Dynamic Economic Dispatch for Combined Heat and Power (Steam and Gas) Units Using Seeker and Bacteria Foraging Optimization Algorithms

Mohamed Ahmed Sadeek Mohamed

doi:doi:10.11648/j.ajetm.20160102.12

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Dynamic Economic Dispatch for Combined Heat and Power (Steam and Gas) Units Using Seeker and Bacteria Foraging Optimization Algorithms

Mohamed Ahmed Sadeek Mohamed

Published in American Journal of Engineering and Technology Management (Volume 1, Issue 2)

Received: 13 July 2016 Accepted: 21 July 2016 Published: 6 August 2016

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Abstract

In this paper, combined heat and power units are incorporated in dynamic economic dispatch to minimize total production costs considering realistic constraints such as ramp rate and spinning reserve limits effects over a short time span. Three evolutionary approaches, namely seeker optimization Algorithm (SOA), Seeker optimization with inertia weight factor (SOAIW) and Bacteria Foraging Optimization Algorithms (BFOA) are successfully implemented to solve the combined heat and power economic dispatch (CHPED) problem. These approaches have been tested on 12-generation units system with two steam, four gas and six cogeneration units. In addition, the performance tests are applied to measure the actual power output and the fuel consumption in every point tests for achieving different curves such as input/output, incremental heat rate and heat rate curves for the twelve units. The results of the four approaches are compared to obtain the best solution. The results show that the seeker optimization with improved inertia weight is able to achieve the best solution at less computational time.

Published in	American Journal of Engineering and Technology Management (Volume 1, Issue 2)
DOI	10.11648/j.ajetm.20160102.12
Page(s)	12-24
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2016. Published by Science Publishing Group

Keywords

Combined Heat and Power Economic Dispatch (CHPED), Seeker Optimization Algorithm (SOA), Bacteria Foraging Optimization Algorithm (BFOA)

