Estimation of New Weighted Controlled Switching Overvoltage by RBFN Model

Hasanpour, M.; Ghanbari, M.; Parvin-Darabad, V.

doi:10.22098/joape.2020.6987.1508

تعداد نشریات	27
تعداد شماره‌ها	364
تعداد مقالات	3,223
تعداد مشاهده مقاله	4,740,165
تعداد دریافت فایل اصل مقاله	3,237,811

	Estimation of New Weighted Controlled Switching Overvoltage by RBFN Model
Journal of Operation and Automation in Power Engineering
مقاله 5، دوره 8، شماره 3، اسفند 2020، صفحه 234-244 اصل مقاله (1.08 M)
نوع مقاله: Research paper
شناسه دیجیتال (DOI): 10.22098/joape.2020.6987.1508
نویسندگان
M. Hasanpour¹؛ M. Ghanbari^* ¹؛ V. Parvin-Darabad¹^،^{، 2}
¹Department of Electrical Engineering, Gorgan Branch, Islamic Azad University, Gorgan, Iran
²Department of Electrical Engineering, Golestan University, Gorgan, Iran
چکیده
Mitigating switching overvoltages (SOVs) and conducting well-suited insulation coordination for handling stresses are very important in UHV transmission Lines. The best strategy in the absence of arresters is controlled switching (CS). Although elaborate works on electromagnetic transients are considered in the process of designing transmission systems, such works are not prevalent in day-to-day operations. The power utility and/or operator have to carefully monitor the peak values of SOVs so this values not to exceed the safe limits. In this paper, we present a novel CS approach in dealing with EMTP/ATP environment, where trapped charge (TC) is intended to train a radial basis function network (RBFN) meta-model that is implemented to calculate SOVs. A new weighted maximum overvoltage factor proposed to find locations of critical failure risk due to SOVs occurred along transmission lines. Power utilities or design engineers can benefit from the presented meta-model in designing a well-suited insulation level without spending time for taking into account the feasible risk value. Besides, the operators can energize the lines sequentially upon their choice; i.e., a safe and proper energization.
کلیدواژه‌ها
Switching overvoltage؛ Transmission Line؛ Controlled Switching؛ RBFN

