Transient wavelet energy-based protection in microgrid power system

Micro-grids comprise Distributed Energy Resources (DER’s) with low voltage distribution networks having controllable loads those can operate with different voltage levels are connected to the micro-grid and operated in grid mode or islanding mode in a coordinated way of control. DER’s provides clear environment-economical benefits for society and consumer utilities. But their development poses great technical challenges mainly protection of main and micro grid. Protection scheme must have to respond to both the main grid and micro-grid faults. If the fault is occurs on main grid, the response must isolate the DER’s from the main grid rapidly to protect the system loads. If the fault ocuurs within the micro-grid, the protection scheme must coordinate and isolates the least priority possible part of the grid to eliminate the fault. In order to deal with the bidirectional energy flow due to large numbers of micro sources new protection schemes are required. The system is simulated using MATLAB Wavelet Tool box and Wavelet based Multi-resolution Analysis is considered. Wavelet based Multi-resolution Analysis is used for detection, discrimination and location of faults on transmission network. This paper is discussed a transient current based micro-grid connected power system protection scheme using Wavelet Approach described on wavelet detailed-coefficients of Mother Biorthogonal 1.5 wavelet. The proposed algorithm is tested in micro-grid connected power systems environment and proved for the detection, discrimination and location of faults which is almost independent of fault impedance, fault inception angle (FIA) and fault distance of feeder line.

Distribution system plays an important role in supplying consumers with electric energy. Due to their structural complexity, these systems have always had difficulties in locating faults for faster restoration. Restoration in distribution systems includes these steps: Fault Location, Isolation, and Service Restoration (FLISR) using manual and automatic switches, which is essential to reduce interruption duration thus to improve system reliability. Therefore, one of the first and the most important steps of reliability improvement is timely locating the fault, thus reinforcing the restoration (FLISR) process. In this article, a fault detection and location method is proposed, using frequency spectrum analysis by Discrete Orthogonal Stockwell Transform (DOST) to extract fault characteristics from the fault current waveform at a certain place of measurement, followed by fault location estimation by regression ANNs. The proposed method first identifies all the possible fault locations using DOST coefficients. Then, the actual fault location is estimated, using the knowledge from distribution system status. The proposed method is tested on IEEE 16-bus distribution test system, revealing that the method is capable to locate various fault types, in a fast and accurate manner, and easily implementable. The effect of the following parameters on the accuracy of the proposed method is analytically discussed: fault location distance from the main bus, faults type, fault inception angle, fault resistance and load variation, where the first four parameters negligibly affect, while the last two might significantly affect the accuracy.

The main objective of utility companies is continuous power supply which motivates them for the quick detection and location of faults occurring in a power system. Fault analysis of different fault condition is a difficult task in a Hybrid power system. The wavelet transform is used for the detection and location of fault taking place in a hybrid power system. For proper fault analysis, exact location of the fault distance from the source and type of fault information is very much essential. The proposed model used in this paper is a hybrid combination of wind energy and photovoltaic generation system. For detecting the fault voltage signals are extracted and passed through wavelet transform. Detailed information about the faulted signal is received. The wavelet transform has the special property of time-frequency resolution, from which we can detect the fault. In this paper wavelet transform (WT) is used for determining the location and detection of fault. For clearing the fault in less time detection and location of fault are two important tasks for a power engineer. All the signals are analyzed using the wavelet transform toolbox after selecting the suitable wavelet level. From the analyzed signal the pre fault and post fault coefficients are derived. The fault detection and location study are simulated in MATLAB/Simulink for a typical power system.

A fault detection and location algorithm on three-terminal transmission line is proposed. Vast literature on fault location shows that to simplify the analysis, line charging currents are often ignored. To improve the accuracy of fault location, synchronized current and voltage measurements from three ends of the three-terminal line are utilized to detect and locate distance to fault while considering the line charging currents. The method first detects the zone at which the fault has occurred and then locates it from the respective line ends. Since three-terminal lines provide solutions for connecting existing system to the grid, facilitating bulk transfer of power, thus the fault detection and location on the same is important to maintain reliability and security of the system. Performance of the proposed algorithm is tested for various fault types, fault locations, fault resistances and fault inception angles. The 200-kV system is simulated in ATP/EMTP; however, the algorithm is developed in MATLAB. The extensive simulation studies demonstrate accuracy of the proposed scheme.

Modern electric supply systems are invariably three phase. The design of transmission and distribution networks is such that normal operations reasonably close to the balanced three phase working conditions to give a complete analysis. A compound generation is a segment of power system in which number of sources commonly attached to a power electronic converter and loads are associated to operate independently. The protection of multi terminal transmission lines is a challenging task due to possible in feed or out feed currents contributed from the tapped lines. The protection scheme is crucial against faults based on traditional over current protection since there are adequate problems due to fault currents in the mode of operation. This paper proposes a novel approach for detection, discrimination of the faults and a control paradigm for four terminal transmission line protection, in presence of PV and wind sources. It deals about transient current based protection scheme for SVC compensated multi terminal transmission system with discrete wavelet transform. Fault indices of all phase currents at all terminals are obtained by analyzing the detail coefficients of current signals using bior 1.5 mother wavelet. This method is analyzed for different types of faults and is found effective for detection and discrimination of fault with various fault inception angle and fault impedance.

