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Journals / Mühendislik Bilimleri ve Tasarım Dergisi / 2026 / Cilt: 9 Sayı: 3

ANALYSIS OF SOCCER LEAGUE COMPETITION ALGORITHM FOR LOAD FREQUENCY CONTROL IN NONLINEAR INTERCONNECTED POWER SYSTEM

FUTBOL LİGİ MÜSABAKASI ALGORİTMASININ DOĞRUSAL OLMAYAN VE BİRBİRİNE BAĞLI GÜÇ SİSTEMLERİNDE YÜK FREKANS KONTROLÜ İÇİN ANALİZİ

Ahmet Doğan(NUH NACI YAZGAN UNIVERSITY)0000-0002-9552-1997
Pages
866–879
Publication Date
2021-09-21
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Simulation results reveal that better dynamic performance of different test systems is obtained using SLC among the considered algorithms.

📌 3 Key Takeaways

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Objective & Hypothesis:Load Frequency Control (LFC) is a significant tool that provides an equilibrium between generating and consuming real power for efficient operation of power system.
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Key Findings & Data:In this paper, design and performance analysis of Soccer League Competition (SLC) algorithm is provided for optimal solution of LFC in nonlinear interconnected power systems.
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Conclusion & Impact:Simulation results reveal that better dynamic performance of different test systems is obtained using SLC among the considered algorithms.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:Optimizasyon · Yük Frekans Kontrolü · PID

Abstract

Load Frequency Control (LFC) is a significant tool that provides an equilibrium between generating and consuming real power for efficient operation of power system. In this paper, design and performance analysis of Soccer League Competition (SLC) algorithm is provided for optimal solution of LFC in nonlinear interconnected power systems. SLC algorithm has ability of escaping from local minimums while increasing searching capability accuracy with their operators. PID controller parameters are optimized in order to minimize Integral of Time multiplied Absolute Error (ITAE) as objective function. In order to demonstrate efficiency of SLC, two different nonlinear test systems are employed as case studies. At the first instant of study, two area nonlinear thermal power plants with proper value of Generation Rate Constraints (GRC) is considered as test system. Then, the simulations are employed for three-area unequal power system consist of important system limitations such as GRC, Time Delay (TD) and Governor Dead Band (GDB). Simulation results reveal that better dynamic performance of different test systems is obtained using SLC among the considered algorithms.

Özet

Yük Frekans Kontrolü (YFK), güç sistemlerinin verimli çalışması için üretilen ve tüketilen aktif güç arasındaki dengeyi sağlayan önemli bir araçtır. Bu çalışmada, doğrusal olmayan ve birbirine bağlı alanların bulunduğu güç sistemlerinde YFK'nın optimum çözümü için Futbol Ligi Müsabakası (FLM) algoritmasının tasarım ve performans analizi gerçekleştirilmiştir. FLM algoritması, operatörleri sayesinde arama kabiliyetinin doğruluğunu artırırken yerel minimumlardan kaçabilirler. PID denetleyicisinin parametreleri, amaç olarak zamanla çoğaltılmış mutlak hatanın integralini en aza indirmek için optimize edilmiştir. FLM algoritmasının etkinliğinin göstermek için, benzetim çalışması olarak iki farklı doğrusal olmayan test sistemi kullanılmıştır. İlk çalışmada, uygun değerde üretim oranı kısıtlamaları olan iki bölgeli doğrusal olmayan termik santral test sistemi göz önünde bulundurulmuştur. Ardından, üretim oranı kısıtlamaları yanında governor etkisiz bölgesi ve zaman gecikmesi gibi önemli fiziksel kısıtlamalardan oluşan eşit olmayan üç bölgeli güç sistemi üzerinde araştırma yapılmıştır. Benzetim sonuçları, dikkate alınan algoritmalar arasında FLM algoritması kullanılarak gerçekleştirilen benzetimlerde test sistemlerinin daha iyi dinamik performanslarının elde edildiğini göstermektedir.

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Cite This Article

Doğan, A. (2021). ANALYSIS OF SOCCER LEAGUE COMPETITION ALGORITHM FOR LOAD FREQUENCY CONTROL IN NONLINEAR INTERCONNECTED POWER SYSTEM. Mühendislik Bilimleri ve Tasarım Dergisi, Cilt: 9 Sayı: 3, 866–879. https://doi.org/10.21923/jesd.832665

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References (19)

