HK1244882B - Energy metering system and method for its calibration - Google Patents

Description

Energy metering system and calibration method thereof

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is related to the following related applications. Co-pending U.S. Application No. 14/586,710, filed on December 30, 2014 (Attorney Docket No. EBL-001), entitled “Energy metering system with self-powered sensors,” and co-pending U.S. Application No. 14/586,696, filed on December 30, 2014 (Attorney Docket No. EBL-002), entitled “Visualization of electrical loads,” disclose additional aspects of the inventive energy metering system disclosed herein. Application EBL-001 provides detailed information regarding powering the sensors of the sensor system. Application EBL-002 provides details regarding visualization of sensor data obtained by the metering system. The disclosures of these applications are incorporated herein by reference.

Technical Field

The present invention relates to an energy metering system for determining the electrical load of a distribution panel. In particular, the present invention relates to an energy metering system capable of determining the electrical load of each circuit. The present invention also relates to methods and apparatus for operating an energy metering system, and in particular to a method for calibrating an energy metering system capable of determining the electrical load of each circuit and a data aggregation apparatus.

Background Art

In conventional energy distribution networks, energy consumption at a site is typically measured at a central supply point, for example between the energy supplier's supply line and the first switchboard for a given site (e.g., a single building or a specific part of a building, such as an apartment, etc.). In this way, all electrical energy consumed at that specific site can be measured, regardless of the given site's electricity distribution system.

Conventional energy metering devices locally record the overall use of electrical energy. Such energy metering systems require regular readings by energy consumers, energy suppliers, or service companies. Recently, several countries have introduced so-called smart metering systems. In smart metering systems, smart metering devices transmit the amount of energy consumed at a specific location back to the utility provider, such as an energy supplier or service company. In some cases, the amount of energy consumed is reported only upon request, for example, for the preparation of utility bills. Other smart energy metering systems allow for more regular feedback of energy consumption data, such as daily or hourly.

Regularly reporting energy consumption to utility providers enables the implementation of new charging strategies. For example, if energy consumers avoid excessive energy consumption during high-demand periods and instead shift their energy consumption to low-demand periods such as nighttime, energy providers can reward energy consumers with lower prices.

While such systems are useful at a macro level, in many cases, energy metering systems that measure energy consumption at a single point across a relatively large site are insufficient for detailed analysis of energy consumption by individual users. For example, a user may detect that they are using a higher-than-average amount of energy at a particular time of day, but may not be able to detect where in the house or apartment that energy is being consumed.

To overcome this problem, devices have been developed that allow the electrical load of specific devices to be measured. Such devices can be fixedly installed at relevant points in the energy distribution network, or they can be provided as intermediary devices that are inserted between the wall socket and the device being tested. While these devices are useful in identifying electrical devices that cause particularly high electrical loads, their installation and use are relatively complex, resulting in high installation costs or limiting their use.

Against this background, the challenge of the present invention is to describe an energy metering system and an associated method of operation thereof that allows an energy consumer or utility provider to obtain a more detailed assessment of electrical energy consumption at a particular location. Preferably, the energy metering system should be easy to deploy and operate.

Summary of the Invention

According to one aspect of the present invention, an energy metering system for determining the electrical load of a distribution panel is provided. The energy metering system includes a plurality of sensors arranged near circuit breakers of the distribution panel, configured to sense magnetic fields in the region of the circuit breakers and provide corresponding sensor data. The system also includes a data processing system for converting the sensor data from the plurality of sensors into electrical load information for a plurality of circuits protected by the corresponding circuit breakers. Furthermore, the system includes a calibration unit electrically connected to one of the plurality of circuits and coupled to the data processing system, wherein the calibration unit is configured to determine at least a reference voltage and a reference current for the connected circuit. The data processing system is configured to calibrate the relationship between the sensor data and the load information based on the reference voltage and reference current determined by the calibration unit in a calibration mode of the energy metering system.

According to another aspect of the present invention, a method for calibrating an energy metering system is provided. The method includes the steps of determining a reference voltage and a reference current for a first circuit branching from a distribution panel; sensing a magnetic field in the region of at least a first circuit breaker configured to protect the first circuit and providing corresponding first sensor data. The method also includes determining first electrical load information for the first circuit based on the measured reference voltage and reference current; and determining calibration data representing a relationship between the provided first sensor data and the determined first electrical load information. In a normal operating mode of the energy metering system, second sensor data corresponding to the magnetic field in the region of a second circuit breaker is converted into second load information based on the determined calibration data. According to a third aspect, a data aggregation device for an energy metering system is provided. The device includes at least one bus connector for connecting a plurality of sensors arranged near circuit breakers of a distribution panel to the data aggregation device, the plurality of sensors being configured to sense the magnetic field in the region of the circuit breakers. The device also includes at least one plug connector for connecting the data aggregation device to the first circuit branching from the distribution panel; and a calibration unit electrically connected to the plug connector. The calibration unit includes circuitry for determining the reference voltage and reference current for the first circuit. The system also includes at least one interface for providing sensor data provided by a plurality of sensors and a reference current and a reference voltage determined by a calibration unit, so as to calibrate a relationship between the provided sensor data and power load information of a first circuit in a calibration mode of the energy metering system, and to convert the provided sensor data into power load information of a plurality of circuits protected by corresponding circuit breakers in a normal operating mode of the energy metering system.

The described systems, methods, and apparatus enable a deeper analysis of the electrical load at a particular location. Furthermore, the described systems are particularly easy to set up, even for consumers.

BRIEF DESCRIPTION OF THE DRAWINGS

Various embodiments of the present invention will be described with reference to the accompanying drawings. In the accompanying drawings, the same reference numerals are used for the same elements of different embodiments. The accompanying drawings include:

FIG1 shows a schematic diagram of an energy metering system according to an embodiment of the present invention;

FIG2 shows a schematic circuit diagram of an energy distribution system according to an embodiment of the present invention;

FIG3 shows a calibration unit of an energy metering system according to an embodiment of the present invention;

FIG4 shows another calibration unit of the energy metering system according to an embodiment of the present invention;

FIG5 shows a state diagram of an energy metering system according to an embodiment of the present invention;

FIG6 shows a flow chart of a method for operating an energy metering system in calibration mode; and

FIG7 shows a flow chart of an operation method of the energy metering system in a normal operating mode.

