Secondary Frequency Regulation Using Exponential PI Controller for a Power System Comprising of Thermal Power Plant and PV Solar Energy System
Abstract
Imbalance between power generation and load demand causes unwanted undulations in frequency and tie-line power responses. These undulations closely affect the reliability/security of the power system, quality of the energy generated and the end user. In accomplishing generation suitable for consumption, secondary frequency regulation (SFR) is an inevitable control technique. In this brief, an exponential PI (EXP-PI) controller is proposed to enhance the performance of SFR in an interconnected power system. Snake optimizer (SO), one of the computational intelligence techniques, is benefitted for adjusting the controller parameters optimally. This way, without the requirement of an expert knowledge, controller parameters are searched optimally by minimizing the value of integral of time-multiplied absolute error (ITAE). To confirm the contribution of SO tuned EXP-PI controller, comparisons with the works in literature are established. It is deduced from the obtained results that the system performance with our proposal has enhanced in terms of oscillation, settling time, maximum overshoot/undershoot and ITAE value of the frequency and tie-line power responses.
Keywords
Secondary Frequency Regulation Exponential PI Controller Thermal Power Plant PV Solar Energy System Snake Optimizer Optimization
References
- P.P. Kumar, A. Kumar Yadav, A. Shastri, and P.A. Alvi, “BWOA assisted PIDF-(1+I) controller for intelligent load frequency management of standalone micro-grid”, ISA Transactions vol. 132, pp. 387–401, 2023.
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- U.K. Rout, R.K. Sahu, and S.Panda, “Design and analysis of differential evolution algorithm based automatic generation control for interconnected power system”, Ain Shams Engineering Journal, vol. 4, no. 3, pp. 409–421, 2013.
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- B. Mohanty, S. Panda, and P.K. Hota, “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, vol. 54, no.1, pp. 77–85, 2014.
- E. Çelik, “Improved stochastic fractal search algorithm and modified cost function for automatic generation control of interconnected electric power systems”, Engineering Applications of Artificial Intelligence, vol. 88, pp. 103407, 2020.
- Sahu R.K., Panda S., Rout U.K., Sahoo D.K., Teaching learning based optimization algorithm for automatic generation control of power system using 2-DOF PID controller, International Journal of Electrical Power and Energy Systems, 77 (5), 287–301, 2016.
- A.K. Barisal, “Comparative performance analysis of teaching learning based optimization for automatic load frequency control of multi-source power systems”, International Journal of Electrical Power and Energy Systems, vol. 66, no.3, pp. 67–77, 2015.
- R.K Sahu, S. Panda, and G.T.C. Sekhar, “A novel hybrid PSO-PS optimized fuzzy PI controller for AGC in multi area interconnected power systems”, International Journal of Electrical Power and Energy Systems, vol.64, no.1, pp. 880–893, 2015.
- S. Padhy, S. Panda, and S. Mahapatra, “A modified GWO technique based cascade PI-PD controller for AGC of power systems in presence of Plug in Electric Vehicles”, Engineering Science and Technology, an International Journal, vol. 20, no. 2, pp. 427–442, 2017.
- E. Çelik, and A. Dalcalı, Performance betterment of load frequency regulation using snake search algorithm for an interconected power system incorporating thermal plant and pv power station, 5th International Antalya Scientific Research and Innovative Studies Congress, pp. 610−621, Antalya, Turkiye,26-28 July 2023.
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- E. Çelik, N. Öztürk, Y. Arya, and C. Ocak, “(1+PD)-PID cascade controller design for performance betterment of load frequency control in diverse electric power systems”, Neural Computing and Applications, vol.33, pp. 15433−15456, 2021.
Termik Güç Santrali ve Fotovoltaik Güneş Enerji Sisteminden Oluşan Güç Sisteminde Üstel PI Denetleyici ile Sekonder Frekans Regülasyonu
Abstract
Güç üretimi ve yük talebi arasında yaşanan bir uyumsuzluk frekans ve bağlantı hattı güç tepkilerinde arzu edilmeyen salınımlara neden olur. Bu salınımlar güç sisteminin güvenirliğini/güvenliğini, üretilen enerjinin kalitesini ve son kullanıcıları yakından etkilemektedirler. Tüketime uygun üretimin gerçekleştirilmesinde sekonder frekans regülasyonu (SFR) kaçınılmaz bir kontrol tekniğidir. Bu çalışmada enterkonnekte bir güç sisteminde SFR performansının artırılması için üstel PI denetleyicisi önerilmiştir. Denetleyici parametrelerinin optimum ayarı için işlemsel zekâ tekniklerinden yılan arama algoritmasından (YAA) faydalanılmıştır. Böylece denetleyici parametreleri zaman ağırlıklı mutlak hatanın integral (ITAE) değeri en az yapılacak şekilde uzman bilgisine gerek duyulmadan optimum şekilde araştırılmıştır. YAA tabanlı üstel PI denetleyicinin alana katkısını doğrulamak amacıyla literatürdeki çalışmalarla karşılaştırmalar gerçekleştirilmiştir. Elden edilen sonuçlardan önerilen yöntem ile sistem performansının frekans ve bağlantı hattı güç tepkilerindeki osilasyon, oturma süresi, maksimum pozitif/negatif aşım ve ITAE değerleri bakımından iyileştiği anlaşılmıştır.
