کنترل فرکانس در ریزشبکه‌‌های چند-حاملی با حضور خودروهای الکتریکی مبتنی بر کنترل‌کننده سیستم استنتاج فازی عصبی تطبیقی

الموضوعات :

سیدعلی سید بهشتی فینی ¹ , سید محمد شریعتمدار ² , وحید امیر ³

1 - گروه برق و کامپیوتر- واحد کاشان، دانشگاه آزاد اسلامی، کاشان، ایران
2 - گروه برق و کامپیوتر- واحد کاشان، دانشگاه آزاد اسلامی، کاشان، ایران
3 - گروه برق و کامپیوتر- واحد کاشان، دانشگاه آزاد اسلامی، کاشان، ایران

تاريخ الإرسال : 01 الثلاثاء , جمادى الثانية, 1443 تاريخ التأكيد : 28 الجمعة , رمضان, 1443 تاريخ الإصدار : 08 الأربعاء , جمادى الأولى, 1445

الکلمات المفتاحية: کنترل فازی, کنترل فرکانس, ریزشبکه, خودرو الکتریکی, فرکانس ثانویه, سیستم استنتاج فازی عصبی تطبیقی,

ملخص المقالة :

امروزه افزایش قیمت سوخت های فسیلی و کاهش منابع از یک سو و آلودگی های زیست محیطی از سوی دیگر باعث افزایش استفاده از منابع تجدیدپذیر گردیده است. در این مقاله ریزشبکه مورد مطالعه از منابع بادی و خورشیدی، ذخیره ساز (باتری و فلایویل) خودرو الکتریکی، دیزل ژنراتور و حضور سیستم های انرژی چند حاملی MCH)) به عنوان انرژی ترکیبی برق و حرارت (CHP) تشکیل شده است. فرکانس ریزشبکه باتوجه به شبکه گاز و پیک مصرف کنترل می شود. در ریزشبکه چند حاملی پخش بار شبکه گاز همزمان با پخش بار الکتریکی منظور می گردد. همچنین فرکانس به صورت غیرخطی کنترل می‌شود. از طرف دیگر روند رو به رشد تولید و به کارگیری خودروهای برقی (V2G) بارهای جدیدی برای شبکه برق ایجاد کرده است که در صورتی که مدیریت صحیحی بر روی نحوه شارژ آنها صورت نگیرد انحراف فرکانس شبکه افزایش یافته و می تواند سبب فروپاشی شبکه گردد. لذا از خودروهای برقی به منظور مشارکت در عملیات تنظیم فرکانس ریزشبکه با روش سیستم استنتاج فازی عصبی تطبیقی (ANFIS) استفاده می شود. به منظور مقایسه روش پیشنهادی در شبیه سازی‌ها از کنترل کننده فازی استفاده شده است. نتایج حاصل از شبیه سازی‌ها در پنج مطالعه مورد بررسی قرار می‌گیرند که بیان گر عملکرد مطلوب روش پیشنهادی در کاهش انحراف فرکانس، استحکام در برابر اغتشاشات و مقاوم بودن در برابر عدم قطعیت‌‌های موجود در سیستم است. همچنین روش پیشنهادی توان خروجی پایدارتری در منابع تولید ریزشبکه دارد.

المصادر:

[1] T. Sun, J. Lu, Z. Li, D. L. Lubkeman, N. Lu, “Modeling combined heat and power systems for microgrid applications", IEEE Trans. on Smart Grid, vol. 9, no. 5, pp. 4172-4180, Sept. 2018 (doi: 10.1109/TS­G.20­1­7.26­52723).

[2] H. Wu, M. Shahidehpour, “A game theoretic approach to risk-based optimal bidding strategies for electric vehicle aggregators in electricity markets with variable wind energy resources”, IEEE Trans. on Sustainable Energy, vol. 7, no. 1, pp. 374- 385, Jan. 2016 (doi: 10.1109/TSTE.2015.2498200).

[3] G. Haddadian, M. Khodayar, M. Shahidehpour, “Accelerating the global adoption of electric vehicles– barriers and drivers”, Electricity Journal, vol. 28, no. 10, pp. 53-68, Dec. 2015 (doi: 10.1016/j.tej.20­15.1­1.0­1­1‌).

[4] A. Dán, C. Farkas, L. Prikler, “V2G effects on frequency regulation and under frequency load shedding in a quasi-islanded grid”, Proceeding of the IEEE/ PowerTech, pp. 1-6, June. 2013 (doi: 10.1109/PTC.2013.6­652­2­20).