DETAILED DESCRIPTION

FIG1 shows a schematic diagram of an energy metering system 100 according to an embodiment of the present invention. Energy metering system 100 includes three subsystems: a sensor subsystem 110, a data acquisition subsystem 140, and a data analysis subsystem 170. In other embodiments, several of these subsystems may be omitted, combined, or divided into further subsystems. For example, analysis subsystem 170 may not be present at the customer's location but may instead be implemented by the utility provider as a cloud-based network service.

According to the described embodiment, the sensor subsystem 110 is mounted directly on a conventional switchboard 112 or in an enclosed fuse box. In the embodiment shown in FIG1 , the switchboard 112 includes two vertically arranged rows of circuit breakers 114. Of course, in other embodiments, the circuit breakers 114 may be arranged horizontally or in a different number of rows and columns. Each circuit breaker 114 is connected to the power supply within the switchboard 112 and is connected to one of several circuits in a specific location, such as an apartment or house. In the described embodiment, the circuit breaker bank 114 includes a main circuit breaker 114a, which protects the entire switchboard 112 and, thereby, all secondary circuit breakers 114 and the associated circuits connected to them. For example, a first secondary circuit breaker 114 may be connected to a first circuit that provides power to a bedroom wall outlet. A second secondary circuit breaker 114 may be connected to a second circuit that provides power to a kitchen wall outlet. The third secondary circuit breaker 114 may be connected directly to a specific high-power appliance, such as an oven, heater, or air conditioning system.

To obtain load information for each individual circuit, in the described embodiment, a sensor 120 is mounted on each of the circuit breakers 114, including the main circuit breaker 114a. Each sensor 120 is configured to sense the strength of a magnetic field in the region of the corresponding circuit breaker 114, such as the strength of a magnetic field emitted by a protective coil or other internal components of the circuit breaker 114. In particular, a single-chip synchronized three-axis digital magnetometer configured to determine the components of a magnetic field or magnetic flux in three different spatial directions can be employed. Such a sensor is known from application US2013/0229173A1 by Paul Bertrand, the contents of which are incorporated herein by reference and are therefore not described in detail here.

For ease of installation, several sensors 120 can be combined to form a sensor arrangement in the form of a sensor strip. Preferably, the individual sensors 120 in the sensor strip are spaced according to the standardized spacing of circuit breakers 114. To accommodate variations in the spacing of circuit breakers 114, a flexible strip can be used to connect the individual sensors 120. Alternatively, separate sensor arrangements can be used. The sensor strip can also include dummy sensors—devices with electrical connections and physical dimensions compatible with the aforementioned sensors 120. Such dummy sensors can be positioned between sensors 120 where circuit breakers 114 are not present. Furthermore, in the case of dual circuit breakers or circuit breakers connected in series on the switchboard 112, a single housing of the sensor arrangement can include two or more sensors 120.

In the described embodiment, each sensor device has an associated microcontroller for operating the sensor 120. This can include ensuring proper timing of each measurement with reference to an external clock signal. The microcontroller can also perform data pre-processing, such as digitizing analog measurements and rejecting clearly incorrect measurements. In the case of a sensor strip or sensor housing with more than one sensor 120, a single microcontroller can be shared by multiple sensors 120.

In the depicted embodiment, each sensor 120 includes a status indicator in the form of a light-emitting diode (LED). The LED can be controlled by a microcontroller to indicate the operating status of the sensor 120. Depending on the number of states to be indicated, single-color or multi-color LEDs can be used. As described below, the LED can also be used during the initial configuration of the energy metering system 100. Furthermore, the LED can be used for more advanced applications, as described in more detail in EBL-002.

In one embodiment, the sensor device is attached to each circuit breaker 114 by means of an adhesive strip or layer on the back of the housing of the sensor device. Other attachment means may be used, for example, a spring clip configured to clip onto a standardized housing of the circuit breaker 114, or a frame provided on the circuit breaker 114 that includes the sensor electronics and an area for providing individual markings or label information. This mechanical attachment means ensures consistent placement of the sensor 120 at a specific location on top of the circuit breaker 114 (e.g., corresponding to an emitting hotspot of the magnetic field). Accurate placement of the sensor 120 at a well-defined location improves the comparability of measurements obtained by different sensors 120.

The individual sensors 120 are connected via an internal bus system that is not visible in FIG1 . The bus system can be a parallel bus system having a plurality of parallel bus lines connected to each sensor in a row of sensors 120 . Alternatively, the bus system can also be configured as a daisy chain, i.e., data is forwarded from one sensor 120 to the next sensor 120 . In the described embodiment, the bus system combines two architectures. In particular, a first part of the bus, which includes power lines, data lines, and clock lines, is connected in parallel to all sensors 120 . This allows, among other things, the operation of all sensors 120 of the sensor subsystem 110 to be synchronized. The second part of the bus includes address lines for connecting all sensors 120 in a row of sensors in a daisy chain configuration, allowing each of the sensors 120 to be addressed sequentially.

At one end of each row of sensors 120, connecting cables 122 and 124 connect to the first sensor 120 in that row. In the depicted embodiment, connecting cables 122 and 124 connect to a junction box 126. As detailed above with respect to sensors 120, junction box 126 preferably attaches to switchboard 112 with the aid of tape, an adhesive layer, or a magnetic fastener, allowing junction box 126 to be attached without opening switchboard 112 and requiring no specialized tools. In another embodiment, the last sensor 120 in a first row of sensors 120 can be directly connected to the first sensor 120 in another row of sensors 120, such that all sensors 120 form a single chain of sensors 120.

The sensor subsystem 110 may include other components not visible in FIG. 1 . For example, the sensor subsystem 110 may include a motion detector that detects the presence of a person near a switchboard, or a front door sensor that detects the open state of a cover door that encloses the fuse box of the switchboard 112. In the event that maintenance is being performed on the switchboard 112 (which could result in inaccurate measurements), the energy metering system 100 can use this additional sensor data to interrupt load measurement. Alternatively, as described further below, data from such sensors can also be used to trigger recalibration of the energy metering system 100. Recalibration can be used to adapt the energy metering system 100 to changed configurations or other external influences, such as different background magnetic fields. Furthermore, different sets of calibration data can be stored for different operating environments (e.g., with an open or closed fuse box). In this case, data from the door sensor can be used to switch the calibration data set accordingly to improve measurement results. Furthermore, the energy metering system 100 can generate a notification to the user or administrator to highlight that a door has been opened or remains open.

