تنظیم فرکانس در ریزشبکه های ترکیبی جزیره ای در حضور عدم قطعیت ها مبتنی برکنترل کننده های عصبی-فازی تطبیقی
محورهای موضوعی : ریز شبکه قدرت
عباس آف
1
,
محسن سیماب
2
,
مهدی نفر
3
,
سیدعلیرضا میرزایی
4
1 - دانشجوی دکتری/دکتری مهندسی برق، گروه مهندسی برق، واحد مرودشت، دانشگاه آزاد اسلامی، مرودشت، ایران
2 - استادیار گروه برق، گروه مهندسی برق، واحد مرودشت، دانشگاه آزاد اسلامی، مرودشت، ایران
3 - استادیار گروه برق، واحد مرودشت، دانشگاه آزاد اسلامی، مرودشت، ایران
4 - استادیار گروه مهندسی برق، واحد داریون، دانشگاه آزاد اسلامی، شیراز، ایران
کلید واژه: ریزشبکه ترکیبی, تنظیم فرکانس, عدم قطعیت پارامتری, کنترل عصبی-فازی تطبیقی, ریزشبکه جزیره‌ای,
چکیده مقاله :
به کارگیری استراتژی کنترل ترکیبی عصبی-فازی الهام گرفته از کنترل PID برای میرا نمودن نوسانات فرکانس در سیستم ریزشبکه هیبریدی جزیره ای (IHMG) درحضوراغتشاشات و نامعینی های پارامتری، در این مقاله بررسی شده است. با توجه به رفتار نامنظم منابع انرژی تجدیدپذیر (RES) نظیر توربین بادی و آرایه های خورشیدی و همچنین ماهیت متغیر با زمان بارهای مصرفی، انحراف فرکانس ریزشبکه از مقدار نامی به خصوص در حالت جزیره ای اجتناب ناپذیر است. تغییرات ناخواسته در بار مصرفی، میزان تابش خورشید، سرعت باد، و همچنین عدم قطعیت های پارامتری ناشی از ثابت های زمانی آن، منابع اصلی اغتشاش، در سیستم ریزشبکه هیبریدی جزیره ای مورد بررسی می باشد. در ساختار فازی کنترل‌کننده پیشنهادی، از خطا، مشتق و انتگرال خطای فرکانسی جهت آموزش و تست شبکه عصبی بهره گرفته شده است. بر اساس معادله تعادل توان بین عرضه و تقاضا، سعی در حداقل نمودن اثر اغتشاش در فرکانس خروجی با بهینه سازی موقعیت توابع عضویت فازی ورودی ها و خروجی آن نموده است. برای ارزیابی بهتر عملکرد روش پیشنهاد شده، رویکرد ANFIS با روش کنترلPID بهینه، موردمقایسه قرارگرفته است. نتایج شبیه سازی، نشان‌دهنده برتری قابل‌توجه روش پیشنهادی در مقایسه با دو روش متداول دیگر از نظر مشخصه های حوزه زمان در حضور اغتشاشات همزمان و عدم قطعیت‌های پارامتری سیستم می باشد.
The capability of a neuro-fuzzy control approach for frequency fluctuation damping in an isolated hybrid microgrid (IHMG) system (DEG/WTG /PV/FC/ESSs) is investigated in this paper. Due to the intermittent behavior of renewable energy sources (RESs) like wind turbines and photovoltaic arrays and the time-varying nature of demands, frequency fluctuation is more likely, specifically in the grid-connected mode. Model parametric uncertainties as well as load changes, wind power, and solar irradiation variations are the main uncertainty sources of the IHMG system. In the suggested approach, a neuro-fuzzy output feedback controller with three inputs that are inspired by PID control is designed considering the power balance between demands and generations, by optimizing fuzzy membership functions’ locations. The proposed controller is compared with two popular other methods on the investigated IHMG system in terms of time-domain characteristics. The outcome illustrates remarkable merit compared to the state-of-the-art methods in the presence of simultaneous disturbances and the model parametric uncertainties.
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_||_[1] S. Rajamand, "Load frequency control and dynamic response improvement using energy storage and modeling of uncertainty in renewable distributed generators," Journal of Energy Storage, vol. 37, p. 102467, 2021, doi: 10.1016/j.est.2021.102467.
[2] U. Datta, A. Kalam, and J. Shi, "The relevance of large-scale battery energy storage (BES) application in providing primary frequency control with increased wind energy penetration," Journal of Energy Storage, vol. 23, pp. 9-18, 2019, doi: 10.1016/j.est.2019.02.013.
[3] M. S. Javed, T. Ma, J. Jurasz, and M. Y. Amin, "Solar and wind power generation systems with pumped hydro storage: Review and future perspectives," Renewable Energy, vol. 148, pp. 176-192, 2020.
[4] D. Ribó-Pérez, P. Bastida-Molina, T. Gómez-Navarro, and E. Hurtado-Pérez, "Hybrid assessment for a hybrid microgrid: A novel methodology to critically analyse generation technologies for hybrid microgrids," Renewable Energy, vol. 157, pp. 874-887, 2020 , doi: 10.1016/j.renene.2020.05.095.