References

[1]	Niknam T, Kavousi Fard A, Baziar A. Multi-objective stochastic distribution feeder reconfiguration problem considering hydrogen and thermal energy production by fuel cell power plants. Energy June 2012; 42 (1): 563e73.
[2]	Rong A, Hakonen H, Lahdelma R. A dynamic regrouping based sequential dynamic programming algorithm for unit commitment of combined heat and power systems. Energy Convers Manage 2009; 50: 1108e15.
[3]	Liu C, Shahidehpour M, Li Z, Fotuhi-Firuzabad M. Component and mode models for the short-term scheduling of combined-cycle units. IEEE Trans Power Syst 2009; 24: 976e90.
[4]	Niknam T, Azizipanah-Abarghooee R, Roosta A, Amiri B. A new multi-objective reserve constrained combined heat and power dynamic economic emission dispatch. Energy 2012; 42: 530e45.
[5]	A. Rong, H. Hakonen, R. Lahdelma, “An Efficient Linear Model and Optimization Algorithm for Multisite Combined Heat and Power Production”, European Journal of Operational Research, Vol. 168, pp. 612-632, 2006.
[6]	K. Nekooei, M. M. Farsangi, H. Nezamabadi-pour, “An Improved Harmony Search Approach to Economic Dispatch”, International Journal on Technical and Physical Problems of Engineering (IJTPE), Issue 8, Vol. 3, No. 3, pp. 25-31, September 2011.
[7]	Y. H. Song, C. S. Chou, T. J. Stonham, “Combined Heat and Power Dispatch by Improved Ant Colony Search Algorithm”, Electric Power Systems Research, Vol. 52, pp. 115-121, 1999.
[8]	C. T. Su, C. L. Chiang, “An Incorporated Algorithm for Combined Heat and Power Economic Dispatch”, Electric Power Systems Research, Vol. 69, pp. 187-195, 2004.
[9]	A. Vasebi, M. Fesanghary, S. M. T. Bathaee, “Combined Heat and Power Economic Dispatch by Harmony Search Algorithm”, International Journal of Electrical Power Energy Systems, Vol. 29, pp. 713-719, 2007.
[10]	L. Wang, C. Singh, “Stochastic Combined Heat and Power Dispatch Based on Multi Objective Particle Swarm Optimization”, International Journal of Electrical Power Energy Systems, Vol. 30, pp. 226-234, 2008.
[11]	Moustafa YG, Mekhamer SF, Moustafa YG, EI-Sherif N, Mansour MM. A modified particle swarm optimizer applied to the solution of the economic dispatch problem. International conference on electrical, electronic, and computer engineering, ICEEC, Cairo, Egypt. pp. 724--31, 2004.
[12]	Park JB, Lee KS, Shin JR, Lee KY. A particle swarm optimization for economic dispatch with nonsmooth cost function. IEEE Trans Power Syst; pp. 20 (1): 34-42, 2005.
[13]	Eberhart RC, Kennedy, JF. A new optimizer using particle swarm theory. In: Proceedings of the 6th international symposium on micro machine and human science, Nagoya, Japan. pp. 39-43, 1 995.
[14]	M. fotuhi-firuzabab, R. Billinton. Asecurity based approach for generating unit scheduling, IEEE, power systems Research Group University of Saskatchewan Saskatoon, Canada.
[15]	Chaohua Dai, Yunfang Zhu and Weirong Chen. Seeker optimization algorithm, Lecture Notes in Artificial Intelligence, Y. Wang, Y. Cheung, and H. Liu (Eds.), Springer- Verlag Berlin Heidelberg: Revised selected paper from CIS 2006, pp. 167–176, 2007.
[16]	Vignesh Kumar, Ferat Sahin. Cognitive maps in swarm robots for the mine detection application. in Proc. of IEEE International Conference on Systems, Man and Cybernetics, 2003, vol. 4, pp. 3364-3369.
[17]	Eustace D, Barnes DP, Gray JO. Co-operant mobile robots for industrial applications. In Proc. of the Inter. Conf. on Industrial Electronics, Control, and Instrumentation, 1993, vol. 1, Maui, HI, USA, pp. 39-44.
[18]	James Kennedy. The particle swarm: Social adaptation of knowledge. In: Proceedings of IEEE International Conference on Evolutionary Computation, 1997, Indianapolis, IN, USA, pp. 303-308.
[19]	Kevin M. Passino, “Bacterial Foraging optimization,” International Journal of Swarm Intelligence Research, pp. 1-16, Jan-Mar 2010.
[20]	K. P Wong and J. Yuryevich, "Evolutionary Programming Based Algorithm for Environmentally Constrained Economic Dispatch", IEEE transaction on Power Systems”, Vol. 13, No. 2, pp 301, May 1998.
[21]	Stephens and J. Krebs, Foraging Theory. Princeton, NJ: Princeton Univ. Press, 1986.
[22]	P. S. R MURTY, O. U. Hyderabad. Operation and Control in Power System, Giriraj Lane, Sultan Bazar. 2008.
[23]	AIEE Working Group Report on Application of Incremental Heat Rates for Economic Dispatch of Power, AIEE publication S-104.

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APA Style

Mohamed Ahmed Sadeek Mohamed. (2016). Dynamic Economic Dispatch for Combined Heat and Power (Steam and Gas) Units Using Seeker and Bacteria Foraging Optimization Algorithms. American Journal of Engineering and Technology Management, 1(2), 12-24. https://doi.org/10.11648/j.ajetm.20160102.12

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ACS Style

Mohamed Ahmed Sadeek Mohamed. Dynamic Economic Dispatch for Combined Heat and Power (Steam and Gas) Units Using Seeker and Bacteria Foraging Optimization Algorithms. Am. J. Eng. Technol. Manag. 2016, 1(2), 12-24. doi: 10.11648/j.ajetm.20160102.12