[5] K. Knezović, S. Martinenas, P.B. Andersen, A. Zecchino, M. Marinelli, “Enhancing the role of electric vehicles in the power grid: Field validation of multiple ancillary services”, IEEE Trans. on Transportation Electrification, vol. 3, no. 1, pp. 201-209, March. 2017 (doi: 10.1109/TTE.2016.2616864‌).

[6] M. Singh, P. Kumar, I. Kar, “Implementation of vehicle to grid infrastructure using fuzzy logic controller”, IEEE Trans. on Smart Grid, vol. 3, no. 1, pp. 565-577, March ‌2012 (doi: 10.1109/TSG.2011.2172697).

[7] M. Datta, T. Senjyu, “Fuzzy control of distributed PV inverters/energy storage systems/electric vehicles for frequency regulation in a large power system”, IEEE Trans. on Smart Grid, vol. 4, no. 1, pp. 479-488, March. 2013 (doi: 10.1109/TSG.2012.2237044‌).

[8] H. Ali, G. Magdy, B. Li, G. Shabib, A.A. Elbaset, D. Xu, Y. Mitani, “A new frequency control strategy in an islanded microgrid using virtual inertia control-based coefficient diagram method”, IEEE Access, vol. 7, pp. 16979-16990, 2019 (doi: 10.1109/ACCESS.2019.2894840).

[9] D. Yu, H. Zhu, W. Han, D. Holburn, “Dynamic multi agent-based management and load frequency control of PV/Fuel cell/wind turbine/CHP in autonomous microgrid system”, Energy, vol. 173, pp. 554-568, April. 2019 (doi: 10.1016/j.energy.2019.02.094).

[10] M. Jayachandran, G. Ravi, “Decentralized model predictive hierarchical control strategy for islanded ac microgrids”, Electric Power Systems Research, vol. 170, pp. 92-100, May 2019 ‌‌(doi: 10.1016/j.epsr.201­9.0­1.0­10).

[11] K.W. Joung, T. Kim, J. Park, “Decoupled frequency and voltage control for stand-alone microgrid with high renewable penetration”, IEEE Trans. on Industry Applications, vol. 55, pp. 122-133, Jan/Feb. 2019 (doi: 10.1109/ICPS.2018.8369983).

[12] C.T. Hsu, T.J. Cheng, H.M. Huang, Y.D. Lee, Y.R. Chang, J.L. Jiang, “Over frequency control of photovoltaic inverters in an island microgrid”, Microelectronics Reliability, vol. 92, pp. 42-54, Jan. 2019 (doi: 10.1016/j.m­icro­rel.2018.11.011).

[13] X. Xu, W. Hu, D. Cao, Q. Huang, C. Chen, Z. Chen, “Optimized sizing of a standalone PV-wind-hydropower station with pumped-storage installation hybrid energy system”, Renewable Energy, vol. 147, pp. 1418-1431, March 2020 (doi: 10.1016/j.renene.2019.09.099).

[14] B. Farahmand, M. Dehghani, N. Vafamand, “Fuzzy model-based controller for blood glucose control in type 1 diabetes: An LMI approach", Biomedical Signal Processing and Control, vol. 54, Article Number: 101627, Sept. 2019 (doi:10.1016/j.bspc.2019.101627).

[15] J. Guo, “Application of full order sliding mode control based on different areas power system with load frequency control”, ISA Transactions, vol. 92, pp. 23-34, Sept. 2019 (doi:­ 10.1016/j.­isatra. 2019.01.036).

[16] J. Sharma, Y.V. Hote, R. Prasad, “PID controller design for interval load frequency control system with communication time delay”, Control Engineering Practice, vol. 89, pp. 154-168, Aug. 2019 (doi: 10.1016/­j.c­on­­engprac.2019.05.016).

[17] P.K. Ray, A. Mohanty, “A robust firefly–swarm hybrid optimization for frequency control in wind/PV/FC based microgrid”, Applied Soft Computing, vol. 85, Article Number: 105823, Dec. 2019 (doi: 10.1016/j.a­soc­.2019.105823).

[18] G. Agundis-Tinajero, J. Segundo-Ramírez, N. Visairo-Cruz, M. Savaghebi, J.M. Guerrero, E. Barocio, “Power flow modeling of islanded ac microgrids with hierarchical control”, International Journal of Electrical Power and Energy Systems, vol. 105, pp. 28-36, Feb. 2019 (doi: 10.1016/J.IJEPES.2018.08.002).

