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Simultaneous adjustment of AVR and optimized PSS outputs effect in power systems for stability improvement

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Due to the problems related to low-frequency oscillations (LFOs) and power systems complexities, using intelligent methods and optimization techniques is essential for solving power system stabilizer (PSS) problems. In this paper, power system stabilizer, based on the PSOPSS, is designed to set the parameters of PSS. Then, the FLC is designed to simultaneously weighting the automated voltage regulator and power system stabilizer outputs, to adjust the excitation controller facing with disturbance. The ability to optimize particle swarm algorithm, in combination with FLC ability to solve complex and nonlinear problems, will effectively improve the stability of the power system. Initially, the simulation was performed on a single machine system in which the PSS optimal parameters were obtained using particle swarm optimization (PSO). Afterwards, with simultaneous regulation of the voltage and damping by the fuzzy logic controller, the effectiveness of the proposed approach, compared with the PSS based on the linear optimization controller, is confirmed. Next, more effective results can be obtained on a multi-machine system with effective placement of the FLPSS, compared with the conventional PSS and with simultaneous adjustment of the output weights of voltage and damping controllers using FLC. The efficiency of the proposed method in response to a variety of disturbances is determined.
Rocznik
Strony
1--13
Opis fizyczny
Bibliogr. 44 poz., rys., tab., wykr.
Twórcy
  • Department of Electrical Engineering, Najafabad Branch, Islamic Azad University Najafabad, 8514143131, Iran
  • Department of Electrical Engineering, Najafabad Branch, Islamic Azad University Najafabad, 8514143131, Iran
Bibliografia
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  • [6] Ghaedi H., Shahgholian G., Hashemi M.: Comparison of the effects of two flatness-based control methods for STATCOM on improving stability in power systems including DFIG based wind farms. Iranian Electric Industry Journal of Quality and Productivity, 8 (15), 2019, 81-90.
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  • [22] Shahgholian G., Karimi H., Mahmoodian H.: Design a power system stabilizer based on fuzzy sliding mode control theory. International Review on Modelling and Simulations, 5 (5), 2012, 2191-2196.
  • [23] Shahgholian G., Movahedi A: Coordinated design of thyristor-controlled series capacitor and power system stabilizer controllers using velocity update relaxation particle swarm optimization for two-machine power system stability. Revue Roumaine Des Sciences Techniques, 59 (3), 2014, 291-301.
  • [24] Khadanga R., Satapathy J.: Time delay approach for PSS and SSSC based coordinated controller design using hybrid PSO-GSA algorithm. International Journal of Electrical Power and Energy Systems, 71, 2015, 262-73.
  • [25] Shahgholian G., Fazeli-Nejad S., Moazzami M., Mahdavian M., Azadeh M., Janghorbani M., Farazpey S.: Power system oscillations damping by optimal coordinated design between PSS and STATCOM using PSO and ABC algorithms. Proceeding of the IEEE/ECTICON, 2016, pp. 1-6.
  • [26] Sambariya D., Prasad R.: Robust tuning of power system stabilizer for small signal stability enhancement using metaheuristic bat algorithm. International Journal of Electrical Power and Energy Systems, 61, 2014, 229-38.
  • [27] Keumarsi V., Simab M., Shahgholian G.: An integrated approach for optimal placement and tuning of power system stabilizer in multi-machine systems. International Journal of Electrical Power and Energy Systems, 63, 2014, 132-139.
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  • [29] Jabari E., Shahgholian G.: PSO Integral-Derivative Stabilizer Design for Improving Damping in Multi-Machine Power System. International Journal Natural and Engineering Sciences, 12 (2), 2019, 40-48.
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  • [34] Adjeroud F., Djahli F., Mayouf A., Devers T.: A coordinated genetic based type-2 fuzzy stabilizer for conventional and superconducting generators. Electric Power Systems Research, 129, 2015, 51-61.
  • [35] Sharifian A., Sharifian S.: A new power system transient stability assessment method based on Type-2 fuzzy neural network estimation. International Journal of Electrical Power and Energy Systems, 64, 2015, 71-87.
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  • [39] Kahouli 0., Jebali M., Alshammari B., Abdallah H. H.: PSS design for damping low-frequency oscillations in a multi-machine power system with penetration of renewable power generations. IET Renewable Power Generation, 13 (1), 2019, 116-127.
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  • [41] Ahmadi-Zebarjad M., Shahgholian G.: Application of a nonlinear hybrid controller in multimachine power system based on a power system stabilizer, Journal of Power Technologies, 97 (4), 2017, 295-301.
  • [42] Ramadan H. S., Bendary A. F., Nagy S.: Particle swarm optimization algorithm for capacitor allocation problem in distribution systems with wind turbine generators. International Journal of Electrical Power and Energy Systems, 84, 2017, 143-152.
  • [43] Jalali S., Shahgholian G.: Designing of power system stabilizer based on the root locus method with lead-lag controller and comparing it with PI controller in multi-machine power system. Journal of Power Technologies, 98 (1), 2018, 45-56.
  • [44] Kundur P.: Power system stability and control, New York: McGraw-Hill, 1993.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-eb81dda5-d34f-418c-8dd9-4cfc66d1fec7
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