A comprehensive review on DC Microgrid protection schemes

This paper explores the most important factors that define the Traveling Wave (TW) propagation on distribution systems. The factors considered in this work are: the distance to the fault location, the fault type, and the crossing of system elements (such as regulators, capacitor banks, laterals, and extra loads within the protection zones). This work uses a realistic, yet simplified, distribution system composed of two protection zones, in which, several combinations of the previously mentioned factors are considered. The simulated fault measurements undergo a signal processing stage in which, first, they are decomposed into independent modes using the Karrenbauer transform. Second, a time–frequency representation is obtained using the Stationary Wavelet Transform (SWT), dividing the signal into several frequency bands. Finally, the Parseval’s Energy (PE) theorem is applied to calculate the signal energy in each frequency band. A qualitative analysis is performed based on the previously calculated energies to outline which are the factors that most affect the TW energy during propagation. The results show that distance, the presence of regulators, either in the propagation path or upstream, and the type of fault are the main factors that affect TW propagation across the system, and therefore they should be considered for TW-based protection schemes for distribution systems.

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Traveling Wave Energy Analysis of Faults on Power Distribution Systems

This paper presents a novel approach for fault location and classification based on combining mathematical morphology (MM) with Random Forests (RF). The MM stage of the method is used to pre-process voltage and current data. Signal vector norms on the output signals of the MM stage are then used as the input features for a RF machine learning classifier and regressor. The data used as input for the proposed approach comprises only a window of 50 µs before and after the fault is detected. The proposed method is tested with noisy data from a small simulated system. These results show 100% accuracy for the classification task and prediction errors with an average of ∼13 m in the fault location task.

An Algorithm for Fast Fault Location and Classification Based on Mathematical Morphology and Machine Learning

A novel method for fault classification and location is presented in this paper. This method is divided into an initial signal processing stage that is followed by a machine learning stage. The initial stage analyzes voltages and currents with a window-based approach based on the dynamic mode decomposition (DMD) and then applies signal norms to the resulting DMD data. The outputs for the signal norms are used as features for a random-forests for classifying the type of fault in the system as well as for fault location purposes. The method was tested on a small distribution system where it showed an accuracy of 100% in fault classification and a mean error of ∼ 30 m when predicting the fault location.

A Machine Learning-based Method using the Dynamic Mode Decomposition for Fault Location and Classification

One of the challenging issues in the realization of medium-voltage DC (MVDC) distribution system is high-speed protection scheme design against quickly rising short circuit fault-DC current. This paper proposes a high-speed protection scheme based on the processing of energy signals through mathematical morphology (MM). The voltage and current signals measured at a distribution line section (DLS) are used to obtain the energy signal. The proposed scheme develops a modified MM-based filter to extract the transient information in the energy signal rapidly and distinctly in the form of positive/negative polarity. The polarity detection of any disturbance in the analysed energy signal indicates the occurrence of a sudden disturbance in the system. The sudden disturbance occurrence confirmation triggers the faulty DLS identification and classification algorithms of the proposed scheme. The faulty DLS identification and classification algorithms are based on the detected polarities of the energy signal. The protection scheme requires low bandwidth communication. The proposed protection scheme is evaluated by using a ±2.5 kV radial distribution network containing 4 feeders under different fault conditions in MATLAB/SIMULINK software. Simulation results verify that the proposed scheme can isolate the faulty portion within a few milliseconds after fault inception under a variety of fault cases. 

High speed protection of medium voltage DC distribution system using modified mathematical morphology

As a result of the increase in penetration of inverter-based generation such as wind and solar, the dynamics of the grid are being modified. These modifications may threaten the stability of the power system since the dynamics of these devices are completely different from those of rotating generators. Protection schemes need to evolve with the changes in the grid to successfully deliver their objectives of maintaining safe and reliable grid operations. This paper explores the theory of traveling waves and how they can be used to enable fast protection mechanisms. It surveys a list of signal processing methods to extract information on power system signals following a disturbance. The paper also presents a literature review of traveling wave-based protection methods at the transmission and distribution levels of the grid and for AC and DC configurations. The paper then discusses simulations tools to help design and implement protection schemes. A discussion of the anticipated evolution of protection mechanisms with the challenges facing the grid is also presented.

/pdf/a-survey-of-traveling-wave-protection-schemes-in-electric-9vhhgbvvxa.pdf

A Survey of Traveling Wave Protection Schemes in Electric Power Systems

DC microgrid fault detection using multiresolution analysis of traveling waves

Shifting from Fossil Fuel Reliance to Green Energy Sovereignty: Ute Mountain Ute Tribe.

This report is a summary of a 3 - year LDRD project that developed novel methods to detect faults in the electric power grid dramatically faster than today?s protection systems. Accurately detecting and quickly removing electrical faults is imperative for power system resilience and national security to minimize impacts to defense critical infrastructure. The new protection schemes will improve grid stability during disturbances and allow additional integration of renewable energy technologies with low inertia and low fault currents. Signal - based fast tripping schemes w ere developed that use the physics of the grid and do not rely on communication to reduce cyber risks for safely removing faults. 

Rudy Montoya

Papers

A Survey of Traveling Wave Protection Schemes in Electric Power Systems

DC microgrid fault detection using multiresolution analysis of traveling waves

Shifting from Fossil Fuel Reliance to Green Energy Sovereignty: Ute Mountain Ute Tribe.

Signal-Based Fast Tripping Protection Schemes for Electric Power Distribution System Resilience.