Please wait a minute...
Frontiers in Energy

ISSN 2095-1701

ISSN 2095-1698(Online)

CN 11-6017/TK

邮发代号 80-972

2019 Impact Factor: 2.657

Frontiers in Energy  2014, Vol. 8 Issue (1): 25-30   https://doi.org/10.1007/s11708-013-0276-4
  RESEARCH ARTICLE 本期目录
Combined heat and power economic dispatch problem using the invasive weed optimization algorithm
Combined heat and power economic dispatch problem using the invasive weed optimization algorithm
T. JAYABARATHI(), Afshin YAZDANI, V. RAMESH, T. RAGHUNATHAN
School of Electrical Engineering, VIT University, Vellore 632014, India
 全文: PDF(138 KB)   HTML
Abstract

Cogeneration units which produce both heat and electric power are found in many process industries. These industries also consume heat directly in addition to electricity. The cogeneration units operate only within a feasible zone. Each point within the feasible zone consists of a specific value of heat and electric power. These units are used along with other units which produce either heat or power exclusively. Hence the economic dispatch problem for these plants optimizing the fuel cost is quite complex and several classical and meta-heuristic algorithms have been proposed earlier. This paper applies the invasive weed optimization algorithm which is inspired by the ecological process of weed colonization and distribution. The results obtained have been compared with those obtained by other methods earlier and showed a marked improvement over earlier ones.