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AMA Style

Mohamed Ahmed Sadeek Mohamed. Dynamic Economic Dispatch for Combined Heat and Power (Steam and Gas) Units Using Seeker and Bacteria Foraging Optimization Algorithms. Am J Eng Technol Manag. 2016;1(2):12-24. doi: 10.11648/j.ajetm.20160102.12

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@article{10.11648/j.ajetm.20160102.12,
  author = {Mohamed Ahmed Sadeek Mohamed},
  title = {Dynamic Economic Dispatch for Combined Heat and Power (Steam and Gas) Units Using Seeker and Bacteria Foraging Optimization Algorithms},
  journal = {American Journal of Engineering and Technology Management},
  volume = {1},
  number = {2},
  pages = {12-24},
  doi = {10.11648/j.ajetm.20160102.12},
  url = {https://doi.org/10.11648/j.ajetm.20160102.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajetm.20160102.12},
  abstract = {In this paper, combined heat and power units are incorporated in dynamic economic dispatch to minimize total production costs considering realistic constraints such as ramp rate and spinning reserve limits effects over a short time span. Three evolutionary approaches, namely seeker optimization Algorithm (SOA), Seeker optimization with inertia weight factor (SOAIW) and Bacteria Foraging Optimization Algorithms (BFOA) are successfully implemented to solve the combined heat and power economic dispatch (CHPED) problem. These approaches have been tested on 12-generation units system with two steam, four gas and six cogeneration units. In addition, the performance tests are applied to measure the actual power output and the fuel consumption in every point tests for achieving different curves such as input/output, incremental heat rate and heat rate curves for the twelve units. The results of the four approaches are compared to obtain the best solution. The results show that the seeker optimization with improved inertia weight is able to achieve the best solution at less computational time.},
 year = {2016}
}

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TY  - JOUR
T1  - Dynamic Economic Dispatch for Combined Heat and Power (Steam and Gas) Units Using Seeker and Bacteria Foraging Optimization Algorithms
AU  - Mohamed Ahmed Sadeek Mohamed
Y1  - 2016/08/06
PY  - 2016
N1  - https://doi.org/10.11648/j.ajetm.20160102.12
DO  - 10.11648/j.ajetm.20160102.12
T2  - American Journal of Engineering and Technology Management
JF  - American Journal of Engineering and Technology Management
JO  - American Journal of Engineering and Technology Management
SP  - 12
EP  - 24
PB  - Science Publishing Group
SN  - 2575-1441
UR  - https://doi.org/10.11648/j.ajetm.20160102.12
AB  - In this paper, combined heat and power units are incorporated in dynamic economic dispatch to minimize total production costs considering realistic constraints such as ramp rate and spinning reserve limits effects over a short time span. Three evolutionary approaches, namely seeker optimization Algorithm (SOA), Seeker optimization with inertia weight factor (SOAIW) and Bacteria Foraging Optimization Algorithms (BFOA) are successfully implemented to solve the combined heat and power economic dispatch (CHPED) problem. These approaches have been tested on 12-generation units system with two steam, four gas and six cogeneration units. In addition, the performance tests are applied to measure the actual power output and the fuel consumption in every point tests for achieving different curves such as input/output, incremental heat rate and heat rate curves for the twelve units. The results of the four approaches are compared to obtain the best solution. The results show that the seeker optimization with improved inertia weight is able to achieve the best solution at less computational time.
VL  - 1
IS  - 2
ER  -

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Author Information

Mohamed Ahmed Sadeek Mohamed

East Delta Electricity Production Company, Ismailia, Egypt

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APA Style

Mohamed Ahmed Sadeek Mohamed. (2016). Dynamic Economic Dispatch for Combined Heat and Power (Steam and Gas) Units Using Seeker and Bacteria Foraging Optimization Algorithms. American Journal of Engineering and Technology Management, 1(2), 12-24. https://doi.org/10.11648/j.ajetm.20160102.12

