Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2020, Cilt: 35 Sayı: 1, 165 - 180, 25.10.2019
https://doi.org/10.17341/gazimmfd.449685

Öz

Kaynakça

  • Referans1. Shokouhandeh H., Jazaeri M., An enhanced and auto‐tuned power system stabilizer based on optimized interval type‐2 fuzzy PID scheme, International Transactions on Electrical Energy Systems, 28(1), 2018.
  • Referans2. Shakarami M.R., Davoudkhani I.F., Wide-area power system stabilizer design based on grey wolf optimization algorithm considering the time delay, Electric Power Systems Research, 133, 149-159, 2016.
  • Referans3. Alkhatib H., Duveau J., Dynamic genetic algorithms for robust design of multimachine power system stabilizers, International Journal of Electrical Power & Energy Systems, 45(1), 242-251, 2013.
  • Referans4. Rogers G., Power system oscillations. Springer Science & Business Media, 2012.
  • Referans5. Kundur P., Klein M., Rogers G.J., Zywno M.S., Application of power system stabilizers for enhancement of overall system stability, IEEE Transactions on Power Systems, 4(2), 614-626, 1989.
  • Referans6. Bollinger K., Laha A., Hamilton R., Harras T, Power stabilizer design using root locus methods, IEEE Transactions on power apparatus and systems, 94(5), 1484-1488, 1975.
  • Referans7. Larsen E.V., Swann D.A., Applying Power System Stabilizers Part II: Performance Objectives and Tuning Concepts, IEEE Transactions on Power Apparatus and Systems, 100(6), 3025-3033, 1981.
  • Referans8. Cai L.J., Erlich I., Simultaneous coordinated tuning of PSS and FACTS damping controllers in large power systems, IEEE Transactions on Power Systems, 20(1), 294-300, 2005.
  • Referans9. Abido M.A., Abdel-Magid Y.L., Eigenvalue assignments in multimachine power systems using tabu search algorithm, Computers & Electrical Engineering, 28(6), 527-545, 2002.
  • Referans10. Abido M.A., Robust design of multimachine power system stabilizers using simulated annealing, IEEE Transactions on Energy conversion, 15(3), 297-304, 2000.
  • Referans11. Hassan L.H., Moghavvemi M., Almurib H.A., Muttaqi K.M., Ganapathy V.G., Optimization of power system stabilizers using participation factor and genetic algorithm, International Journal of Electrical Power & Energy Systems, 55, 668-679, 2014.
  • Referans12. Ekinci S., Demiroren A., Hekimoglu B., Parameter optimization of power system stabilizers via kidney-inspired algorithm, Transactions of the Institute of Measurement and Control, 2018.
  • Referans13. Ekinci S., Demiroren A., PSO based PSS design for transient stability enhancement, IU-Journal of Electrical & Electronics Engineering, 15(1), 1855-1862, 2015.
  • Referans14. Sambariya D.K., Prasad R., Robust tuning of power system stabilizer for small signal stability enhancement using metaheuristic bat algorithm, International Journal of Electrical Power & Energy Systems, 61, 229-238, 2014.
  • Referans15. Eke İ., Taplamacıoğlu M.C., Kocaarslan İ., Design of robust power system stabilizer based on Artificial Bee Colony Algorithm, Journal of the Faculty of Engineering and Architecture of Gazi University, 26(3), 683-690, 2011.
  • Referans16. Abd-Elazim S.M., Ali E.S., Power system stability enhancement via bacteria foraging optimization algorithm, Arabian Journal for Science and Engineering, 38(3), 599-611, 2013.
  • Referans17. Hameed K.A., Palani S., Robust design of power system stabilizer using harmony search algorithm, Automatika, 55(2), 162-169, 2014.
  • Referans18. Islam N.N., Hannan M.A., Shareef H., Mohamed A., An application of backtracking search algorithm in designing power system stabilizers for large multi-machine system, Neurocomputing, 237, 175-184, 2017.
  • Referans19. Guesmi T., Alshammari B.M., An improved artificial bee colony algorithm for robust design of power system stabilizers, Engineering Computations, 34(7), 2131-2153, 2017.
  • Referans20. Shayeghi H., Ghasemi A., Shayanfar H., PID type stabilizer design for multi machine power system using IPSO procedure, Computer Science and Engineering, 1(2), 36-42, 2011.
  • Referans21. Khodabakhshian A., Hemmati R., Multi-machine power system stabilizer design by using cultural algorithms, International Journal of Electrical Power & Energy Systems, 44(1), 571-580, 2013.
  • Referans22. Khodabakhshian A., Hemmati R., Moazzami M., Multi-band power system stabilizer design by using CPCE algorithm for multi-machine power system, Electric Power Systems Research, 101, 36-48, 2013.
  • Referans23. Abd-Elazim S.M., Ali E.S., A hybrid particle swarm optimization and bacterial foraging for optimal power system stabilizers design, International Journal of Electrical Power & Energy Systems, 46, 334-341, 2013.
