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Ant Colony Optimization Based Load Frequency Control of Multi-area Interconnected Thermal Power System with Governor Dead-Band Nonlinearity

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Smart Trends in Systems, Security and Sustainability

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 18))

Abstract

The interconnected thermal power system consists of several areas. Various parameters should be provided to reach power systems’ firm operation. The current work proposed an optimization algorithm, namely Ant colony optimization (ACO) to optimize the Proportional-Integral-Derivative (PID) controller for the load frequency control of two-area interconnected non-reheat thermal power system with Governor dead band nonlinearity. The ACO in used to determine optimal controller’s parameters, where an objective function, namely Integral Time Absolute Error is conducted. A comparative study for the ACO performance to the Craziness based Particle swarm optimization (CPSO) is studied to examine the proposed approach performance in the interconnecting thermal power system. The result established the ACO optimized PID controller response superiority of the compared to the CPSO optimized controller.

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References

  1. Demiroren, A., Zeynelgil, A.L., Sengor, N.S.: The application of ANN technique to load frequency control for three-area power systems. IEEE Porto Power Tech Conference on 10–13 Sept 2001, Portugal, pp. 1–5

    Google Scholar 

  2. Ali, E.S., Abd-Elazim, S.M.: Bacteria foraging optimization algorithm based load frequency controller for interconnected power system. Electric Power Energy Syst. 33, 633–638 (2011)

    Article  Google Scholar 

  3. Azar, A.T.: Fuzzy Systems. IN-TECH 2010, Vienna, Austria

    Google Scholar 

  4. Chon, N.: Some aspects of tie-line biased control on interconnected power systems. Am. Inst. Elect. Eng. Trans. 75, 1415–1436 (1957)

    Google Scholar 

  5. Das, S., Kothari, M.L., Kothari, D.P., Nanda, J.: Variable structure control strategy to automatic generation control of interconnected reheat thermal system. IEE Proc-D. 138, 579–585 (1991)

    Article  Google Scholar 

  6. Dey, N., Samanta, S., Chakraborty, S., Das, A., Chaudhuri, S.S., Suri, J.S.: Firefly algorithm for optimization of scaling factors during embedding of manifold medical information: an application in ophthalmology imaging. J. Med. Imaging Health Inform. 4, 384–394 (2015)

    Article  Google Scholar 

  7. Dey, N., Samanta, S., Yang, X.S., Chaudhuri, S.S., Das, A.: Optimization of scaling factors in electrocardiogram signal watermarking using cuckoo search. Int. J. Bio-Inspired Comput. (IJBIC) 5, 315–326 (2014)

    Article  Google Scholar 

  8. Francis, R., Chidambaram, I.A.: Optimized PI+ load-frequency controller using BWNN approach for an interconnected reheat power system with RFB and hydrogen electrolyser units. Electric Power Energy Syst. 67, 381–392 (2015)

    Article  Google Scholar 

  9. Jagatheesan, K., Anand, B., Ebrahim, M.A.: Stochastic particle swarm optimization for tuning of PID controller in load frequency control of single area reheat thermal power system. Int. J. Electr. Power Eng. 8, 33–40 (2014)

    Google Scholar 

  10. Jagatheesan, K., Anand, B., Dey, N.: Automatic generation control of thermal-thermal-hydro power systems with PID controller using ant colony optimization. Int. J. Serv. Sci. Manag. Eng. Technol. 6, 18–34 (2015)

    Google Scholar 

  11. Jagatheesan, K., Jeyanthi, S., Anand, B.: Conventional load frequency control of an interconnected multi-area reheat thermal power systems using HVDC link. Int. J. Sci. Eng. Res. 5, 88–92 (2014)

    Google Scholar 

  12. Ebrahim, M.A., Mostafa, H.E., Gawish, S.A., Bendary, F.M.: Design of decentralized load frequency based-PID controller using stochastic particle swarm optimization technique. In: International Conference on Electric Power And Energy Conversion System, pp. 1–6 (2009)

    Google Scholar 

  13. Pan, C.T., Liaw, C.M.: An adaptive controller for power system load-frequency control. IEEE Trans. Power Syst. 4, 122–128 (1989)

