Intelligence: 1-8.

Vlachos, A.; Petikas, I.; Kyriakides, S., 2011. Economic Load Dispatch Problem Based On A Memetic Algorithm. Journal Of Statistics And Management System.14(5): 975-993.

Vanaja, B.; Hemamdini, S.; Sishaj P., 2008. Artifical Immune Based Economic Load With Value Point Effect. IEEE Conference on TENCON 2008. 1-8.

Kumano, T., 2011. A Functional Optimization Based Dynamic Economic Load Dispatch Considering Ramping Rate Of Thermal Units Output, IEEE Conference And Exposition On Power Systems. 1-8.

Da Silva, I.N.; Nepomuceno, L., 2001. An Efficient Neural Approach To Economic Load Dispatch In Power System, Power Engineering Society Summer Meeting. 2: 1269-1279.

Panigrahi, B.K.; Yadav, S.R.; Aggarwal, Shubham.; Tiwari, M.K., 2007. A Clonal Algorithm To Solve Economic Load Dispatch. Electric Power Systems Research. 77(10): 1381- 1389.

Zhisheng, Zhang., 2010. Quantum-Behaved Particle Swarm Optimization Algorithm For Economic Load Dispatch Of Power System. Expert Systems With Applications. 37(2): 1800-1803.

Hosseinnezhad, Vahid.; Babaei, Ebrahim., 2013. Economic load dispatch using θ-PSO. International Journal Of Electrical Power & Energy Systems. 49: 160-169.

Lee, K.Y.; Sode-yome, A.; Park, J.H., 1998. Adaptive Hopfield Neural Networks For Economic Load Dispatch. IEEE Transactions On Power Systems.13(2): 519-526.

Mandal, Barun; Kumar, Roy, Provas; Mandal, Sanjoy., 2014. Economic Load Dispatch Using Krill Herd Algorithm. International Journal Of Electrical Power & Energy Systems. 57: 1-10.

Dos, Leandro.; Coelho, Santos.; Lee, Chu-Sheng., 2008. Solving Economic Load Dispatch Problems In Power Systems Using Chaotic And Gaussian Particle Swarm Optimization Approaches. International Journal Of Electrical Power & Energy Systems. 30(5): 297-307.

Birbil S. I. and Fang S. C., 2003. An Electromagnetism-Like Mechanism for Global Optimization. Journal of Global Optimization. 25(3): 263-282.

Lin J.L., Wu C.H. and Chung H.Y., 2012. Performance Comparison of Electromagnetism-Like Algorithm for Global Optimization, Applied Mathematics, , 3: 1265-1275.

Yurtkuran A. and Emel E., 2010. A New Hybrid Electromagnetism-Like Algorithm for Capacitated Vehicle Routing Problems. Expert Systems with Applications. 37(4): 3427-3433.

Su C. T. and Lin H. C., 2011. Applying Electromagnetism-Like Mechanism for Feature Selection. Information Sciences. 181(5): 972-986.

Debels D., De Reyck B., Leus R., et al., 2006. A Hybrid Scatter Search/Electromagnetism Meta-Heuristic for Project Scheduling. European Journal of Operational Research. 169(2): 638-653.

Chang P. C., Chen S. H. and Fan C. Y., 2009. A Hybrid Electromagnetism-Like Algorithm for Single Machine Scheduling Problem. Expert Systems with Applications. 36(2): 1259-1267.

Naderi B., Tavakkoli-Moghaddam R. and Khalili M., 2010. Electromagnetism-Like Mechanism and Simulated Annealing Algorithms for Flowshop Scheduling Problems Minimizing the Total Weighted Tardiness and Makespan.†Knowledge-Based Systems. 23(2): 77-85.

Rocha A. M. A. C. and Fernandes E. M. G. P., 2009. Hybridizing the Electromagnetism-like Algorithm with Descent Search for Solving Engineering Design Problems. International Journal of Computer Mathematics. 86(10-11): 1932-1946.

STEEN M.,2000. Greenhouse Gas Emissions from Fossil Fuel Fired Power Generation Systems, The Energy Technology Observatory (ETO) at the Institute for Advanced Materials of the DG-JRC: 11.

Transparent Cost Database. 2015. Open Energy Information (en). Accessed Nov 1, 2015: http://en.openei.org/wiki/Transparent_Cost_Database

Downloads

Published

2016-06-08

How to Cite

NEW DEVELOPMENT OF ANALYSIS TOOL FOR OPTIMIZING GENERATION COST WITH GAS EMISSION VIA AN ELECTROMAGNETISM LIKE ALGORITHM. (2016). Jurnal Teknologi, 78(6-3). https://doi.org/10.11113/jt.v78.8939