Sensor subsystem 110, including sensor 120, connecting cables 122 and 124, and junction box 126, is connected to data acquisition subsystem 140 by means of feeder cable 130. In particular, feeder cable 130 plugs into junction box 126 at one end and into local data aggregation device 142 at the other end.

In the depicted embodiment, the data aggregation device 142 is integrated into an AC adapter-type housing having a plug connector for plugging the data aggregation device 142 into a conventional wall outlet 144. Plugging the data aggregation device 142 into the wall outlet 144 powers up the data acquisition subsystem 140 and the connected sensor subsystem 110. Furthermore, plugging the data aggregation device 142 into the wall outlet 144 also connects the data aggregation device 142 to the circuit branching off from the distribution board 112. This, in turn, allows for automatic calibration of the energy metering system, as described below.

Although not shown in FIG1 , the data aggregation device may include additional interfaces for connecting other sensors to the energy metering system 100. For example, the data aggregation device 142 may include a plug connector or wireless interface for collecting data from other utility or home automation sensors, such as gas, water, or heat meters. This data may also be recorded along with the electrical load information to facilitate metering and billing for the site.

In the embodiment of FIG1 , the data acquisition subsystem 140 is located near the switchboard 112, for example, in the same room, but outside the switchboard 112 or the surrounding fuse box itself. In contrast, the data analysis subsystem 170 is located in a different location. For example, the switchboard 112, sensor subsystem 110, and data acquisition subsystem 140 may be installed in a basement, garage, or other difficult-to-reach location in the building. In contrast, the data analysis subsystem 170 may be installed in a hallway, office, or living room within the building. In other embodiments, the data acquisition subsystem 140 and/or the data analysis subsystem 170 may be integrated into the switchboard 112.

In order to establish a data link between the data acquisition subsystem 140 and the data analysis subsystem 170, the data aggregation device 142 includes a wireless transmission system 146, such as a Wi-Fi link according to the IEEE standard series 802.11. In the embodiment of Figure 1, the data analysis subsystem 170 includes a remote terminal 172 with a corresponding wireless transmission system 174. Alternatively, the data aggregation device 142 and the remote terminal 172 can also be connected by means of a direct cable or another suitable data transmission system. In particular, when the data aggregation device 142 is integrated into the distribution board 112, power line communication can be used to avoid problems with wireless data communication from within the fuse box. In addition, the data aggregation device 142, the terminal 172 and/or other parts for data processing can be connected to a data network (e.g., the Internet) for data exchange.

In the depicted embodiment, the remote terminal 172 is mounted on a wall using a backplate 176, which also provides power to the terminal 172 via wireless power transmission. Alternatively, the terminal 172 may include a built-in power supply or may be connected to an external power source via a cable. Power is provided via a power cable 180 from an AC/DC adapter 178 connected to the backplate 176. The AC/DC adapter 178 can be plugged into any outlet at the location where the terminal 172 is to be mounted.

In the described embodiment, terminal 172 performs the majority of the data processing for energy metering system 100. Specifically, terminal 172 receives sensor data provided by sensor 120 regarding the magnetic field strength in the region of each circuit breaker 114, as well as reference currents and reference voltages determined by data aggregation device 142. The processing of received data by terminal 172 will be described in greater detail later. In alternative embodiments, some or all of the processing is performed by other components of the data processing system, such as sensor subsystem 11 or data acquisition subsystem 140. Furthermore, some or all of the processing may be performed by an external entity via a data network, such as a cloud service provided by a utility provider.

In another embodiment, the load information obtained by the terminal 172 is also forwarded to a cloud service arranged in a data network, in particular the Internet (not shown). To this end, the terminal can be connected to the data network by means of a network component such as a modem, a router or a wireless data network access device. Alternatively, the data aggregation device can forward the load information directly to the cloud service. In this case, the terminal can download the load data from the cloud service instead of from the data aggregation device. The cloud service that can be provided by the utility provider includes a database for storing power load information. In the described embodiment, the database includes current and historical load information for all power-consuming devices with a compatible energy metering system 100. In addition, the database 194 can also store additional load information, such as load information reported by conventional smart metering devices.

FIG. 2 shows a schematic circuit diagram of an energy distribution system 200 in the region of a switchboard 112 , for example the switchboard 112 according to FIG. 1 .

In the embodiment shown in FIG2 , the power supply network provides electrical energy by means of two different phase lines L1 and L2 and a neutral conductor N. Although FIG2 shows a circuit diagram of a two-phase power supply network with a separate neutral conductor N, those skilled in the art will appreciate that the systems, devices, and methods of the present invention may also be applicable to other power supply network topologies, including single-phase, two-phase, three-phase, or multi-phase power distribution networks with or without a neutral conductor.

At a distribution panel 112, separate circuits C1 to C6 branch off from two phase lines L1 and L2. In the example presented, three circuits branch off from each of the phase lines L1 and L2. Each of the circuits C1 to C6 is protected by a corresponding circuit breaker 114. Furthermore, a separate sensor 120 is installed near each of the circuit breakers 114 for measuring the magnetic flux near that circuit breaker 114. When the magnetic flux in the area of the circuit breaker 114 is correlated with the current flowing through the circuits C1 to C6, this device allows the load status of each of the circuits C1 to C6 to be detected.

As shown in FIG2 , circuit C1 is connected to a wall outlet 144. Furthermore, data aggregation device 142 is also connected to first circuit C1 via wall outlet 144. As described in detail above with reference to FIG1 , data aggregation device 142 is also connected to each of sensors 120. By observing the electrical characteristics of circuit C1 and the sensor data provided by sensors 120 of corresponding circuit breakers 114, data aggregation device 142 or a separate data processing system connected to data aggregation device 142 can establish a correlation between the load of circuit C1 and the sensor data observed at the corresponding sensors 120. In one embodiment, the sensors 120 used during calibration can correspond to sensors provided on individual circuit breakers protecting circuit C1. In another embodiment, as described in detail below, sensors integrated into or attached to the surface of a conventional smart meter or main circuit breaker 114a can be considered during calibration. Of course, both approaches may be combined, such as by calibrating the relationship between the current of circuit C1 attached to the main circuit breaker 114 a and the relative response of the sensor 120 and the sensors 120 attached to the individual secondary circuit breakers 114 .