  • Referans24. Eslami M., Shareef H., Khajehzadeh M., Optimal design of damping controllers using a new hybrid artificial bee colony algorithm, International Journal of Electrical Power & Energy Systems, 52, 42-54, 2013.
  • Referans25. Ekinci S., Hekimoglu B., Multi-machine power system stabilizer design via HPA algorithm, Journal of the Faculty of Engineering and Architecture of Gazi University, 32(4), 1271-1285, 2017.
  • Referans26. Saremi S., Mirjalili S., Lewis A., Grasshopper Optimisation Algorithm: Theory and application, Advances in Engineering Software, 105, 30-47, 2017.
  • Referans27. El-Fergany A.A., Electrical characterisation of proton exchange membrane fuel cells stack using grasshopper optimizer, IET Renewable Power Generation, 12(1), 9-17, 2017.
  • Referans28. Tumuluru P., Ravi B., GOA-based DBN: Grasshopper Optimization Algorithm-based Deep Belief Neural Networks for Cancer Classification, Int. J. of Appl. Eng. Research, 12, 14218-14231, 2017.
  • Referans29. Wu J., Wang H., Li N., Yao P., Huang Y., Su Z., Yu Y., Distributed trajectory optimization for multiple solar-powered UAVs target tracking in urban environment by Adaptive Grasshopper Optimization Algorithm, Aerospace Science and Technology, 70, 497-510, 2017.
  • Referans30. Łukasik S., Kowalski P.A., Charytanowicz M., Kulczycki P., Data clustering with grasshopper optimization algorithm, in Proc. 2017 Federated Conf. on Computer Science and Information Systems (FedCSIS); 71-74.
  • Referans31. Barman M., Dev Choudhury N.B., Sutradhar S., A regional hybrid GOA-SVM model based on similar day approach for short-term load forecasting in Assam, India, Energy, 145, 710-720, 2018.
  • Referans32. Mafarja M., Aljarah I., Heidari A.A., Hammouri A.I., Faris H., Ala’M A.Z., Mirjalili S., Evolutionary population dynamics and grasshopper optimization approaches for feature selection problems, Knowledge-Based Systems, 145, 25-45, 2018.
  • Referans33. Hekimoglu B., Ekinci S., Grasshopper Optimization Algorithm for Automatic Voltage Regulator System, in Proc. The 5th International Conference on Electrical and Electronics Engineering (ICEEE), Istanbul, Turkey, 152-156, 03-05, May, 2018.
  • Referans34. Tang Y., Cui M., Hua C., Li L., Yang Y., Optimum design of fractional order PIλDμ controller for AVR system using chaotic ant swarm, Expert Systems with Applications, 39(8), 6887-6896, 2012.
  • Referans35. Sikander A., Thakur P., Bansal R.C., Rajasekar S., A novel technique to design cuckoo search based FOPID controller for AVR in power systems, Computers & Electrical Engineering, 2017, in press.
  • Referans36. Ekinci S., Demirören A., Modeling, simulation, and optimal design of power system stabilizers using ABC algorithm, Turkish Journal of Electrical Engineering & Computer Sciences, 24(3), 1532-1546, 2016.
  • Referans37. Podlubny I., Fractional-order systems and PID controllers. IEEE Transactions on automatic control, 44(1), 208-214, 1999.
  • Referans38. Shah P., Agashe S., Review of fractional PID controller. Mechatronics, 38, 29-41, 2016.
  • Referans39. Sauer P.W., Pai M.A., Chow J.H., Power system dynamics and stability: with synchrophasor measurement and power system toolbox. Hoboken, NJ, USA: IEEE Press, Wiley, 2018.
  • Referans40. Mondal D., Chakrabarti A., Sengupta A., Power system small signal stability analysis and control. Academic Press, 2014.
  • Referans41. Guesmi T., Farah A., Abdallah H.H., Ouali A., Robust design of multimachine power system stabilizers based on improved non-dominated sorting genetic algorithms, Electrical Engineering, 1-13, 2017.
  • Referans42. Kundur P., Power System Stability and Control. New York, NY, USA: McGraw-Hill, 1994.
  • Referans43. Gaing Z.L., A particle swarm optimization approach for optimum design of PID controller in AVR system, IEEE Transactions on Energy Conversion, 19(2), 384-391, 2004.
  • Referans44. Ekinci S., Application and comparative performance analysis of PSO and ABC algorithms for optimal design of multi-machine power system stabilizers, Gazi University Journal of Science, 29(2),323-334, 2016.
  • Referans45. Ekinci S., Hekimoğlu B., Uysal E., PID güç sistemi kararlı kılıcısı parametrelerinin belirlenmesi için böbrek-ilhamlı algoritma, Politeknik Dergisi, 2018, DOI: 10.2339/politeknik.417765.
  • Referans46. Ekinci S., Lale Zeynelgil H., Demiroren A., A didactic procedure for transient stability simulation of a multi-machine power system utilizing SIMULINK. International Journal of Electrical Engineering Education, 53(1), 54-71, 2016.

