Data Mining and Neural Networks Based Self-Adaptive Protection Strategies for Distribution Systems with DGs and FCLs

Tang, Wen; Yang, Hong-Tzer

doi:10.3390/en11020426

Cited by 20 publications

(10 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Proposed solution work properly in active system networks with many additional power sources and new devices like fault current limiters (FCLs) etc. since zero-sequence current flow is not affected by Dy transformers and YYn transformers, ungrounded at MV side [34,35]. Local energy sources could affect zero-sequence current flow if YNyn transformer is used [36,37].…”

Section: Methods Of Fault Localizationmentioning

confidence: 99%

Detection and Location of Earth Fault in MV Feeders Using Screen Earthing Current Measurements

Łowczowski

Lorenc

Zawodniak³

et al. 2020

Energies

View full text Add to dashboard Cite

The paper analyzes the utilization of cable screen currents for earth fault identification and location. Attention is paid on cable and mixed feeders—cable and overhead lines. The principle of operation is based on utilization of 3 criterion values: Ratio of cable screen earthing current and zero sequence cable core current—RF110/15, phase shift between cable screen earthing current and zero sequence cable core current—α and cable screen admittance defined as a ratio of cable screen earthing current and zero sequence voltage—Y0cs. Earth fault location is possible thanks to discovered relation between RF110/15 and α, whereas Y0cs allows for reliable detection of earth faults. Detection and identification are very important because it allows to increase the reliability of supply—reduce downtime and number of consumers affected by the fault. The article presents a phase to ground fault current flow for different power system configurations. At the end solution, which improves location capabilities is proposed. The solution is analyzed in PSCAD software and verified by network experiment.

show abstract

Section: Methods Of Fault Localizationmentioning

confidence: 99%

Detection and Location of Earth Fault in MV Feeders Using Screen Earthing Current Measurements

Łowczowski

Lorenc

Zawodniak³

et al. 2020

Energies

View full text Add to dashboard Cite

show abstract

“…Table 2 lists operating factors, with their respective levels, as proposed in the literature. This list does not exclude the existence of other factors [13,22,23,33]. The non-faulted operation factors were chosen to cover as much as possible of the range of normal operating scenarios of the microgrid.…”

Section: Step 1: Determining Factors and Levels For Normal And Faultementioning

confidence: 99%

“…The definition and selection of attributes is a critical process in the application of ML techniques. The features should be selected, seeking to maximize the amount of information that they capture from the database [13]. Additionally, if a lower number of attributes is employed, the dimensionality of the problem space is also reduced, which can improve the performance of ML techniques on a given dataset [39].…”

Section: Stage Ii: Input Data Adjustmentmentioning

confidence: 99%

“…Additionally, if a lower number of attributes is employed, the dimensionality of the problem space is also reduced, which can improve the performance of ML techniques on a given dataset [39]. Several attributes for FD approaches have been proposed in [13,[21][22][23]26,40]. In this work, the 49 attributes listed in Table 3 were used.…”

Section: Stage Ii: Input Data Adjustmentmentioning

confidence: 99%

“…These protection schemes can be classified into three classes: external protection, adaptive protection, and fault detection. The external protection (EP) approach uses additional equipment such as reactances, super-capacitors, or fault current limiters (FCL) for preventing misfiring of the protection devices [12][13][14]. However, these solutions lack flexibility and, therefore, are not suitable for microgrids, where topology changes and DER connection/disconnection is possible [15].…”

mentioning

confidence: 99%

See 2 more Smart Citations

Intelligent Fault Detection System for Microgrids

et al. 2020

View full text Add to dashboard Cite

The dynamic features of microgrid operation, such as on-grid/off-grid operation mode, the intermittency of distributed generators, and its dynamic topology due to its ability to reconfigure itself, cause misfiring of conventional protection schemes. To solve this issue, adaptive protection schemes that use robust communication systems have been proposed for the protection of microgrids. However, the cost of this solution is significantly high. This paper presented an intelligent fault detection (FD) system for microgrids on the basis of local measurements and machine learning (ML) techniques. This proposed FD system provided a smart level to intelligent electronic devices (IED) installed on the microgrid through the integration of ML models. This allowed each IED to autonomously determine if a fault occurred on the microgrid, eliminating the requirement of robust communication infrastructure between IEDs for microgrid protection. Additionally, the proposed system presented a methodology composed of four stages, which allowed its implementation in any microgrid. In addition, each stage provided important recommendations for the proper use of ML techniques on the protection problem. The proposed FD system was validated on the modified IEEE 13-nodes test feeder. This took into consideration typical features of microgrids such as the load imbalance, reconfiguration, and off-grid/on-grid operation modes. The results demonstrated the flexibility and simplicity of the FD system in determining the best accuracy performance among several ML models. The ease of design's implementation, formulation of parameters, and promising test results indicated the potential for real-life applications.Energies 2020, 13, 1223 2 of 21 as improved reliability, integration of renewable energies, reduction of network losses, and better voltage profile [7]. Nevertheless, microgrids present new challenges such as bidirectional power flow, considerable variations on fault currents levels, as well as power intermittency and quality issues, and additionally possible network reconfiguration, due to the presence of renewable energy sources [8]. Protection systems inside the distribution grid are particularly affected because they are based on the principle of overcurrent and unidirectional power flow [9]. Thus, traditional overcurrent protection schemes do not adequately protect microgrids [10].Several approaches have been proposed in the literature to deal with microgrid protection [11]. These protection schemes can be classified into three classes: external protection, adaptive protection, and fault detection. The external protection (EP) approach uses additional equipment such as reactances, super-capacitors, or fault current limiters (FCL) for preventing misfiring of the protection devices [12][13][14]. However, these solutions lack flexibility and, therefore, are not suitable for microgrids, where topology changes and DER connection/disconnection is possible [15]. The adaptive protection (AP) approach works online to dynamically modify protec...

show abstract

Data Mining and Analysis in Power and Energy Systems: An Introduction to Algorithms and Applications *

Lezama¹

2022

Intelligent Data Mining and Analysis in Power and Energy Systems

View full text Add to dashboard Cite

Data Mining and Neural Networks Based Self-Adaptive Protection Strategies for Distribution Systems with DGs and FCLs

Cited by 20 publications

References 23 publications

Detection and Location of Earth Fault in MV Feeders Using Screen Earthing Current Measurements

Detection and Location of Earth Fault in MV Feeders Using Screen Earthing Current Measurements

Intelligent Fault Detection System for Microgrids

Data Mining and Analysis in Power and Energy Systems: An Introduction to Algorithms and Applications *

Contact Info

Product

Resources

About