A system includes a processor operatively coupled to memory. The processor performs operations that include obtaining electrical measurements of a power system. The processor determines a scaled energy value of a first set of the electrical measurements that are scaled with respect to a second set of electrical measurements. The processor determines that a potential ringdown event occurred by comparing the scaled energy value to a threshold energy value. The processor determines that the potential ringdown event is a confirmed ringdown event by comparing a scaled error value to a threshold error value. The processor generates one or more mode estimates from the confirmed ringdown event.

Methods for use in a measurement system. Some embodiments comprise at least one sensor unit and a control unit, wherein the at least one sensor unit is configured to detect a physical quantity and to form a sensor data signal. The method comprises, at the control unit, receiving a data receive signal from the sensor unit, and interpreting the data receive signal to be one of at least the sensor data signal and another data signal, wherein the interpreting is based on an attribute information intrinsic to the data receive signal. Furthermore, there is a sensor unit for use in measurement data acquisition, an apparatus configured to control a measurement data acquisition, a measurement system for use in measurement data acquisition, and a medium incorporating a sequence of operation steps that, when executed, perform a method for use in a measurement system for data acquisition.

Certain aspects and features include a system and method for monitoring the operational status of assets in an electric power distribution system. For example, an asset monitoring system identifies a zone of operation for an asset under evaluation. The asset monitoring application identifies meters connected to transformers in the zone of operation and obtains meter voltages for the meters over multiple intervals. The asset monitoring application determines a primary voltage for at least one transformer based on at least one meter voltage. The asset monitoring application uses the primary voltage in a power flow calculation to estimate an operational setting for the asset. The asset monitoring application compares the voltages from the power flow analysis using the estimated operational setting and the voltages from the meter voltages across multiple time intervals. Based on the comparison, the asset monitoring application determines an operational status of the asset.

A method of enhanced backward/forward sweep based power flow analysis is described. The method can include performing a backward sweep to determine first branch currents of a radial distribution network based on nodal voltages determined at a last iteration. The radial distribution network can include nodes and branches that are sequentially numbered and belong to different layers. A forward sweep is determined to determine first nodal voltages of the radial distribution network based on the first branch currents. Second branch currents of the radial distribution network are determined based on the first nodal voltages. The second branch current of the respective node is a sum of a nodal injection current of the respective node that is updated based on the first nodal voltage of the respective node, and if available, the first branch currents of branches emanating from the respective node.

Systems, methods, and devices are provided for controlling part of an electric power distribution system using an intelligent electronic device that may rely on communication from wireless electrical measurement devices. Wireless electrical measurement devices associated with different phases of power on an electric power distribution system may send wireless messages containing electrical measurements for respective phases to an intelligent electronic device. When wireless communication with one of the wireless electrical measurement devices becomes inconsistent or lost, the intelligent electronic device may synthesize the electrical measurements of the missing phase using electrical measurements of remaining phases. The intelligent electronic device may use the synthesized electrical measurements to control part of the electric power distribution system.

A diagnostic device includes electrical connectors, load, power supply, switching circuitry, sensors, and processor. The connectors include first and second sets of terminals for connecting to the conductors of a branch circuit in an upstream and downstream direction, respectively, at an outlet location along the circuit. The switching circuitry can isolate the upstream and downstream sections of the circuit from the outlet location, and selectively connect or disconnect the power supply or the load to the upstream or downstream section. The sensors measure electrical characteristics on the conductors of the circuit to monitor load currents, such as on power, neutral and ground lines, of the upstream and downstream circuit sections. The processor controls the switching circuitry, and obtains diagnostic information corresponding to the monitored load currents on the upstream and downstream sections of the branch circuit, from the measurements performed by the sensors.

A method and a system for dispatching an independent energy storage power station is provided. The method includes: determining the current typical secondary frequency regulation scenario according to the predicted AGC frequency regulation instruction for the next stage; dispatching, for the continuous upward adjustment response scenario, the independent energy storage power station to participate in the upward adjustment response according to the data required for the continuous upward adjustment; dispatching, for the continuous downward adjustment response scenario, the independent energy storage power station to participate in the downward adjustment response according to the data required for the continuous downward adjustment; and preferably, for the upward and downward adjustment fluctuation response scenario, dispatching the independent energy storage power station to participate in the upward and downward adjustment fluctuation response according to the data required for the upward and downward adjustment.

Various examples are directed to a solar power electrolyzer system comprising a first electrolyzer stack, a second electrolyzer stack, a first converter and a first converter controller. The first electrolyzer stack may be electrically coupled in series with a photovoltaic array. The first converter may be electrically coupled in series with the first electrolyzer stack and electrically coupled in series with the photovoltaic array. The second electrolyzer stack electrically may be coupled at an output of the first converter. The first converter controller may be configured to control a current gain of the first converter.

To ensure safety of people needing to service a low-voltage network of an electric power distribution system, dwellings being connected to this network may include autonomous units for producing electricity, thus generating voltage and endangering the people servicing the work. Data are obtained from consumption records from the meter of each dwelling, in regular time intervals, and meteorological data are also obtained in the geographical area of these dwellings, in order to identify at least some weather conditions conducive to the production of energy by autonomous units. A model is then applied for detecting, based on the first and second data, a coincidence between periods of lower consumption measured by a meter and weather conditions conducive to electricity production by autonomous units during these periods. Therefore, information on the presence of autonomous units in the dwelling can be deduced and given to people before their servicing.

A Multi-Phase Simulation Environment (“MPSE”) is provided which simulates the conductor current and voltage or electric field of multiple phases of an electrical power distribution network to one or more sensing or measuring devices and includes independent control of wireless network connectivity for each sensing or measuring device, independent control of GPS RF to each device, and interface to a back-end analytics and management system.