Furthermore, since the sensors 120 are arranged close to one another, the correlation established with respect to the circuit C1 can also be used to establish the power loads of other circuits C2 to C6 that are not directly connected to the data aggregation device 142. For example, the background magnetic field present at all sensors 120 can be identified by comparing a predetermined load pattern of the circuit C1 with the sensor data provided by the first sensor 120. Furthermore, interference between adjacent circuits can be established based on the cross-correlation of the sensor data of the individual sensors 120.

To support more accurate measurements and to independently verify the load information determined by the data processing system, the overall power consumption of the energy distribution system 200 can be measured by a summation measurement device 210. For example, the additional measurement circuit can be a main circuit breaker 114a, a residual current circuit breaker (RCCB), also known as a ground fault circuit interrupter (GFCI), a ground fault interrupter (GFI), or an appliance leakage current interrupter (ALCI), or a conventional smart meter, arranged directly in the power line leading to the distribution panel 112. The summation measurement device 210 is arranged before the first branch point at a particular location and can provide data aggregation device 142 with data regarding the current, voltage, and/or power of the energy supplied to the distribution panel 112. Such data can be provided by the summation measurement device 210 itself or by additional sensors 120 disposed on the surface of the summation measurement device 210. Such data can be provided directly, i.e., via a cable connection as shown in FIG. 2, or indirectly, i.e., via a data network such as a local building automation network or the Internet. The summed measurement value provided by summing measurement device 210 or another measurement device may be compared to the sum of all loads calculated based on the sensor data for each sensor 120. This comparison may be used to validate the sensor data, to identify circuits that are not connected to any circuit breakers 114 or that have no sensors 120 or have faulty sensors 120, and for calibration purposes, as described in more detail below.

In order to perform calibration of the energy metering system 100, the calibration unit is temporarily or permanently connected to the data processing system. The calibration unit can be connected externally, for example, by means of a plug-in device such as the data aggregation device 142. Alternatively, the calibration unit can be connected internally within the switchboard 112, for example, by being integrated into the summing measuring device 210 or by providing a separate functional unit on a distribution rail arranged within the switchboard 112.

FIG3 shows a first calibration unit 300 that can be integrated into a switchboard 112, a data aggregation device 142, or a terminal 172 according to the embodiment of FIG1 . In the embodiment described with reference to FIG3 , calibration unit 300 is integrated into an intermediate device that has a plug connector 310 on the input side and a socket 320 on the output side. Calibration unit 300 can be used to connect an external load 330 to a circuit C1 branching off from the energy distribution system 200. In the schematic circuit diagram shown in FIG3 , circuit C1 is protected by circuit breaker 114, as described in detail above with reference to FIG1 and FIG2 .

To establish a relationship between the electrical load of circuit C1 and the sensor data provided by sensor 120 disposed near the corresponding circuit breaker 114, calibration unit 300 includes a voltage measurement circuit 340 and a current measurement circuit 350. Instead of the internal current measurement circuit shown in FIG3 , an external current transformer (CT) can be used to measure the current of external load 330. Various circuit configurations for measuring the voltage and current of household loads such as heaters, air conditioning systems, or washing machines are known in the art. Therefore, a detailed description of circuits 340 and 350 is omitted.

It is important to note that, in addition to the voltage measured by circuit 340 and the current measured by circuit 350, the load of circuit C1 may depend on further electrical parameters. In particular, an inductive or capacitive load (e.g., an electric motor) may have an input current that is out of phase with respect to the AC supply voltage of circuit C1. In this particular case, in addition to the voltage and current, the phase angle between the input current and the input voltage should be established by calibration unit 300. The phase angle can be established by a separate circuit for measuring the phase angle (not shown in FIG. 3 ). Alternatively, the phase angle can be determined by sampling the voltage and current using a sampling frequency that is higher than the frequency of the AC supply voltage—that is, oversampling—and correlating the sampled data in a subsequent processing stage.

In the embodiment shown in FIG3 , calibration unit 300 further includes a microcontroller 360, an interface 370, and a memory 380 connected by an internal bus system. To calibrate sensor 120, microcontroller 360 executes a calibration algorithm. The calibration algorithm compares the power consumption of load 330, calculated based on the reference current and reference voltage provided by circuits 350 and 340, with the sensor data provided by magnetic sensor 120. In this way, raw sensor data regarding the magnetic field in the area of circuit breaker 114 can be converted into meaningful load data, such as the current or power flowing through circuit breaker 114. In other embodiments, the calibration algorithm can be executed by other parts of the data processing system, such as terminal 172 or a cloud service connected to energy metering system 100 via the Internet.

Preferably, the comparison can be performed with a varying external load 330. For example, the calibration can be performed repeatedly over an extended period of time, or the user can be instructed to deliberately vary the load 330 during the calibration phase, for example by switching the load 330 on and off or switching the load 330 to a different operating mode.

Once calibration unit 300 establishes a correlation between the sensor data provided by sensor 120 via interface 370 using the reference voltage provided by voltage measurement circuit 340 and the reference current provided by current measurement circuit 350, calibration data representing the correlation is stored in memory 380 or another suitable memory, such as a memory of the corresponding sensor 120, data aggregation unit 142, terminal 172, or a database of a cloud service. In the depicted embodiment, memory 380 may be a flash memory or similar non-volatile storage device that stores the established calibration data even when calibration unit 300 or data aggregation device 142 is disconnected from circuit C1.

Figure 4 shows an alternative calibration unit 400 that may be integrated in the switchboard 112, the data aggregation device 142 or the terminal 172. The components on the input side of the calibration unit 400 correspond to the calibration unit 300 described with reference to Figure 3. For the sake of brevity, repetition of the description of these elements is omitted.