Çekirge optimizasyon algoritması kullanılarak çok makinalı güç sistemi için gürbüz kesir dereceli PID kararlı kılıcısı tasarımı

Yıl 2020, Cilt: 35 Sayı: 1, 165 - 180, 25.10.2019
https://doi.org/10.17341/gazimmfd.449685

Öz

Geleneksel türev-tabanlı metotların ve diğer
sezgisel-üstü algoritmaların eksiklerini gidermek amacıyla, bu çalışmada yeni
bir sezgisel-üstü teknik olan çekirge optimizasyon algoritmasının (GOA) kesir
dereceli oransal-integral-türev (FOPID) kontrolör yapılı güç sistemi kararlı
kılıcısının (PSS) gürbüz tasarımında kullanılması önerilmiştir. FOPID tipi PSS
parametrelerinin ayarlama problemi, zaman tanım bölgesi tabanlı bir amaç
fonksiyonu ile bir optimizasyon problemine dönüştürüldü ve GOA ile çözüldü.
Önerilen yaklaşım farklı yüklenme koşulları ve arızalara maruz kalan çok
makinalı güç sistemine uygulandı. Önerilen GOA-tabanlı yeni tasarlanan FOPID
yapılı kararlı kılıcının (GOA-FOPIDPSS) performansı GA-, ABC- ve ayrıca
önerilen GOA-tabanlı klasik yapılı kararlı kılıcılar ile karşılaştırdı.
Önerilen kararlı kılıcının üstünlüğü, potansiyeli ve gürbüzlüğü lineer olmayan
simülasyon çalışmaları ve bazı dinamik performans indeksleri vasıtasıyla
doğrulandı. Analiz sonuçları, önerilen GOA-FOPIDPSS kontrolörünün farklı
arızalar ve geniş çalışma koşullarında düşük frekanslı salınımlara mükemmel
sönümleme performansı verdiğini göstermiştir.

