Abstract
This paper presents a new algorithm for the detection of ferroresonance oscillations in medium voltage (MV) power systems. The proposed method is based on an analysis of estimated flux resulting from the voltage in open delta voltage transformer (VT) connection. The testing results proved that the new solution is capable of identifying quickly and reliably ferroresonance oscillations and it does not maloperate during faults. In addition, this method is simple for hardware implementation. The developed solution has been thoroughly tested on simulation runs (from the MATLAB2019b/Simulink program), as well as recorded signals.
Highlights
The ferroresonance phenomenon may happen in power configurations where a nonlinear inductance, e.g., representing a magnetizing branch of a voltage transformer (VT) or power transformer, etc., is connected to a capacitance [1,2]
With a significant probability of occurrence, ferroresonance oscillations take place in distribution medium voltage (MV) networks with isolated neutral, where VTs are in parallel with the zero-sequence network capacitance [1,3]
By the formula: Ta + Ts where n is the number of sample (n = 1,2,3,..., inf), ud is the voltage in open delta VT connection, T
Summary
The ferroresonance phenomenon may happen in power configurations where a nonlinear inductance, e.g., representing a magnetizing branch of a voltage transformer (VT) or power transformer, etc., is connected to a capacitance [1,2]. The ferroresonance oscillations may be initiated when the VT iron core inductance becomes saturated, which may be a case when the VT terminal voltage suddenly increases This may be a consequence of switching operations in VT secondaries, clearing the nearby single-phase-to-ground fault, etc. Under such conditions, nonlinear oscillations may appear, being characterized by high voltage, significant currents, and waveform distortions, mainly by subharmonic and/or higher frequency components. Nonlinear oscillations may appear, being characterized by high voltage, significant currents, and waveform distortions, mainly by subharmonic and/or higher frequency components Such a disturbance may be dangerous for power system elements, since it increases the thermal (due to overcurrent) and electrical (due to overvoltage) stresses that may destroy VT or other equipment. The algorithm should be capable of distinguishing ferroresonance from short-circuits and other disturbances so that they are not misclassified
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