In contrast to calibration unit 300 of FIG3 , calibration unit 400 of FIG4 includes an internal load simulation circuit 410, which can be controlled by a microcontroller 420 to generate a predetermined load pattern. In this embodiment, it is sufficient to establish a reference voltage V using voltage measurement circuit 340 at plug connector 310. Based on knowledge of load simulation circuit 410 and the selected load pattern, the corresponding reference current and electrical load on circuit C1 can be established by internal microcontroller 420 or an external data processing device.

In the embodiment shown in FIG4 , load simulation circuit 410 includes a relatively large capacitive element 430 that can be charged via a first switch 440 and discharged via a second switch 450. By controlling first switch 440 and second switch 450 using microcontroller 420, a predetermined load pattern for circuit C1 can be simulated. Of course, other circuits can also be used to generate one or more predetermined load patterns on the input side of calibration unit 400.

5 shows a state diagram of the data aggregation device 142 with a built-in calibration unit, such as the calibration unit 300 or 400. In another embodiment, the calibration unit may be integrated into other parts of the energy metering system 100, such as the terminal 172.

In the power-on state 510, the data aggregation device 142 is plugged into a wall outlet 144. Alternatively, the data aggregation device 142 may be installed within a distribution board 112, for example, on a distribution rail or connected to one of the circuits via a wire. Thus, the data aggregation device is provided with an operating voltage that can be detected by a primary voltage detection circuit (not shown) of a calibration unit. Upon detecting the provided voltage, a data processing device, such as the microcontroller 360 or 420 of the data aggregation device 142, enters the initialization state 520.

In the initialization state 520, the data processing device can establish a communication channel with other components of the energy metering system 100 (e.g., the individual sensors 120 or sensor strips of the sensor subsystem 110, the terminals 172 of the data analysis subsystem 170, and/or external cloud services). In the depicted embodiment, each sensor 120 includes an integrated controller. These controllers can be addressed via address lines configured as a daisy chain. Thus, the data processing device of the local data aggregation device 142 can establish the presence, number, and relative positions of the sensors 120 by iteratively addressing each microcontroller in the row of sensors 120.

Furthermore, the terminal 172 can be contacted via conventional network discovery methods. For example, the wireless transmission systems 146 and 172 can use a predetermined network identifier or key upon power-up. Such a network identifier can be stored in the respective devices by the manufacturer or can be configured by the user in a configuration mode. In the case where the data aggregation device 142 and the terminal 172 utilize power line communication, a unique signature transmitted via the power line can be used for pairing. Once pairing is established, the associated communication parameters, such as the communication channel used, the network identifier, and/or the encryption key, can be stored in the non-volatile memory of each device.

In addition to the physical connection, during the first initialization of the energy metering system 100, the user may be prompted to enter additional data about the switchboard 112 or the energy distribution system 200 using an appropriate user interface, such as provided by the data provider aggregation device 142, the terminal 172, or a smartphone application, as described in detail in co-pending application EBL-002.

For example, when the system is first powered on, the data aggregation device 142 may sequentially illuminate the LED of each identified sensor 120. For each indicated sensor 120, the user is prompted to provide information about the corresponding circuit, such as the zone or electricity consumer name protected by the corresponding circuit breaker 114. This information, along with the address of the corresponding sensor 120, is then stored in the non-volatile memory of the energy metering system 100 for later reference. For example, this information can be used to display the energy consumption measured by the energy metering system 100 in operating mode on the screen of a terminal 172 or smartphone application, along with the name of the associated zone or electricity consumer. In contrast, the user may be prompted to tag the sensor 120 or circuit breaker 114 using the sensor 120 address determined by the energy metering system 100. Once information for a given sensor 120 is captured, the data aggregation device activates the LED of the next sensor 120 until information for all sensors has been captured.

While establishing connections and capturing additional data with respect to system 100 is described above with respect to initialization state 520 , in other embodiments, one or more of the above steps may also be performed as part of calibration mode 540 described below.

In the initialization state 520, the data processing device may optionally check whether calibration data for the energy metering system 100 are already stored in a non-volatile memory, for example in the memory 380. If calibration data (i.e., data from a previous calibration of the energy metering system 100) are already stored, the energy metering system 100 may proceed directly to the normal operation mode 530, in which the sensor data of the sensor 120 are converted into circuit-specific load information based on the previously stored calibration data.

If, during the initialization state 520, the energy metering system 100 detects that no calibration data is stored in the memory or that the stored calibration data is insufficient, or if the data aggregation device 142 is configured to recalibrate upon each power-up, the energy metering system 100 enters the calibration mode 540. The energy metering system 100 remains in the calibration mode 540 until sufficient calibration data is collected by the calibration unit. In another embodiment, the energy metering system 100 may also re-enter the calibration mode 540 at regular intervals or perform an ongoing calibration process.

Once the correlation between the sensor data of at least one sensor 120 of the sensor subsystem 110 and the reference current and reference voltage of the calibration unit has been established, the calibration data can be stored in optional step 550, and the energy metering system 100 enters normal operating mode 530. Preferably, the calibration data is stored in the same entity that also performs the conversion of the magnetic sensor data into current data or other load information. For example, in a local device, the calibration data can be stored by each sensor 120, the data aggregation device 142, or the terminal 172. If the data is fed back to each sensor 120, after initial calibration, the microprocessor of the sensor 120 can directly convert the measured magnetic field data into load information, thereby alleviating the need for complex post-processing. In cloud-based solutions, the calibration data can be stored in cloud storage, enabling more sophisticated, big data-based analysis methods. In the case of regular or ongoing calibration processing, the calibration data can be updated as needed, and historical calibration data can be maintained where possible.

FIG6 illustrates the steps performed in calibration mode 540 in greater detail.

In a first step 610, a reference voltage V of the circuit connected to the calibration unit is determined. For example, the voltage measurement circuit 340 may measure the line voltage between the phase conductor and the neutral conductor of a plug connector 310 plugged into a wall socket 144 connected to the circuit C1 branching from the distribution board 112. In alternative embodiments, the reference voltage V may be provided by an external entity such as a conventional smart meter or the summing metering device 210.

In a subsequent step 620, a reference current I of the test load through circuit C1 is determined. For example, the input current of external load 330 can be measured by means of current measurement circuit 350 as described above with reference to FIG3 . Alternatively, reference current I can be calculated based on knowledge of the load pattern implemented by load simulation circuit 410 described above with reference to FIG4 . In addition, reference current I can be provided by an external entity, such as a current transformer (CT) installed around the circuit branching from distribution board 112, a conventional smart meter, or another summing measurement device 210.

