Artificial bee colony optimization for economic dispatch with valve point effect

doi:10.1007/s11708-014-0316-8

Front. Energy

2014, Vol. 8

Issue (4) : 449-458 https://doi.org/10.1007/s11708-014-0316-8

RESEARCH ARTICLE

Artificial bee colony optimization for economic dispatch with valve point effect

Yacine LABBI^1,^*(

),Djilani Ben ATTOUS¹,Belkacem MAHDAD²

1. Department of Electrical Engineering, University of El-Oued, El-Oued 39014, Algeria
2. Department of Electrical Engineering, University of Biskra, Biskra 07000, Algeria

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Abstract

In recent years, various heuristic optimization methods have been proposed to solve economic dispatch (ED) problem in power systems. This paper presents the well-known power system ED problem solution considering valve-point effect by a new optimization algorithm called artificial bee colony (ABC). The proposed approach has been applied to various test systems with incremental fuel cost function, taking into account the valve-point effects. The results show that the proposed approach is efficient and robust when compared with other optimization algorithms reported in literature.

Keywords artificial bee colony (ABC) algorithm economic dispatch (ED) valve-point effect optimization

Corresponding Author(s): Yacine LABBI

Just Accepted Date: 09 October 2014 Online First Date: 24 November 2014 Issue Date: 09 January 2015

Cite this article:

Yacine LABBI,Djilani Ben ATTOUS,Belkacem MAHDAD. Artificial bee colony optimization for economic dispatch with valve point effect[J]. Front. Energy, 2014, 8(4): 449-458.

URL:

https://academic.hep.com.cn/fie/EN/10.1007/s11708-014-0316-8
https://academic.hep.com.cn/fie/EN/Y2014/V8/I4/449

Fig.1 Fuel cost versus power output for 6 valve steam turbine units

Tab.1 Generator data of test system 1

Tab.2 Results obtained by proposed method for test system 1

Tab.3 Comparison of proposed method for test system 1

Fig.2 Convergence of fitness value with valve-point effects for load demand 850 MW

Fig.3 Distribution of objective function value for 30 trails for load demand 850 MW

Tab.4 Generator data of test system 2

Tab.5 Results obtained by proposed method for test system 2 (1800 MW)

Tab.6 Results obtained by proposed method for test case 2 (2520 MW)

Tab.7 Comparison of proposed method for test system 2 (1800 MW)

Fig.4 Convergence of fitness value with valve-point effects for load demand 1800 MW

Fig.5 Convergence of fitness value with valve-point effects for load demand 1800 MW

Tab.8 Comparison of proposed method for test case 2 (2520 MW)

Fig.6 Distribution of objective function value for 30 trails for load demand of 1800 MW

Fig.7 Distribution of objective function value for 30 trails for load demand of 2520 MW

Generator power output	ABC	NPSO-LRS [25]	NPSO [25]	MDE [26]	CBPSO-RVM [27]	FAPSO-NM [28]
P_g1/MWP_g2/MWP_g3/MWP_g4/MWP_g5/MWP_g6/MWP_g7/MWP_g8/MWP_g9/MWP_g10/MWP_g11/MWP_g12/MWP_g13/MWP_g14/MWP_g15/MWP_g16/MWP_g17/MWP_g18/MWP_g19/MWP_g20/MWP_g21/MWP_g22/MWP_g23/MWP_g24/MWP_g25/MWP_g26/MWP_g27/MWP_g28/MWP_g29/MWP_g30/MWP_g31/MWP_g32/MWP_g33/MWP_g34/MWP_g35/MWP_g36/MWP_g37/MWP_g38/MWP_g39/MWP_g40/MWTotal cost/($·h^–1)	110.7944110.791397.4473179.741787.8268139.9897259.5761284.5962284.5294130.0033168.790394.0010215.4183394.2843394.2274394.1741489.2802489.2863511.2606511.2471523.3126523.2619523.2069523.2790523.2828523.282810.003510.060110.006388.0050189.8676189.9970179.4734164.8527164.8280164.8093109.9733109.9999109.9544511.2777121479.6467	113.9761113.998697.4241179.732789.6511105.4044259.7502288.4534284.646204.812168.831194214.7663394.2852304.5187394.2811489.2807489.2832511.2845511.3049523.2916523.2853523.2797523.2994523.2865523.29361010.00011089.0139190190190199.9998165.1397172.027511011093.0962511.2996121664.43	113.9891113.633497.55180.005997140300300284.5797130.0517243.7131169.0104125393.9662304.7586304.512489.6024489.6087511.7903511.2624523.3274523.2196523.4707523.0661523.3978523.289710.020810.092710.062188.9456189.9951190190165.9825172.4153191.2978109.9893109.9521109.8733511.5671121704.73	110.831110.81597.399179.73487.808140259.6284.604284.601130168.799168.799214.759394.28394.28304.519489.279489.28511.28511.279523.279523.28523.28523.28523.281523.27910101092.645190190189.999164.831164.802164.805109.999109.999109.999511.278121414.79	11411497.4859179.733197140300300286.00791309494214.7598304.5196394.2794394.2794489.2794489.2794511.2794511.2794523.2796523.2794523.2797523.2802523.2795523.279410101097190190190200166.8603200110110110511.2794121555.32	111.38110.9397.41179.3389.22140259.62284.66284.66130168.82168.82214.75394.28304.54394.3489.29489.29511.28511.29523.33523.48523.33523.33523.33523.3310101088.7190190190165166165110110110511.3121418.3

Tab.9 Best power output for 40-generator system (Load = 10500 MW)

Tab.10 Comparison of results (load= 10500 MW)

Fig.8 Convergence of fitness value with valve-point effects for load demand 10500 MW

Fig.9 Distribution of objective function value for 30 trails for load demand 10500 MW

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