Aşırı Akım Röle Optimizasyonunda Optimizasyon Algoritmalarının Karşılaştırmalı Analizi

Year 2023, , 25 - 32, 28.12.2023

Özge Özgüner , Ebubekir Seyyarer

https://doi.org/10.46810/tdfd.1311104

Abstract

Optimizasyon algoritmaları, belirli bir amaç fonksiyonunun minimum veya maksimum değerini bulmayı amaçlayan problemleri çözmede yaygın olarak kullanılmaktadır. Optimizasyon yöntemleri, en iyi alternatifi seçmek için hem matematiksel hem de sezgisel yaklaşımları kullanmaktadır. Bu çalışmada Aşırı Akım Rölelerinin Koordinasyon (Overcurrent Relay Coordination - ORC) problemini dört optimizasyon algoritması kullanarak en aza indirgemeyi ve sonuçlarını karşılaştırmayı amaçlamaktadır. Aşırı akım röleleri, güç sistemlerinde arızaları tespit eden ve hasarı en aza indiren kritik koruyucu cihazlardır. Güç sistemlerinin güvenliğini sağlamak için koruma rölelerinin doğru seçimi ve ayarlanması önem arz etmektedir. ORC, bir elektrik dağıtım sisteminde röle çalışma süreleri ve ayarları, yük değişiklikleri ve bakım gereksinimleri gibi çok sayıda kısıtlamanın dikkate alınmasını içermektedir. Hasançelebi trafo merkezinin ORC sorunu için Fidan Gelişim Algoritması (Saplings Growing up Algorithm -SGA), Lig Şampiyonluk Algoritması (League Championship Algorithm - LCA), Genetik Algoritma (Genetic Algorithm - GA) ve Balina Optimizasyon Algoritması (Whale Optimization Algorithm - WOA) ile üretilen sonuçlar karşılaştırılmaktadır. Elde edilen sonuçlara göre, WOA’nın diğer optimizasyon algoritmalarına göre daha hızlı sonuçlar ürettiği görülmektedir.

Keywords

Fidan Gelişim Algoritması, Lig Şampiyonluk Algoritması, Genetik Algoritma, Balina Optimizasyon Algoritması, Aşırı – Akım Röle Koordinasyonu

Comparative Analysis of Optimization Algorithms in Overcurrent Relay Optimization

Abstract

Optimization algorithms are commonly used to solve problems aiming to find the minimum or maximum value of a specific objective function. Optimization methods use both mathematical and heuristic approaches to select the best alternative. This study aims to minimize the Overcurrent Relay Coordination (ORC) problem of Overcurrent Relays using four optimization algorithms and compare the results. Overcurrent relays are critical protective devices that detect faults and minimize damage in power systems. Proper selection and adjustment of protective relays are essential to ensure the security of power systems. ORC involves considering numerous constraints such as relay operation times and settings, load changes, and maintenance requirements in an electric distribution system. The results generated by the Saplings Growing up Algorithm (SGA), League Championship Algorithm (LCA), Genetic Algorithm (GA), and Whale Optimization Algorithm (WOA) for the ORC problem in Hasançelebi transformer substation are compared. According to the results obtained, it is observed that the WOA produces faster results than other optimization algorithms.

Keywords

Saplings Growing up Algorithm, League Championship Algorithm, Genetic Algorithm, Whale Optimization Algorithm, Overcurrent Relay Coordination