In optional step 630 , a phase angle between the established reference voltage V and reference current I may be determined. The phase angle may be measured, calculated, or approximated based on knowledge of the specific load.

In step 640, the current power consumption P of the load can be calculated based on the parameters established in the previous steps. In particular in the case of non-ohmic consumers, the power P can be expressed as a vector value based on the input parameters provided in steps 310 to 330. Alternatively or in addition, the power factor of the circuit can also be calculated.

In parallel, in step 650, sensor data B is collected from at least one sensor 120 attached to a circuit breaker 114 protecting the circuit C1 connected to the test load. According to the described embodiment, the acquired sensor data may include magnetic flux components in all three spatial dimensions of the magnetic field near the circuit breaker 114. Therefore, the sensor data B regarding magnetic field strength may also be represented as a vector. Sensor 120 may be directly attached to a circuit breaker 114 protecting an individual branch circuit C1. Alternatively, sensor 120 may be located on a main circuit breaker 114a, a residual current circuit breaker, or all or a group of circuits. In at least some embodiments, step 650 includes acquiring sensor data B from all sensors 120 connected to the data aggregation device 142.

In a subsequent step 660 , a correlation between the power P and the sensor data B can be established.

In the case where a sensor 120 located on main circuit breaker 114a is used for calibration, the load pattern generated by the test load will always result in corresponding sensor data for the sensor 120 located on main circuit breaker 114a. In this case, by establishing a correlation between the load pattern and the sensor data associated with main circuit breaker 114a, the energy metering system can be calibrated. Sensors 120 associated with each branch circuit C1 through C6 can then be calibrated by comparing the known load of main circuit breaker 114a with the relative loads of each secondary circuit breaker 114. For example, if the current through main circuit breaker 114a increases by a known amount, such as 1A, the calibration algorithm can determine which of the sensors 120 also detected the current increase. Assuming the increased current is caused by a single circuit (e.g., C1), the corresponding sensor 120 can be calibrated by noting that the observed magnetic field data corresponds to a 1A current change in C1.

In the absence of a main circuit breaker, where sensors are not provided on the main circuit breaker, or where the topology of the energy distribution system 200 is unknown, step 660 may comprise a preliminary analysis of which circuit and/or phase of the multiphase power supply network the calibration unit 300 or 400 is connected to. To this end, the signature of the load pattern generated or determined in steps 610 to 640 may be compared with the sensor data of each sensor obtained in step 650. Typically, the highest correlation between the sensor data B of any one sensor and the load pattern will indicate a particular sensor 120 attached to the circuit breaker 114 protecting the circuit connected to the calibration unit 300 or 400.

In a similar manner, for example, by establishing cross-correlations between the sensor data B provided by different sensors 120, the sensor hierarchy, such as the primary power sensor and the secondary sensors 120 for each circuit C1 to C6, can also be determined. Furthermore, it can be determined which of the sensors 120 are protecting circuits belonging to the same phase of the multiphase power supply network and which are protecting circuits belonging to different phases. Similarly, by establishing the timing of load peaks for each phase in the multiphase power supply network, the number of all phases and the relative phase angles between all phases can be established. In other words, the energy metering system 100 is learning the configuration of the monitored energy distribution system 200. The assignment of sensors 120 to the various phases in the multiphase energy distribution system 200 can be persistently stored in a configuration table, such as in memory 380 or in a database system for storing and processing subsequently acquired load information.

To establish the actual calibration of the sensor 120, once the relevant sensor 120 is identified, the corresponding sensor data B can be analyzed in more detail. In the described embodiment, both the calculated power P and the sensor data B are represented as vectors. Therefore, conceptually, the matrix C can be established by means of the cross product between the power vector P and the inverse vector B ^-1 of the sensor data B. More specifically, the process of self-learning the calibration matrix disclosed by Paul Bertrand in US 2013/0229173A1 can be adopted. The matrix C can be used as calibration data to establish the correlation between the magnetic field measured at the sensor 120 and the load of the corresponding circuit C1. Similar to other information determined in the calibration mode, the matrix C can be permanently stored in a calibration table or other suitable data structure, such as in the memory 380 or in a database system for storing and processing subsequently obtained load information.

To establish a more precise correlation and also to identify systematic shifts in the permanent magnetic field present, for example, near circuit breaker 114, the above steps can be repeated multiple times. Furthermore, it is possible to consider using sensor data from additional sensors 120, particularly sensors 120 positioned immediately before and/or after sensor 120 for protecting the test load, to counteract any interference from adjacent circuits. In these cases, more complex statistical analysis methods can be employed to establish a correlation between the sensor data B provided by at least one sensor 120 and reference measurements provided by the calibration unit. Furthermore, the sensor data B of one or more individual sensors 120 can be correlated with summed data provided by a smart metering device or another summing measurement device 210 for measuring the total power consumption of one or all phases of the power supply network.

If calibration data cannot be established for the main circuit breaker, a single circuit, such as C1, can be calibrated with reference to the main circuit breaker 114a as described above. In this case, the calibration data obtained for circuit C1 can also be used for the other circuits C2 to C6, especially when the circuit breaker 114 and the sensor 120 have comparable electrical and magnetic characteristics.

7 shows a flow chart of the energy metering system 100 in a normal operating mode 530. In operation, information about the electrical load of a specific circuit can be established individually based on the sensor data B provided.

To this end, in step 710, the magnetic field is measured by a sensor 120 arranged near the circuit breaker 114 of the specific circuit. Based on this measurement, corresponding sensor data B are provided by the sensor 120 for further processing.

In a subsequent step 720, the sensor data B, again a three-dimensional vector value in the given example, can be multiplied with the calibration data C, in this example a matrix, to establish an instantaneous current I or power P representing the electrical load of the corresponding circuit. In the case of obtaining the current, this current can be multiplied with the line voltage measured or known at a later processing state to obtain the corresponding power P.

