Combined heat and power economic dispatch problem using firefly algorithm

Afshin YAZDANI, T. JAYABARATHI, V. RAMESH, T. RAGHUNATHAN

Front. Energy ›› 2013, Vol. 7 ›› Issue (2) : 133-139.

PDF(147 KB)
PDF(147 KB)
Front. Energy ›› 2013, Vol. 7 ›› Issue (2) : 133-139. DOI: 10.1007/s11708-013-0248-8
RESEARCH ARTICLE
RESEARCH ARTICLE

Combined heat and power economic dispatch problem using firefly algorithm

Author information +
History +

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 to optimize the fuel cost is quite complex and several classical and meta-heuristic algorithms have been proposed earlier. This paper applies the firefly algorithm, which is inspired by the behavior of fireflies which attract each other based on their luminosity. The results obtained have been compared with those obtained by other methods earlier and showed a marked improvement over the earlier methods.

Keywords

combined heat and power (CHP) economic dispatch / meta-heuristic algorithm / firefly algorithm / cogeneration

Cite this article

Download citation ▾
Afshin YAZDANI, T. JAYABARATHI, V. RAMESH, T. RAGHUNATHAN. Combined heat and power economic dispatch problem using firefly algorithm. Front Energ, 2013, 7(2): 133‒139 https://doi.org/10.1007/s11708-013-0248-8

References

[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[5]
Wong K P, Algie C. Evolutionary programming approach for combined heat and power dispatch. Electric Power Systems Research, 2002, 61(3): 227–232
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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
CrossRef Google scholar
[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]
Yang X S. Firefly algorithms for multimodal optimization in stochastic algorithms: foundations and applications. SAGA 2009. Lecture Notes in Computer Science, 2009, 5792: 169–178
CrossRef Google scholar
[17]
Yang X S, Sadat Hosseini S S, Gandomi A H. Firefly Algorithm for solving non-convex economic dispatch problems with valve loading effect. Applied Soft Computing, 2012, 12(3): 1180–1186
CrossRef Google scholar
[18]
Apostolopoulos T, Vlachos A. Application of the firefly algorithm for solving the economic emissions load dispatch problem. International Journal of Combinatorics, 2011, 2011: 1–23
CrossRef Google scholar
[19]
Rampriya B, Mahadevan K, Kannan S. Unit commitment in deregulated power system using Lagrangian firefly algorithm. In: Proceedings of 2010 IEEE International Conference on Communication Control and Computing Technologies (ICCCCT), Ramanathapuram, India, 2010, 389–393
[20]
Horng M H, Liou R J. Multilevel minimum cross entropy threshold selection based on the firefly algorithm. Expert Systems with Applications, 2011, 38(12): 14805–14811
CrossRef Google scholar
[21]
Dos Santos Coelho L, de Andrade Bernert D L, Mariani V C. A chaotic firefly algorithm applied to reliability-redundancy optimization. In: Proceedings of 2011 IEEE Congress on Evolutionary Computation (CEC), New Orleans, USA, 2011, 517–521
[22]
Gandomi A H, Yang X-S, Alavi A H. Mixed variable structural optimization using firefly algorithm. Computers and Structures, 2011, 89(23,24): 2325–2336
[23]
Horng M H. Vector quantization using the firefly algorithm for image compression. Expert Systems with Applications, 2012, 39(1): 1078–1091
CrossRef Google scholar
[24]
Senthilnath J, Omkar S N, Mani V. Clustering using firefly algorithm: Performance study. Swarm and Evolutionary Computation, 2011, 1(3): 164–171
CrossRef Google scholar

Acknowledgements

Gratitude goes to the Chancellor, Vice-Chancellor and Vice-Presidents of VIT University, Vellore, for providing the excellent infrastructure facilities and encouragement which have made this research work possible.

RIGHTS & PERMISSIONS

2014 Higher Education Press and Springer-Verlag Berlin Heidelberg
AI Summary AI Mindmap
PDF(147 KB)

Accesses

Citations

Detail

Sections
Recommended

/