یک روش بهینه برای تعیین وضعیت اتصال ریزشبکه به شبکه سراسری با استفاده از اطلاعات محلی

نوع مقاله : علمی-پژوهشی

نویسندگان

دانشکده مهندسی برق و کامپیوتر- دانشگاه بیرجند

چکیده

به‌منظور عملکرد مناسب سیستم کنترل و حفاظت ریزشبکه، لازم است تغییر وضعیت اتصال ریزشبکه با شبکه سراسری در کم‌ترین زمان ممکن شناسایی شود. در این مقاله، یک روش بهینه‌سازی به‌منظور تعیین پارامترهای ورودی روش کلاسه‌بندی به کمک اطلاعات محلی پیشنهاد شده است. هدف مسئله بهینه‌سازی، حداقل‌کردن زمان تشخیص و افزایش دقت تشخیص است. همچنین در روش کلاسه‌بندی سه حالت وقوع جزیره، اتصال مجدد به شبکه و سایر رخدادها در نظر گرفته شده است. تابع هدف این مسئله به‌صورت مجموع وزن‌دار ضریب زمان و خطای تشخیص رله تعریف شده است. با توجه به این‌که ورودی‌های مسئله تشخیص می‌توانند پارامترهای مختلف شبکه مانند فرکانس، ولتاژ، جریان، توان و یا مؤلفه‌های توالی آن‌ها و یا نرخ تغییرات آن‌ها باشند، متغیرهای مسئله بهینه‌سازی، تعداد و نوع پارامترهای ورودی مسئله کلاسه‌بندی در نظر گرفته شده است. از الگوریتم ژنتیک برای حل این مسئله بهینه‌سازی و از روش ماشین بردار پشتیبان برای کلاسه‌بندی استفاده شده است. به‌منظور بررسی صحت روش پیشنهادی، حالات مختلفی از شرایط بهره‌برداری ریزشبکه در نظر گرفته شده و در هر حالت، رخدادهای متفاوتی مدل‌سازی شده‌اند. مقایسه نتایج حاصله با نتایج سایر مقالات برتری روش پیشنهادی را نشان می‌دهد.

کلیدواژه‌ها

عنوان مقاله [English]

An Optimal Approach for Determining Microgrid State of Connection to Utility with Local Information

نویسندگان [English]

  • N. Hatefi Torshizi
  • H. Najafi
  • A. Saberi noghabi
Faculty of Electrical and Computer Engineering, University of Birjand, Birjand, Iran
چکیده [English]

For correct performanceof protection and control systems in microgrids, the islanding conditions should be identified as soon as possible.In this paper, an optimal method is proposed to determine the input parameters of classification method by using local information. The goal of optimization is to minimizie the time and maximize the percision of microgrid connection state detection. Also, in classification method, three states, i.e. islanding, reconnecting to the utility and other events are considered. The objective function of this problem is defined as summation of weighted time factor and detection error. The inputs of the islanding detection problem can be a large number of network parameters such as frequency, voltage, current, power, their sequence components or the rate of change. Consequently, the variables of the classification problem are the number and type of input parameters of the classification problem.The genetic algorithm is used to solve this optimal problem, and support vector machine is used for the classification. In order to assess the validity of the proposed method, different situations are considered for the operation of the grid, and in each case, different events are modeled. The results are compared with the methods of other papers, and the advantage of the suggested method is shown.

کلیدواژه‌ها [English]

  • Genetic algorithm
  • islanding detection
  • local information
  • microgrid
  • reconnection
  • support vector machine