    Article  Google Scholar 

  14. Jagatheesan, K., Anand, B., Dey, N: Evolutionary algorithm based LFC of single area thermal power system with different steam configurations and non-linearity. In: Proceedings of The third International Conference on Information Systems Design and Intelligent Applications 2016 (INDIA-2016), pp. 185–194 (2016)

    Google Scholar 

  15. Samanta, S., Acharjee, S., Mukherjee, A., Das, D., Dey, N.: Ant weight lifting algorithm for image segmentation. In: 2013 IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), pp. 1–5 (2013)

    Google Scholar 

  16. Sahu, R.K., Panda, S., Padhan, S.: A hybrid firefly algorithm and pattern search technique for automatic generation control of multi area power systems. Electric Power Energy Syst. 64, 9–23 (2015)

    Article  Google Scholar 

  17. Gozde, H., Taplamacioglu, M.C.: Automatic generation control application with craziness based particle swarm optimization in a thermal power system. Electr. Power Energy Syst. 33, 8–16 (2011)

    Article  Google Scholar 

  18. Gozde, H., Taplamacioglu, M.C., Kocaarslan, I.: Comparative performance analysis of Artificial Bee Colony algorithm in automatic generation control for interconnected reheat thermal power system. Electric Power Energy Syst. 42, 167–178 (2012)

    Article  Google Scholar 

  19. Jagatheesan, K., Anand, B., Baskaran, K., Dey, N., Ashour, A.S., Bala, V.E.: Effect of non-linearity and boiler dynamics in automatic generation control of multi-area thermal power system with proportional-integral-derivative and ant colony optimization technique. Recent advances in nonlinear dynamics and synchronisation with selected applications, Springer (Germany), in the Series “Studies in Computational Intelligence” (2016)

    Google Scholar 

  20. Jagatheesan, K., Anand, B., Dey, N., Ashour, A.S.: Artificial intelligence in performance analysis of load frequency control in thermal-wind-hydro power systems. Int. J. Adv. Comput. Sci. Appl. 6(7) (2015)

    Google Scholar 

  21. Jagatheesan, K., Anand, B., Samanta, S., Dey, N., Santhi, V., Ashour, A.S., Balas, V.E.: Application of flower pollination algorithm in load frequency control of multi-area interconnected power system with non-linearity. Neural Comput. Appl. (NCAA) (2016)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Duy Tan University, Danang, Vietnam

    Gia Nhu Nguyen

  2. Deptartment of EEE, Mahendra Institute of Engineering and Technology, Namakkal, Tamilnadu, India

    K. Jagatheesan

  3. Faculty of Engineering, Department of Electronics and Electrical Communications Engineering, Tanta University, Tanta, Egypt

    Amira S. Ashour

  4. Deptartment of EEE, Hindusthan College of Engineering and Technology, Coimbatore, Tamilnadu, India

    B. Anand

  5. Deptartment of Information Technology, Techno India College of Technology, Kolkata, India

    Nilanjan Dey

Authors
  1. Gia Nhu Nguyen
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  2. K. Jagatheesan
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  3. Amira S. Ashour
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  4. B. Anand
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  5. Nilanjan Dey
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Corresponding author

Correspondence to Gia Nhu Nguyen .

Editor information

Editors and Affiliations

  1. School of Science and Technology, Middlesex University, London, United Kingdom

    Xin-She Yang

  2. Department of Mathematics and Computer Science, Liverpool Hope University, Liverpool, United Kingdom

    Atulya K. Nagar

  3. Sabar Institute of Technology, Gujarat Technological University, Gujarat, India

    Amit Joshi

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Nguyen, G.N., Jagatheesan, K., Ashour, A.S., Anand, B., Dey, N. (2018). Ant Colony Optimization Based Load Frequency Control of Multi-area Interconnected Thermal Power System with Governor Dead-Band Nonlinearity. In: Yang, XS., Nagar, A., Joshi, A. (eds) Smart Trends in Systems, Security and Sustainability. Lecture Notes in Networks and Systems, vol 18. Springer, Singapore. https://doi.org/10.1007/978-981-10-6916-1_14

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  • DOI: https://doi.org/10.1007/978-981-10-6916-1_14

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6915-4

  • Online ISBN: 978-981-10-6916-1

  • eBook Packages: EngineeringEngineering (R0)

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