Maiden Application of Skill Optimization Algorithm on Cascaded Multi-Level Neuro-Fuzzy based Power system Stabilizers for Damping Oscillations

ABINANDS RAMSHANKER, SUPRAVA CHAKRABORTY

Abstract


Power system oscillation is a significant threat among interconnected power systems that may lead to instability. The success of oscillation damping is primarily responsible for a modern power system's safe operation. However, the development of damping controllers is a multimodal optimization problem with constraints which challenges the traditional optimization algorithms. This paper critically examines damping schemes and controller stability analyses to find solutions to these issues and improve the performance of a multi-machine power system(MMPS). This paper reveals the technique of improving power system stability by employing the Skill Optimization Algorithm (SOA) to optimize the gains of the conventional power system stabilizer (PSS) and the Neuro-Fuzzy inputs-output scaling parameters. This study aims to propose a multi-level Neuro-Fuzzy power system stabilizers (MLNFPSS) to reduce the instability of a multi-machine two-area power system(MMTAPS) under fault conditions. The simulations were run on a MMTAPS considering a transmission line fault in the middle. The analysis leads to the deduction that the proposed MLNFPSS response is more efficient than conventional PSS under symmetrical three-phase faults. All control strategies have been executed, and the simulation results have been assessed using MATLAB 2016b/Simulink.

Keywords


Multi-machine, Stability, multi-level Neuro-Fuzzy controller; PSS; SOA.

Full Text:

PDF

References


M. A. Hannan, N. N. Islam., "Artificial Intelligent Based Damping Controller Optimization for the Multi-Machine Power System: A Review," IEEE Access, vol. 6, pp.39574 - 39594, 13 Jul. 2018.

P. Kundur, J. Paserba, and etc., "Overview on definition and classification of power system stability," in CIGRE/IEEE PES Inter. Sympo. Qual. and Sec, of Elec. Power Deli. Sys, 2003. CIGRE/PES 2003, Montreal, Quebec, Canada, Canada, 8-10 Oct. 2003.

L. L. GRIGSBY, Power System Stability and Control, Boca Raton, USA: CRC Press, Taylor & Francis Group, 2012.

M. L. Kothari, J. Nanda, and K. Bhattacharya, “Design of variable structure power system stabilizers with desired eigen values in the sliding mode,” IEE Proceedings C Generation, Transmission and Distribution, vol. 140, no. 4, p. 263, 1993.

A. Hariri and O. P. Malik, “Adaptive-network-based Fuzzy Logic Power System Stabilizer,” IEEE WESCANEX 95. Communications, Power, and Computing. Conference Proceedings, pp. 111–116, 1995.

Hoang, P. and K. Tomosovic, “Design and Analysis of an Adaptive Fuzzy Power System Stabilizer.” IEEE Transaction Energy Conversion, Vol. 11. 1996.

Abido. M.A. and L. Abdel-Magid. “Design of power system stabilizers using evolutionary programming.” IEEE Transaction on Energy Conversion, Vol. 17. 2000.

B. Saleem, R. Badar, A. Manzoor, M. A. Judge, J. Boudjadar, and S. U. Islam, “Fully adaptive recurrent Neuro-fuzzy control for power system stability enhancement in Multi Machine System,” IEEE Access, vol. 10, pp. 36464–36476, Apr. 2022.

B. Douidi, L. Mokrani, and M. Machmoum, “A new cascade fuzzy power system stabilizer for multi-machine system stability enhancement,” Journal of Control, Automation and Electrical Systems, vol. 30, no. 5, pp. 765–779, Jun. 2019.

N. M. A. Ibrahim, B. E. Elnaghi, H. A. Ibrahem, and H. E. A. Talaat, “Modified particle swarm optimization based on lead-lag power system stabilizer for improve stability in multi-machine power system,” International Journal on Electrical Engineering and Informatics, vol. 11, no. 1, pp. 161–182, Mar. 2019.

