Skip to main content

Fuzzified PSO Algorithm for OPF with FACTS Devices in Interconnected Power Systems

  • Conference paper
Book cover Swarm, Evolutionary, and Memetic Computing (SEMCCO 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6466))

Included in the following conference series:

Abstract

This paper presents a new computationally efficient improved stochastic algorithm for solving Optimal Power Flow (OPF) in interconnected power systems with FACTS devices. This proposed technique is based on the combined application of Fuzzy logic strategy incorporated in Particle Swarm Optimization (PSO) algorithm, hence named as Fuzzified PSO (FPSO). The FACTS devices considered here include Static Var Compensator (SVC), Static Synchronous Compensator (STATCOM), Thyristor Controlled Series Capacitor (TCSC) and Unified Power Flow Controller (UPFC). The proposed method is tested on single area IEEE 30-bus system and interconnected two area systems. The optimal solutions obtained using Evolutionary Programming (EP), PSO and FPSO are compared and analyzed. The analysis reveals that the proposed algorithm is relatively simple, efficient and reliable.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 119.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 159.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Basu, M.: Optimal power flow with FACTS devices using differential evolution. Electrical Power and Energy Systems 30, 150–156 (2008)

    Article  Google Scholar 

  2. Biskas, P.N., Bakirtzis, A.G.: ‘Decentralized security constrained DC-OPF of interconnected power systems’. In: IEE Proceedings Generation, Transmission and Distribution, vol. 151(6), pp. 747–754 (2004)

    Google Scholar 

  3. Chung, T.S., Ge, S.: Optimal power flow incorporating FACTS devices and power flow control constraints. In: IEEE Conference, vol. 98, pp. 415–419 (1998)

    Google Scholar 

  4. Ge, S.Y., Chung, T.S.: Optimal active power flow incorporating power flow control needs in flexible AC transmission systems. IEEE Transactions on Power Systems 14(2), 738–744 (1998)

    Article  Google Scholar 

  5. Ge, S.Y., Chung, T.S., Wong, Y.K.: A new method to incorporate FACTS devices in optimal power flow. In: IEEE Conference, vol. 98, pp. 122–127 (1998)

    Google Scholar 

  6. Hingorani, N.G., Gyugyi, L.: Understanding FACTS: Concepts and Technology of Flexible AC Transmission Systems, The institute of Electrical and Electronics Engineers, New York (2000)

    Google Scholar 

  7. Lai, L.L., Ma, J.T.: Power flow control in FACTS using evolutionary programming. IEEE Transactions on Power Systems 95, 109–113 (1995)

    Google Scholar 

  8. Li, N., Xu, Y., Chen, H.: FACTS-based power flow control in interconnected power systems. IEEE Transactions on Power Systems 15(1), 257–262 (2000)

    Article  Google Scholar 

  9. Padhy, N.P., Abdel-Moamen, M.A.: Power flow control and solutions with multiple and multi-type FACTS devices. Electric Power Systems Research 74, 341–351 (2005)

    Article  Google Scholar 

  10. Padhy, N.P., Abdel-Moamen, M.A.R., Trivedi, P.K., Das, H.: A hybrid model for optimal power flow incorporating FACTS devices. IEEE Transactions on Power Systems 1, 510–515 (2001)

    Google Scholar 

  11. Poli, R., Kennedy, J., Blackwell, T.: Particle swarm optimization: An overview. Swarm Intelligence 1(1), 33–57 (2007)

    Article  Google Scholar 

  12. Fukuyama, Y., Tahyama, S., Yoshida, H., Kawata, K., Nahnishi, Y.: A particle swarm optimization for reactive power and voltage control considering voltage security assessment. IEEE IRons. on Power Systems, 1232–1239 (2000)

    Google Scholar 

  13. Trelea, I.: The particle swarm optimization algorithm: Convergence analysis and parameter selection. Inf. Process. Lett. 85(6), 317–325 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  14. Zheng, Y., Ma, L., Zhang, L., Qian, I.: On the convergence analysis and parameter selection in particle swarm optimization. In: Proc. Int. Conf. Machine Learning Cybern., pp. 1802–1807 (2003)

    Google Scholar 

  15. Liang, J.J., Suganthan, P.N.: Dynamic Multi-Swarm Particle Swarm Optimizer. In: IEEE Swarm Intelligence Symposium, Pasadena, CA, USA, pp. 124–129 (2005)

    Google Scholar 

  16. El-sharkh, M.Y., El-Keib, A.A., Chen, H.: A fuzzy evolutionary programming based solution methodology for security-constrained generation maintenance scheduling. Electric Power system Research 67, 67–72 (2003)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2010 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Jothi Swaroopan, N.M., Somasundaram, P. (2010). Fuzzified PSO Algorithm for OPF with FACTS Devices in Interconnected Power Systems. In: Panigrahi, B.K., Das, S., Suganthan, P.N., Dash, S.S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2010. Lecture Notes in Computer Science, vol 6466. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17563-3_56

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-17563-3_56

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-17562-6

  • Online ISBN: 978-3-642-17563-3

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics