Skip to main content
Log in

An Optimizer to Tune Fractional-Order Power System Stabilizer for Synchronous Generator Considering Governor Effect and Exciter Voltage Fluctuation

  • Published:
Journal of Control, Automation and Electrical Systems Aims and scope Submit manuscript

Abstract

In this paper, an intelligent optimizer has been developed and applied to tune fractional proportional integral power system stabilizer (FOPIPSS) to suppress the low frequency oscillation in a synchronous generator connected in single machine infinite bus system (SMIB). As, the power network is interconnected system, the conventional methods of tuning fractional PSS are complex and time-consuming. To avoid the mathematical and calculation burden of parameter tuning of FOPIPSS, a comparative performance class topper optimization is developed. The proposed optimized FOPIPSS is examined for SMIB system under three different conditions: disturbance in mechanical torque, mechanical torque change in the presence of fluctuation in exciter voltage and disturbance in exciter voltage in the presence of the governor-turbine system. The result analysis shows the effectiveness of the optimized FOPIPSS for SMIB systems comparing with the existing results.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  • Abd Elazim, S., & Ali, E. (2016). Optimal power system stabilizers design via cuckoo search algorithm. International Journal of Electrical Power & Energy Systems, 75, 99.

    Article  Google Scholar 

  • Abdulkhader, H. K., Jacob, J., & Mathew, A. T. (2019). Robust type-2 fuzzy fractional order PID controller for dynamic stability enhancement of power system having RES based microgrid penetration. International Journal of Electrical Power & Energy Systems, 110, 357.

    Article  Google Scholar 

  • Acharya, D., & Das, A. (2019). Rai. In 2019 2nd international conference on innovations in electronics, signal processing and communication (IESC) (pp. 148–153). IEEE.

  • Acharya, D., & Das, D.K. (2021a). In 2021 4th Biennial international conference on nascent technologies in engineering (ICNTE) (pp. 1–5). IEEE.

  • Acharya, D., & Das, D. K. (2021b). Optimal coordination of over current relay using opposition learning-based gravitational search algorithm. The Journal of Supercomputing,77, 1–21.

  • Acharya, D., & Das, D. K. (2021c). Swarm optimization approach to design PID controller for artificially ventilated human respiratory system. Computer Methods and Programs in Biomedicine,198, 105776.

  • Acharya, D., Das, D. K., & Srivastava, A. (2020). In 2020 IEEE Calcutta conference (CALCON) (pp. 45–49). IEEE.

  • Awange, J. L., Paláncz, B., Lewis, R. H., & Völgyesi, L. (2018). Mathematical geosciences (pp. 167–184). Springer.

  • Ayas, E. M., & Sahin, S. (2020). FOPID controller with fractional filter for an automatic voltage regulator. Computers & Electrical Engineering, 90, 106895.

    Article  Google Scholar 

  • Barhaghtalab, M. H., Meigoli, V., Zavvar, M., Mirhassannia, S. M., & Yosefi, N. (2018). Optimal fuzzy controller based on chaotic invasive weed optimization for damping power system oscillation. Smart Science, 6(2), 134.

    Article  Google Scholar 

  • Bhukya, J., & Mahajan, V. (2019). Optimization of damping controller for PSS and SSSC to improve stability of interconnected system with DFIG based wind farm. International Journal of Electrical Power & Energy Systems, 108, 314.

    Article  Google Scholar 

  • Cao, Y., Zhang, H., Li, W., Zhou, M., Zhang, Y., & Chaovalitwongse, W. A. (2018). Comprehensive learning particle swarm optimization algorithm with local search for multimodal functions. IEEE Transactions on Evolutionary Computation, 23(4), 718.

    Article  Google Scholar 

  • Chathoth, I., Ramdas, S. K., & Krishnan, S. T. (2015). Fractional-order proportional-integral-derivative-based automatic generation control in deregulated power systems. Electric Power Components and Systems, 43(17), 1931.

    Article  Google Scholar 

  • Chitara, D., Niazi, K. R., Swarnkar, A., & Gupta, N. (2018). Cuckoo search optimization algorithm for designing of multimachine power system stabilizer. IEEE Transactions on Industry Applications, 54, 3056–3065.

    Article  Google Scholar 

  • Das, P., Das, D. K., & Dey, S. (2018). A new class topper optimization algorithm with an application to data clustering. IEEE Transactions on Emerging Topics in Computing, 8, 948–959.

    Google Scholar 

  • Eltag, K., Aslamx, M. S., & Ullah, R. (2019). Dynamic stability enhancement using fuzzy PID control technology for power system. International Journal of Control Automation and Systems, 17(1), 234.

    Article  Google Scholar 

  • Feliachi, A., Zhang, X., & Sims, C. S. (1988). Power system stabilizers design using optimal reduced order models. I. Model reduction. IEEE Transactions on Power Systems, 3(4), 1670.

    Article  Google Scholar 

  • Fereidouni, A., Vahidi, B., Mehr, T. H., & Tahmasbi, M. (2013). Improvement of low frequency oscillation damping by allocation and design of power system stabilizers in the multi-machine power system. International Journal of Electrical Power & Energy Systems, 52, 207.

    Article  Google Scholar 

  • Gurumurthy, G., Das, D.K., & Mathpal P. (2017). In 2017 14th IEEE India council international conference (INDICON) (IEEE) (pp. 1–6).

  • Hosseini, H., Tusi, B., Razmjooy, N., & Khalilpoor, M. (2011). In 2011 2nd international conference on control, instrumentation and automation (ICCIA) (pp. 62–67). IEEE.

  • Hsu, Y. Y., & Hsu, C. Y. (1986). Design of a proportional-integral power system stabilizer. IEEE Transactions on Power systems, 1(2), 46.

    Article  Google Scholar 

  • Huang, T., & Chen, S. (1993). Power system pi controller design via optimal subeigenstructure assignment. Electric Machines and Power Systems, 21(4), 437.

    Article  Google Scholar 

  • Kumar, C., Rao, M. V., Seshadri, P., Pandey, V., Ghangrekar, C., Chitturi, S., Shrivastava, V., & Gartia, A. (2018). In 2018 IEEE PES Asia-Pacific power and energy engineering conference (APPEEC) (pp. 701–706). IEEE.

  • Lin, A., Sun, W., Yu, H., Wu, G., & Tang, H. (2019). Adaptive comprehensive learning particle swarm optimization with cooperative archive. Applied Soft Computing, 77, 533.

    Article  Google Scholar 

  • Lu, C., Zhang, J., Zhang, X., Zhao, Y. et al. (2018). Wide-area oscillation identification and damping control in power systems. Foundations and Trends® in Electric Energy Systems 2(2), 133.

  • Merrikh-Bayat, F. (2012). Rules for selecting the parameters of Oustaloup recursive approximation for the simulation of linear feedback systems containing PI\(\lambda \)D\(\mu \) controller. Communications in Nonlinear Science and Numerical Simulation, 17(4), 1852.

    Article  MathSciNet  Google Scholar 

  • Milici, C., Drăgănescu, G., & Machado. J. T. (2018). Introduction to fractional differential equations. Introduction to fractional differential equations.

  • Pan, I., & Das, S. (2013). Frequency domain design of fractional order PID controller for AVR system using chaotic multi-objective optimization. International Journal of Electrical Power & Energy Systems, 51, 106.

    Article  Google Scholar 

  • Peres, W., Júnior, I. C. S., & Passos Filho, J. A. (2018). Gradient based hybrid metaheuristics for robust tuning of power system stabilizers. International Journal of Electrical Power & Energy Systems, 95, 47.

  • Rahmatian, M., & Seyedtabaii, S. (2019). Multi-machine optimal power system stabilizers design based on system stability and nonlinearity indices using Hyper-Spherical Search method. International Journal of Electrical Power & Energy Systems, 105, 729.

    Article  Google Scholar 

  • Ray, P. K., Paital, S .R., Mohanty, A., Eddy, F. Y. Krishnan, A., Gooi, H., & Amaratunga, G. (2018) Firefly algorithm scaled fractional order fuzzy PID based PSS for transient stability improvement. In 2018 19th international Carpathian control conference (ICCC) (pp. 428–433). IEEE.

  • Roy, P., & Roy, B. K. (2016). Dual mode adaptive fractional order PI controller with feedforward controller based on variable parameter model for quadruple tank process. ISA Transactions, 63, 365.

    Article  Google Scholar 

  • Sahu, P. R., Hota, P. K., & Panda, S. (2018). Modified whale optimization algorithm for fractional-order multi-input SSSC-based controller design. Optimal Control Applications and Methods, 39(5), 1802.

    Article  MathSciNet  MATH  Google Scholar 

  • Salgotra, A., & Pan, S. (2018). Model based PI power system stabilizer design for damping low frequency oscillations in power systems. ISA Transactions, 76, 110.

    Article  Google Scholar 

  • Shair, J., Basit, M. A., & Badar, R. (2018). In 2018 1st international conference on power, energy and smart grid (ICPESG) (pp. 1–6). IEEE.

  • Sharma, S., & Narayan, S. (2017). In 2017 8th international conference on computing, communication and networking technologies (ICCCNT) (pp. 1–7). IEEE.

  • Shu, Y., Zhou, X., & Li, W. (2018). Analysis of low frequency oscillation and source location in power systems. CSEE Journal of Power and Energy Systems, 4(1), 58.

    Article  Google Scholar 

  • Sikander, A., Thakur, P., Bansal, R., & Rajasekar, S. (2018). A novel technique to design cuckoo search based FOPID controller for AVR in power systems. Computers & Electrical Engineering, 70, 261.

    Article  Google Scholar 

  • Tepljakov, A. (2017). Fractional-order modeling and control of dynamic systems. Springer.

  • Tharwat, A., Gaber, T., Hassanien, A. E., & Elnaghi, B. E. (2017). In Handbook of research on machine learning innovations and trends (pp. 614–635). IGI Global.

  • Wang, D., Mu, C. (2019). ADP-based supplementary design for load frequency control of power systems. In Adaptive critic control with robust stabilization for uncertain nonlinear systems (pp. 281–304).

  • Wang, D., Song, B., Kang, C., & Xu, J. (2018a). In 2018 2nd IEEE advanced information management, communicates, electronic and automation control conference (IMCEC) (pp. 780–784). IEEE.

  • Wang, D., Ma, N., Wei, M., & Liu, Y. (2018b). Parameters tuning of power system stabilizer PSS4B using hybrid particle swarm optimization algorithm. International Transactions on Electrical Energy Systems, 28, e2598.

Download references

Funding

No external funding sources supported this research article.

Author information

Authors and Affiliations

Authors

Contributions

DA carried out the conceptualization, methodology, writing and drafting the article. DKD carried out conceptualization, methodology, supervision, corrections, review and editing.

Corresponding author

Correspondence to Dushmanta Kumar Das.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical Approval

For this research article, the authors did not undertake work that involved human participants or animals.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Acharya, D., Das, D.K. An Optimizer to Tune Fractional-Order Power System Stabilizer for Synchronous Generator Considering Governor Effect and Exciter Voltage Fluctuation. J Control Autom Electr Syst 34, 407–419 (2023). https://doi.org/10.1007/s40313-022-00962-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40313-022-00962-7

Keywords

Navigation