کنترل‌کننده تطبیقی عصبی- فازی و مبدل منبع امپدانسی به منظور کنترل توان شبکه هیبریدی متشکل از ژنراتور القایی دو سو تغذیه و سلول خورشیدی
محورهای موضوعی : مهندسی برق و کامپیوترعلی اکبر حبیبی 1 , برزو یوسفی 2 * , عبدالرضا نوری شیرازی 3 , محمد رضوانی 4
1 - دانشگاه آزاد اسلامی واحد نور، دانشکده فنی مهندسی
2 - دانشگاه آزاد اسلامی واحد نور،دانشکده فنی مهندسی
3 - دانشگاه آزاد اسلامی واحد نور،دانشکده فنی مهندسی
4 - دانشگاه آزاد اسلامی واحد نور،دانشکده فنی مهندسی
کلید واژه: ژنراتور القایی دو سو تغذیه, سیستم هیبرید, کنترل‌کننده تطبیقی عصبی- فازی, مبدل منبع امپدانسی,
چکیده مقاله :
امروزه، ژنراتورهای القایی دو سو تغذیه و سلول‌های خورشیدی به طور گسترده‌ای در صنایع مختلف و نیروگاه‌های بادی در حال استفاده هستند که هر کدام با استفاده از روش‌های کنترلی مختلفی مورد بهره‌برداری قرار گرفته‌اند. در میان روش‌های ارائه‌شده به منظور کنترل DFIG، روش کنترل مستقیم توان بیشتر مورد توجه بوده است. استفاده از این روش به دلیل مزایایی همانند مقاومت در برابر تغییر پارامترها، پاسخ دینامیکی سریع، عدم وجود مدار کنترل جریان، افزایش قابلیت اطمینان و کاهش پیچیدگی سیستم، در مقایسه با سایر روش‌های کنترلی دارای برتری‌های نسبی بوده است. هرچند نوسانات توان، گشتاور زیاد، فرکانس سوئیچینگ بالا و عملکرد ضعیف در توان‌های پایین، از جمله معایب این روش کنترلی هستند. از سوی دیگر در میان روش‌های کنترل سلول‌های خورشیدی، مدل کنترلی منبع امپدانسی Z بسیار مورد توجه پژوهشگران و بهره‌برداران قرار گرفته است. هر کدام از این روش‌ها به طور جداگانه، بسیار مورد مطالعه قرار گرفته‌اند. در پژوهش حاضر، جهت کنترل ساختار شبکه هیبریدی، ساختار کنترل پیشنهادی متشکل از مدل منبع امپدانسی Z و سیستم کنترلی تطبیقی عصبی- فازی برای بهبود عملکرد سیستم پیشنهاد داده می‌شود که دارای ساختار ساده و دقت کنترلی بالا است، نسبت به تغییرات سیستم مقاوم بوده و می‌تواند با صرف هزینه پایین و در محیط زمان واقعی پیاده‌سازی شود. به منظور تأیید کارایی و برتری این روش کنترلی، سناریوهای مختلفی در نظر گرفته شده و با روش دیگری نیز مقایسه شده است. نتایج شبیه‌سازی نشان‌دهنده کاهش قابل توجه نوسانات توان و ولتاژ، افزایش دامنه ولتاژ، گشتاور و جریان ژنراتور و همچنین افزایش قابلیت اطمینان سیستم بوده است.
Renewable energies outfitted with low latency assets as wind turbines and photovoltaic exhibits give significant adverse consequences through power framework dynamic protections. For this issue, in view of fostering a high voltage direct current (HVDC) interface, a versatile Neuro-Fuzzy-based damping regulator is introduced in this paper for working on unique execution of low inertia resources associated with power frameworks. The created power framework comprises of various age sources including seaward and inland wind turbines (WTs), photovoltaic exhibits (PVs) and limited doubly fed induction generators (DFIGs) which are incorporated together through an interconnected framework. For this situation, thinking about various functional and innovative conditions, damping execution of proposed ANFIS plot is assessed. The proposed plot is a non-model-based regulator which utilizes the benefits of both neural and fluffy rationales together for giving a quick and secure design of damping regulator through continuous recreations. To research ANFIS plot through genuine cases, considering a commonplace microgrid comprises of various low-latency assets (for example WT, PV, DFIG), the framework damping exhibitions through hamper occasions are assessed. Recreation results demonstrate viability and effectiveness of the proposed plot for damping dynamic motions of low inertia resources with high damping proportions with respect to extreme issue occasions.