[19] F.O. Hocaoglu, O.N. Gerek, M. Kurban, “The effect of model generated solar radiation data usage in hybrid (wind–PV) sizing studies”, Energy Conversion and Management, vol. 50, pp. 2956-2963, Dec. 2019 (doi: 10.1016/j.enconman.2009.07.011).

[20] D. Qin, Q. Sun, R. Wang, D. Ma, M. Liu, “Adaptive bidirectional droop control for electric vehicles parking with vehicle-to-grid service in microgrid”, CSEE Journal of Power and Energy Systems, vol. 6, no. 4, pp. 793-805, Dec. 2020 (doi: 10.17775/CSEEJPES.2020.00310).

[21] U.C. Prusty, P.C. Nayak, R.C. Prusty S. Panda, “Impact of vehicle to grid mode electric vehicles in standalone microgrid for frequency regulation”, Proceeding of the IEEE/ISSSC, pp. 1-6, Gunupur Odisha, India, Dec. 2020 )doi: 10.1109/iSSSC50941.2020.9358834(‌.

[22] M. H. Khooban, T. Niknam, F. Blaabjerg, T. Dragičević, “A new load frequency control strategy for micro-grids with considering electrical vehicles”, Electric Power Systems Research, vol. 143, pp. 585-598, Feb. 2017 (doi: 10.1016/j.epsr.2016.10.057).

[23] S. Iqbal, A. Xin, M.U. Jan, S. Salman, A.U.M. Zaki, H.U. Rehman M.F. Shinwari, M.A. Abdelbaky, “V2G strategy for primary frequency control of an industrial microgrid considering the charging station operator”, Electronics, vol. 9, no. 4, p. 549, March 2020(doi: 10.3390/electronics9040549).

[24] H. Fan, L. Jiang, C.K. Zhang, C. Mao, “Frequency regulation of multi-area power systems with plug-in electric vehicles considering communication delays”,  IET Generation, Transmission & Distribution, vol. 10, no. 14, pp. 3481-3491, Nov. 2016 (doi: 10.1049/iet-gtd.2016.0108).

[25] W. Yan, L. Sheng, D. Xu, W. Yang, Q. Liu, “H_∞ robust load frequency control for multi-area interconnected power system with hybrid energy storage system”, Applied Sciences, vol. 8, no. 10, Article Number: 1748, Sept. 2018 (doi: 10.3390/ app8101748).

[26] Y. Xu, C. Li, Z. Wang, N. Zhang, B. Peng, “Load frequency control of a novel renewable energy integrated micro-grid containing pumped hydropower energy storage”, IEEE Access, vol. 6, pp. 29067-29077, April  2018 (doi: 10.1109/ACCESS.2018.2826015).

[27]  P. Ivanova, O. Linkevics, A. Sauhats, “Cost-benefit analysis of CHP plants taking into account air cooling technologies”, Proceeding of the IEEE/EEEIC, pp. 1-6, Milan, Italy, June 2017 (doi: 10.1109/EEE­IC.20­17.79­7­74­04).

[28]  S. Murali, R. Shankar, P. Aryan, “A novel optimization technique for LFC and virtual inertia emulation of a multi area hybrid power system”, Proceeding of the IEEE/ICEFEET, pp. 1-6, Patna, India , July 2020 (doi: 10.1109/ICEFEET49149.2020.9186998).

[29] A.X.R. Irudayaraj, N.I.A. Wahab, M.G. Umamaheswari, M.A.M. Radzi, N.B. Sulaiman, V. Veerasamy, S.C. Prasanna, R. Ramachandran, “A matignon’s theorem based stability analysis of hybrid power system for automatic load frequency control using atom search optimized FOPID controller”, IEEE Access, vol. 8, pp. 168751-168772, 2020 (doi: 10.1109/ACCESS.2020.3021212).

[30] D. Mohanty, S. Panda, “Robust frequency control of hybrid power system with EV and HP", Proceeding of t­he IEEE/ICEPE, pp. 1-5,  Shillong, Meghalaya, India, March 2021 (doi: 10.1109/ICEPE50861.2­021.94­0437­2­).

[31] H. Lund, W. Kempton, “Integration of renewable energy into the transport and electricity sectors through V2G”, Energy Policy, vol. 36, no. 9, pp. 3578-3587, Sept. 2008 (doi: 10.1016/j.enpol.2008.06.007).

