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Geomagnetically induced currents (GICs) are referred to the quasi-DC current flows in power networks, driven by complex space weather-related phenomena. Such currents are a potential threat to the power delivery capability of electrical grids. To mitigate the detrimental impacts of GICs on critical infrastructures, the GICs should be monitored in power systems. Being inherently DC from the power frequency point of view, the components of GICs are, however, challenging and costly to monitor in AC power grids. This paper puts forward a novel methodology for the real-time estimation of GICs in power transformers. Such aim is attained by means of an extended Kalman filter (EKF)-based approach, mounted on the nonlinear state-space model of the transformer, whose parameters can be derived from standard tests. The proposed EKF-based algorithm employs the available measurements for the transformer differential protection. The proposed approach, relying on the differential current, can properly deal with the external sources of interference like harmonic excitation and loading. The EKF-based estimator presented is validated by simulation and experimental data. The results verify the ability of the proposed approach to robustly estimate the GIC level during various operating conditions., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Intelligent Electrical Power Grids

Fast internal detection and location in Shunt Ca-pacitor Banks (SCBs) can lead to the prevention of damages to other SCBs' elements and consequently avoid undesirable performance and effects in power system operation. This paper targets the performance of phasor-based algorithms of failure detection and fault location of SCBs. Being dependent on the fundamental phasor components which usually are calculated based on the Discrete Fourier Transform (DFT), the failure detection and fault location algorithms suffer from almost one-cycle delay. This paper provides sub-cycle phasor estimation based on the least-square technique. The proposed algorithm is evaluated for different configurations of SCBs considering different fuse protection designs. The proposed method provides a criterion for relay decision-making in the case of multiple faulty phases condition. The proposed method is designed to monitor and detect consecutive failures based on the existing data of commercial relays. Performance evaluations are conducted under different circumstances namely voltage unbalance conditions and multiple internal fault locations., QC 20230214

During fault occurrence close to the distributed generators (DGs) produces a fundamental sinusoidal component with time-variant magnitude. An enhanced dynamic phasor estimation is proposed in this paper that aims to deal with phasor estimation problem of fault current signals considering transient behavior of DGs. To such aim, an enhanced hybrid method based on integral based DC removal filter and improved Least Square (LS) is presented. The presented algorithm takes into account the effects of decaying DC and also the harmonic components. The effectiveness of the phasor estimator is assessed generating short circuit fault scenarios in a sample wind farm consist of some doubly-fed induction generators (DFIGs) in MATLAB. Simulation results reveal that the proposed phasor estimator can precisely calculate and track the time-variant phasor of the fault current with minimum effect from harmful components that may be existed in the fault current signal., QC 20220822Part of proceedings: ISBN 978-1-6654-8537-1

Proliferation of renewable energy sources (RESs) has increased the reliability and flexibility in the operation of the power networks. Nevertheless, different technologies of RESs with different sizes and grid-connection technologies may impose threats to the power grid's stability. This paper targets transient stability in distribution networks. More specifically, this paper investigates the allocation of different types of distributed generations (DGs) considering the maximization of transient stability margin. The latter maximization helps to minimize the deterioration of the inverter-based DGs. The transient stability based objective function (OF) basically relies on the critical and clearing angles. Besides transient stability, the improvement of voltage profile and minimization of power losses are taken into account. The proposed algorithm is implemented on the IEEE 33-bus test system and furthermore, several scenarios are conducted to ensure the effectiveness of the proposed algorithm under fault conditions., QC 20220822Part of proceedings: ISBN 978-1-6654-8537-1

Saturation phenomena in the current transformer (CT) may impose severe deformation in the secondary current of a CT. Obviously, CT saturation profoundly impacts the performance of the phasor estimation algorithms which can result in the mal-operation of the protective relays. Besides of CT saturation, presence of decaying DC component is another factor that affects the performance of the phasor estimators. This paper provides a comparative analysis between full-cycle and sub-cycle phasor estimators to evaluate their abilities under the CT saturation with/without decaying DC component. Through the following investigation, the sensitivity of the different phasor estimators is evaluated under CT saturation, DC decaying, and noisy conditions. The precision and robustness of the different phasor estimator are evaluated under different simulation results in MATLAB software and furthermore the requirements about phasor estimator for dealing with CT saturation are discussed., QC 20220822Part of proceedings: ISBN 978-1-6654-8537-1

Owing to the large magnitude of the inrush currents, the functionality of differential protection of power transformer may be threatened in correct discrimination between inrush and internal faults. This paper enhances the functionality of differential protection through a computationally efficient method that utilizes the phase angle current signals of the current transformers (CTs). The proposed discrimination criterion (PDC) tracks the fundamental phase angle of the current signals of the CTs. While during an internal fault, the phase angles of both CTs are almost constant and in phase, during the external fault and inrush currents, the phase angles of both CTs have notable distance. On this ground, this paper employs a developed Kalman filter based phase angle estimator to measure the fundamental phase angles of the current signals of the CTs. Afterward, PDC is introduced that measures the distance between the estimated phase angles of the CT’s currents. Evaluating the effectiveness of the PDC with several simulated and experimental recorded current signals reveals the PDC is able to detect internal faults even in presence of CT saturation and also to deal with inrush and external fault currents.

