A Fast Voltage Collapse Detection and Prevention Based on Wide Area Monitoring and Control

Document Type: Research paper


Department of Electrical Engineering, Lorestan University, Khorramabad, Iran


Voltage stability is one of the most important factors in maintaining reliable operation of power systems. When a disturbance occurs in the power system, it usually causes instabilities and sometimes leads to voltage collapse (VC). To avoid such problems, a novel approach called Vector Analysis (VA) is proposed that exploits a new instability detection index to provide wide area voltage stability for the power systems. The presented index is calculated based on measuring the active and reactive powers that flow through the bus which is connected to the generator bus. Moreover, when the proposed VA approach predicts VC, through disconnecting weak lines and based on network graph, zoning is carried out in the power system. After zoning, damaged and undamaged zones will be differentiated and damaged zones requires load shedding (LS) which is accomplished using ANFIS-TSK (AN-T) intelligent method. The presented approach is applied to the IEEE-39 bus test system. The obtained simulation results demonstrate acceptable performance of the presented approach compared with other suggested methods in terms of speed and accuracy.


Main Subjects

[1]    D. Meng, “China’s protection technique in preventing power system blackout to world”, Int. Conf. Adv. Power Syst. Autom. Prot., pp. 1838-1844, 2011.

[2]    A. Pama et al., “Static voltage stability improvement with battery energy storage considering optimal control of active and reactive power injection”, Electr. Power Syst. Res., vol. 79, pp. 303-312, 2019.

[3]    D. Marujo, A. Zambroni, B. Lopes, M. Santos and K.  Lo, “On control actions effects by using QV curves”, IEEE Trans. Power Syst., vol. 30, pp. 1298-1305,2017.

[4]    H. Li, A. Bose and V. Venkatasubramanian, “Wide-area voltage monitoring and optimization” IEEE Trans. Smart Grid, vol. 7, pp. 785-793, 2016.

[5]    Y. Wang, C. Wang, F. Lin, W. Li, L. Wang and J. Zhao, “Incorporating generator equivalent model into voltage stability analysis”, IEEE Trans. Power Syst., vol.28, pp.4857-4866, 2013.

[6]    R. Sodhi, S. Srivastava and S. Singh, “A simple scheme for wide area detection of impending voltage instability”, IEEE Trans. Smart Grid, vol. 63, pp. 1020-1031, 2013.

[7]    M. Mohammadniaei, F. Namdari and M. R. Shakarami, “A new algorithm for zoning of power system to protect from voltage collapse”, 31th Int. Power System Conf., pp. 2147-2151, 2016.

[8]    A. Chandra and A. Pradhan, “Online voltage stability and load margin assessment using wide area measurements”, Int. J. Electr. Power Energy Syst., vol. 6, pp.392-401, 2019.

[9]    S. Dasgupta, M. Paramasivam, U. Vaidya and V. Ajjarapu, “Real-Time Monitoring of Short-TermVoltage Stability Using PMU Data”, IEEE Trans. Power Syst., vol.28, pp.3702-3711, 2013.

[10]    V. Balamourgan, T. Sidhu and M. Sachdev, “Technique for online prediction of voltage collapse”, IEEE Proc. Gener. Transm. Dist.,  vol.15, pp. 453-460, 2004.

[11]    R. Tiwari, K. Niazi and V. Gupta, “Line collapse proximity index for prediction of voltage collapse in power systems”, Int. J. Electr. Power Energy Syst., vol. 8, pp.41-51, 2012.

[12]    I. Musirin and T. Rahman, “Novel fast voltage stability index (FVSI) for voltage stability analysis in power transmission system”, Proc. student conf. res. Dev., pp. 265-268, 2002.

[13]    S. Pérez-londoño, L. Rodríguez and G. Olivar, “A simplified voltage stability index (SVSI)”, Int. J. Electr. Power Energy Syst., vol. 63, pp. 806-813, 2014.

[14]    K. Sajan, V. Kumar and B. Tyagi, “Genetic algorithm based support vector machine for on-line voltage stability monitoring”, Int. J. Electr. Power Energy Syst.,vol. 8, pp. 200-208, 2015.

[15]    H. Aliyari, R. Effatnejad and M. Savaghebi, “Solving Multi-Objective Optimal Power Flow Using Modified GA and PSO Based on Hybrid Algorithm”, J. Oper. Autom. Power Eng., vol. 5, pp. 51-60, 2017.

[16]    A. Saffarian and M. Sanaye-Pasand, “Enhancement of Power System Stability Using Adaptive Combinational Load Shedding Methods”, IEEE Trans. Power Syst., vol. 26, pp. 1010-1020, 2011.

[17]    W. Council, “WECC coordinated off-nominal frequency load shedding and restoration requirements”, 2005.

[18]    H. Shayeghi and A. Younesi, “Mini/Micro-Grid Adaptive Voltage and Frequency Stability Enhancement Using Q-learning Mechanism through the Offset of PID Controller”, J. Oper. Autom. Power Eng., vol. 7, pp.107-118, 2019.

[19]    H. Shayeghi and A. Younesi, “A Robust Discrete FuzzyP+FuzzyI+FuzzyD Load Frequency Controller for Multi-Source Power System in Restructuring Environment”,  J. Oper. Autom. Power Eng., vol.5, pp.61-74, 2017.

[20]    T. Cutsem and C. Vournas, “Voltage stability of electric power systems”, Springer, 2008.

[21]    A. Eshraghi and R. Ghorbani, “Islanding detection and over voltage mitigation using controllable loads”, Sustain. Energy, Grids Networks, vol. 6, pp. 125-135, 2016.

[22]    J. Jones and W. Kirkland, “Computer algorithm for selection of frequency relays for load shedding”, IEEE Comput. Appl. Power, vol. 1, pp. 21-25, 1988.

[23]    W. Council, “WECC coordinated off-nominal frequency load shedding and restoration requirements”, 2005.

[24]    K. Hornik, M. Stinchcombe, H. White and P. Auer, “Degree of Approximation Results for Feedforward Networks Approximating Unknown Mappings and Their Derivatives”, Neural Comput., vol. 6, pp. 1262-1275, 1994.

[25]    B. Kosko, “Fuzzy systems as universal approximators”, IEEE Trans. Comput., vol. 43, pp. 1329-1333, 1994.


[26]    K. Seethalekshmi et al., “A Synchrophasor Assisted Frequency and Voltage Stability Based Load Shedding Scheme for Self-Healing of Power System”, IEEE Trans. Smart Grid, vol. 2, pp. 221-230, 2011.