Kaynakça

  • Referans1. Shokouhandeh H., Jazaeri M., An enhanced and auto‐tuned power system stabilizer based on optimized interval type‐2 fuzzy PID scheme, International Transactions on Electrical Energy Systems, 28(1), 2018.
  • Referans2. Shakarami M.R., Davoudkhani I.F., Wide-area power system stabilizer design based on grey wolf optimization algorithm considering the time delay, Electric Power Systems Research, 133, 149-159, 2016.
  • Referans3. Alkhatib H., Duveau J., Dynamic genetic algorithms for robust design of multimachine power system stabilizers, International Journal of Electrical Power & Energy Systems, 45(1), 242-251, 2013.
  • Referans4. Rogers G., Power system oscillations. Springer Science & Business Media, 2012.
  • Referans5. Kundur P., Klein M., Rogers G.J., Zywno M.S., Application of power system stabilizers for enhancement of overall system stability, IEEE Transactions on Power Systems, 4(2), 614-626, 1989.
  • Referans6. Bollinger K., Laha A., Hamilton R., Harras T, Power stabilizer design using root locus methods, IEEE Transactions on power apparatus and systems, 94(5), 1484-1488, 1975.
  • Referans7. Larsen E.V., Swann D.A., Applying Power System Stabilizers Part II: Performance Objectives and Tuning Concepts, IEEE Transactions on Power Apparatus and Systems, 100(6), 3025-3033, 1981.
  • Referans8. Cai L.J., Erlich I., Simultaneous coordinated tuning of PSS and FACTS damping controllers in large power systems, IEEE Transactions on Power Systems, 20(1), 294-300, 2005.
  • Referans9. Abido M.A., Abdel-Magid Y.L., Eigenvalue assignments in multimachine power systems using tabu search algorithm, Computers & Electrical Engineering, 28(6), 527-545, 2002.
  • Referans10. Abido M.A., Robust design of multimachine power system stabilizers using simulated annealing, IEEE Transactions on Energy conversion, 15(3), 297-304, 2000.
  • Referans11. Hassan L.H., Moghavvemi M., Almurib H.A., Muttaqi K.M., Ganapathy V.G., Optimization of power system stabilizers using participation factor and genetic algorithm, International Journal of Electrical Power & Energy Systems, 55, 668-679, 2014.
  • Referans12. Ekinci S., Demiroren A., Hekimoglu B., Parameter optimization of power system stabilizers via kidney-inspired algorithm, Transactions of the Institute of Measurement and Control, 2018.
  • Referans13. Ekinci S., Demiroren A., PSO based PSS design for transient stability enhancement, IU-Journal of Electrical & Electronics Engineering, 15(1), 1855-1862, 2015.
  • Referans14. Sambariya D.K., Prasad R., Robust tuning of power system stabilizer for small signal stability enhancement using metaheuristic bat algorithm, International Journal of Electrical Power & Energy Systems, 61, 229-238, 2014.
  • Referans15. Eke İ., Taplamacıoğlu M.C., Kocaarslan İ., Design of robust power system stabilizer based on Artificial Bee Colony Algorithm, Journal of the Faculty of Engineering and Architecture of Gazi University, 26(3), 683-690, 2011.
  • Referans16. Abd-Elazim S.M., Ali E.S., Power system stability enhancement via bacteria foraging optimization algorithm, Arabian Journal for Science and Engineering, 38(3), 599-611, 2013.
  • Referans17. Hameed K.A., Palani S., Robust design of power system stabilizer using harmony search algorithm, Automatika, 55(2), 162-169, 2014.
  • Referans18. Islam N.N., Hannan M.A., Shareef H., Mohamed A., An application of backtracking search algorithm in designing power system stabilizers for large multi-machine system, Neurocomputing, 237, 175-184, 2017.
  • Referans19. Guesmi T., Alshammari B.M., An improved artificial bee colony algorithm for robust design of power system stabilizers, Engineering Computations, 34(7), 2131-2153, 2017.
  • Referans20. Shayeghi H., Ghasemi A., Shayanfar H., PID type stabilizer design for multi machine power system using IPSO procedure, Computer Science and Engineering, 1(2), 36-42, 2011.
  • Referans21. Khodabakhshian A., Hemmati R., Multi-machine power system stabilizer design by using cultural algorithms, International Journal of Electrical Power & Energy Systems, 44(1), 571-580, 2013.
  • Referans22. Khodabakhshian A., Hemmati R., Moazzami M., Multi-band power system stabilizer design by using CPCE algorithm for multi-machine power system, Electric Power Systems Research, 101, 36-48, 2013.
  • Referans23. Abd-Elazim S.M., Ali E.S., A hybrid particle swarm optimization and bacterial foraging for optimal power system stabilizers design, International Journal of Electrical Power & Energy Systems, 46, 334-341, 2013.