[5] A. Sefidgar-Dezfouli , M. Joorabian and E. Mashhour "Optimal Scheduling of Smart Microgrid for Stable and Economic Islanding using Demand as the Spinning Reserve," Computational Intelligence in Electrical Engineering , vol. 10, no. 3, pp. 25-40, 2019.
[6] A. Rahman, L. C. Saikia, and N. Sinha, "Automatic generation control of an interconnected two-area hybrid thermal system considering dish-stirling solar thermal and wind turbine system," Renewable energy, vol. 105, pp. 41-54, 2017, doi :10.1016/J.RENENE.2016.12.048.
[7] J. Uche, A. Muzás, L. Acevedo, S. Usón, A. Martínez, and A. Bayod, "Experimental tests to validate the simulation model of a Domestic Trigeneration Scheme with hybrid RESs and Desalting Techniques," Renewable Energy, vol. 155, pp. 407-419, 2020, doi: 10.1016/j.renene.2020.03.147.
[8] C. S. A. Nandar, "Robust PI control of smart controllable load for frequency stabilization of microgrid power system," Renewable Energy, vol. 56, pp. 16-23, 2013, doi: 10.1016/j.renene.2012.10.032.
[9] T. Senjyu, T. Nakaji, K. Uezato, and T. Funabashi, "A hybrid power system using alternative energy facilities in isolated island," IEEE Transactions on energy conversion, vol. 20, no. 2, pp. 406-414, 2005, doi: 10.1109/TEC.2004.837275.
[10] D.-J. Lee and L. Wang, "Small-signal stability analysis of an autonomous hybrid renewable energy power generation/energy storage system part I: Time-domain simulations," IEEE Transactions on energy conversion, vol. 23, no. 1, pp. 311-320, 2008, doi: 10.1109/TEC.2007.914309.
[11] I. Hussain, S. Ranjan, D. C. Das, and N. Sinha, "Performance analysis of flower pollination algorithm optimized PID controller for wind-PV-SMES-BESS-diesel autonomous hybrid power system," International Journal of Renewable Energy Research (IJRER), vol. 7, no. 2, pp. 643-651, 2017.
[12] J. Li, P. Liu, and Z. Li, "Optimal design and techno-economic analysis of a solar-wind-biomass off-grid hybrid power system for remote rural electrification: A case study of west China," Energy, vol. 208, p. 118387, 2020, doi: 10.1016/j.energy.2020.118387.
[13] M. Ranjan and R. Shankar, "A literature survey on load frequency control considering renewable energy integration in power system: Recent trends and future prospects," Journal of Energy Storage, vol. 45, p. 103717, 2022, doi: 10.1016/j.est.2021.103717.
[14] M. Eslami, "Low-Frequency Stability Based on Optimal Design of Proportional Integral-Deferential-Fractional Order Fuzzy Controller Based on Intelligent Hybrid Algorithm," Computational Intelligence in Electrical Engineering, vol. 13, no. 1, pp. 103-120, 2022.
[15] M. A. Jirdehi, V. S. Tabar, S. Ghassemzadeh, and S. Tohidi, "Different aspects of microgrid management: A comprehensive review," Journal of Energy Storage, vol. 30, p. 101457, 2020, doi: 10.1016/j.est.2020.101457.
[16] X. Yang, J. Su, M. Ding, and D. Yan, "Research on frequency control for microgrid in islanded operation," Power System Technology, vol. 34, no. 1, pp. 164-168, 2010.
[17] D. Gielen, F. Boshell, D. Saygin, M. D. Bazilian, N. Wagner, and R. Gorini, "The role of renewable energy in the global energy transformation," Energy Strategy Reviews, vol. 24, pp. 38-50, 2019 , doi: 10.1016/j.esr.2019.01.006.
[18] R. Carli and M. Dotoli, "Decentralized control for residential energy management of a smart users ʼ microgrid with renewable energy exchange," IEEE/CAA Journal of Automatica Sinica, vol. 6, no. 3, pp. 641-656, 2019, doi: 10.1109/JAS.2019.1911462.
[19] H. Bevrani, H. Golpîra, A. R. Messina, N. Hatziargyriou, F. Milano, and T. Ise, "Power system frequency control: An updated review of current solutions and new challenges," Electric Power Systems Research, vol. 194, p. 107114, 2021, doi: 10.1016/j.epsr.2021.107114.
[20] M. Rahmani, F. Faghihi, and B. Mozafari, "Analysis and Evaluation of Hybrid Cooperative Frequency Control for Micro Grids in Islanding Mode in Case of Solar Panel Outage and Load Variation," Journal of Environmental Science and Technology, vol. 21, no. 7, pp. 49-61, 2019 , doi: 10.22034/JEST.2019.22825.3229.