References

• Chong EK, Żak SH. Gradient methods. An Introduction to Optimization (Fourth ed.). Hoboken: Wiley. 2013:131-60.
• Govan A. Introduction to optimization. InNorth Carolina State University, SAMSI NDHS, Undergraduate workshop 2006 (Vol. 3, p. 6).
• Aydın A. Metasezgisel yöntemlerle uçak çizelgeleme problemi optimizasyonu [Doctoral dissertation]. Turkey: Marmara University; 2009.
• Nevzat ON. Trends in Power System Protection Researches: A Review of Fundamental Relays. Balkan Journal of Electrical and Computer Engineering. 2018 Oct 10;6(4):247-56.
• Zeineldin HH, Sharaf HM, Ibrahim DK, Abou El-Zahab EE. Optimal protection coordination for meshed distribution systems with DG using dual setting directional over-current relays. IEEE transactions on smart grid. 2014 Sep 24;6(1):115-23.
• Akdağ O, Yeroğlu C. Güç sistemlerinde aşırı akım koruma koordinasyon modelinin oluşturulması, benzetimi ve optimizasyonu. Erzincan University Journal of Science and Technology. 2019 Mar 3;12(1):202-14.
• Ortmeyer TH, Hiyama T, Salehfar H. Power quality effects of distribution system faults. International Journal of Electrical Power & Energy Systems. 1996 Jun 1;18(5):323-9.
• Zeineldin H, El-Saadany EF, Salama MA. Optimal coordination of directional overcurrent relay coordination. InIEEE Power Engineering Society General Meeting, 2005 2005 Jun 16 (pp. 1101-1106). IEEE.
• So CW, Li KK. Overcurrent relay coordination by evolutionary programming. Electric power systems research. 2000 Feb 1;53(2):83-90.
• Meskin M, Domijan A, Grinberg I. Optimal co-ordination of overcurrent relays in the interconnected power systems using break points. Electric Power Systems Research. 2015 Oct 1;127:53-63.
• Acharya D, Das DK. Güç dağıtım sisteminde optimum aşırı akım röle koordinasyonu için etkili bir optimizer. Uygulamalarla uzmanlık sistmeleri. 1 Ağustos 2022;199:116858.
• Atsever MB, Hocaoğlu MH. Aşırı Akım Röle Koordinasyonu için Bozkurt Algoritmasının Kapsamlı Performans Analizi. Türk Mühendislik Araştırma ve Eğitimi Dergisi. 2022 Nov 11;1(2):52-61.
• Noghabi AS, Sadeh J, Mashhadi HR. Considering different network topologies in optimal overcurrent relay coordination using a hybrid GA. IEEE Transactions on Power Delivery. 2009 Sep 22;24(4):1857-63.
• Soman SA. Lectures on power system protection. NPTEL, [online] Available: www.cdeep.iitb.ac.in. 2010.
• Uthitsunthorn D, Kulworawanichpong T. Optimal overcurrent relay coordination using genetic algorithms. In 2010 international conference on advances in energy engineering 2010 Jun 19 (pp. 162-165). IEEE.
• Gokhale SS, Kale VS. An application of a tent map initiated Chaotic Firefly algorithm for optimal overcurrent relay coordination. International Journal of Electrical Power & Energy Systems. 2016 Jun 1;78:336-42.
• Razavi F, Abyaneh HA, Al-Dabbagh M, Mohammadi R, Torkaman H. A new comprehensive genetic algorithm method for optimal overcurrent relays coordination. Electric Power Systems Research. 2008 Apr 1;78(4):713-20.
• Alam MN, Das B, Pant V. A comparative study of metaheuristic optimization approaches for directional overcurrent relays coordination. Electric Power Systems Research. 2015 Nov 1;128:39-52.
• Gaikwad AD, Kavita S. Improved League Championship Algorithm (ILCA) for Load Balancing in Cloud Computing. International Journal of Next-Generation Computing. 13.5 2022.
• Langazane SN, Akshay KS. Effects of particle swarm optimization and genetic algorithm control parameters on overcurrent relay selectivity and speed. IEEE Access 10. 2022: 4550-4567.
• Rizal AS, Umam MN, Syaputra AM, Gemayel A. Study of overcurrent relays coordination optimization based on genetic algorithms. In 2020 international conference on technology and policy in energy and electric power (ICT-PEP) IEEE. 2020 Sep: 100-103.
• Wadood A, Khurshaid T, Farkoush SG, Yu J, Kim CH, Rhee SB. Nature-inspired whale optimization algorithm for optimal coordination of directional overcurrent relays in power systems. Energies. 2019.
• Bedekar PP, Bhide SR, Kale VS. Optimum coordination of overcurrent relays in distribution system using genetic algorithm. In2009 International Conference on Power Systems 2009 Dec 27 (pp. 1-6). IEEE.
• Khurshaid T, Wadood A, Farkoush SG, Yu J, Kim CH, Rhee SB. An improved optimal solution for the directional overcurrent relays coordination using hybridized whale optimization algorithm in complex power systems. IEEE Access. 2019 Jul 1;7:90418-35.
• Seyyarer E, Cengiz HA, Ayata F, Uçkan T, Karcı A. Fidan Gelişim ve Lig Şampiyonluk Algoritmaları Kullanarak Aşırı-Akım Rölelerin Optimum Koordinasyonu. Computer Science. 2018 Sep 9;3(2):1-4.
• Seyyarer A, Akdağ O, Hark C, Karci A, Yeroğlu C. Overcurrent relay coordination of 154/34, 5 kV Hasançelebi substation by league championship algorithm. In2017 International Artificial Intelligence and Data Processing Symposium (IDAP) 2017 Sep 16 (pp. 1-6). IEEE.
• Karci A. Natural inspired computational intelligence method: saplings growing up algorithm. In2007 IEEE International Conference on Computational Cybernetics 2007 Oct 19 (pp. 221-226). IEEE.
• Karci A, Alatas B. Thinking capability of saplings growing up algorithm. International conference on intelligent data engineering and automated learning. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006.
• Kashan AH. League championship algorithm: a new algorithm for numerical function optimization. In2009 international conference of soft computing and pattern recognition 2009 Dec 4 (pp. 43-48). IEEE.
• Wangchamhan T, Chiewchanwattana S, Sunat K. Efficient algorithms based on the k-means and Chaotic League Championship Algorithm for numeric, categorical, and mixed-type data clustering. Expert Systems with Applications. 2017 Dec 30;90:146-67.
• Kashan AH. League Championship Algorithm (LCA): An algorithm for global optimization inspired by sport championships. Applied Soft Computing 16. 2014: 171-200.
• Mathew TV. Genetic algorithm. Report submitted at IIT Bombay. 2012:53.
• Keshav R. Sharma [Internet]. 2022 [Cited 2023 Sep 21]. Available from: https://vidyasheela.com/post/gentle-introduction-to-genetic-algorithm
• Kumar M, Husain DM, Upreti N, Gupta D. Genetic algorithm: Review and application. Available at SSRN 3529843. 2010 Dec 1.
• Mirjalili S, Lewis A. The whale optimization algorithm. Advances in engineering software. 2016 May 1;95:51-67.
• Goldbogen JA, Friedlaender AS, Calambokidis J, Mckenna MF, Simon M, Nowacek DP. Integrative approaches to the study of baleen whale diving behavior, feeding performance, and foraging ecology. BioScience. 2013 Feb 1;63(2):90-100.
• Karababa S. Harmoniklerin dijital aşırı akım röleleri üzerine etkisinin incelenmesi [Master’s dissertation]. Turkey: Yıldız Technical University; 2008.
• Amraee T. Coordination of directional overcurrent relays using seeker algorithm. IEEE Transactions on Power Delivery. 2012 Apr 10;27(3):1415-22.