مراجع

[1]    N. Hatziargyriou, Microgrids: architectures and control. John Wiley & Sons, 2013.
[2]    S. Chowdhury and P. Crossley, Microgrids and active distribution networks. The Institution of Engineering and Technology, 2009.
[3]    J. Ho, K. Chua, and S. Chou, "Performance study of a microturbine system for cogeneration application," Renewable energy, vol. 29, no. 7, pp. 1121-1133, 2004.
[4]    J. M. Guerrero et al., "Distributed generation: Toward a new energy paradigm," IEEE Industrial Electronics Magazine, vol. 1, no. 4, pp. 52-64, 2010.
[5]    A. Gholami, F. Aminifar, and M. Shahidehpour, "Front lines against the darkness: enhancing the resilience of the electricity grid through microgrid facilities," IEEE Electrification Magazine, vol. 4, no. 1, pp. 18-24, 2016.
[6]    A. Mehrizi-Sani and R. Iravani, "Potential-function based control of a microgrid in islanded and grid-connected modes," IEEE Transactions on Power Systems, vol. 25, no. 4, pp. 1883-1891, 2010.
[7]    L. Che, M. E. Khodayar, and M. Shahidehpour, "Adaptive Protection System for Microgrids: Protection practices of a functional microgrid system," IEEE Electrification Magazine, vol. 2, no. 1, pp. 66-80, 2014.
[8]    M. Abdel-Salam, A. Abdallah, R. Kamel, and M. Hashem, "Improvement of Protection Coordination for a Distribution System Connected to a Microgrid using Unidirectional Fault Current Limiter," Ain Shams Engineering Journal, vol. 8, no. 3, pp. 405-414, 2017.
[9]    H. Zeineldin and J. L. Kirtley, "A simple technique for islanding detection with negligible nondetection zone," IEEE Transactions on Power Delivery, vol. 24, no. 2, pp. 779-786, 2009.
[10]   G. Marchesan, M. R. Muraro, G. Cardoso Junior, L. Mariotto, and A. P. de Morais, "Passive Method for Distributed Generation Island Detection Based on Oscillation Frequency," IEEE Transactions on Power Delivery, vol. PP, no. 99, pp. 1-1, 2015.
[11]   H. Zeineldin, T. Abdel-Galil, E. El-Saadany, and M. Salama, "Islanding detection of grid connected distributed generators using TLS-ESPRIT," Electric Power Systems Research, vol. 77, no. 2, pp. 155-162, 2007.
[12]   M. Bakhshi, R. Noroozian, and G. Gharehpetian, "Anti-islanding scheme for synchronous DG units based on Tufts–Kumaresan signal estimation method," Power Delivery, IEEE Transactions on, vol. 28, no. 4, pp. 2185-2193, 2013.
[13]   B. Guha, R. J. Haddad, and Y. Kalaani, "A passive islanding detection approach for inverter-based distributed generation using rate of change of frequency analysis," in SoutheastCon, pp. 1-6, 2015.
[14]   H. Samet, F. Hashemi, and T. Ghanbari, "Islanding detection method for inverter-based distributed generation with negligible non-detection zone using energy of rate of change of voltage phase angle," IET Generation, Transmission & Distribution, vol. 9, no. 15, pp. 2337-2350, 2015.
[15]   H. Muda and P. Jena, "Phase angle-based PC technique for islanding detection of distributed generations," IET Renewable Power Generation, vol. 12, no. 6, pp. 735-746, 2018.
[16]   J. Merino, P. Mendoza-Araya, G. Venkataramanan, and M. Baysal, "Islanding detection in microgrids using harmonic signatures," IEEE Transactions on Power Delivery, vol. 30, no. 5, pp. 2102-2109, 2015.
[17]   H. Muda and P. Jena, "Rate of change of superimposed negative sequence impedance based islanding detection technique for distributed generations," IET Generation, Transmission & Distribution, vol. 10, no. 13, pp. 3170-3182, 2016.
[18]   A. R. Di Fazio, G. Fusco, and M. Russo, "Islanding detection method based on a Thevenin-like model," IET Generation, Transmission & Distribution, vol. 9, no. 13, pp. 1747-1754, 2015.
[19]   A. Ghanem, M. Rashed, M. Sumner, M. A. Elsayes, and I. I. Mansy, "Grid impedance estimation for islanding detection and adaptive control of converters," IET Power Electronics, vol. 10, no. 11, pp. 1279-1288, 2017.
[20]   K. Sareen, B. R. Bhalja, and R. P. Maheshwari, "Universal islanding detection technique based on rate of change of sequence components of currents for distributed generations," IET Renewable Power Generation, vol. 10, no. 2, pp. 228-237, 2016.
[21] مهرداد حیدری ارجلو، سید قدرت‌اله سیف‌السادات و مرتضی رزاز, «یک روش هوشمند تشخیص جزیره در شبکهٔ توزیع دارای تولیدات پراکنده مبتنی بر تبدیل موجک و نزدیک‌ترین K-همسایگی (KNN)», مجله مهندسی برق دانشگاه تبریز, دوره 43، شماره 1، صفحه 26-15، بهار 1392.
[22]   X. Kong, X. Xu, Z. Yan, S. Chen, H. Yang, and D. Han, "Deep learning hybrid method for islanding detection in distributed generation," Applied Energy, vol. 210, pp. 776-785, 2018.
[23]   R. Teodorescu and M. Liserre, Grid converters for photovoltaic and wind power systems. John Wiley & Sons, 2011.
[24]   H. Geng, D. Xu, B. Wu, and G. Yang, "Active islanding detection for inverter-based distributed generation systems with power control interface," IEEE Transactions on Energy Conversion, vol. 26, no. 4, pp. 1063-1072, 2011.
