A vehicle-grid integration management system determines use of a power grid by an electric vehicle in a dual multi-part rate structure including a grid account portion associated with a relationship between the electric vehicle and the power grid, a group account portion associated with a relationship between the vehicle group and the electric vehicle and/or the power grid, a consumption portion associated with a volume of electricity drawn from the power grid by the electric vehicle over a time period, a supply portion associated with a volume of electricity delivered to the power grid by the electric vehicle over the time period, a demand portion associated with an upper threshold of electricity drawn from the power grid by the electric vehicle over the time period, and a capacity portion associated with an upper threshold of electricity delivered to the power grid by the electric vehicle over the time period.

A system for autonomously validating the topology information of an electrical power distribution system is provided. For example, the system includes a group of meters previously determined to be connected to the same transformer of an electrical power distribution system. The group of meters is configured to perform family check periodically or upon request and to identify orphan meters in the group. The identified orphan meter can contact a community device communicatively connected to meters in more than one group to request a community check. The community device performs the community check by contacting meters in other groups of meters and obtain their family signature data. The community device further determines whether the orphan meter belongs to a new family based on the voltage data of the orphan meter and the family signature data of other groups. The orphan meter can report the community check results to a headend system.

A power management system including a management apparatus configured to assign divided computation processing constituting at least a part of predetermined computation processing to a distributed computing device placed in a facility, wherein the management apparatus includes a receiver configured to receive a message including an information element indicating executability of computation processing by the distributed computing device, and a controller configured to perform assignment processing configured to assign the divided computation processing to the distributed computing device based on the executability of the computation processing.

Provided is a power management apparatus for controlling power distribution from a location that includes a storage battery and a current control type converter to another location that includes a storage battery, the power management apparatus including: a monitor unit that acquires a status of the storage battery at each location; a judgment unit that determines, based on the status of the storage battery at each location that has been acquired by the monitor unit, a duration of power distribution to a certain location, and one or more locations from which power is to be distributed to the certain location; and a control unit that controls each location serving as a distribution source such that power distribution is performed for the duration determined by the judgment unit.

A method for determining whether a power system is encountering a malicious attack is provided. The method comprises: receiving a plurality of first phasor measurement unit (PMU) measurements from a plurality of PMUs of the power system; determining a plurality of expected PMU measurements associated with a future time period based on an optimization algorithm that uses differences between a plurality of consecutive predictive entries and the plurality of first PMU measurements; receiving, from the plurality of PMUs, a plurality of second PMU measurements associated with the future time period; determining whether the power system is encountering the malicious attack based on comparing the plurality of expected PMU measurements with the plurality of second PMU measurements; and executing an action based on whether the power system is encountering the malicious attack.

Methods, computer systems, and apparatus, including computer programs encoded on computer storage media, for training a machine-learning model for predicting event tags. The system obtains asset data for an electric power distribution system in a geographic area. The asset data includes: for each of a plurality of electrical assets of the electrical power distribution system, data indicating one or more characteristics of the electrical asset. The system further obtains sensor data for the electric power distribution system. The sensor data includes measurement data from a plurality of electric sensors. The system generates, by processing the asset data and the sensor data, partition data that includes, for each of the plurality of electrical assets, an assignment that assigns the electrical asset to one of a set of feeder networks.

A method for predicting the operation state of a power distribution network based on scene analysis is provided, comprising the following steps of step 10) obtaining the network structure and historical operation information of a power distribution system; step 20) extracting representative scene sequence fragments of output of the DGs according to historical output sequences of the DGs; step 30) obtaining a multi-scene prediction result of a future single-time section T.sub.0 through matching the historical similar scenes; step 40) establishing a future multi-time section operation scene tree; and step 50) deeply traversing all scenes in the future multi-time section operation scene tree, performing power distribution network load flow analysis for each scene, calculating the line current out-of-limit risk and the busbar voltage out-of-limit risk of the power distribution network, and obtaining a future operation state variation tendency of the power distribution network with the DGs.

Examples relate to adjusting load power consumption based on a power option agreement. A computing system may receive power option data that is based on a power option agreement and specify minimum power thresholds associated with time intervals. The computing system may determine a performance strategy for a load (e.g., set of computing systems) based on a combination of the power option data and one or more monitored conditions. The performance strategy may specify a power consumption target for the load for each time interval such that each power consumption target is equal to or greater than the minimum power threshold associated with each time interval. The computing system may provide instructions the set of computing systems to perform one or more computational operations based on the performance strategy.

An industrial process field device includes first and second loop terminals configured to couple to a two-wire process control loop. Device circuitry is powered from the process control loop and monitors a process variable or controls a control device. A current regulator is in series with the loop terminals, and regulates a loop current. A first shunt voltage regulator regulates a voltage across the device circuitry. Supplemental circuitry is connected in series with the first shunt voltage regulator and the second loop terminal, and is powered by power from the two-wire process control loop shunted through the first shunt voltage regulator. A second shunt voltage regulator is connected in series with the first shunt voltage regulator and the second loop terminal, and in parallel with the supplemental circuitry, and regulates a voltage across the supplemental circuitry.

A method for reducing and/or managing energy-related stress in an electrical system includes processing electrical measurement data from or derived from energy-related signals captured by at least one intelligent electronic device (IED) in the electrical system to identify and track at least one energy-related transient in the electrical system. An impact of the at least one energy-related transient on equipment in the electrical system is quantified, and one or more transient-related alarms are generated in response to the impact of the at least one energy-related transient being near, within or above a predetermined range of the stress tolerance of the equipment. The transient-related alarms are prioritized based in part on at least one of the stress tolerance of the equipment, the stress associated with one or more transient events, and accumulated energy-related stress on the equipment. One or more actions are taken in the electrical system in response to the transient-related alarms to reduce energy-related stress on the equipment in the electrical system.