It is important to note that, in normal operating mode 530, there is no need to provide a reference current to the data processing system. However, in cases where the calibration unit is permanently attached to the energy metering system 100, continuously providing a reference voltage and/or reference current can help improve the accuracy of the determined load information and support regular or ongoing calibration processes. In particular, the measured current can be converted into a measured power for a given circuit using the voltage. Furthermore, by means of constant or repeated voltage measurements via the voltage measurement circuit 340, changes in the supply voltage provided by the utility provider can be detected and used to correct the load information calculated based on the sensor data B. Even in cases where the calibration unit is not permanently connected to the energy distribution system 200, other available data, such as output data from a smart meter or another summing metering device 210, can be used to verify the load information calculated by the energy metering system 100.

As described in detail above, the various components of the described energy metering system 100 are particularly easy to install, even for consumers. In particular, there is no need to open the switchboard 112 or disconnect any wires of the energy distribution system 200 in order to perform the installation. This eliminates the risk of electric shock and the requirement for specialized or certified technicians.

For example, as described in detail above with reference to FIG1 , each sensor 120 for monitoring the circuit branching off from the corresponding circuit breaker 114 can be simply attached to the front of the circuit breaker 114 with the aid of double-sided tape or Velcro fasteners. Furthermore, if the calibration unit 300 or 400 is integrated into the data aggregation device 142 or into the terminal 172 of the wall socket 144 that is plugged into one of the circuits of the distribution board 112, there is no need to establish an additional connection between the energy metering system 100 and the electric energy distribution system 200.

In other words, energy metering system 100 represents a so-called plug-and-play solution that does not require disassembly of distribution panel 112 and can be installed by virtually anyone, including individual consumers. All that is required for installation is attaching sensor 120 to circuit breaker 114; relatively simply connecting sensor 120 to junction box 126 and data aggregation device 142; and plugging data aggregation device 142 and terminal 172 into corresponding wall outlets 144. Of course, terminal 172 and data aggregation device 142 can also be integrated into a single device, further minimizing the effort required to set up energy metering system 100.

As described in detail above with respect to the various embodiments described, data processing (i.e., calibration) and conversion of sensor data into power load information can be performed by data aggregation device 142 or terminal 172. Furthermore, data processing can also be performed by an external service provided by, for example, a utility metering company, for example, via a cloud service. In this embodiment, aggregation device 142 or terminal 172 can be configured to forward the sensor data obtained by sensor 120 to a wide area network, particularly the Internet.

In the case where sensor data is transmitted over a public network such as the Internet, data encryption may be applied by the data aggregation device 142 or the terminal 172, or any other device used to forward the data to the service provider. Of course, for increased security, data encryption may also be applied to the communication between the data aggregation device 142 and the terminal 172, especially when the connection between the data aggregation device 142 and the terminal 172 is wireless.

The energy metering system 100 described above allows for many novel applications, such as fine-grained analysis of power consumption of a specific site, subunit, user, circuit, or electronic device.

For example, energy consumption in different rooms of a building or apartment can be analyzed. Furthermore, suspicious activity can be automatically detected by noting high power consumption at unusual times or locations. Another application is to indirectly detect the presence or absence of people in specific parts of a building based on power consumption.

Furthermore, based on a comparison of load information for a particular location with load information or averages for other locations, recommendations can be provided to consumers to reduce their own energy consumption, thereby contributing to the reduction of greenhouse gas emissions. Similarly, users can also provide information regarding their personal budgets, for example, via terminal 172 or a web service. In this case, the energy metering system 100 can draw the user's attention to high energy consumption before exceeding a preset power budget, enabling the consumer to reduce their energy use to remain within the agreed-upon budget. Furthermore, suppliers can predict a particular consumer's electricity needs based on that consumer's historical records and potentially further information (e.g., weather or temperature data).

Furthermore, energy usage can be monitored over time with high resolution, for example, every minute, every second, or even more frequently, such as at 100 Hz or higher. By monitoring circuit-specific load information over time, abnormal events, such as faults or appliance wear, can be detected by noting sudden or slow drops or increases in associated electrical loads. Harmonic analysis of the switching characteristics of individual electrical devices can be performed at even higher sampling frequencies, such as several kHz, allowing identification of individual devices even when connected to the same circuit. Such analysis can be based on a Fourier transform of the acquired current.

While the energy metering system 100 has been described with respect to various currently preferred embodiments, it is noted that the described system can be modified in a variety of ways without departing from the inventive concepts disclosed herein. In particular, the system can utilize permanently installed current transformers to establish the reference current, as opposed to plug-and-play devices. Furthermore, the calibration unit can be integrated into other devices, such as a smart meter or summing meter 210, or provided as a separate device permanently connected to the electrical energy distribution system 200.

Reference Signs List

100 Energy Metering System

110 Sensor Subsystem

112 switchboard

114 Circuit Breaker

114a Main circuit breaker

120 sensors

122 Connection Cable

124 Connection Cable

126 junction box

130 Feeder Cable

140 Data Acquisition Subsystem

142 Data Aggregation Device

144 wall sockets

146 Wireless Transmission System

170 Data Acquisition Subsystem

172 Remote Terminal

174 Wireless Transmission System

176 back panel

178 AD/DC adapter

180 power supply cable

200 Energy Distribution System

210 Total measuring device

300 calibration units

310 plug connector

320 socket

330 External load

340 Voltage Measurement Circuit

350 Current Measurement Circuit

360 microcontroller

370 interface

380 memory

400 calibration units

410 Load Simulation Circuit

420 microcontroller

430 Capacitive Components

440 First Switch

450 Second switch

Claims (19)