[1] M. Alizadeh Bidgoli, W. Yang, and A. Ahmadian, "DFIM versus synchronous machine for variable speed pumped storage hydropower plants: a comparative evaluation of technical performance," Renewable Energy, vol. 159, pp. 72-86, Oct. 2020.
[2] S. Ranjbar, M. R. Aghamohammadi, and F. Haghjoo, "A new scheme of WADC for damping inter-area oscillation based on CART technique and thevenine impedance," Int. J. of Electric. Power and Energy Syst., vol. 94, pp. 339-353, Jan. 2018.
[3] U. Abdolwahid, J. F. Manwell, and J. G. McGowan, "Development of a dynamic control comunication system for hybrid power systems," IET Renew. Power Gener., vol. 1, no. 1, pp. 70-80, Mar. 2007.
[4] M. A. Bidgoli and S. M. T. Bathaee, "Full-state variables control of a grid-connected pumped storage power plant using non-linear controllers," Electric Power Component. and Syst., vol. 43, no. 3, pp. 260-270, 2015.
[5] A. V. da Rosa, Fundamental of Renewable Energy Processes, 2nd Edition, Academic Press in an Imprint of Elsevier, 2009.
[6] R. Fiestas, et al., Wind Power 2008 Sectors Year Book: Analysis and Data, Spanish Wind Power Association, 2008.
[7] G. W. E. Council, "Global wind 2015 report," Ed, 2015.
[8] S. Ranjbar, M. R. Aghamohammadi, and F. Haghjoo, "Adaptive wide area damping controller for damping inter-area oscillations on power system," in Proc. 24rd Iranian Conf. on Electrical Engineering, ICEE2’16, pp. 1609-1614, Shiraz, Iran, 10-12 May 2016.
[9] I. Sepehrirad, R. Ebrahimi, E. Alibeiki, and S. Ranjbar, "Intelligent differential protection scheme for controlled islanding of microgrids based on decision tree technique," J. Control, Automation and Electrical Systems, vol. 31, no. 5, pp. 1233-1250, 2020.
[10] P. S. Ogeti, Robust Active and Reactive Power Control Schemes for a Doubly Fed Induction Generator-Based Wind Energy Conversion System, PhD Thesis, National Institute of Technology Rourkela, 2016.
[11] S. Ranjbar, M. R. Aghamohammadi, and F. Haghjoo, "Real time wide area damping control signal to damp inter-area oscillation in power system," in Proc. 25th Iranian Conf. on Electrical Engineering, ICEE’17, pp. 1324-1329, Tehran, Iran, 2-4 May 2017.
[12] B. Chandrashekhar and P. S. Laad, "Modelling and analysis of magnetically coupled impedance source inverter for solar photovoltaic systems," in Proc. 6th IEEE Int. Conf. on Inventive Computation Technologies, ICICT’21, pp. 335-339, Coimbatore, India, 20-22 Jan. 2021.
[13] L. Yushan, B. Ge, H. Abu-Rub, and H. Sun, "Hybrid pulsewidth modulated single-phase quasi-Z-source grid-tie photovoltaic power system," IEEE Trans. Ind. Informatic, vol. 12, no. 2, pp. 621-632, Apr. 2016.
[14] A. Ramanjaneyulu and A. Chowdhury, "An implanted hybrid three quasi Z source inverter for photovoltaic power generation applications," in Proc. IEEE Int. Students' Conf. on Electrical, Electronics and Computer Science, SCEECS’18, 6 pp., Bhopal, India, 24-25 Feb. 2018.
[15] A. JeraldineViji, R. Priya, and B. Pushpa, "PV combined ZSI-DVR with fuzzy logic controller for power quality improvement," in Proc. IEEE Int. Conf. on System, Computation, Automation and Networking, ICSCAN’21, 6 pp., Puducherry, India, 30-31 Jul. 2021.
[16] S. Sajadian and R. Ahmadi, "Model predictive control of dual-mode operations Z-source inverter: islanded and grid-connected," IEEE Trans. on Power Electronics, vol. 33, no. 5, pp. 4488-4497, May 2017.