S. Sharma and S. Narayan, “Damping of low frequency oscillations using robust PSS and TCSC controllers,” 2017 8th International Conference on Computing, Communication and Networking Technologies (ICCCNT), Jul. 2017. [69] B. Mohandes, Y. L. Abdelmagid, and I. Boiko, “Development of PSS tuning rules using multi-objective optimization,” Int. J. Electr. Power Energy Syst., vol. 100, pp. 449–462, Sep. 2018.

C. Zhang, D. Ke, Y. Sun, C. Y. Chung, J. Xu, and F. Shen, “Coordinated Supplementary Damping Control of DFIGURE and PSS to Suppress Inter-Area Oscillations With Optimally Controlled Plant Dynamics,” IEEE Trans. Sustain. Energy, vol. 9, no. 2, pp. 780–791, Apr. 2018.

Y. He, X. Liu, C. Zhang, and Z. Chen, “A new model for State-of- Charge (SOC) estimation for high-power Li-ion batteries,” Appl. Energy, vol. 101, pp. 808–814, 2013.

M. A. Magzoub, N. B. Saad, and R. B. Ibrahim, “Power system stabiliser for single machine in infinite bus based on optimal control methods,” in 2014 IEEE 8th International Power Engineering and Optimization Conference (PEOCO2014), 2014, pp. 313–317.

F. Milla and M. A. Duarte-Mermoud, “Predictive optimized adaptive PSS in a single machine infinite bus,” ISA Trans., vol. 63, pp. 315– 327, Jul. 2016.

R. Jalayer and B.-T. Ooi, “Co-Ordinated PSS Tuning of Large Power Systems by Combining Transfer Function-Eigenfunction Analysis (TFEA), Optimization, and Eigenvalue Sensitivity,” IEEE Trans. Power Syst., vol. 29, no. 6, pp. 2672–2680, Nov. 2014.

T. Surinkaew and I. Ngamroo, “Coordinated Robust Control of DFIGURE Wind Turbine and PSS for Stabilization of Power Oscillations Considering System Uncertainties,” IEEE Trans. Sustain. Energy, vol. 5, no. 3, pp. 823–833, Jul. 2014.

Z. Assi Obaid, L. M. Cipcigan, and M. T. Muhssin, “Power system oscillations and control: Classifications and PSSs’ design methods: A review,” Renew. Sustain. Energy Rev., vol. 79, pp. 839–849, Nov. 2017.

Ghandakly AA, Idowu P (1990) Design of a model reference adaptive stabilizer for the exciter and governor loops of power generators. IEEE Trans Power Syst 5(3):887–893. https://doi. org/10.1109/59.65918

Chen S, Malik OP (1995) Power system stabilizer design using /spl mu/ synthesis. IEEE Trans Energy Convers 10(1):175–181. https://doi.org/10.1109/60.372584

Jacobson CA, Stankovic AM, Tadmor G, Stevens MA (1996) Towards a dissipativity framework for power system stabilizer design. IEEE Trans Power Syst 11(4):1963–1968. https://doi.org/ 10.1109/59.544671

Lam DM, Yee H (1998) A study of frequency responses of gen- erator electrical torques for power system stabilizer design. IEEE Trans Power Syst 13(3):1136–1142. https://doi.org/10.1109/59. 709111

Qiu W, Vittal V, Khammash M (2004) Decentralized power sys- tem stabilizer design using linear parameter varying approach. IEEE Trans Power Syst 19(4):1951–1960. https://doi.org/10. 1109/TPWRS.2004.836269

Ba-muqabel AA, Abido MA (2006) Review of conventional power system stabilizer design methods. In: 2006 IEEE GCC conference (GCC), Manama, Bahrain, Mar. 2006, pp 1–7. https:// doi.org/10.1109/IEEEGCC.2006.5686203

S. Pereira, P. Ferreira, and A. I. F. Vaz, “Optimization modeling to support renewables integration in power systems,” Renew. Sustain. Energy Rev., vol. 55, pp. 316–325, 2016.