  • Referans24. Eslami M., Shareef H., Khajehzadeh M., Optimal design of damping controllers using a new hybrid artificial bee colony algorithm, International Journal of Electrical Power & Energy Systems, 52, 42-54, 2013.
  • Referans25. Ekinci S., Hekimoglu B., Multi-machine power system stabilizer design via HPA algorithm, Journal of the Faculty of Engineering and Architecture of Gazi University, 32(4), 1271-1285, 2017.
  • Referans26. Saremi S., Mirjalili S., Lewis A., Grasshopper Optimisation Algorithm: Theory and application, Advances in Engineering Software, 105, 30-47, 2017.
  • Referans27. El-Fergany A.A., Electrical characterisation of proton exchange membrane fuel cells stack using grasshopper optimizer, IET Renewable Power Generation, 12(1), 9-17, 2017.
  • Referans28. Tumuluru P., Ravi B., GOA-based DBN: Grasshopper Optimization Algorithm-based Deep Belief Neural Networks for Cancer Classification, Int. J. of Appl. Eng. Research, 12, 14218-14231, 2017.
  • Referans29. Wu J., Wang H., Li N., Yao P., Huang Y., Su Z., Yu Y., Distributed trajectory optimization for multiple solar-powered UAVs target tracking in urban environment by Adaptive Grasshopper Optimization Algorithm, Aerospace Science and Technology, 70, 497-510, 2017.
  • Referans30. Łukasik S., Kowalski P.A., Charytanowicz M., Kulczycki P., Data clustering with grasshopper optimization algorithm, in Proc. 2017 Federated Conf. on Computer Science and Information Systems (FedCSIS); 71-74.
  • Referans31. Barman M., Dev Choudhury N.B., Sutradhar S., A regional hybrid GOA-SVM model based on similar day approach for short-term load forecasting in Assam, India, Energy, 145, 710-720, 2018.
  • Referans32. Mafarja M., Aljarah I., Heidari A.A., Hammouri A.I., Faris H., Ala’M A.Z., Mirjalili S., Evolutionary population dynamics and grasshopper optimization approaches for feature selection problems, Knowledge-Based Systems, 145, 25-45, 2018.
  • Referans33. Hekimoglu B., Ekinci S., Grasshopper Optimization Algorithm for Automatic Voltage Regulator System, in Proc. The 5th International Conference on Electrical and Electronics Engineering (ICEEE), Istanbul, Turkey, 152-156, 03-05, May, 2018.
  • Referans34. Tang Y., Cui M., Hua C., Li L., Yang Y., Optimum design of fractional order PIλDμ controller for AVR system using chaotic ant swarm, Expert Systems with Applications, 39(8), 6887-6896, 2012.
  • Referans35. Sikander A., Thakur P., Bansal R.C., Rajasekar S., A novel technique to design cuckoo search based FOPID controller for AVR in power systems, Computers & Electrical Engineering, 2017, in press.
  • Referans36. Ekinci S., Demirören A., Modeling, simulation, and optimal design of power system stabilizers using ABC algorithm, Turkish Journal of Electrical Engineering & Computer Sciences, 24(3), 1532-1546, 2016.
  • Referans37. Podlubny I., Fractional-order systems and PID controllers. IEEE Transactions on automatic control, 44(1), 208-214, 1999.
  • Referans38. Shah P., Agashe S., Review of fractional PID controller. Mechatronics, 38, 29-41, 2016.
  • Referans39. Sauer P.W., Pai M.A., Chow J.H., Power system dynamics and stability: with synchrophasor measurement and power system toolbox. Hoboken, NJ, USA: IEEE Press, Wiley, 2018.
  • Referans40. Mondal D., Chakrabarti A., Sengupta A., Power system small signal stability analysis and control. Academic Press, 2014.
  • Referans41. Guesmi T., Farah A., Abdallah H.H., Ouali A., Robust design of multimachine power system stabilizers based on improved non-dominated sorting genetic algorithms, Electrical Engineering, 1-13, 2017.
  • Referans42. Kundur P., Power System Stability and Control. New York, NY, USA: McGraw-Hill, 1994.
  • Referans43. Gaing Z.L., A particle swarm optimization approach for optimum design of PID controller in AVR system, IEEE Transactions on Energy Conversion, 19(2), 384-391, 2004.
  • Referans44. Ekinci S., Application and comparative performance analysis of PSO and ABC algorithms for optimal design of multi-machine power system stabilizers, Gazi University Journal of Science, 29(2),323-334, 2016.
  • Referans45. Ekinci S., Hekimoğlu B., Uysal E., PID güç sistemi kararlı kılıcısı parametrelerinin belirlenmesi için böbrek-ilhamlı algoritma, Politeknik Dergisi, 2018, DOI: 10.2339/politeknik.417765.
  • Referans46. Ekinci S., Lale Zeynelgil H., Demiroren A., A didactic procedure for transient stability simulation of a multi-machine power system utilizing SIMULINK. International Journal of Electrical Engineering Education, 53(1), 54-71, 2016.
Toplam 46 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Makaleler
Yazarlar