Keywords
Sekonder Frekans Regülasyonu (SFR) Üstel PI Denetleyici Termik Güç Santrali Fotovoltaik Güneş Enerji Sistemi Yılan Arama Algoritması Optimizasyon
References
- P.P. Kumar, A. Kumar Yadav, A. Shastri, and P.A. Alvi, “BWOA assisted PIDF-(1+I) controller for intelligent load frequency management of standalone micro-grid”, ISA Transactions vol. 132, pp. 387–401, 2023.
- E. Yalçin, E. Çam, T. Vardar, and M. Lüy, “PID kontrolör ile iki bölgeli güç sistemlerinde yük frekans kontrolünün incelenmesi”, Uluslararası Mühendislik Araştırma ve Geliştirme Dergisi, vol. 5, no. 2, pp. 7–11, 2013.
- K.S.S. Ramakrishna, and T.S.Bhatti, “Sampled-data automatic load frequency control of a single area power system with multi-source power generation”, Electrical Power Components and Systems, vol. 35 no. 8, pp. 955–980, 2007.
- E. Çelik, “Performance analysis of SSA optimized fuzzy 1PD-PI controller on AGC of renewable energy assisted thermal and hydro-thermal power systems”, vol. 13, pp. 4103−4122, 2022.
- S. Panda, B. Mohanty, and P.K. Hota, “Hybrid BFOA-PSO algorithm for automatic generation control of linear and nonlinear interconnected power systems”, Applied Soft Computing, vol. 13, no. 12, pp. 4718–4730, 2013.
- U.K. Rout, R.K. Sahu, and S.Panda, “Design and analysis of differential evolution algorithm based automatic generation control for interconnected power system”, Ain Shams Engineering Journal, vol. 4, no. 3, pp. 409–421, 2013.
- S.M. Abd-Elazim, and E.S. Ali, “Load frequency controller design of a two-area system composing of PV grid and thermal generator via firefly algorithm”, Neural Computing and Applications, vol. 30, pp. 607−616, 2018.
- S. Padhy, and S. Panda, “A hybrid stochastic fractal search and pattern search technique based cascade PI-PD controller for automatic generation control of multi-source power systems in presence of plug in electric vehicles”, CAAI Transactions on Intelligence Technology, vol. 2, no. 1, pp. 12–25, 2017.
- Z.Y. Yenen, G. Bal, E. Çelik, N. Öztürk, U. Güvenç, and Y. Arya, “Yük frekans kontrolünde kullanılan ikincil denetleyicilerin optimizasyonuna yönelik yeni bir hedef fonksiyonu tasarımı”, Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, vol. 36, no.4, pp. 2053−2067, 2021.
- B. Mohanty, S. Panda, and P.K. Hota, “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, vol. 54, no.1, pp. 77–85, 2014.
- E. Çelik, “Improved stochastic fractal search algorithm and modified cost function for automatic generation control of interconnected electric power systems”, Engineering Applications of Artificial Intelligence, vol. 88, pp. 103407, 2020.
- Sahu R.K., Panda S., Rout U.K., Sahoo D.K., Teaching learning based optimization algorithm for automatic generation control of power system using 2-DOF PID controller, International Journal of Electrical Power and Energy Systems, 77 (5), 287–301, 2016.
- A.K. Barisal, “Comparative performance analysis of teaching learning based optimization for automatic load frequency control of multi-source power systems”, International Journal of Electrical Power and Energy Systems, vol. 66, no.3, pp. 67–77, 2015.
- R.K Sahu, S. Panda, and G.T.C. Sekhar, “A novel hybrid PSO-PS optimized fuzzy PI controller for AGC in multi area interconnected power systems”, International Journal of Electrical Power and Energy Systems, vol.64, no.1, pp. 880–893, 2015.
- S. Padhy, S. Panda, and S. Mahapatra, “A modified GWO technique based cascade PI-PD controller for AGC of power systems in presence of Plug in Electric Vehicles”, Engineering Science and Technology, an International Journal, vol. 20, no. 2, pp. 427–442, 2017.
- E. Çelik, and A. Dalcalı, Performance betterment of load frequency regulation using snake search algorithm for an interconected power system incorporating thermal plant and pv power station, 5th International Antalya Scientific Research and Innovative Studies Congress, pp. 610−621, Antalya, Turkiye,26-28 July 2023.
- E. Çelik, G. Bal, N. Öztürk, E. Bekiroglu, E.H. Houssein, C. Ocak, and G. Sharma, “Improving speed control characteristics of PMDC motor drives using nonlinear PI control”, Neural Computing and Applications, https://doi.org/10.1007/s00521-024-09568-3.
- F.A. Hashim, and A.G. Hussien, “Snake Optimizer: A novel meta-heuristic optimization algorithm”, Knowledge-Based Systems vol. 242, pp. 108320, 2022.
- E. Çelik, N. Öztürk, Y. Arya, and C. Ocak, “(1+PD)-PID cascade controller design for performance betterment of load frequency control in diverse electric power systems”, Neural Computing and Applications, vol.33, pp. 15433−15456, 2021.
Details
| Primary Language | Turkish |
|---|---|
| Subjects | Electrical Energy Transmission, Networks and Systems |
| Journal Section | Research Articles |
| Authors | |
| Early Pub Date | April 27, 2024 |
| Publication Date | April 30, 2024 |
| Submission Date | March 20, 2024 |
| Acceptance Date | April 15, 2024 |
| Published in Issue | Year 2024 Volume: 6 Issue: 1 |
