KaydedilenlerDerginizi ekleyin

Dergiler / Istanbul University Journal of Electrical and Electronics Engineering / 2017 / Cilt: 17 - Sayı: 2

FUZZY RULE TABLE OPTIMIZATION OF POWER SYSTEM STABILIZER USING GENETIC ALGORITHM

Murat CANER
Seydi Vakkas ÜSTÜN
Yüksel OĞUZ
Sayfa
3489–3496
Yayın Tarihi
2022-10-18
DOI
—
🏛️Bu makalenin bibliyografik verileri ve tam metin bağlantısı DergiPark üzerinden sağlanmıştır.
DergiPark Kaydı ↗
✨

Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

The effectiveness of the proposed approach was discussed by comparing it with the five rule tables.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:This paper investigated the rule table optimization of fuzzy power system stabilizer (FPSS) benefiting from rule basis of related previous studies.
📊
Temel Bulgular & Veri:This work proposed to contribute optimization performance of FPSS adding these rule tables to the initial population of GA.
💡
Sonuç & Katkı:The effectiveness of the proposed approach was discussed by comparing it with the five rule tables.
🔬Tür:Modelleme & Sayısal Simülasyon
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Alan Parametreleri

Abstract

This paper investigated the rule table optimization of fuzzy power system stabilizer (FPSS) benefiting from rule basis of related previous studies. In the previous studies, fuzzy rules for Power System Stabilizer (PSS) were obtained by trial and error according to the experience of experts. There were a few rule tables occurred in that way in the literature. In this subject field, five rule tables with a few differences among them were taken. Genetic algorithm (GA) was employed as an optimization method, and single machine infinite bus (SMIB) model was used for simulation system. This work proposed to contribute optimization performance of FPSS adding these rule tables to the initial population of GA. Thus GAs reached an optimum solution more quickly. Simulation studies and the integral of absolute error (IAE) performance results for four loading conditions were shown. The effectiveness of the proposed approach was discussed by comparing it with the five rule tables.

🔖

Bu Makaleye Atıf Yap

CANER, M., ÜSTÜN, S. V., OĞUZ, Y. (2022). FUZZY RULE TABLE OPTIMIZATION OF POWER SYSTEM STABILIZER USING GENETIC ALGORITHM. Istanbul University Journal of Electrical and Electronics Engineering, Cilt: 17 - Sayı: 2, 3489–3496. https://ajindex.com/articles/543562

📄 Tam Metin PDF Okuyucu

📄

PDF görüntüleyici hazırlanıyor...

Kaynakça (1)

  1. Lu, J., Nehrir, M.H. and Pierre, D.A., "A fuzzy logicbased adaptive power system stabilizer for multimachine systems," Electr. Power Syst. Res., vol. 60, no. 2, pp. 115-121, 2001. doi:10.1109/PESS.2000.867421 [2] Bouchama, Z. and Harmas, M.N., "Optimal robust adaptive fuzzy synergetic power system stabilizer design," Electr. Power Syst. Res., vol. 83, no. 1, pp. 170-175, Feb. 2012. doi:10.1016/j.epsr.2011.11.003 [3] Wang, S.K. "Coordinated parameter design of power system stabilizers and static synchronous compensator using gradual hybrid differential evaluation," Int. J. Electr. Power Energy Syst., vol. 81, pp. 165-174, Oct. 2016. doi:10.1016/j.ijepes.2016.02.016 [4] Mitra, P., Chowdhury, S., Chowdhury, S.P., Pal, S.K., Lahiri, R.N. and Song, Y.H., "Performance of A Fuzzy Power System Stabilizer With Tie Line Active Power Deviation Feedback," 2006 IEEE PES Power Syst. Conf. Expo., pp. 884-889, 2006. doi:10.1109/PSCE.2006.296431 [5] Malik, O.P., "A Fuzzy Logic Based PSS Using a Standardized Rule Table,", Electric Machines & Power Systems, Volume 27, Issue 3, pp. 295-310, 1999. doi:10.1080/073135699269316 [6] Hwang, G-H., Kim, D-W., Lee, J-H. and An, Y-J., "Design of fuzzy power system stabilizer using adaptive evolutionary algorithm," Eng. Appl. Artif. Intell., vol. 21, no. 1, pp. 86-96, 2008. doi:10.1016/j.engappai.2006.11.008 [7] Mrad, F., Karaki, S. and Copti, B., "A novel fuzzy logic synchronous machine stabilizer," IAS '97. Conf. Rec. 1997 IEEE Ind. Appl. Conf. Thirty-Second IAS Annu. Meet., vol. 2, pp. 797-803. doi:10.1109/IAS.1997.628953 [8] Cheng Y. and Elangovan, S., "Enhanced power system stabilizer via integrated tabu-fuzzy knowledge based controller," Int. J. Electr. Power Energy Syst., vol. 25, no. 7, pp. 543-550, 2003. doi:10.1016/S0142- 0615(02)00160-6 [9] Safaee B. and Mashhadi, S.K.M., "Fuzzy membership functions optimization of fuzzy controllers for a quad rotor using particle swarm optimization and genetic algorithm," in 2016 4th International Conference on Control, Instrumentation, and Automation (ICCIA), 2016, vol. 7, pp. 256-261. doi:10.1109/ICCIAutom.2016.7483170 [10] Abido, M.A. and Abdel-Magid, Y.L., "A hybrid neurofuzzy power system stabilizer for multimachine power systems," IEEE Trans. Power Syst., vol. 13, no. 4, pp. 1323-1330, 1998. doi:10.1109/59.736272 [11] Hongesombut, K. and Mitani, Y., "Implementation of Advanced Genetic Algorithm to Modern Power System Stabilization Control," pp. 1-6. doi:10.1109/PSCE.2004.1397451 [1