This document describes systems and techniques for evaluating and improving distribution-grid observability. These systems and techniques allow engineers to quantify the observability of a distribution grid, which represents an ability to combine actual measurements and various types of computations (e.g., analytics, estimators, forecasters), from a system model. Distribution engineers can also identify islands of observability where operating parameters, including voltages, currents, and power flows, can be determined from available sensor readings. By exclusion, distribution engineers can similarly identify areas of the distribution grid with observability deficiencies that may require additional instrumentation to maintain proper operation. Distribution engineers, using an iterative or automated process, can determine the observability of the system model with new or relocated sensors to generate a sensor allocation plan. The sensor allocation plan can indicate the number and location of sensors to either maximize observability for a fixed sensor cost or minimize sensor cost for predetermined observability.

A transformer area identification method determines a corresponding electric meter mounting relationship by identifying a power jump characteristic based on a power statistic of each node in a power supply network of a transformer area, thereby eliminating the influence of line loss power and increasing identification accuracy. In addition, the identification is performed based on change characteristics of unidentified total power and power of an electric meter in a to-be-identified domain, to reduce interference of a power fluctuation of an identified electric meter to the identification and increase the identification accuracy. Moreover, iterative identification is used, so that the to-be-identified domain is smaller and a convergence speed is faster. The transformer area identification method uses a power jump algorithm to identify the transformer area, thereby eliminating the influence of the line loss power and increasing the identification accuracy.

An electric energy meter includes a plurality of first terminals for receiving a measure of current of each of one or more phases of power and a plurality of second terminals for receiving a measure of voltage of each of one or more phases of power. A controller is configured to analyze the measure of current and the measure of voltage of each of the one or more phases of power in order to detect power quality issues in one or more of the one or more phases of power. For each of the detected power quality issues, the controller is configured to determine whether the detected power quality issue is caused by a utility generating the power or a consumer consuming the power and to communicate a message indicating the detected power quality issues via a communications port operably coupled to the controller.

An intelligent electronic device IED has enhanced power quality and communications capabilities. The IED can perform energy analysis by waveform capture, detect transient on the front-end voltage input channels and provide revenue measurements. The IED splits and distributes the front-end input channels into separate circuits for scaling and processing by dedicated processors for specific applications by the IED. Front-end voltage input channels are split and distributed into separate circuits for transient detection, waveform capture analysis and revenue measurement, respectively. Front-end current channels are split and distributed into separate circuits for waveform capture analysis and revenue measurement, respectively.

An intelligent electronic device IED has enhanced power quality and communications capabilities. The IED can perform energy analysis by waveform capture, detect transient on the front-end voltage input channels and provide revenue measurements. The IED splits and distributes the front-end input channels into separate circuits for scaling and processing by dedicated processors for specific applications by the IED. Front-end voltage input channels are split and distributed into separate circuits for transient detection, waveform capture analysis and revenue measurement, respectively. Front-end current channels are split and distributed into separate circuits for waveform capture analysis and revenue measurement, respectively.

An intelligent electronic device (IED) has enhanced power quality and communications capabilities. The power meter can perform energy analysis by waveform capture, detect transient on the front end voltage input channels and provide revenue measurements. The power meter splits and distributes the front end input channels into separate circuits for scaling and processing by dedicated processors for specific applications by the power meter. Front end voltage input channels are split and distributed into separate circuits for transient detection, waveform capture analysis and revenue measurement, respectively. Front end current channels are split and distributed into separate circuits for waveform capture analysis and revenue measurement, respectively.

An intelligent electronic device (IED) has enhanced power quality and communications capabilities. The power meter can perform energy analysis by waveform capture, detect transient on the front end voltage input channels and provide revenue measurements. The power meter splits and distributes the front end input channels into separate circuits for scaling and processing by dedicated processors for specific applications by the power meter. Front end voltage input channels are split and distributed into separate circuits for transient detection, waveform capture analysis and revenue measurement, respectively. Front end current channels are split and distributed into separate circuits for waveform capture analysis and revenue measurement, respectively.

The present invention relates to a device and a method for measurement of electrical signals in an industrial automation and control system. The device comprises an input circuit, configured to receive an electrical input signal (100), scale the electrical input signal by a scaling factor and to set the scaling factor according to a scaling signal (110), an Analog-to-Digital Converter, ADC (220), which is electrically connected to the input circuit, wherein the ADC is configured to convert the scaled electrical input signal (103) into an intermediate digital signal (120), and a first signal path (211), connected to an digital end of the ADC, configured to create the scaling signal (110) and to send the scaling signal (110) to the input circuit, wherein, based on the intermediate digital signal of a sample period and the scaling factor of the sample period, the scaling factor for a subsequent sample period is set.

The present invention relates to a device and a method for measurement of electrical signals in an industrial automation and control system. The device comprises an input circuit, configured to receive an electrical input signal (100), scale the electrical input signal by a scaling factor and to set the scaling factor according to a scaling signal (110), an Analog-to-Digital Converter, ADC (220), which is electrically connected to the input circuit, wherein the ADC is configured to convert the scaled electrical input signal (103) into an intermediate digital signal (120), and a first signal path (211), connected to an digital end of the ADC, configured to create the scaling signal (110) and to send the scaling signal (110) to the input circuit, wherein, based on the intermediate digital signal of a sample period and the scaling factor of the sample period, the scaling factor for a subsequent sample period is set.

Provided is a missing data correction method and apparatus, and more particularly, a missing data correction method that estimates missing power and energy from an electricity meter in consideration of a case in which power data and energy data collected from the electricity meter are missing and generates continuous power data according to the estimated power and energy.