  1. Abou El-Ela, A. A., El-Sehiemy, R. A., Kinawy, A. M., & Mouwafi, M. T. (2016). Optimal capacitor placement in distribution systems for power loss reduction and voltage profile improvement. IET Generation, Transmission and Distribution, 10(5), 1209–1221. https://doi.org/10.1049/iet-gtd.2015.0799
  2. Ali, E. S., & Abd-Elazim, S. M. (2013). BFOA based design of PID controller for two area Load Frequency Control with nonlinearities. International Journal of Electrical Power and Energy Systems, 51, 224–231. https://doi.org/10.1016/j.ijepes.2013.02.030
  3. Chandra Sekhar, G. T., Sahu, R. K., Baliarsingh, A. K., & Panda, S. (2016). Load frequency control of power system under deregulated environment using optimal firefly algorithm. International Journal of Electrical Power and Energy Systems, 74, 195–211. https://doi.org/10.1016/j.ijepes.2015.07.025
  4. Dogan, A. (2019). Load Frequency Control of Two Area and Multi Source Power System Using Grey Wolf Optimization Algorithm. ELECO 2019 - 11th International Conference on Electrical and Electronics Engineering, 81–84. https://doi.org/10.23919/ELECO47770.2019.8990643
  5. Farhangi, R., Boroushaki, M., & Hosseini, S. H. (2012). Load-frequency control of interconnected power system using emotional learning-based intelligent controller. International Journal of Electrical Power and Energy Systems, 36(1), 76–83. https://doi.org/10.1016/j.ijepes.2011.10.026
  6. Golpîra, H., Bevrani, H., & Golpîra, H. (2011). Application of GA optimization for automatic generation control design in an interconnected power system. Energy Conversion and Management, 52(5), 2247–2255. https://doi.org/10.1016/j.enconman.2011.01.010
  7. Gozde, H., Cengiz Taplamacioglu, M., & Kocaarslan, I. (2012). Comparative performance analysis of Artificial Bee Colony algorithm in automatic generation control for interconnected reheat thermal power system. International Journal of Electrical Power and Energy Systems, 42(1), 167–178. https://doi.org/10.1016/j.ijepes.2012.03.039
  8. Guha, D., Roy, P. K., & Banerjee, S. (2016). Load frequency control of interconnected power system using grey Wolf optimization. Swarm and Evolutionary Computation, 27, 97–115. https://doi.org/10.1016/j.swevo.2015.10.004
  9. Guha, D., Roy, P. K., & Banerjee, S. (2018). Application of backtracking search algorithm in load frequency control of multi-area interconnected power system. Ain Shams Engineering Journal, 9(2), 257–276. https://doi.org/10.1016/j.asej.2016.01.004
  10. Imthias Ahamed, T. P., Nagendra Rao, P. S., & Sastry, P. S. (2002). A reinforcement learning approach to automatic generation control. Electric Power Systems Research, 63(1), 9–26. https://doi.org/10.1016/S0378-7796(02)00088-3
  11. Khuntia, S. R., & Panda, S. (2012). Simulation study for automatic generation control of a multi-area power system by ANFIS approach. Applied Soft Computing Journal, 12(1), 333–341. https://doi.org/10.1016/j.asoc.2011.08.039
  12. Mohanty, B., Panda, S., & Hota, P. K. (2014). Controller parameters tuning of differential evolution algorithm and its application to load frequency control of multi-source power system. International Journal of Electrical Power and Energy Systems, 54, 77–85. https://doi.org/10.1016/j.ijepes.2013.06.029
  13. Moosavian, N. (2015). Soccer league competition algorithm for solving knapsack problems. Swarm and Evolutionary Computation, 20, 14–22. https://doi.org/10.1016/j.swevo.2014.10.002
  14. Moosavian, N., & Kasaee Roodsari, B. (2014). Soccer league competition algorithm: A novel meta-heuristic algorithm for optimal design of water distribution networks. Swarm and Evolutionary Computation, 17, 14–24. https://doi.org/10.1016/j.swevo.2014.02.002
  15. Moosavian, N., & Roodsari, B. K. (2014). Soccer League Competition Algorithm, a New Method for Solving Systems of Nonlinear Equations. International Journal of Intelligence Science, 04(01), 7–16. https://doi.org/10.4236/ijis.2014.41002
  16. Sahu, R. K., Panda, S., & Padhan, S. (2015a). A hybrid firefly algorithm and pattern search technique for automatic generation control of multi area power systems. International Journal of Electrical Power and Energy Systems, 64, 9–23. https://doi.org/10.1016/j.ijepes.2014.07.013
  17. Sahu, R. K., Panda, S., & Padhan, S. (2015b). A novel hybrid gravitational search and pattern search algorithm for load frequency control of nonlinear power system. Applied Soft Computing Journal, 29, 310–327. https://doi.org/10.1016/j.asoc.2015.01.020
  18. Umrao, R., Kumar, S., Mohan, M., & Chaturvedi, D. K. (2012). Load Frequency Control methodologies for power system. ICPCES 2012 - 2012 2nd International Conference on Power, Control and Embedded Systems, 179–184. https://doi.org/10.1109/ICPCES.2012.6508133
  19. Yeşil, E., Güzelkaya, M., & Eksin, I. (2004). Self tuning fuzzy PID type load and frequency controller. Energy Conversion and Management, 45(3), 377–390. https://doi.org/10.1016/S0196-8904(03)00149-3