[25]   H. Ding et al., "A novel islanding detection based on adaptive active current disturbance," in Transportation Electrification Asia-Pacific (ITEC Asia-Pacific), pp. 1-5, 2014.
[26] مجید معظمی، رحمت‌الله هوشمند، امین خدابخشیان و  عبدالرضا بهوندی, «یک روش جدید تشخیص جزیره‌ای شدن اکتیو در سیستم‌های ریزشبکه با استفاده از تزریق جریان توالی منفی» مجله مهندسی برق دانشگاه تبریز, دوره 46، شماره 2، صفحه  293-279، تابستان 1395.
[27]  H. Zeineldin, E. El-Saadany, and M. Salama, "Islanding detection of inverter-based distributed generation," IEE Proceedings-Generation, Transmission and Distribution, vol. 153, no. 6, pp. 644-652, 2006.
[28]   X. Chen and Y. Li, "An islanding detection algorithm for inverter-based distributed generation based on reactive power control," IEEE Transactions on Power Electronics, vol. 29, no. 9, pp. 4672-4683, 2014.
[29]   M. Ropp, M. Begovic, and A. Rohatgi, "Analysis and performance assessment of the active frequency drift method of islanding prevention," IEEE Transactions on Energy Conversion, vol. 14, no. 3, pp. 810-816, 1999.
[30]   R. Azim, F. Li, Y. Xue, M. Starke, and H. Wang, "An islanding detection methodology combining decision trees and Sandia frequency shift for inverter-based distributed generations," IET Generation, Transmission & Distribution, vol. 11, no. 16, pp. 4104-4113, 2017.
[31]   Y. Jung, J.-Y. Choi, B. Yu, G. Yu, and J.-h. So, "A novel active frequency drift method of islanding prevention for the grid-connected photovoltaic inverter," in Power Electronics Specialists 36th Conference, pp. 1915-1921, 2005.
[32]   A. Yafaoui, B. Wu, and S. Kouro, "Improved active frequency drift anti-islanding detection method for grid connected photovoltaic systems," IEEE transactions on power electronics,vol. 27, no. 5, pp. 2367-2375, 2012.
[33]   G. Wang et al., "State variable technique islanding detection using time-frequency energy analysis for DFIG wind turbine in microgrid system," ISA Transactions, 2018.
[34]   S. Kar and S. R. Samantaray, "Time-frequency transform-based differential scheme for microgrid protection," IET Generation, Transmission & Distribution, vol. 8, no. 2, pp. 310-320, 2014.
[35]   K. El-Arroudi, G. Joos, I. Kamwa, and D. T. McGillis, "Intelligent-based approach to islanding detection in distributed generation," IEEE transactions on power delivery, vol. 22, no. 2, pp. 828-835, 2007.
[36]   Q. Cui, K. El-Arroudi, and G. Joos, "Islanding Detection of Hybrid Distributed Generation under Reduced Non-detection Zone," IEEE Transactions on Smart Grid, 2017.
[37]   M. R. Alam, K. M. Muttaqi, and A. Bouzerdoum, "A multifeature-based approach for islanding detection of DG in the subcritical region of vector surge relays," IEEE Transactions on Power Delivery, vol. 29, no. 5, pp. 2349-2358, 2014.
[38]   M. R. Alam, K. M. Muttaqi, and A. Bouzerdoum, "Evaluating the effectiveness of a machine learning approach based on response time and reliability for islanding detection of distributed generation," IET Renewable Power Generation, vol. 11, no. 11, pp. 1392-1400, 2017.
[39]   O. N. Faqhruldin, E. F. El-Saadany, and H. H. Zeineldin, "A universal islanding detection technique for distributed generation using pattern recognition," IEEE Transactions on Smart Grid, vol. 5, no. 4, pp. 1985-1992, 2014.
[40]   S. D. Kermany, M. Joorabian, S. Deilami, and M. A. Masoum, "Hybrid islanding detection in microgrid with multiple connection points to smart grids using fuzzy-neural network," IEEE Transactions on Power Systems, vol. 32, no. 4, pp. 2640-2651, 2017.
[41]   S. Kar and S. R. Samantaray, "Data-mining-based intelligent anti-islanding protection relay for distributed generations," IET Generation, Transmission & Distribution, vol. 8, no. 4, pp. 629-639, 2013.
[42]   M. R. Alam, K. M. Muttaqi, and A. Bouzerdoum, "An approach for assessing the effectiveness of multiple-feature-based SVM method for islanding detection of distributed generation," IEEE Transactions on Industry Applications, vol. 50, no. 4, pp. 2844-2852, 2014.
[43]   K. El-Arroudi and G. Joos, "Data mining approach to threshold settings of islanding relays in distributed generation," IEEE Transactions on power systems, vol. 22, no. 3, pp. 1112-1119, 2007.
[44]   S. Raza, H. Mokhlis, H. Arof, J. Laghari, and H. Mohamad, "A sensitivity analysis of different power system parameters on islanding detection," IEEE Transactions on Sustainable Energy, vol. 7, no. 2, pp. 461-470, 2016.
[45]   S. Raza, H. Mokhlis, H. Arof, K. Naidu, J. A. Laghari, and A. S. M. Khairuddin, "Minimum-features-based ANN-PSO approach for islanding detection in distribution system," IET Renewable power generation, vol. 10, no. 9, pp. 1255-1263, 2016.
[46]   K. Narayanan, S. A. Siddiqui, and M. Fozdar, "Hybrid islanding detection method and priority-based load shedding for distribution networks in the presence of DG units," IET Generation, Transmission & Distribution, vol. 11, no. 3, pp. 586-595, 2017.

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