[17] A. Badhoutiya and A. Yadav, "Boost control for PV applications using impedance source inverter," in Proc. 2nd IEEE Int. Conf. on Recent Trends in Electronics, Information & Communication Technology, RTEICT’17, pp. 1967-1970, Bangalore, India, 19-20 May 2017.
[18] A. Shabani, M. A. Bidgoli, and A. Deihimi, "Comparison of DDPMSG and DFIG concepts for wind turbines," in Proc. 5th Annual IEEE Int. Power Electronics, Drive Systems and Technologies Conf., PEDSTC’14, pp. 512-517, Tehran, Iran, 5-6 Feb. 2014.
[19] M. J. Alinezhad, M. Radmehr, and S. Ranjbar, "Adaptive wide area damping controller for damping inter-area oscillations considering high penetration of wind farms," Int. Trans. Electric. Energy Syst., vol. 30, no. 6, Article ID: e12392, Jun. 2020.
[20] T. Amraee and S. Ranjbar, "Transient instability prediction using decision tree technique," IEEE Trans. Power Syst., vol. 28, no. 3, pp. 3028-3037, Aug. 2013.
[21] F. Faust and M. Godoysimoes, Integration of Alternative Solaces of Energy, John Wiley & Sons, Inc. 2006.
[22] J. I. Leon, et al., "Feed-forward space vector modulation for single-phase multilevel cascaded converters with any DC voltage ratio," IEEE Trans. Ind. Electronic, vol. 56, no. 2, pp. 315-325, Feb. 2009.
[23] J. M. Mendel, "General type-2 fuzzy logic systems made simple: a tutorial," IEEE Trans. Fuzzy Syst., vol. 22, no. 5, pp. 1162-1182, Oct. 2014.
[24] T. Ramesh, A. K. Panda, and S. S. Kumar, "Type-2 fuzzy logic control based MRAS speed estimator for speed sensorless direct torque and flux control of an induction motor drive," ISA Trans., vol. 57, pp. 262-275, Jul. 2015.
[25] G. J. Su and F. Z. Peng, "A low cost, triple-voltage bus DC-DC converter for automotive applications," in Applied Power Electronics Conf. and Exposition, APEC, Twentieth Annual IEEE, vol. 2, pp. 1015-1021, Mar. 2005.
[26] M. Bidgoli, S. M. Alizadeh, T. Bathaee, and A. Shabani, "Design a nonlinear auxiliary input for DFIG-based application using Lyapunov theory," in Proc. 5th IEEE Annual Int. Power Electronics, Drive Systems and Technologies Conf., PEDSTC’14, pp. 102-107, Tehran, Iran, 5-6 Feb. 2014.
[27] S. Ranjbar, M. R. Aghamohammadi, and F. Haghjoo, "Damping inter-area oscillation in power systems using local PSSs based on global control signals," in Proc. Iranian Conf. on Electrical Engineering, ICEE’17,Tehran, Iran, 2-4 May 2017.
[28] A. Florescu, et al.,, "The advantages, limitations and disadvantages of Z-source inverter," CAS Proc. Int. Semiconductor Conf., vol. 2, pp. 483-486, Sinaia, Romania, 11-13 Oct. 2010.
[29] S. Honarbari and M. Alizadeh Bidgoli, "Designing a quasi-z-source inverter with energy storage to improve grid power quality," IETE J. of Research, vol. 8, no. 4, pp. 2445-2453, 2020.
[30] H. F. Ahmed, H. Cha, S. Kim, and H. Kim, "Switched coupled-inductor quasi-Z-source inverter," IEEE Trans. Power Electron., vol. 31, no. 2, pp. 1241-1254, Feb. 2016.
[31] B. Ge, et al., "An active filter method to eliminate DC-side low frequency power for single-phase quasi-Z source inverter," IEEE Trans. Ind. Electronic, vol. 63, no. 8, pp. 4838-4848, Aug. 2016.
[32] D. Sun, B. Ge, D. Bi, and F. Z. Peng, "Analysis and control of quasi-Z source inverter with battery for grid-connected PV system," Int. J. Electr. Power Energy Syst., vol. 46, pp. 234-240, Mar. 2013.