1. An energy metering system for determining the electrical load of a switchboard, the energy metering system comprising: Multiple sensors are used to sense the magnetic field emitted by the circuit breaker of the distribution panel and provide corresponding sensor data, wherein each of the multiple sensors is attached to the housing of the corresponding circuit breaker and is configured to measure the magnetic field emitted by the corresponding circuit breaker. A data processing system is used to convert sensor data from the multiple sensors into power load information for multiple circuits protected by corresponding circuit breakers during normal operation; and A calibration unit, electrically connected to one of the plurality of circuits and coupled to the data processing system, is configured to determine at least the reference voltage and reference current of the connected circuit among the plurality of circuits. The data processing system is configured to: in the calibration mode of the energy metering system, calibrate the relationship between the sensor data and the load information based on the reference voltage and reference current determined by the calibration unit, and A preliminary analysis is conducted regarding which of the plurality of circuits the calibration unit is connected to. 2. The energy metering system according to claim 1, wherein the data processing system includes a local data aggregation device, and wherein the calibration unit is integrated into the local data aggregation device. 3. The energy metering system of claim 2, wherein the local data aggregation device includes a primary circuit and a plug connector for connecting the local data aggregation device to a socket, and wherein the primary circuit is configured to: provide operating energy to the local data aggregation device and measure a primary voltage applied to the plug connector. 4. The energy metering system of claim 3, wherein the primary circuit is further configured to: detect the connection of the plug connector to the power supply voltage provided by the socket, and wherein the calibration unit is configured to activate the calibration mode when it is detected that the local data aggregation device is connected to the power supply voltage. 5. The energy metering system according to claim 2, wherein the local data aggregation device is further configured to: perform a calibration process locally based on the reference voltage and the reference current in the calibration mode, and, in a normal operating mode, locally convert sensor data of the plurality of sensors into power load information of the plurality of circuits based on the result of the calibration process. 6. The energy metering system according to claim 2, wherein the data processing system further includes a remote data analysis device, the local data aggregation device and the remote data analysis device are connected via at least one data connection, and the remote data analysis device is configured to: perform calibration processing based on a reference voltage and a reference current provided by the local data aggregation device in the calibration mode, and convert sensor data of the plurality of sensors into power load information of the plurality of circuits based on the result of the calibration processing in the normal operation mode. 7. The energy metering system according to claim 1, wherein the calibration unit includes a voltage measurement circuit configured to: measure the line voltage of the connected circuit, and provide the measured line voltage as a reference voltage to the data processing system. 8. The energy metering system of claim 7, wherein the calibration unit is further configured to apply a predetermined load mode to the connected circuit during the calibration process. 9. The energy metering system of claim 7, wherein the calibration unit further includes a socket for connecting an external load and a current measuring circuit configured to measure the current flowing through the external load, wherein the calibration unit is further configured to determine the reference current based on the current flowing through the external load. 10. The energy metering system of claim 1, wherein at least one of the calibration unit and the processing system is further configured to determine at least one of the following data: the phase angle between the reference voltage and the reference current, and the frequency of the reference voltage. 11. The energy metering system of claim 1, further comprising at least one additional sensor configured to detect at least one of the following: the presence of an operator near the distribution panel and the opening of the cover of the distribution panel, wherein, in the event that the at least one additional sensor indicates the presence of an operator or the opening of the cover, the data processing system is configured to perform at least one of the following steps: interrupting the conversion of sensor data from the plurality of sensors into power load information; recalibrating the relationship between the sensor data and the load information; converting the sensor data from the plurality of sensors into power load information based on calibration data associated with the opening state of the cover; and sending a predetermined notification. 12. The energy metering system of claim 1, wherein the data processing system includes a local data aggregation device, and wherein the calibration unit is part of an intelligent metering device or a total measurement device independent of the local data aggregation device. 13. A method for calibrating an energy metering system, the method comprising the following steps: Determine the reference voltage and reference current of the first circuit branching off from the distribution panel and connected to the calibration unit; The sensor is configured to at least protect the magnetic field emitted by the first circuit breaker of the first circuit and provide corresponding first sensor data; The first power load information of the first circuit is determined based on the determined reference voltage and reference current; Calibration data that represents the relationship between the provided first sensor data and the determined first electrical load information; and In the normal operating mode of the energy metering system, based on the determined calibration data, the second sensor data corresponding to the magnetic field emitted by the second circuit breaker is converted into second power load information. The method also includes a preliminary analysis of which of the multiple circuits the calibration unit is connected to. 14. The method of claim 13, wherein the first circuit breaker is a main circuit breaker protecting all or a group of circuits branching off from the distribution panel, and the second circuit breaker is a secondary circuit breaker protecting only the first or second circuit branching off from the distribution panel; and in the conversion step, calibration of the second circuit breaker is determined by correlating the measured change in load of the main circuit breaker with the change in sensor data obtained by the second sensor, based on calibration data determined for the main circuit breaker. 15. The method of claim 13, wherein the first circuit breaker protects only the first circuit branching off from the distribution panel, and the second circuit breaker protects only the second circuit branching off from the distribution panel; and in the conversion step, the calibration data determined for the first circuit breaker is also used to convert the second sensor data into corresponding second load information. 16. The method of claim 15, wherein the stored calibration data is further used to: convert the provided first sensor data into first load information of the first circuit in the normal operating mode of the energy metering system. 17. The method of claim 13, wherein when the calibration unit of the energy metering system is connected to the first circuit, the steps of measurement, sensing, determination, calibration, and storage are performed automatically. 18. A data aggregation device for an energy metering system, the data aggregation device comprising: At least one bus connector for connecting a plurality of sensors to the data aggregation device, the plurality of sensors for sensing magnetic fields emitted by circuit breakers in a distribution panel, wherein each of the plurality of sensors is attached to the housing of a corresponding circuit breaker and configured to measure the magnetic field emitted by the corresponding circuit breaker. At least one plug connector for connecting the data aggregation device to a first circuit branching off from the distribution panel; A calibration unit, connected to the plug connector, the calibration unit including circuitry for determining a reference voltage and a reference current of the first circuitry connected to the calibration unit; and At least one interface is provided for providing sensor data from the plurality of sensors and reference current and reference voltage determined by the calibration unit, for calibrating the relationship between the provided sensor data and the power load information of the first circuit in the calibration mode of the energy metering system, and for converting the provided sensor data into power load information of the plurality of circuits protected by corresponding circuit breakers in the normal operation mode of the energy metering system. A preliminary analysis is conducted regarding which of the plurality of circuits the calibration unit is connected to, and The data aggregation device further includes at least one data processing device, which is connected to the at least one bus connector and the calibration unit through the at least one interface. The at least one data processing device is configured to: calibrate the relationship between the provided sensor data and the power load information in the calibration mode, and convert the provided sensor data into the power load information in the normal operation mode. 19. The data aggregation apparatus of claim 18, wherein the at least one interface includes a data network interface, wherein the data network interface is configured to send at least one of the following data to a remote data analysis device connected to the data aggregation apparatus via at least one data network: provided sensor data, determined power load information, determined reference current, and determined reference voltage.