A single ended directional fault section identifier and fault locator for double circuit transmission lines using combined wavelet and ANN approach

Faults in the power system affect the reliability, safety, and stability. Power-distribution systems are familiar with the different faults that can damage the overall performance of the entire system, from which they need to be effectively cleared. Underground power systems are more complex and require extra accuracy in fault detection and location for optimum fault management. Slow processing and the unavailability of a protection zone for relay coordination are concerns in fault detection and location, as these reduce the performance of power-protection systems. In this regard, this article proposes an optimized solution for a fault detection and location framework for underground cables based on a discrete wavelet transform (DWT). The proposed model supports area detection, the identification of faulty sections, and fault location. To overcome the abovementioned facts, we optimize the relay coordination for the overcurrent and timing relays. The proposed protection zone has two sequential stages for the current and time at which it optimizes the current and time settings of the connected relays through Newton–Raphson analysis (NRA). Moreover, the traveling times for the DWT are modeled, which relate to the protection zone provided by the relay coordination, and the faulty line that is identified as the relay protection is not overlapped. The model was tested for 132 kV/11 kV and 16-node networks for underground cables, and the obtained results show that the proposed model can detect and locate the cable’s faults speedily, as it detects the fault in 0.01 s, and at the accurate location. MATLAB/Simulink (DigSILENT Toolbox) is used to establish the underground network for fault location and detection.

This paper presents a wavelet based protection scheme for a multi terminal transmission system in presence of SVC. Increase in the power transfer capability and the efficient utilization of available transmission lines, improving power system stability and controllability have made strides and created Flexible AC Transmission (FACTS). These FACTS devices have adverse effects on distance protection. Severe under reaching is the most important problem of relay which is caused by current injection at the point of connection to the system. This work presents a efficient method based on wavelet transform. A wavelet based multi resolution analysis is used to find the detailed coefficients of the signals which are utilized to calculate fault index. These fault indexes are compared with the threshold value to detect and classify faults on transmission system. The proposed algorithm is proved for the detection, classification and location of faults on Transmission lines which is almost independent of fault impedance, fault inception angle, fault distance of transmission line and location of SVC.

Components of electrical power systems are susceptible to failures caused by lightning strikes, aging or human errors. These faults can cause equipment damage, affect system reliability, and results in expensive repair costs. As electric power systems are becoming more complex, traditional protection methods face limitations and shortcomings. The evolution of the traditional power system to the smart grid (SG) has changed the way to operate and protect power systems. The development of SGs calls for advanced fault diagnosis techniques to prevent undesired interruptions and expenses. Faults in power systems can occur at anytime and anywhere, can be caused by a natural disaster or an accident, and their occurrence can be hardly predicted or avoided; therefore, it is crucial to accurately estimate the fault location and quickly restore service. The development of methods capable of accurately detecting, locating and removing faults is essential (i.e. fast isolation of faults is necessary to maintain the system stability at transmission levels; accurate and fast detection and location of faults are essential for increasing reliability and customer satisfaction at distribution levels). This has motivated the development of new and more efficient methods. Methods developed to detect and locate faults in power systems can be divided into two categories, conventional and artificial intelligence-based techniques. Although the utilization of artificial intelligence (AI) techniques offer tremendous potential, they are challenging and time consuming (i.e. many AI techniques require training data for processing). This paper presents a survey of the application of AI techniques to fault diagnosis (detection, classification and location of faults) of lines and cables of power systems at both transmission and distribution levels. The paper provides a short introduction to AI concepts, a brief summary of the application of AI techniques to power system analysis and design, and a discussion on AI-based fault diagnosis methods.

Fault location and distance protection in transmission lines are essential smart grid technologies ensuring reliability of the power system and achieve the continuity of service. The objective of this chapter is to presents an accurate algorithm for estimating fault location in Extra High Voltage (EHV) transmission lines using Artificial Neural Networks (ANNs) for high speed protection. The development of this algorithm is based on disturbed transmission line models. The proposed fault protection (fault detection/classification and location) uses only the three phase currents signals at the one end of the line. The proposed technique uses five ANNs networks and consists of two steps, including fault detection/classification and fault location. For fault detection/classification, one ANN network is used in order to identify the fault type; the fault detection/classification procedure uses the fundamental components of pre-fault and post-fault sequence samples of three phase currents and zero sequence current. For fault location, four ANNs networks are used in order to estimate the exact fault location in transmission line. Magnitudes of pre-fault and post-fault of three phase currents are used. The ANNs are trained with data under a wide variety of fault conditions and used for the fault classification and fault location on the transmission line. The proposed fault detection/classification and location approaches are tested under different fault conditions such as different fault locations, different fault resistances and different fault inception angles via digital simulation using MATLAB software in order to verify the performances of the proposed methods. The ANN-based fault classifier and locator gives high accuracy for all tests under different fault conditions. The simulations results show that the proposed scheme based on ANNs can be used for on-line fault protection in transmission line.

