Abstract
Multimachine systems are complex power systems consisting of multiple generators, loads, and transmission lines. In these kinds of systems, maintaining stability is a difficult task. Different damping controllers, like the power system stabilizer and FACTS controllers, are used to maintain stability. The design of the control scheme ensures that the PSS and SSSC work together in a coordinated manner. The controller parameter is optimized by using metaheuristic methods. In this work, a salp swarm algorithm (SSA) is proposed to tune the controller parameters for the multi-machine system. The statistical analysis is carried out to assess the performances of the SSA method against some other promising methods. The objective of this work is considered as minimization of rotor speed deviation. The rotor speed deviation is suppressed by using SSA tuned damping controllers. The mean rotor speed deviation obtained using SSA is 0.000601 pu. Using MATLAB simulation, the performance of multi-machine system is examined in terms of speed deviation between inter-area and local-area, injected voltage, and tie-line power. The simulation result suggests the supremacy of SSA over other methods considered for comparative study.
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References
Alomoush M (2017) Concurrent optimal design of TCSC and PSS using symbiotic organisms search algorithm. Turk J Electr Eng Comput Sci 25(5):3904–3919. https://doi.org/10.3906/elk-1703-147
Bhattacharya K, Nanda J, Kothari ML (1997) Optimization and performance analysis of conventional power system stabilizers. Int J Electr Power Energy Syst 19(7):449–458. https://doi.org/10.1016/s0142-0615(97)00015-x
Cai LJ, Erlich I (2005) Simultaneous coordinated tuning of PSS and FACTS damping controllers in large power systems. IEEE Trans Power Syst 20(1):294–300. https://doi.org/10.1109/TPWRS.2004.841177
Do Bomfim ALB, Taranto GN, Falcâo DM (2000) Simultaneous tuning of power system damping controllers using genetic algorithms. IEEE Trans Power Syst 15(1):163–169. https://doi.org/10.1109/59.852116
Du W, Dong W, Wang Y, Wang H (2021) A method to design power system stabilizers in a multi-machine power system based on single-machine infinite-bus system model. IEEE Trans Power Syst 36(4):3475–3486. https://doi.org/10.1109/TPWRS.2020.3041037
Gholipour E, Nosratabadi SM (2015) A new coordination strategy of SSSC and PSS controllers in power system using SOA algorithm based on Pareto method. Int J Electr Power Energy Syst 67:462–471. https://doi.org/10.1016/j.ijepes.2014.12.020
Kar MK, Kumar S, Singh AK, Panigrahi S (2021a) A modified sine cosine algorithm with ensemble search agent updating schemes for small signal stability analysis. Int Trans Electr Energy Syst. https://doi.org/10.1002/2050-7038.13058
Kar MK, Kumar S, Singh AK, Panigrahi S (2021b) Reactive power management by using a modified differential evolution algorithm. Opt Control Appl Methods. https://doi.org/10.1002/oca.2815
Kar MK, Kumar S, Singh AK, Panigrahi S, Cherukuri M (2022) Design and analysis of FOPID-based damping controllers using a modified grey wolf optimization algorithm. Int Trans Electr Energy Syst 20:22. https://doi.org/10.1155/2022/5339630
Kumar L, Kar MK, Kumar S (2022) Reactive power management of transmission network using evolutionary techniques. J Electr Eng Technol. https://doi.org/10.1007/s42835-022-01185-1
Kundur P (1994). Power system stability and control by prabha Kundur.pdf. In: McGraw-Hill, Inc, p 1167
Murali D, Rajaram M, Reka N (2010) Comparison of FACTS devices for power system stability enhancement. Int J Comput Appl 8(4):30–35. https://doi.org/10.5120/1198-1701
Panda S (2009) Multi-objective evolutionary algorithm for SSSC-based controller design. Electric Power Syst Res 79(6):937–944. https://doi.org/10.1016/j.epsr.2008.12.004
Panda S (2011) Differential evolution algorithm for SSSC-based damping controller design considering time delay. J Franklin Inst 348(8):1903–1926. https://doi.org/10.1016/j.jfranklin.2011.05.011
Panda S, Padhy NP, Patel RN (2008) Power-system stability improvement by PSO optimized SSSC-based damping controller. Electric Power Compon Syst 36(5):468–490. https://doi.org/10.1080/15325000701735306
Sahu PR, Hota PK, Panda S (2019) Modified whale optimization algorithm for coordinated design of fuzzy lead-lag structure-based SSSC controller and power system stabilizer. Int Trans Electr Energy Syst 29(4):1–21. https://doi.org/10.1002/etep.2797
Sahu PR, Hota PK, Panda S, Lenka RK, Padmanaban S, Blaabjerg F (2021) Coordinated design of FACTS controller with PSS for stability enhancement using a novel hybrid whale optimization algorithm-nelder mead approach. Electric Power Compon Syst 49(16–17):1363–1378. https://doi.org/10.1080/15325008.2022.2129860
Sahu PR, Lenka RK, Khadanga RK, Hota PK, Panda S, Ustun TS (2022) Power system stability improvement of FACTS controller and PSS design: a time-delay approach. Sustainability 14(21):14649. https://doi.org/10.3390/su142114649
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Appendix
Appendix
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1.
MMPS:
Generators: SB1=SB3= 2100 MVA, SB2= 4200 MVA, VB= 13.8 kV, f= 60 Hz
Loads: Load 1= Load 3= 250 MW, Load 2= 50 MW
Transformers: 13.8/500 kV, f =60 Hz, SBT1=SBT3= 2100 MVA, SBT2=1400 MVA
Injected voltage magnitude limit: Vq= \(\pm \) 0.2
Machine 1: Pe1= 1280 MW (0.6095 pu)
Machine 2: Pe2 =3480.6 MW (0.8287pu)
Machine 3: Pe3 =880 MW (0.419pu)
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Kar, M.K. Stability analysis of multi-machine system using FACTS devices. Int J Syst Assur Eng Manag 14, 2136–2145 (2023). https://doi.org/10.1007/s13198-023-02044-6
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DOI: https://doi.org/10.1007/s13198-023-02044-6