Abstract:
A distribution network management system includes a power generation device including a renewable energy power generation source, and is connected to a distribution network through a first node; a first distributed device including a first distributed resource, connected to the distribution network through a second node, and configured to receive first node information and power generation information from the power generation device and attempt to control the first distributed resource so that an overvoltage for the first node is resolved; and a second distributed device including a second distributed resource, connected to the distribution network through a third node which is located farther away from the first node than the second node, and configured to, when the first node information and the power generation information are received from the first distributed device, attempt to control the second distributed resource so that the overvoltage for the first node is resolved.
Abstract:
The present provides an arc detection apparatus that includes: a current sensor configured to sense the first current that flows through the first line of a system in which the influence of noise according to the operation is detected in the first frequency band; a frequency data creator configured to digitally process sensed values of the first current in the first time period and the second time period, respectively, in order to thereby create the first frequency data and the second frequency data for the first frequency band; and an arc determination unit configured to determine the possibility of the generation of an arc of the system according to comparison data between the first frequency data and the second frequency data.
Abstract:
An embodiment of the present disclosure provides an arc risk management method comprising: pre-processing measurement values of currents flowing into an electric apparatus; estimating a level of arc energy in the electric apparatus by inputting the measurement values into one artificial intelligence network comprising a first layer including a dilated convolutional neural network and a second layer including a recurrent neural network; and indicating an arc risk to the electric apparatus in a quantitative way according to the level of arc energy.
Abstract:
An embodiment of the present disclosure provides an arc detection method, in which an apparatus detects arcs, comprising the steps of: obtaining time series data for measured values of an electric current flowing in a wire; calculating first statistical values indicating dispersion degrees with time of the measured values or dispersion degrees with time of variances of the measured values from the time series data; and determining that an arc occurs in the wire or that the possibility of arc occurrence in the wire is high in a case when at least one of the first statistical values is out of a predefined range.
Abstract:
An embodiment of the present disclosure provides an arc detection method, in which an apparatus detects arcs, comprising the steps of: obtaining time series data for measured values of an electric current flowing in a wire; calculating first statistical values indicating dispersion degrees with time of the measured values or dispersion degrees with time of variances of the measured values from the time series data; and determining that an arc occurs in the wire or that the possibility of arc occurrence in the wire is high in a case when at least one of the first statistical values is out of a predefined range.