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Determining the Necessity and Timing of Controlled Islanding in Power System: a wide-area intelligent-based method | ||
| International Journal of Industrial Electronics Control and Optimization | ||
| مقاله 10، دوره 4، شماره 3، آبان 2021، صفحه 367-376 اصل مقاله (1.33 MB) | ||
| نوع مقاله: Research Articles | ||
| شناسه دیجیتال (DOI): 10.22111/ieco.2021.35777.1304 | ||
| نویسندگان | ||
Hojatolah Makvandi1؛ Mahmood Joorabian  2؛ Hassan Barati1
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| 1Department of Electrical Engineering, Dezful Branch, Islamic Azad University, Dezful, Iran | ||
| 2Department of Electrical Engineering, Faculty of Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran | ||
| چکیده | ||
| The present study introduces a new extensive-area ANFIS (Adaptive Neuro-Fuzzy Interface System)-based method to detect wide area instability and control the time of controlled islanding execution within power systems. The ANFIS parameters are optimized by the PSO method to increase the method’s accuracy at various disturbances and loading circumstances. In addition, to take various stability margins within the areas into account, a novel parallel ANFIS network (P-ANFIS) is implemented in which a distinct ANFIS is allocated for every nearby area. Extended off-line studies are performed to train ANFIS to respond in real-time accurately based on the selected wide area input signals. These parameters are monitored continuously through a wide area measurement system (WAMS) and the proposed P-ANFIS starts to assess the stability between related areas in real-time in the case of potentially unstable oscillations. Once an unstable oscillation is detected, the islanding command is transmitted to perform the controlled islanding scheme. The suggested technique is used in an IEEE 39 bus power system and its performance is demonstrated at different disturbances in terms of both speed and accuracy. It is found that the suggested ANFIS-based technique can determine islanding requirement and its time of execution properly at different disturbances. | ||
| کلیدواژه‌ها | ||
| WAMS؛ islanding detection؛ ANFIS؛ PSO | ||
| مراجع | ||
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[1] L.L. Lai, H.T. Zhang, C.S. Lai, F.Y. Xu, S. Mishra,"Investigation on July 2012 Indian blackout.", International Conference on Machine Learning and Cybernetics, pp. 92-97, Jul. 2013 [2] Y. Makarov, Y, Reshetov, Y. Strojev, N. Voropai, “Blackout prevention in the United States, Europe, and Russia”, Proceedings of the IEEE, Vol. 93, No. 11, pp, 1942 - 1955, Nov. 2005, [3] K. Yamashita, S.K. Joo, J. Li, P. Zhang, C.C. Liu. “Analysis, control, and economic impact assessment of major blackout events”, European Transactions on electrical Power, Vol. 18, No. 8, pp. 854-871, Nov. 2008 [4] M. Abasi, M. Joorabian, A. Saffarian, S.G. Seifossadat, “A novel complete dynamic and static model of 48-pulse VSC-based GUPFC for parallel transmission lines”, International Journal of Industrial Electronics, Control and Optimization, Vol. 3, No. 4, pp. 447-457, Mar. 2020 [5] M.M. Adibi, R.J Kafka, S. Maram, L.M. Mili, “On power system controlled separation”. IEEE Transaction on Power Systems, Vol. 21, No. 4, pp. 1894 – 1902, Nov. 2006 [6] L. Ding, F, Gonzalez, P. Wall, V. Terzija, “Two-step spectral clustering-controlled islanding algorithm”, IEEE Transaction on Power Systems, Vol. 28, No. 1, pp. 75 - 84 Feb. 2013 [7] N. Senroy, G.T. Heydt, "Timing of a controlled islanding strategy." 