Investigate Advanced Techniques for Power System Protection, Fault Detection, and Restoration is a critical area of study aimed at enhancing the reliability and resilience of electrical grids. As modern power systems face increasing complexities due to the integration of renewable energy sources, aging infrastructure, and growing demand for electricity, innovative protection strategies have become essential to mitigate risks associated with electrical faults and disturbances. The significance of this topic lies not only in improving the operational efficiency of power systems but also in minimizing economic losses and ensuring public safety. Advanced techniques in power system protection encompass a range of methodologies, including the implementation of digital protective relays, circuit breakers, and sophisticated communication systems. These technologies enable real-time monitoring and rapid fault detection, which are vital for maintaining continuous power supply. The evolution of machine learning (ML) and artificial intelligence (AI) has further revolutionized this field by facilitating self-healing grids that can autonomously detect, diagnose, and restore service after outages, significantly reducing outage durations and enhancing reliability metrics such as the System Average Interruption Duration Index (SAIDI). Despite the advancements, challenges remain, particularly concerning cyber security risks, regulatory compliance, and the adaptation of protection schemes to accommodate fluctuating energy sources. These complexities necessitate ongoing research and development to create adaptive systems capable of responding to dynamic operational conditions while safeguarding infrastructure integrity. Moreover, the integration of emerging technologies must balance innovation with practical application, ensuring that protective measures not only meet current needs but also anticipate future demands within the energy sector. This investigation into advanced power system protection techniques is pivotal for addressing the pressing issues of system reliability and resilience in the face of evolving electrical grid dynamics. It highlights the critical role of technology in modernizing utility operations and lays the groundwork for future advancements in grid management and outage restoration strategies. Key Words: Power system protection, Fault detection, Distributed Energy Resources (DERs), Islanding, Grid reconnection, Fault localization, Microgrid protection, Fault current variability, System resilience

Although automation technology has a good application prospect in the field of power system, the current research on the role of automation technology on power system protection and control is relatively small. Accordingly, a research program on power system protection and control based on automation technology is developed. The main simulation and analysis software for this research is first determined, and the CNN-based power system fault identification algorithm and protection scheme are designed by combining the line multi-channel characteristics of the power system. It is found that the security and stability of the power system cannot be maintained for a long time only by relying on the protection scheme, and in response to this dilemma, the PLC-based fuzzy PID voltage controller is used to realize the intelligent control of the power system and monitoring of the equipment in the scope of automation technology. Finally, with the help of the above analysis tools, the scheme of this paper is verified and analyzed. The CNN-based power system fault identification algorithm performs well, with the values of 99.29%, 97.53%, and 98.39% for each performance index, and the protection scheme is able to quickly complete the repair within 20ms of the fault occurrence. In addition, the introduction of fuzzy PID controller power system control strategy, the quality of voltage output and equipment speed has a significant role in improving the power system to promote the development of power system in the direction of more efficient, safer and smarter.

Wide-area fault detection and location for cross-country and evolving faults have not been discussed before in the open literature. This paper presents an innovative wide-area backup protection scheme for untransposed transmission lines considering cross-country and evolving faults. Synchronized voltages and currents measurements in the phase domain are used for fault detection and location. The proposed scheme can distinguish transmission line faults from other external faults or different operating conditions. The faulty line is correctly identified, and the locations of all fault types including cross-country and evolving faults are estimated precisely. The proposed scheme is investigated under different fault locations, fault resistances, fault types, and fault inception angles. In addition, the influence of transmission line parameter errors and synchronization errors on the proposed scheme is investigated. Extensive simulation studies are applied to New England 39-bus test system, and the simulation results prove that the proposed scheme yields better performance for all simulated cases.

Resilience-oriented placement of multi-carrier microgrids in power systems with switchable transmission lines

Transmission system serves as a crucial link between generating stations and consumers. Early detection and accurate location of faults on a transmission line is essential to prevent the occurrence of blackouts. Also monitoring of real-time states of power system during faults will enhance the situational awareness for power system operators. Wide Area Measurement and Protection Systems (WAMPS) based on Phasor Measurement Unit (PMU) are a promising solution for dynamic real-time monitoring and protection of power system. This paper deals with detection and location of faults on a transmission system using PMU based technology. Performance of WAMPS is largely dependent on the performance of information and communication technologies infrastructure. At the application level, event-driven communication strategy is used in this paper for communicating the real-time data from PMU to the centralized controller. Also, linear state estimation based only on synchronized measurements for fault detection is presented. The estimated states of the system are compared to a certain threshold and if any abnormality is found, fault is detected and located. The proposed methodology is implemented on IEEE 9 bus system in MATLAB/Simulink.