A. R. Jordehi, “Optimisation of electric distribution systems: A review,” Renew. Sustain. Energy Rev., vol. 51, pp. 1088–1100, 2015.

Devarapalli R, Kumar V (2021) Power system oscillation damp- ing controller design: a novel approach of integrated HHO-PSO algorithm. Archiv Control Sci 31(3):553–591. https://doi.org/10. 24425/acs.2021.138692

Devarapalli R, Bhattacharyya B, Kumari A (2021) A novel approach of intensified barnacles mating optimization for the mitigation of power system oscillations. Concurr Comput: Prac- tice Exp 33(17):e6303. https://doi.org/10.1002/cpe.6303

Devarapalli R, Bhattacharyya B (2021) A novel hybrid AGWO- PSO algorithm in mitigation of power network oscillations with STATCOM. Numerical Algebra, Control Optimiz 11(4):579. https://doi.org/10.3934/naco.2020057

Devarapalli R, Bhattacharyya B, Sinha NK (2020) An intelligent EGWO-SCA-CS algorithm for PSS parameter tuning under system uncertainties. Int J Intell Syst 35(10):1520–1569. https://doi.org/10.1002/int.22263

Devarapalli R, Bhattacharyya B (2020) A hybrid modified grey wolf optimization-sine cosine algorithm-based power system sta- bilizer parameter tuning in a multimachine power system. Optim Control Appl Meth 41(4):1143–1159. https://doi.org/10.1002/ oca.2591

Sahu PR, Hota PK, Panda S (2019) Modified whale optimiza- tion algorithm for coordinated design of fuzzy lead-lag structure- based SSSC controller and power system stabilizer. Int Trans Electr Energ Syst 29(4):e2797. https://doi.org/10.1002/etep.2797

Dasu B, Sivakumar M, Srinivasarao R (2019) Interconnected multi-machine power system stabilizer design using whale opti- mization algorithm. Prot Control Mod Power Syst 4(1):2. https:// doi.org/10.1186/s41601-019-0116-6

Rana MJ, Shahriar MS, Shafiullah M (2019) Levenberg–Mar- quardt neural network to estimate UPFC-coordinated PSS param- eters to enhance power system stability. Neural Comput Applic 31(4):1237–1248. https://doi.org/10.1007/s00521-017-3156-8

Rajbongshi R, Saikia LC (2019) Performance of coordinated interline power flow controller and power system stabilizer in combined multiarea restructured ALFC and AVR system. Int Trans Electr Energ Syst 29(5):e2822. https://doi.org/10.1002/ 2050-7038.2822

Devarapalli R, Bhattacharyya B (2019) Optimal parameter tun- ing of power oscillation damper by MHHO algorithm. In: 2019 20th International conference on intelligent system application to power systems (ISAP), pp 1–7. doi: https://doi.org/10.1109/ ISAP48318.2019.9065988

Devarapalli R, Bhattacharyya B (2019) Application of modified Harris Hawks optimization in power system oscillations damp- ing controller design. In 2019 8th international conference on power systems (ICPS), pp 1–6. https://doi.org/10.1109/ICPS4 8983.2019.9067679

Bagheri M, Mukhatov M, Abedinia O, Naderi MS, Naderi MS, Ghadimi N (2018) Application and design of new control- ler based on fuzzy PID and FACTS devices in multi-machine power system. In: 2018 IEEE international conference on envi- ronment and electrical engineering and 2018 IEEE industrial and commercial power systems Europe (EEEIC / I&CPS Europe), Palermo, pp 1–6. doi: https://doi.org/10.1109/EEEIC.2018.84944 08

Thu WM, Lin KM (2018) Mitigation of low frequency oscil- lations by optimal allocation of power system stabilizers: case study on MEPE test system. EPE 10(08):333–350. https://doi. org/10.4236/epe.2018.108021

Dey, P., Bhattacharya, A. and Das, P. (2017), "Tuning of power system stabilizer for small signal stability improvement of interconnected power system", Applied Computing and Informatics, Vol. 16 No. 1/2, pp. 3-28. https://doi.org/10.1016/j.aci.2017.12.004