[32] S.F. Aliabadi, S.A. Taher, M. Shahidehpour, “Smart deregulated grid frequency control in presence of renewable energy resources by EVs charging control", IEEE Trans. on Smart Grid, vol. 9, no. 2, pp. 1073-1085, March. 2018 (doi: 10.1109/TSG.2016.2575061).

[33] M.U. Jan, A. Xin, M.A. Abdelbaky, H.U. Rehman, S. Iqbal, “Adaptive and fuzzy PI controllers design for frequency regulation of isolated microgrid integrated with electric vehicles”, IEEE Access, vol. 8, pp. 87621-87632, Jan. 2020 (doi: 10.1109/ACCESS.2020.2993178).

[34] S. Amamra, J. Marco, “Vehicle-to-Grid aggregator to support power grid and reduce electric vehicle charging cost”, IEEE Access, vol. 7, pp. 178528-178538, 2019 (doi: 10.1109/ACCESS.2019.2958664).

[35] S. Kumar, K.K. Jaladi, “Grid connected electric vehicle charging station using PV source”, Proceeding of the IEEE/ICMICA, pp. 1-4, Kurukshetra, India, June 2020 (doi: 10.1109/ICMICA48462.2020.9242806).

[36]  A. Annamraju, S. Nandiraju, “Robust frequency control in a renewable penetrated power system: An adaptive fractional order-fuzzy approach'', Protection and Control of Modern Power Systems, vol. 4, no. 1, p. 16, Dec. 2019 (doi: 10.1186/s41601-019-0130-8).

[37] X. Liu, Y. Zhang, K.Y. Lee, “Coordinated distributed MPC for load frequency control of power system with wind farms'', IEEE Trans. on Industrial Electronics, vol. 64, no. 6, pp. 5140-5150, June 2017 (doi: 10.1109/ TIE.2016.2642882).

[38]  X. Kong, X. Liu, L. Ma, K.Y. Lee, “Hierarchical distributed model predictive control of standalone wind/solar/battery power system”, IEEE Trans. on Systems, Man, and Cybernetics, vol. 49, no. 8, pp. 1570-1581, Aug. 2019 (doi: 10.1109/TSMC.2019.2897646).

[39] W. Eshetu, P. Sharma, C. Sharma, “ANFIS based load frequency control in an isolated micro grid”, Procee­din­g of the IEEE/ICIT, pp. 1165-1170, Lyon, France, Feb. 2018 (doi: 10.1109/ICIT.201­8.8­352­343). 

[40] J. Yang, Z. Zeng, Y. Tang, J. Yan, H. He, Y. Wu, “Load frequency control in an isolated micro grid system with electric vehicles based on MGPT”, Energies, vol. 8, no. 3, pp. 2145-2164, Mar. 2015 (doi: 10.3390/en8­0321­4­5).

[41] J.S.R. Jang, “ANFIS: adaptive-network-based fuzzy inference system”, IEEE Trans. on Systems, Man, and Cybernetics, vol. 23, no. 3, pp. 665-685, May/June 1993 (doi: 10.1109/21.256541).

[42]  N. Mathur, I. Glesk, A. Buis “Comparison of adaptive neuro-fuzzy inference system (ANFIS) and Gaussian processes for machine learning (GPML) algorithms for the prediction of skin temperature in lower limb prostheses”,  Medical Engineering and Physics, vol. 38, no. 10, pp.‌ 1083-1089, Oct. 2016 )doi: org/10.1016/ j.medengphy. 2016.07.003).

[43] S. Prakash, A.K. Bhardwaj, S.K. Shinha “Neuro fuzzy hybrid intelligent approach for four-area load freq­ue­ncy control of interconnected power system”, Proceeding of the IEEE/ ICPCES, pp. 1-7, Allahabad, India, Dec. 2012 (doi: 10.1109/ICPCES.2012.6508124).

[44] C. Mu, Y. Tang, H. He, “Observer-based sliding mode frequency control for micro-grid with photovoltaic energy integration”, Proceeding of the IEEE/PESGM, pp. 1-5, Boston, MA, USA, July 2016 (doi: 10.110­9/PE­S­GM.2016.7742001).

[45]  M. Tavakoli, E. Pouresmaeil, J. Adabi, R. Godina, J.P.S. Catalão, “Load-frequency control in a  multi-source power system connected to wind farms through multi terminal HVDC systems”,  Computers and Operations Research, vol. 96, pp. 305-315, Aug. 2018 (doi: 10.1109/PESGM. 2016.7742001).