2005/2006 IEEE/PES Transmission and Distribution Conference and Exhibition, pp, 483-491, May. 2016. [8] N. Senroy, G.T. Heydt, V. Vittal, "Decision tree assisted controlled islanding.", IEEE Transaction on Power Systems, Vol. 21, No. 4, pp. 1790-1797, Nov. 2006. [9] Gh. Isazadeh, A. Khodabakhshian, E. Gholipour, “A new intelligent wide area controlled islanding detection method in interconnected power systems”, International Transaction on electrical energy systems, Vol. 27, No 7, Jul. 2017 [10] J. Yan, C.C. Liu, U. Vaidya, “PMU-based monitoring of rotor angle dynamics”, IEEE Transaction on Power Systems, Vol 26, No. 4, pp. 2125 - 2133, Nov. 2011 [11] D.P. Wadduwage, C.Q. Wu, U.D. Annakkage.”Power system transient stability analysis via the concept of Lyapunov exponents”. Electric Power System Research, Vol. 104, pp. 183-192, Nov. 2013. [12] Gh. Isazadeh, A. Khodabakhshian, E. Gholipour. “A New Intelligent Controlled Islanding Scheme in Large Interconnected Power Systems”, IET generation transmission Distribution, Vol. 9, No. 16, pp. 2686 – 2696, Dec. 2015. [13] K. Sun, K. Hur, P. Zhang. “A new unified scheme for controlled power system separation using synchronized phasor measurements”, IEEE Transaction on Power Systems, Vol. 26, No. 3, pp. 1544 – 1554, Aug. 2011 [14] M.R. Salimian, M.R Aghamohammadi, “A new index based on proximity of inter-area oscillation to UEP point for predicting proper time of controlled islanding”, International Journal of Electrical Power & Energy Systems, Vol. 104, pp. 383-400, Jan. 2019, [15] T. Amraee, H. Saberi, “Controlled islanding using transmission switching and load shedding for enhancing power grid resilience”, International Journal of Electrical Power & Energy Systems, Vol. 91, pp. 135-143, Oct. 2017. [16] M. Amini, H. Samet, A.R. Seifi, M. Al-Dhaifallah, Z.M. Ali, “An Effective Multi-Solution Approach for Power System Islanding”. IEEE Access, pp. 93200 – 93210, May. 2020. [17] F. TANG, J. YANG, Q. LIAO, et al. “Out-of-step oscillation splitting criterion based on bus voltage frequency.”, Journal of Modern Power Systems and Clean Energy, Vol. 3, No. 3, pp. 341 - 352, Sep. 2015. [18] S. Mohagheghi, G.K. Venayagamoorthy, R.G. Harley,” Optimal neuro-fuzzy external controller for a STATCOM in the 12-Bus benchmark power system”, IEEE Trans. Power Delivery, Vol. 22, No. 4, pp. 2548-2558, Oct. 2007. [19] R. Jang, T. Sun, and E. Mizutani, “Neuro-Fuzzy and Soft Computing a Computational Approach to Learning and Machine Intelligence.” IEEE Transactions on Automatic Control, (1997). Vol. 42, No. 10 , pp. 1482 – 1484, Oct. 1997 [20] J.-S. R. Jang, “ANFIS: Adaptive Network-Based Fuzzy Inference Systems”, IEEE Transactions on Systems., Man, Cybern, Vol. 23, No. 3, pp. 665 – 685, May. /Jun. 1993 [21] Y.del Valle, G.K Venayagamoorthy, S. Mohagheghi, J.-C. Hernandez, R.G. Harley, “Particle Swarm Optimization: Basic Concepts, Variants and Applications in Power Systems”, IEEE Transaction on Evolutionary Computation, Vol. 12, No. 2, Apr. 2008 [22] H. Yoshida, K. Kawata, Y. Fukuyama, S. Takayama, Y. Nakanishi, A Particle Swarm Optimization for Reactive Power and Voltage Control Considering Voltage Security Assessment”, IEEE Transaction on Power Sytems, Vol. 15, No. 4, pp. 1232 – 1239, Nov. 2000 [23] R. Gurusinghe, A. D. Rajapakse, “Post-Disturbance Transient Stability Status Prediction Using Synchrophasor Measurements”, IEEE Trans. on Power Systems, Vol. 31, No. 5, pp. 3656-3664, Sep. 2016. [24] M. Abasi, M. Razaz, G. Seifossadat, S. Moosapour “Presenting a New Formulation to Analyze and Determine Unbalance Voltage Produced at the Place of Load Resulting from Network and Loads Unbalance and Asymmetry of Transmission Lines in Radial Power Systems’’, Majlesi Journal of Energy Management, Vol. 4, No. 3, pp.1-7, Sep. 2015. [25] M. Abasi, S.G. Seifossadat, M. Razaz, S.S. Moosapour “Determining the contribution of different effective factors to individual voltage unbalance emission in n-bus radial power systems, Journal International Journal of Electrical Power & Energy Systems", International Journal of Electrical Power & Energy Systems, Vol. 94, No.12, pp.393-404, Jan. 2018. [26] Power Systems Test Case Archive, https://www.ee.washington.edu/research/pstca/39 bus, 05/06/2020 | ||
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