Determining optimum location and number of automatic switching devices in distribution systems

2003 ◽  
Author(s):  
Ying He ◽  
G. Andersson ◽  
R.N. Allan
Keyword(s):  
Distribution Systems ◽  
Optimum Location ◽  
Automatic Switching ◽  
Switching Devices

THE ERROR MINIMIZATION OF DIGITAL FOURIER FILTER USED IN UNIPROCESSOR PROTECTIVE RELAYING FOR 6–33 kV ELECTRICAL NETWORKS

2005 ◽  
Vol 14 (05) ◽  
pp. 953-963
Author(s):  
ABDULLAH I. AL-ODIENAT ◽  
OMAR Y. RADAIDEH
Keyword(s):  
New Method ◽  
Error Minimization ◽  
Electrical Networks ◽  
Protective Relaying ◽  
Oscillatory Frequency ◽  
Software Structure ◽  
Functional Features ◽  
Automatic Switching ◽  
Switching Devices

In this paper, a new method for error minimization of digital Fourier filter is proposed. The proposed method is tested by operating the electrical networks at oscillatory frequency. The functional features of microprocessor protective relaying and automatic switching devices are considered. The software structure of uniprocessor protective relaying and automatic switching equipments for the 6–33 kV lines are also presented.

Identification of Faulted Feeder Section in Distribution Systems Using Overcurrent Information from Switching Devices

2014 ◽  
Vol 15 (2) ◽  
pp. 171-176 ◽  
Author(s):  
Yuan Liao
Keyword(s):  
Case Studies ◽  
Network Structure ◽  
Multiple Solutions ◽  
Distribution Systems ◽  
Essential Role ◽  
Single Fault ◽  
Switching Devices

Abstract Promptly locating faults in distribution systems plays an essential role in restoring services. Presence of laterals may lead to multiple solutions by impedance-based method. One possible way for quickly identifying the faulted feeder section is to utilize the overcurrent information provided by the switching devices installed in the system. This article presents an enhanced method that identifies the faulted feeder section based on the information from switching devices and the network structure. The proposed method is general, applicable to presence of a single-fault or multi-faults, and suitable for single- or multi-source networks. The advantages over existing methods are elimination of iterative steps for multi-source systems. Case studies have demonstrated that the method is effective in identifying the faulted section.

scholarly journals Topology identification in distribution system via machine learning algorithms

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252436
Author(s):  
Peyman Razmi ◽  
Mahdi Ghaemi Asl ◽  
Giorgio Canarella ◽  
Afsaneh Sadat Emami
Keyword(s):  
Machine Learning ◽  
Distribution System ◽  
Distribution Systems ◽  
Learning Algorithms ◽  
Distribution Networks ◽  
Machine Learning Algorithms ◽  
Supervised Machine Learning ◽  
Voltage Profile ◽  
Topology Identification ◽  
Switching Devices

This paper contributes to the literature on topology identification (TI) in distribution networks and, in particular, on change detection in switching devices’ status. The lack of measurements in distribution networks compared to transmission networks is a notable challenge. In this paper, we propose an approach to topology identification (TI) of distribution systems based on supervised machine learning (SML) algorithms. This methodology is capable of analyzing the feeder’s voltage profile without requiring the utilization of sensors or any other extraneous measurement device. We show that machine learning algorithms can track the voltage profile’s behavior in each feeder, detect the status of switching devices, identify the distribution system’s typologies, reveal the kind of loads connected or disconnected in the system, and estimate their values. Results are demonstrated under the implementation of the ANSI case study.

scholarly journals Investigation on GaN HEMTs Based Three-Phase STATCOM with Hybrid Control Scheme

Micromachines ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 464
Author(s):  
Chao-Tsung Ma ◽  
Zhen-Huang Gu
Keyword(s):  
Neural Network ◽  
Power Generation ◽  
Distribution Systems ◽  
Reactive Power ◽  
Hybrid Control ◽  
Three Phase ◽  
Control Scheme ◽  
Gan Hemts ◽  
Hybrid Control Scheme ◽  
Switching Devices

The modern trend of decarbonization has encouraged intensive research on renewable energy (RE)-based distributed power generation (DG) and smart grid, where advanced electronic power interfaces are necessary for connecting the generator with power grids and various electrical systems. On the other hand, modern technologies such as Industry 4.0 and electrical vehicles (EV) have higher requirements for power converters than that of conventional applications. Consequently, the enhancement of power interfaces will play an important role in the future power generation and distribution systems as well as various industrial applications. It has been discovered that wide-bandgap (WBG) switching devices such as gallium nitride (GaN) high electron mobility transistors (HEMTs) and silicon carbide (SiC) metal-oxide-semiconductor field-effect transistors (MOSFETs) offer considerable potential for outperforming conventional silicon (Si) switching devices in terms of breakdown voltage, high temperature capability, switching speed, and conduction losses. This paper investigates the performance of a 2kVA three-phase static synchronous compensator (STATCOM) based on a GaN HEMTs-based voltage-source inverter (VSI) and a neural network-based hybrid control scheme. The proportional-integral (PI) controllers along with a radial basis function neural network (RBFNN) controller for fast reactive power control are designed in synchronous reference frame (SRF). Both simulation and hardware implementation are conducted. Results confirm that the proposed RBFNN assisted hybrid control scheme yields excellent dynamic performance in terms of various reactive power tracking control of the GaN HEMTs-based three-phase STATCOM system.

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