Herrera JD, Rios MA (2017) A Multiobjective damping function for coordinated control of power system stabilizer and power oscillation damping. Int J Energy Power Eng 11(12):1183–1189

Santra S, Paul S (2017) PSO based robust power system stabi- lizer design using mixed sensitivity based H output-feedback control in LMI approach. In: 2017 Third international conference on research in computational intelligence and communication networks (ICRCICN), Kolkata, pp 273–278. https://doi.org/10. 1109/ICRCICN.2017.8234520

Khodabakhshian A, Esmaili MR, Bornapour M (2016) Optimal coordinated design of UPFC and PSS for improving power sys- tem performance by using multi-objective water cycle algorithm. Int J Electr Power Energy Syst 83:124–133. https://doi.org/10. 1016/j.ijepes.2016.03.052

Shahgholian G et al., (2016) Power system oscillations damp- ing by optimal coordinated design between PSS and STATCOM using PSO and ABC algorithms. In: 2016 13th International con- ference on electrical engineering/electronics, computer, telecom- munications and information technology (ECTI-CON), Chiang Mai, Thailand, pp 1–6. doi: https://doi.org/10.1109/ECTICon. 2016.7561458

L. H. Hassan, M. Moghavvemi, H. A. F. Almurib, K. M. Muttaqi, and V. G. Ganapathy, “Optimization of power system stabilizers using participation factor and genetic algorithm,” Int. J. Electr. Power Energy Syst., vol. 55, pp. 668–679, Feb. 2014.

Y. A. Katsigiannis, P. S. Georgilakis, and E. S. Karapidakis, “Hybrid Simulated Annealing–Tabu Search Method for Optimal Sizing of Autonomous Power Systems With Renewables,” IEEE Trans. Sustain. Energy, vol. 3, no. 3, pp. 330–338, Jul. 2012.

K. R. M. Vijaya Chandrakala and S. Balamurugan, “Simulated annealing based optimal frequency and terminal voltage control of multi source multi area system,” Int. J. Electr. Power Energy Syst., vol. 78, pp. 823–829, Jun. 2016.

P. Acharjee, “Optimal power flow with UPFC using security constrained self-adaptive differential evolutionary algorithm for restructured power system,” Int. J. Electr. Power Energy Syst., vol. 76, pp. 69–81, Mar. 2016.

Jong-Bae Park, Yun-Won Jeong, Joong-Rin Shin, and K. Y. Lee, “An Improved Particle Swarm Optimization for Nonconvex Economic Dispatch Problems,” IEEE Trans. Power Syst., vol. 25, no. 1, pp. 156–166, Feb. 2010.

S. A. Taher and S. A. Afsari, “Optimal location and sizing of DSTATCOM in distribution systems by immune algorithm,” Int. J. Electr. Power Energy Syst., vol. 60, pp. 34–44, Sep. 2014.

Hadi Givi (2022). Skill Optimization Algorithm (SOA) (https://www.mathworks.com/matlabcentral/fileexchange/110675-skill-optimization-algorithm-soa), MATLAB Central File Exchange. Retrieved October 7, 2022.

H. Givi and M. Hubalovska, "Skill optimization algorithm: a new human-based metaheuristic technique," Computers, Materials & Continua, vol. 74, no.1, pp. 179–202, 2023.




DOI (PDF): https://doi.org/10.20508/ijrer.v12i4.13534.g8590

Refbacks

  • There are currently no refbacks.


Online ISSN: 1309-0127

Publisher: Gazi University

IJRER is cited in SCOPUS, EBSCO, WEB of SCIENCE (Clarivate Analytics);

IJRER has been cited in Emerging Sources Citation Index from 2016 in web of science.

WEB of SCIENCE in 2025; 

h=35,

Average citation per item=6.59

Last three Years Impact Factor=(1947+1753+1586)/(146+201+78)=5286/425=12.43

Category Quartile:Q4