مراجع
[1] R. Shariatinasab, J. Safar and H. Falaghi, “Optimisation of arrester location in risk assessment in distribution network”, IET Gener. Transm. Distrib., vol. 8, pp. 151-159, 2014. [2] M. Akafi, “Estimation of SOV on transmission lines using fuzzy method”, M.S. thesis in Electrical Engineering, Power Systems, Faculty of Engineering The University of Birjand., Iran, 2012. [3] N. Eskandari and S. Jalilzadeh, “Electrical load manageability factor analyses by artificial neural network training”, J. Oper. Autom. Power Eng., vol. 7, pp. 187-195, 2019. [4] A. Deihimi and A. Rahmani, “An intelligent method based on WNN for estimating voltage harmonic waveforms of non-monitored sensitive loads in distribution network”, J. Oper. Autom. Power Eng., vol. 6, pp. 13-22, 2018. [5] D. Thukaram, H. Khincha and S. Khandelwal, “Estimation of switching transient peak overvoltages during transmission line energization using artificial neural network”, Electr. Power Syst. Res., vol. 76, 2006. [6] S. Taher and I. Sadeghkhani, “Estimation of magnitude and time duration of temporary overvoltages using ANN in transmission lines during power system restoration”, Simul. Modell. Pract. Theory, vol. 18, 2010. [7] R. Shariatinasab et al., “Optimization of surge arrester’s location on EHV and UHV power networks using simulation optimization method”, IEEJ Trans., vol. 128, 2008. [8] R. Shariatinasab, M. Akafi and M. Farshad, “Estimation of SOV on transmission lines using neuro-fuzzy method”, Intell. Syst. Electr. Eng., vol. 3, pp. 55-66, 2013. [9] A. Hamza, S. Ghania, A. Emam and A. Shafy, “Statistical analysis of SOV and insulation coordination for a 500 kv transmission line”, 19th Int. Symp. High Voltage Eng., pp. 1-4, 2016. [10] H. Seyedi and S. Tanhaeidilmaghani, “New CS approach for limitation of transmission line SOV”, IET Gener. Transm. Distrib., vol. 7, 2013. [11] M. Atefi and M. Sanaye-Pasand, “Improving controlled closing to reduce transients in HV transmission lines and circuit breakers”, IEEE Trans. Power Delivery, vol. 2, 2013. [12] M. Sanaye-Pasand, , M. Dadashzadeh and M. Khodayar, “Limitation of transmission line SOV using switchsync relays”, Int. Conf. Power Syst. Transients, pp. 1-6, 2005. [13] D. Lin et al., “An adaptive reclosure scheme for parallel transmission lines with shunt reactors”, IEEE Trans. Power Delivery, vol. 30, pp. 2581-89, 2015. [14] P. Mestas, M. Tavares and A. Gole, “Implementation and performance evaluation of a reclosing method for shunt reactor-compensated transmission lines”, IEEE Trans. Power Delivery, vol. 26, pp. 954-962, 2011. [15] K. Dantas, W. Neves and D. Fernandes, “An approach for controlled reclosing of shunt-compensated transmission lines”, IEEE Trans. Power Delivery, vol. 29, pp. 1203-11, 2014. [16] K. Bhatt, B. Bhalja and U. Parikh, “Controlled switching technique for minimization of switching surge during energization of uncompensated and shunt compensated transmission lines for circuit breakers having pre-insertion resistors”, Int. J. Electr. Power Energy Syst., vol. 103, pp. 347-359, 2018. [17] I. Ibrahim and H. Dommel, “A knowledge base for switching surge transients”, Int. Conf. Power Syst. Transients, pp. 1-6, 2005. [18] M. Cervantes et al, “Simulation of SOV and validation with field tests”, IEEE Trans. Power Delivery, vol. 33, 2018. [19] J. Das, “Transients in electrical systems: analysis, recognition, and mitigation”, the McGraw-Hill Companies, USA, 2010. [20] R. Rocha and J. Tavora, “EMTP model for CS simulation by means of TACS routine”, Int. Conf. Power Syst. Transients, pp. 254-259, 1997. [21] A. Hileman, “Insulation coordination for power systems”, Marcel Dekker Inc., New York, 1999. [22] R. Shariatinasab et al., “Probabilistic evaluation of optimal location of surge arrester on EHV and UHV networks due to switching and lightning surges”, IEEE Trans. Power Delivery, vol. 24, 2009. [23] R. Smeets et al., “Switching in electrical transmission and distribution systems”, John Wiley & Sons, 2014. [24] S. Hosseinian, M. Abedi and B. Vahidi, “Digital computer studies of random switching of Iranian standard 400 kV lines”, 3rd Int. Conf. Properties Appl. Dielectric Mater., pp. 542–545, 1991. [25] A. Clerici, G. Ruckstuhl and A. Vian, “Influence of shunt reactors on switching surges”, IEEE Trans. Power Apparatus Syst., vol. 89, 1970. [26] W. Hofbauer et al., “Controlled closing on shunt reactor compensated transmission lines - Part II”, IEEE Trans. Power Delivery, vol. 12, 1997. [27] K. Dantas, W. Neves and D. Fernandes, “An Approach for controlled reclosing of shunt-compensated transmission lines”, IEEE Trans. on Power Delivery, vol. 29, 2014. [28] Cigre Working Group, “SOV in EHV and UHV systems with special reference to closing and reclosing transmission lines”, Electra 30, pp. 70-122, 1973. [29] M. Hasanpour, M. Ghanbari and V. Parvin-Darabad, “Estimation of switching surge flashover rate of point on wave switching over-voltages along transmission line by adaptive neuro-fuzzy inference system meta-model”, IET Sci. Meas. Technol, vol. 13, pp. 1326-1334, 2019. [30] ABB, “Controlled switching, buyer's & application guide”, (ABB, Ludvika, Sweden, 4th edn.), pp. 33-54, 2013. [31] A. Alexandridis et al, “A fast and efficient method for training categorical radial basis function networks”, IEEE Trans. Neural Network Learn. Syst., vol. 28, 2017. [32] A. Alexandridis, E. Chondrodima and H. Sarimveis, “Radial basis function network training using a nonsymmetric partition of the input space and particle swarm optimization”, IEEE Trans. Neural Network Learn. Syst., vol. 24, pp. 219-230, 2013.
آمار تعداد مشاهده مقاله: 906 تعداد دریافت فایل اصل مقاله: 881

سامانه مدیریت نشریات علمی. قدرت گرفته از سیناوب

پیوندهای مفید

آمار

Estimation of New Weighted Controlled Switching Overvoltage by RBFN Model