This paper deals with driving effective DC series arc models from the original Nottingham arc model. The original Nottingham arc model has three constant parameters and suffers significant inaccuracy for modeling the series arc faults. To avoid the inaccuracy in the modeling, at first, a Nottingham model is developed that is relevant to voltage and current of the fault with three parameters including one constant model order for exponents of the current and two time-series coefficients. Also, to further improvement in the model's accuracy, a two-fold Nottingham model is proposed that is relevant to voltage and current of the fault with five parameters including two constant model orders for exponents of the current and three time-series coefficients. Finally, a full-time-variant Nottingham model is proposed that mathematically contains three time-series parameters including one time-variant model order of the current exponent. In the full-time-variant Nottingham model, the optimal parameters corresponding to each sliding window of data are utilized. In all the proposed models the arc coefficients are estimated using a new formulation using the least-squares error (LSE) technique. Verifying the effectiveness of the proposed models through actual data, the accuracy of the proposed models is compared with the original Nottingham model.

This paper puts forward a new algorithm based on Kullback Leibler divergence (KLD) for discriminating inrush and internal fault currents in power transformers. Specifically, the main idea of this algorithm is to utilize the current signal discrepancy of the distribution with ideal fault current waveforms. To such an aim, the proposed index reproduces the differential current signal. Utilizing fast modified least squares technique (MLSE), the differential current signal is generated. Applying the reconstructed differential current and ideal sinusoidal waveforms to the KLD indicator, the distribution discrepancy of the current signal from ideal sinusoidal waveform discriminates inrush and internal fault currents. Also the internal/external identification (IEI) index is introduced that utilizes the phase content of the signals from CTs on both sides to distinguish internal and external faults, especially the faults accompanied with CT saturation. As a result, the proposed method can distinguish inrush currents, internal and external fault currents with/without current transformer (CT) saturation and internal fault currents during transformer energization. The performance of the proposed index is evaluated using practically recorded data and is further compared with the state-of-the-art.

This study tries to outline a comprehensive approach established on the kinetic energy of the distributed generations (DGs) for islanding mode detection in micro-grids. More specifically, the proposed index calculates the rate of change of kinetic energy over reactive power (ROCOKORP) for each DG at the point of common coupling (PCC). Despite the islanding detection being the most challenging issue during complete match between the load and generation of DGs, the proposed method can swiftly deal with such an issue, therefore confirming its superiority. Other challenging conditions where islanding detection can either be difficult or confused with other events such as loads inside the non-detection zone (NDZ), various fault types, and loads at various power factors have also been considered to investigate the effectivity of the proposed approach. The proposed method’s performance has been verified and evaluated in comparison to the state-of-the-art via a simulation testbed.

This paper deals with a fault detection investigation of SCBs, and it is focused on the faulty phase detection and the number of faulty capacitor units. Unlike previous methods, the proposed method provides a relay decision making criterion which determine the faulty capacitors, and the number of capacitor failures in case of multiple faulty phase conditions. The proposed algorithm is applied on different wye configurations of SCBs considering different protection designs (i.e., fuseless, internally and externally fused units). Since the detection of capacitor failures in SCBs are based on the fundamental phasor component, there may occur a significant delay in decision making in the case of an external short circuit fault in the power system. The aforementioned condition, which will be mathematically proven, happens due to a capacitor discharge after fault clearance. To deal with this condition, a method is proposed by applying an algorithm, in which the fundamental component of the voltage signal is extracted in one cycle. Performance evaluations associated with the proposed method are provided for different fault conditions, fault locations, and different levels of harmonics and, they are further discussed through the implementation of the proposed method in MATLAB environment., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Intelligent Electrical Power Grids

Vacuum circuit breaker operation causes transient overvoltages that may lead to severe damages to transformer insulation. Since the parameters affecting these overvoltages have stochastic nature, a statistical analysis may provide detailed insight into the overvoltages from the point of view of insulation coordination applications. In this paper, a statistical analysis of the overvoltage variations of the step-up transformer during vacuum circuit breaker operation is conducted. Some variables, including switching angle, current chopping, high-frequency current quenching capability, and wind turbine power, are assumed as random variables. Besides, some indicators representing the switching overvoltage characteristics such as the amplitude, the number of restrikes, and the rate of rise are extracted. By performing a probabilistic analysis, the destructiveness due to switching overvoltages on typical transformer insulation can be investigated. The sensitivity of different surge protective devices and their effectivities are also analyzed and statistically evaluated. The applied methodology is very useful because of the stochastic nature of the switching overvoltages. In this work, the impact of protective equipment on each of the overvoltage indicators is analyzed. It is also found that considering only the amplitudes of transient overvoltages is not enough to draw conclusions about the safety of the transformer when exposed to frequent switching surges., Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public., Intelligent Electrical Power Grids