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ACS Style

Mohamed Ahmed Sadeek Mohamed. Dynamic Economic Dispatch for Combined Heat and Power (Steam and Gas) Units Using Seeker and Bacteria Foraging Optimization Algorithms. Am. J. Eng. Technol. Manag. 2016, 1(2), 12-24. doi: 10.11648/j.ajetm.20160102.12

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AMA Style

Mohamed Ahmed Sadeek Mohamed. Dynamic Economic Dispatch for Combined Heat and Power (Steam and Gas) Units Using Seeker and Bacteria Foraging Optimization Algorithms. Am J Eng Technol Manag. 2016;1(2):12-24. doi: 10.11648/j.ajetm.20160102.12

Copy | Download

@article{10.11648/j.ajetm.20160102.12,
  author = {Mohamed Ahmed Sadeek Mohamed},
  title = {Dynamic Economic Dispatch for Combined Heat and Power (Steam and Gas) Units Using Seeker and Bacteria Foraging Optimization Algorithms},
  journal = {American Journal of Engineering and Technology Management},
  volume = {1},
  number = {2},
  pages = {12-24},
  doi = {10.11648/j.ajetm.20160102.12},
  url = {https://doi.org/10.11648/j.ajetm.20160102.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajetm.20160102.12},
  abstract = {In this paper, combined heat and power units are incorporated in dynamic economic dispatch to minimize total production costs considering realistic constraints such as ramp rate and spinning reserve limits effects over a short time span. Three evolutionary approaches, namely seeker optimization Algorithm (SOA), Seeker optimization with inertia weight factor (SOAIW) and Bacteria Foraging Optimization Algorithms (BFOA) are successfully implemented to solve the combined heat and power economic dispatch (CHPED) problem. These approaches have been tested on 12-generation units system with two steam, four gas and six cogeneration units. In addition, the performance tests are applied to measure the actual power output and the fuel consumption in every point tests for achieving different curves such as input/output, incremental heat rate and heat rate curves for the twelve units. The results of the four approaches are compared to obtain the best solution. The results show that the seeker optimization with improved inertia weight is able to achieve the best solution at less computational time.},
 year = {2016}
}

Copy | Download

TY  - JOUR
T1  - Dynamic Economic Dispatch for Combined Heat and Power (Steam and Gas) Units Using Seeker and Bacteria Foraging Optimization Algorithms
AU  - Mohamed Ahmed Sadeek Mohamed
Y1  - 2016/08/06
PY  - 2016
N1  - https://doi.org/10.11648/j.ajetm.20160102.12
DO  - 10.11648/j.ajetm.20160102.12
T2  - American Journal of Engineering and Technology Management
JF  - American Journal of Engineering and Technology Management
JO  - American Journal of Engineering and Technology Management
SP  - 12
EP  - 24
PB  - Science Publishing Group
SN  - 2575-1441
UR  - https://doi.org/10.11648/j.ajetm.20160102.12
AB  - In this paper, combined heat and power units are incorporated in dynamic economic dispatch to minimize total production costs considering realistic constraints such as ramp rate and spinning reserve limits effects over a short time span. Three evolutionary approaches, namely seeker optimization Algorithm (SOA), Seeker optimization with inertia weight factor (SOAIW) and Bacteria Foraging Optimization Algorithms (BFOA) are successfully implemented to solve the combined heat and power economic dispatch (CHPED) problem. These approaches have been tested on 12-generation units system with two steam, four gas and six cogeneration units. In addition, the performance tests are applied to measure the actual power output and the fuel consumption in every point tests for achieving different curves such as input/output, incremental heat rate and heat rate curves for the twelve units. The results of the four approaches are compared to obtain the best solution. The results show that the seeker optimization with improved inertia weight is able to achieve the best solution at less computational time.
VL  - 1
IS  - 2
ER  -

Copy | Download