According to the eigenvalue analysis and time response parameters results, the FA-PID-PSS (case-II) can stabilize the system for all operating conditions.
📌 3 Key Takeaways
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Objective & Hypothesis:This paper presents the design of a proportional-integral-derivative power-system-stabilizer using the firefly algorithm for tuning of stabilizer parameters and washout (reset).
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Key Findings & Data:The system performance with firefly algorithm tuned controller is compared with Bat-Algorithm optimized Conventional-Power-System-Stabilizer controller.
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Conclusion & Impact:According to the eigenvalue analysis and time response parameters results, the FA-PID-PSS (case-II) can stabilize the system for all operating conditions.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:“Conventional power system stabilizer” · “Firefly algorithm optimized proportional integral derivative based power system stabilizer (FA-PID-PSS)” · “Bat algorithm optimized conventional power system stabilizer (BA-CPSS)”
Abstract
This paper presents the design of a proportional-integral-derivative power-system-stabilizer using the firefly algorithm for tuning of stabilizer parameters and washout (reset). The proposed optimization of parameters is carried out with eigenvalue analysis based objective function for two cases to guarantee the stability for the single-machine-infinite-bus system model for a wide range of operating conditions. The system performance with firefly algorithm tuned controller is compared with Bat-Algorithm optimized Conventional-Power-System-Stabilizer controller. The power system robustness is tested on 133 operating conditions. According to the eigenvalue analysis and time response parameters results, the FA-PID-PSS (case-II) can stabilize the system for all operating conditions.
Farhad, Z., EKE, I., TEZCAN, S. S., SAFI, S. J. (2018). A Robust PID Power System Stabilizer Design of Single Machine Infinite Bus System using Firefly Algorithm. Gazi University Journal of Science, Cilt: 31 - Sayı: 1, 155–172. https://ajindex.com/articles/254682
Mohamed Kamari, N. A., Musirin, I., Othman, M. M. and Hamid, Z. A., “PSS-LL Based Power System Stability Enhancement Using IPSO Approach”, IEEE 7th International Power engineering and Optimization conference (PEOCO2013), 2013; Page(s): 658 - 663
Shubhanga, Dr. K. N., Yadi Anantholla, Mr. “Manual for A Multi-machine Small-signal Stability Program”, Version-1, India
Abdul Jaleel, J., Thanvy, N., “A Comparative Study between PLPD,PID and Lead-Lag controllers for Power System Stabilizer” 2013 International Conference on Circuits, Power and Computing Technologies [ICCPCT-2013], India, (2013)
Demello, FP., Concordia, C. “Concepts of synchronous machine stability as affected by excitation control”. IEEE Trans Power Apparatus System 1969; PAS-88:316–29
Sebaa, K., Boudour, M., “Optimal locations and tuning of robust power system stabilizer using genetic algorithms”. Electr Power Syst Res 2009;79:406–16
Peng, Z., Malik, OP., “Design of an adaptive PSS based on recurrent adaptive control theory”. IEEE Trans Energy Convers,2009;24:884–92
Ramakrishna, G., Malik, OP., “Adaptive PSS using a simple on-line identifier and linear pole-shift controller”. Electrical Power Syst Res, 2010; 80:406–16.http:// dx.doi.org/10.1016/j.epsr.2009.10.004
Sambariya, D.K., Prasad, R., “Robust tuning of power system stabilizer for small signal stability enhancement using metaheuristic bat algorithm” Electrical Power and Energy Systems 61 (2014) 229–238, journal homepage
EKE,I., TAPLAMACIOĞLU, M. C. ve KOCA ARSLAN, I., “Power System Stabilizer Design for Rotor angle stability ”, International Journal of Engineering Research and Development, Vol.3, No.2, June 2011
Al-Duwaish, H.N., Al-Hamouz, Z.M., “A neural network based adaptive sliding mode controller: application to a power syst stabilizer”. Energy Convers Manage 2011; 52:1533-8
Soliman, M., Elshafei A.L., Bendary, F., Mansour, W. LMI., “Static output-feedback design of fuzzy Sower System Stabilizers”. Expert System Appl 2009; 36:6817–25
Mukherjee, V., Ghoshal, SP., “Intelligent particle swarm optimized fuzzy PID controller for AVR system”, Electrical Power System Res 2007; 77:1689–98
Bhati, PS., Gupta, R., “Robust fuzzy logic power system stabilizer based on evolution and learning”. Int J Electrical Power Energy System 2013; 53:357–66