Baran Hekimoğlu 0000-0002-1839-025X

Yayımlanma Tarihi 25 Ekim 2019
Gönderilme Tarihi 31 Temmuz 2018
Kabul Tarihi 16 Mart 2019
Yayımlandığı Sayı Yıl 2020 Cilt: 35 Sayı: 1

Kaynak Göster

APA Hekimoğlu, B. (2019). Çekirge optimizasyon algoritması kullanılarak çok makinalı güç sistemi için gürbüz kesir dereceli PID kararlı kılıcısı tasarımı. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 35(1), 165-180. https://doi.org/10.17341/gazimmfd.449685
AMA Hekimoğlu B. Çekirge optimizasyon algoritması kullanılarak çok makinalı güç sistemi için gürbüz kesir dereceli PID kararlı kılıcısı tasarımı. GUMMFD. Ekim 2019;35(1):165-180. doi:10.17341/gazimmfd.449685
Chicago Hekimoğlu, Baran. “Çekirge Optimizasyon Algoritması kullanılarak çok Makinalı güç Sistemi için gürbüz Kesir Dereceli PID Kararlı kılıcısı tasarımı”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 35, sy. 1 (Ekim 2019): 165-80. https://doi.org/10.17341/gazimmfd.449685.
EndNote Hekimoğlu B (01 Ekim 2019) Çekirge optimizasyon algoritması kullanılarak çok makinalı güç sistemi için gürbüz kesir dereceli PID kararlı kılıcısı tasarımı. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 35 1 165–180.
IEEE B. Hekimoğlu, “Çekirge optimizasyon algoritması kullanılarak çok makinalı güç sistemi için gürbüz kesir dereceli PID kararlı kılıcısı tasarımı”, GUMMFD, c. 35, sy. 1, ss. 165–180, 2019, doi: 10.17341/gazimmfd.449685.
ISNAD Hekimoğlu, Baran. “Çekirge Optimizasyon Algoritması kullanılarak çok Makinalı güç Sistemi için gürbüz Kesir Dereceli PID Kararlı kılıcısı tasarımı”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi 35/1 (Ekim 2019), 165-180. https://doi.org/10.17341/gazimmfd.449685.
JAMA Hekimoğlu B. Çekirge optimizasyon algoritması kullanılarak çok makinalı güç sistemi için gürbüz kesir dereceli PID kararlı kılıcısı tasarımı. GUMMFD. 2019;35:165–180.
MLA Hekimoğlu, Baran. “Çekirge Optimizasyon Algoritması kullanılarak çok Makinalı güç Sistemi için gürbüz Kesir Dereceli PID Kararlı kılıcısı tasarımı”. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, c. 35, sy. 1, 2019, ss. 165-80, doi:10.17341/gazimmfd.449685.
Vancouver Hekimoğlu B. Çekirge optimizasyon algoritması kullanılarak çok makinalı güç sistemi için gürbüz kesir dereceli PID kararlı kılıcısı tasarımı. GUMMFD. 2019;35(1):165-80.