Key wordscombined heat and power (CHP)    economic dispatch    meta-heuristic algorithm    invasive weed optimization    cogeneration
收稿日期: 2013-02-15      出版日期: 2014-03-05
Corresponding Author(s): JAYABARATHI T.,Email:tjayabarathi@vit.ac.in   
 引用本文:   
. Combined heat and power economic dispatch problem using the invasive weed optimization algorithm[J]. Frontiers in Energy, 2014, 8(1): 25-30.
T. JAYABARATHI, Afshin YAZDANI, V. RAMESH, T. RAGHUNATHAN. Combined heat and power economic dispatch problem using the invasive weed optimization algorithm. Front Energ, 2014, 8(1): 25-30.
 链接本文:  
https://academic.hep.com.cn/fie/CN/10.1007/s11708-013-0276-4
https://academic.hep.com.cn/fie/CN/Y2014/V8/I1/25
Fig.1  
Fig.2  
MethodOptimal resultsCost/$
P1P2H2P3H3H4
IGA_MU [15]0.00160.0039.9940.0075.000.009257.07
LR [2]0.00160.0040.0040.0075.000.009257.07
ACSA [11]0.08150.9348.8449.0065.790.379452.20
GT [10]0.00157.9226.0042.08 a89.00 a0.009207.64
HS [3]0.00160.0040.0040.0075.000.009257.07
Proposed IWO algorithm0.0002159.999840.0040.0075.000.009257.08
Tab.1  
Fig.3  
Fig.4  
Fig.5  
Fig.6  
CasesMethodDemandUnit 1Unit 2Unit 3Unit 4Unit 5Cost/$
PdHdP1P2H2P3H3P4H4H5
1HS [3]300150134.7448.2081.0916.2323.92100.856.2938.7013723.20
IWO134.7340.0075.0020.8637.6104.410.0037.413683.65
2HS [3]250175134.6752.9985.6910.1139.7352.234.1845.4012284.45
IWO134.5940.0075.0010.9438.9864.478.8152.2112134.33
Tab.2  
Fig.7  
Fig.8  
Fig.9  
Fig.10  
1 Rooijers F J, van Amerongen R A M. Static economic dispatch for co-generation systems. IEEE Transactions on Power Systems , 1994, 9(3): 1392–1398
doi: 10.1109/59.336125
2 Guo T, Henwood M I, van Ooijen M. An algorithm for combined heat and power economic dispatch. IEEE Transactions on Power Systems , 1996, 11(4): 1778–1784
doi: 10.1109/59.544642
3 Vasebi A, Fesanghary M, Bathaee S M T. Combined heat and power economic dispatch by harmony search algorithm. International Journal of Electrical Power & Energy Systems , 2007, 29(10): 713–719
doi: 10.1016/j.ijepes.2007.06.006
4 Khorram E, Jaberipour M. Harmony search algorithm for solving combined heat and power economic dispatch problems. Energy Conversion and Management , 2011, 52(2): 1550–1554
doi: 10.1016/j.enconman.2010.10.017
5 Wong K P, Algie C. Evolutionary programming approach for combined heat and power dispatch. Electric Power Systems Research , 2002, 61(3): 227–232
doi: 10.1016/S0378-7796(02)00028-7
6 Wang L F, Singh C. Stochastic combined heat and power dispatch based on multi-objective particle swarm optimization. International Journal of Electrical Power & Energy Systems , 2008, 30(3): 226–234
doi: 10.1016/j.ijepes.2007.08.002
7 Subbaraj P, Rengaraj R, Salivahanan S. Enhancement of combined heat and power economic dispatch using self adaptive real-coded genetic algorithm. Applied Energy , 2009, 86(6): 915–921
doi: 10.1016/j.apenergy.2008.10.002
8 Sinha N, Bhattacharya T. Genetic Algorithms for non-convex combined heat and power dispatch problems. In: Proceedings of TENCON 2008–2008 IEEE Region 10 Conference , Hyderabad, India, 2008, 1–5
9 Sinha N, Saikia L C, Malakar T. Optimal solution for non-convex combined heat and power dispatch problems using differential evolution. In: Proceedings of 2010 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC) , Coimbatore, India, 2010, 1–5
10 Sudhakaran M. Slochanal S M R. Integrating genetic algorithms and tabu search for combined heat and power economic dispatch. In: Proceedings of TENCON 2003-Conference on Convergent Technologies for Asia-Pacific Region , Bangalore, India, 2003, 67–71
11 Song Y H, Chou C S, Stonham T J. Combined heat and power economic dispatch by improved ant colony search algorithm. Electric Power Systems Research , 1999, 52(2): 115–121
doi: 10.1016/S0378-7796(99)00011-5
12 Basu M. Bee colony optimization for combined heat and power economic dispatch. Expert Systems with Applications , 2011, 38(11): 13527–13531
13 Rong A, Lahdelma R. Efficient algorithms for combined heat and power production planning under the deregulated electricity market. European Journal of Operational Research , 2007, 176(2): 1219–1245
doi: 10.1016/j.ejor.2005.09.009
14 Hosseini S S S, Jafarnejad A, Behrooz A H, Gandomi A H. Combined heat and power economic dispatch by mesh adaptive direct search algorithm. Expert Systems with Applications , 2011, 38(6): 6556–6564
doi: 10.1016/j.eswa.2010.11.083
15 Su C T, Chiang C L. An incorporated algorithm for combined heat and power economic dispatch. Electric Power Systems Research , 2004, 69(2,3): 187–195
16 Mehrabian A R, Lucas C. A novel numerical optimization algorithm inspired from weed colonization. Ecological Informatics , 2006, 1(4): 355–366
doi: 10.1016/j.ecoinf.2006.07.003
17 Ghosh A, Das S, Chowdhury A, Giri R. An ecologically inspired direct search method for solving optimal control problems with Bézier parameterization. Engineering Applications of Artificial Intelligence , 2011, 24(7): 1195–1203
doi: 10.1016/j.engappai.2011.04.005
18 Mehrabian A R, Yousefi-Koma A. A novel technique for optimal placement of piezoelectric actuators on smart structures. Journal of the Franklin Institute , 2011, 348(1): 12–23
doi: 10.1016/j.jfranklin.2009.02.006
19 Basak A, Pal S, Das S, Abraham A, Snasel V. A modified invasive weed optimization algorithm for time-modulated linear antenna array synthesis. In: Proceedings of IEEE Congress on Evolutionary Computation (CEC) . Barcelona, Spain, 2010, 1–8
20 Kundu D, Suresh K, Ghosh S, Das S, Panigrahi B K, Das S. Multi-objective optimization with artificial weed colonies. Information Sciences , 2011, 181(12): 2441–2454
doi: 10.1016/j.ins.2010.09.026
21 Sedighy S H, Mallahzadeh A R, Soleimani M, Rashed-Mohassel J. Optimization of printed Yagi antenna using invasive weed optimization (IWO). IEEE Antennas and Wireless Propagation Letters , 2010, 9: 1275–1278
doi: 10.1109/LAWP.2011.2105458
22 Hajimirsadeghi H, Lucas C. A hybrid IWO/PSO algorithm for fast and global optimization. In: Proceedings of IEEE EUROCON 2009, St. Petersburg, Russia , 2009, 1964–1971
23 Giri R, Chowdhury A, Ghosh A, Das S, Abraham A, Snasel V. A modified invasive weed optimization algorithm for training of feed-forward neural networks. In: Proceedings of 2010 IEEE International Conference on Systems Man and Cybernetics (SMC) . Istanbul, Turkey, 2010, 3166–3173
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed