Combined Economic and Emission Dispatch Solution using Artificial Bee Colony Algorithm with Fuzzy Approach

  • Authors

    • M N. Abdullah
    • G Y. Sim
    • A Azmi
    • S H. Shamsudin
    2018-08-13
    https://doi.org/10.14419/ijet.v7i3.15.17405
  • Artificial Bee Colony Algorithm, Best Compromise Solution, Combined Economic and Emission Dispatch, Fuzzy Approach

  • The cost and emission minimization in power system operation become important issue in power dispatch due to increase of environmental pollution and fossil fuel price. Therefore, combined economic and emission dispatch (CEED) must be considered in generation scheduling in order to provide balanced solution for optimal cost and emissions level of power generation. In this paper, an Artificial Bee Colony (ABC) algorithm with Fuzzy best compromise solution is proposed to determine the optimal cost and emission level by converting the multi-objective (cost and emission) into single objective problem using weighted sum method approach. The best compromise solution among Pareto front solution was determined by fuzzy approach. The effectiveness of ABC algorithm has been validated in terms of the best solution, convergence behaviour and consistency for power system benchmark such as IEEE 30-bus 6-unit system and 10-unit system. The comparison study shows that ABC algorithm capable to obtain a better performance of minimizing the cost and emission level in power generation.

     

     

  • References

    1. [1] Murugan R, Mohan MR. Modified Artificial Bee Colony Algorithm For Solving Economic Dispatch Problem 2012;7.

      [2] Secui DC. A new modified artificial bee colony algorithm for the economic dispatch problem. Energy Convers Manag 2015;89:43–62. doi:10.1016/j.enconman.2014.09.034.

      [3] Secui DC. The chaotic global best artificial bee colony algorithm for the multi-area economic/emission dispatch. Energy 2015;93:2518–45. doi:10.1016/j.energy.2015.10.012.

      [4] Abedinia O, Garmarodi D, Rahbar R, Javidzadeh F. Multi-objective Environmental/Economic Dispatch Using Interactive Artificial Bee Colony Algorithm. J Basic Appl Sci Res 2012;2:11272–81.

      [5] Shilaja C, Ravi K. Optimization of emission/economic dispatch using euclidean affine flower pollination algorithm (eFPA) and binary FPA (BFPA) in solar photo voltaic generation. Renewable Energy 2017;107:550–66. doi:10.1016/j.renene.2017.02.021.

      [6] Liang H, Liu Y, Li F, Shen Y. A multiobjective hybrid bat algorithm for combined economic/emission dispatch. International Journal of Electrical Power & Energy System 2018;101:103–15. doi:10.1016/j.ijepes.2018.03.019.

      [7] Benasla L, Belmadani A, Rahli M. Spiral Optimization Algorithm for solving Combined Economic and Emission Dispatch. International Journal of Electrical Power & Energy System 2014;62:163–74. doi:10.1016/j.ijepes.2014.04.037.

      [8] Abdelaziz AY, Ali ES, Abd Elazim SM. Flower pollination algorithm to solve combined economic and emission dispatch problems. Eng Sci Technol an Int J 2016;19:980–90. doi:10.1016/j.jestch.2015.11.005.

      [9] Zhou J, Wang C, Li Y, Wang P, Li C, Lu P, et al. A multi-objective multi-population ant colony optimization for economic emission dispatch considering power system security. Appl Math Model 2017;45:684–704. doi:10.1016/j.apm.2017.01.001.

      [10] Aydin D, Özyön S, Yaşar C, Liao T. Artificial bee colony algorithm with dynamic population size to combined economic and emission dispatch problem. Int J Electr Power Energy Syst 2014;54:144–53. doi:http://dx.doi.org/10.1016/j.ijepes.2013.06.020.

      [11] Abdullah MN, Tawai R, Yousof MF. Comparison of Constraints Handling Methods for Economic Load Dispatch Problem using Particle Swarm Optimization Algorithm. Int J Adv Sci Eng Inf Technol 2017;7:1322–7.

      [12] Modiri-Delshad M, Rahim NA. Multi-objective backtracking search algorithm for economic emission dispatch problem. Appl Soft Comput J 2016;40:479–94. doi:10.1016/j.asoc.2015.11.020.

      [13] Chandrasekaran K, Simon SP. Multi-objective unit commitment problem with reliability function using fuzzified binary real coded artificial bee colony algorithm. IET Generation Transmission & distribution 2012;6:1060–73.

      [14] Abdelaziz AY, Ali ES, Abd Elazim SM. Flower pollination algorithm to solve combined economic and emission dispatch problems. Eng Sci Technol an Int J 2016;19:980–90. doi:10.1016/j.jestch.2015.11.005.

      [15] Gopalakrishnan R, Krishnan A. Intelligence technique to solve combined economic and emission dispatch. Int. Conf. Pattern Recognition, Informatics Med. Eng., IEEE; 2012, p. 347–52. doi:10.1109/ICPRIME.2012.6208370.

      [16] Karaboga D. An Idea Based On Honey Bee Swarm For Numerical Optimization (Technical Report-TR06, OCTOBER, 2005) 2005.

      [17] de Athayde Costa e Silva M, Klein CE, Mariani VC, Dos Santos Coelho L. Multiobjective scatter search approach with new combination scheme applied to solve environmental/economic dispatch problem. Energy 2013;53:14–21. doi:10.1016/j.energy.2013.02.045.

      [18] Hota PK, Barisal AK, Chakrabarti R. Economic emission load dispatch through fuzzy based bacterial foraging algorithm. International Journal of Electrical Power & Energy System 2010;32:794–803. doi:http://dx.doi.org/10.1016/j.ijepes.2010.01.016.

      [19] Wu LH, Wang YN, Yuan XF, Zhou SW. Environmental / economic power dispatch problem using multi-objective differential evolution algorithm. Electrical Power System Research 2010;80:1171–81. doi:10.1016/j.epsr.2010.03.010.

      [20] Roy PK, Bhui S. Electrical Power and Energy Systems Multi-objective quasi-oppositional teaching learning based optimization for economic emission load dispatch problem. International Journal of Electrical Power & Energy System 2013;53:937–48. doi:10.1016/j.ijepes.2013.06.015.

      [21] Bhattacharjee K, Bhattacharya A, Halder S. Electrical Power and Energy Systems Solution of Economic Emission Load Dispatch problems of power systems by Real Coded Chemical Reaction algorithm. International Journal of Electrical Power & Energy System 2014;59:176–87. doi:10.1016/j.ijepes.2014.02.006.

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  • How to Cite

    N. Abdullah, M., Y. Sim, G., Azmi, A., & H. Shamsudin, S. (2018). Combined Economic and Emission Dispatch Solution using Artificial Bee Colony Algorithm with Fuzzy Approach. International Journal of Engineering & Technology, 7(3.15), 46-51. https://doi.org/10.14419/ijet.v7i3.15.17405