A method for detecting non-technical losses in an electrical power system includes measuring an area under a squared RMS current curve for a power cable in the electrical power system over at least one time interval, measuring an active and a reactive energy for the power cable over the at least one time interval, and characterizing a cable reactance and a cable resistance using the active energy, the reactive energy, and the area under the squared RMS current curve. The method further includes determining an active energy loss and a reactive energy loss over the at least one time interval using the area under the squared RMS current curve and the reactance and the resistance of the cable, and detecting a non-technical loss in the electrical power system based on the active energy loss and the reactive energy loss over the at least one time interval.

This disclosure relates to a method and apparatuses for detecting and reporting suspected tampering of an energy meter to a utility. The method and apparatus uses a plurality of sensors to obtain data relating to one or more input parameters based on the type of input signal. The input parameters are mapped with a tamper type to provide a classification of one or more output parameters. The output parameters are compared to one or more operating conditions of the energy meter to identify one or more suspected tampers. Any suspected tampers are reported to the utility.

Analysis of smart meter and/or similar data based on frequency content is disclosed. In various embodiments, for each of a plurality of resource consumption nodes a time series data including for each of a series of observation times a corresponding resource consumption data associated with that observation time is received. At least a portion of the time series data, for each of at least a subset of the plurality of resource consumption nodes, is transformed into a frequency domain. A feature set based at least in part on the resource consumption data as transformed into the frequency domain is used to detect that resource consumption data associated with a particular resource consumption node is anomalous.

An anti-tamper device for a utility meter, in particular for an enclosure thereof, providing a guideway for a sealing element, wherein in a sealed state of the utility meter, at least a section of the sealing element extends along the guideway. Furthermore, an enclosure for a utility meter comprising a socket configured for receiving an anti-tamper device, as well as a utility meter comprising an anti-tamper device, and/or an enclosure. The guideway is provided with a predetermined breaking zone configured to break when the sealing element exerts a predefined breaking force onto the anti-tamper device.

An abnormal electricity use method is disclosed. An embodiment includes: classifying a transformer into a public transformer or a dedicated transformer, the public transformer corresponding to a plurality of first users; the dedicated transformer corresponding to one second user; recognizing a first abnormal user from the first users based upon the smart meter reading of the public transformer and the smart meter reading of the first user; or recognizing the first abnormal user from the first users based upon the smart meter reading of the first user; and recognizing a second abnormal user from the second user based upon the smart meter reading of the second user or the smart meter reading of the dedicated transformer. Respective personalized anomaly recognition policies are used for the public transformer having a plurality of first users and the dedicated transformer having only one second user, to improve the recognition accuracy and speed.

Various embodiments relate to detecting loss of electrical energy. A method of detecting loss of electrical energy may include determining, for a number of time samples, a neutral current and an imputed neutral current of an electrical energy metering system. Further, the method may include determining, for each of the number of time samples, a squared difference between the neutral current and the imputed neutral current. The method may further include detecting, based on the squared difference, loss of electrical energy from the electrical energy metering system.

A meter case used with a utility meter is disclosed. The meter shell includes a plurality of snap fit joints assembled on the meter case arranged to engage a module cover to mount the module cover to the meter shell. The module cover further includes wire housing formed along an inner periphery of the module cover that houses a wire having a first end and a second end therein. A metal shield placed behind the meter shell is electrically coupled to a first connector. A terminal electrically connected to the metal shield is arranged to discharge current to ground. An electrical contact electrically coupled to the second end of the wire is arranged to engage the first connector to establish an electrical connection to the metal shield for the discharge to ground of electrostatic currents sensed by wire.

An electricity meter comprising an electrically-controlled electromechanical switch is disclosed. The electromechanical switch comprises a rotary actuator comprising a generally-cylindrical permanent magnet rotor having a central axis, a stator comprising a closed stator core and first and second opposite stator poles inwardly-projecting from the closed stator core towards the rotor and first and second coils wound around the first and second stator poles respectively. The electromechanical switch comprises a switch comprising at least one pair of first and second contacts wherein the first contact is movable. The electromechanical switch comprises mechanical linkage between the rotary actuator and the movable contact(s) configured such that rotation of the rotor from a first angular position to a second angular position causes the switch to be opened, and rotation from the second angular position to the first angular position causes the switch to be closed.

A method of detecting conditions indicative of energy meter tampering, meter faults or energy loss (e.g. due to energy theft) is disclosed. The method includes receiving energy consumption data from an energy meter indicating consumption of energy at a location served by the energy meter. Event data is also received from the meter comprising one or more events generated by the energy meter. The consumption data is analysed to detect a predetermined consumption condition. The event data is analysed to detect a predetermined event or event pattern in the event data. An alert condition is generated in response to detecting both the consumption condition and the event or event pattern.

A centralising meter is connected to a data concentrator via a first powerline communication network and to remote basic meters via a second powerline communication network. The centralising meter emulates a smart electricity meter application with respect to the data concentrator for each remote basic meter, in order in particular to construct a corresponding load curve. When the ratio of an energy consumption declared by all the remote basic meters to an energy consumption measured by the centralising meter is below a predefined threshold and when furthermore a plurality of load curves show a drop to zero, a fraud is detected. The centralising meter compares total energy consumptions estimated from extrapolations of certain load curves with the measured energy consumption, to identify which remote basic meter is subject to the fraud.