[21] P. K. Ray, S. R. Mohanty, and N. Kishor, "Proportional–integral controller based small-signal analysis of hybrid distributed generation systems," Energy Conversion and Management, vol. 52, no. 4, pp. 1943-1954, 2011, doi: 10.1016/j.enconman.2010.11.011.
[22] C. Wang, Y. Mi, Y. Fu, and P. Wang, "Frequency control of an isolated micro-grid using double sliding mode controllers and disturbance observer," IEEE Transactions on Smart Grid, vol. 9, no. 2, pp. 923-930, 2016 , doi: 10.1109/TSG.2016.2571439.
[23] A. Bagheri, A. Jabbari, and S. Mobayen, "An intelligent ABC-based terminal sliding mode controller for load-frequency control of islanded micro-grids," Sustainable Cities and Society, vol. 64, p. 102544, 2021 , doi: 10.1016/j.scs.2020.102544.
[24] A. Latif, A. Pramanik, D. C. Das, I. Hussain, and S. Ranjan, "Plug in hybrid vehicle-wind-diesel autonomous hybrid power system: frequency control using FA and CSA optimized controller," International Journal of System Assurance Engineering and Management, vol. 9, no. 5, pp. 1147-1158, 2018 , doi: 10.1007/s13198-018-0721-1.
[25] S. Ganguly, C. K. Shiva, and V. Mukherjee, "Frequency stabilization of isolated and grid connected hybrid power system models," Journal of Energy Storage, vol. 19, pp. 145-159, 2018 ,doi: 10.1016/j.est.2018.07.014.
[26] X. Li, Y.-J. Song, and S.-B. Han, "Frequency control in micro-grid power system combined with electrolyzer system and fuzzy PI controller," Journal of Power Sources, vol. 180, no. 1, pp. 468-475, 2008, doi: 10.1016/j.jpowsour.2008.01.092.
[27] A. Annamraju and S. Nandiraju, "Robust frequency control in an autonomous microgrid: a two-stage adaptive fuzzy approach," Electric Power Components and Systems, vol. 46, no. 1, pp. 83-94, 2018, doi: 10.1080/15325008.2018.1432723.
[28] T. Mahto and V. Mukherjee, "A novel scaling factor based fuzzy logic controller for frequency control of an isolated hybrid power system," Energy, vol. 130, pp. 339-350, 2017, doi: 10.1016/j.energy.2017.04.155.
[29] M. I. Alomoush, "Load frequency control and automatic generation control using fractional-order controllers," Electrical Engineering, vol. 91, no. 7, pp. 357-368, 2010, doi: 10.1007/s00202-009-0145-7.
[30] T. Mahto, H. Malik, V. Mukherjee, M. A. Alotaibi, and A. Almutairi, "Renewable generation based hybrid power system control using fractional order-fuzzy controller," Energy Reports, vol. 7, pp. 641-653, 2021, doi: 10.1016/J.EGYR.2021.01.022.
[31] D. Rerkpreedapong, A. Hasanovic, and A. Feliachi, "Robust load frequency control using genetic algorithms and linear matrix inequalities," IEEE Transactions on Power Systems, vol. 18, no. 2, pp. 855-861, 2003, doi: 10.1109/TPWRS.2003.811005.
[32] M. Dashtdar et al., "Improving the power quality of island microgrid with voltage and frequency control based on a hybrid genetic algorithm and PSO," IEEE Access, 2022, doi: 10.1109/ACCESS.2022.3201819.
[33] D. Mishra, P. C. Sahu, R. C. Prusty, and S. Panda, "A fuzzy adaptive fractional order-PID controller for frequency control of an islanded microgrid under stochastic wind/solar uncertainties," International Journal of Ambient Energy, pp. 1-10, 2021, doi: 10.1080/01430750.2021.1914163.
[34] D. Sharma, "Fuzzy with adaptive membership function and deep learning model for frequency control in PV-based microgrid system," Soft Computing, vol. 26, no. 19, pp. 9883-9896, 2022, doi: 10.1007/s00500-022-07342-y.
[35] H. Karimi, M. T. Beheshti, A. Ramezani, and H. Zareipour, "Intelligent control of islanded AC microgrids based on adaptive neuro-fuzzy inference system," International Journal of Electrical Power & Energy Systems, vol. 133, p. 107161, 2021, doi: 10.1016/j.ijepes.2021.107161
[36] D. Gamage, X. Zhang, A. Ukil, C. Wanigasekara, and A. Swain, "Design of ANFIS Controller for a DC Microgrid," in International Conference on Energy, Power and Environment: Towards Clean Energy Technologies, 2021, pp. 1-6, doi: 10.1109/ICEPE50861.2021.9404439.
[37] L. Wang, D.-J. Lee, W.-J. Lee, and Z. Chen, "Analysis of a novel autonomous marine hybrid power generation/energy storage system with a high-voltage direct current link," Journal of Power Sources, vol. 185, no. 2, pp. 1284-1292, 2008, doi: 10.1016/j.jpowsour.2008.08.037.
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