MONITORING OF ELECTRICAL PARAMETERS

MX434687BActive Publication Date: 2026-06-12CLOUDFM INTEGRATED SERVICES LTD

Patent Information

Authority / Receiving Office: MX · MX
Patent Type: Patents
Current Assignee / Owner: CLOUDFM INTEGRATED SERVICES LTD
Filing Date: 2023-07-06
Publication Date: 2026-06-12

AI Technical Summary

Technical Problem

Monitoring electrical parameters in installations consumes large amounts of data bandwidth and storage due to frequent and extensive data transmission and storage requirements, especially when parameters are monitored at higher frequencies or in greater numbers.

Method used

A method and system that compare differences between current and previous sets of monitored parameters with a threshold criterion, transmitting and storing only when the difference exceeds the threshold, thereby reducing data bandwidth and storage consumption.

Benefits of technology

Adequate monitoring of significant parameter changes is maintained while significantly reducing data bandwidth and storage consumption by selectively transmitting and storing only notable parameter variations.

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Abstract

A method for monitoring parameters of an electrical installation comprises performing a plurality of successive iterations of a process in which the difference between a current set of one or more monitored parameters of the electrical installation and a previous set of one or more monitored parameters of the electrical installation is compared to a threshold criterion. When the difference is determined to exceed the threshold criterion, the current set of one or more monitored parameters is transmitted and / or stored. Conversely, when the difference is determined not to exceed the threshold criterion, the current set of one or more monitored parameters is not transmitted and / or stored. This can help reduce data bandwidth consumption and / or data storage requirements.

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Description

MONITORING OF ELECTRICAL PARAMETERS The present invention relates to a method for monitoring parameters of an electrical installation and to a system for monitoring parameters of an electrical installation. It is often desirable to monitor parameters of an electrical installation, for example, to analyze electricity consumption for predictive maintenance and diagnostics. Examples of electrical installations that can benefit from such monitoring include residential, commercial, and industrial installations. It is also often desirable to measure and / or derive parameters locally within the electrical installation, but then transmit and / or store these parameters remotely for further analysis. As will be seen, when electrical parameters are monitored more frequently and / or when a greater number of different electrical parameters are monitored, it may be necessary to transmit and / or store a larger amount of data for the installation. Of course, transmitting and / or storing a larger amount of data will consume significant amounts of data bandwidth and / or storage space. The aim is to provide improvements related to the monitoring of electrical installation parameters. Therefore, according to one aspect of the present invention, a method is provided for monitoring parameters of an electrical installation, the method comprising: to perform a plurality of successive iterations of a process in which a difference between a current set of one or more monitored parameters of the electrical installation and a previous set of one or more monitored parameters of the electrical installation is compared with a threshold criterion; where, when it is determined that the difference exceeds the threshold criterion, the current set of one or more monitored parameters is transmitted and / or stored; and where, when it is determined that the difference does not exceed the threshold criterion, the current set of one or more monitored parameters is not transmitted and / or stored. Similarly, according to another aspect of the present invention, a system is provided for monitoring parameters of an electrical installation; the system comprises: processing circuitry configured to perform a plurality of successive iterations of a process in which a difference between a current set of one or more monitored parameters of the electrical installation and a previous set of one or more monitored parameters of the electrical installation is compared to a threshold criterion; wherein, when the processing circuitry determines that the difference exceeds the threshold criterion, the processing circuitry is configured to transmit and / or store the current set of one or more monitored parameters; and wherein, when the processing circuitry determines that the difference does not exceed the threshold criterion, the processing circuitry is configured not to transmit and / or store the current set of one or more monitored parameters; and As will be seen, the embodiments of the present invention provide a way in which CQQtrQn / cznz / a / uli to adequately monitor variable electrical parameters of an electrical installation while helping to reduce data bandwidth consumption and / or data storage. In particular, by identifying particular sets of one or more monitored parameters for which the threshold criterion has been exceeded, and therefore for which a significant change in the monitored parameters is more likely to have occurred, and then transmitting and / or storing those particular sets of one or more monitored parameters, the embodiments of the present invention can enable the adequate monitoring of significant changes in the parameters of the electrical installation.Furthermore, by identifying other specific sets of one or more monitored parameters for which the threshold criterion was not exceeded, and therefore for which a noticeable change in the monitored parameters is less likely to have occurred, and then not transmitting and / or storing those other specific sets of one or more monitored parameters, the embodiments of the present invention can help reduce the amount of data bandwidth and / or data storage consumed when monitoring the electrical installation. Essentially, the embodiments of the present invention provide a way to reduce data granularity without significant loss of data fidelity. In some models, the threshold criterion may comprise one or more threshold values. However, in preferred models, the threshold criterion comprises a single threshold value. The difference compared to the threshold criterion may comprise or be based on a modulo of the difference between the current set of one or more monitored parameters and the previous set of one or more monitored parameters. In some configurations, each set of one or more monitored parameters may comprise a single monitored parameter. In these configurations, the difference compared to the threshold criterion may comprise or be based on a scalar difference between a current monitored parameter and a previous monitored parameter. The magnitude of the scalar difference can then be compared to the threshold value. However, in preferred configurations, each set of one or more monitored parameters may comprise a plurality of monitored parameters. These preferred configurations can help reduce the processing load placed on the system by reducing the number of threshold comparisons that need to be made for the plurality of monitored parameters.In these preferred modes, the difference compared to the threshold criterion may comprise or be based on a vector difference between a vector formed from the current set of monitored parameters and a vector formed from the previous set of monitored parameters. As will be seen, a vector difference between a first and second vector involves determining a third vector by calculating respective differences between corresponding elements of the first and second vectors. The magnitude of the difference vector can then be compared to the threshold value. In preferred modes, when the difference is determined to exceed the threshold criterion, the current set of one or more monitored parameters in the current iteration can be converted into the previous set of one or more monitored parameters in a subsequent iteration, i.e., for comparison with a new “current” set of one or more monitored parameters in that subsequent iteration. In these modes, by iteratively updating the previous set of one or more parameters In preferred modes, when the difference is determined not to exceed the threshold criterion, the current set of one or more monitored parameters in the current iteration may not become the previous set of one or more monitored parameters in a subsequent iteration. Rather, the previous set of one or more monitored parameters in the current iteration may be retained as the previous set of one or more monitored parameters in a subsequent iteration, i.e., for comparison with a new “current” set of one or more monitored parameters in that subsequent iteration. In these modes, by not updating the previous set of one or more monitored parameters, the suitability of the difference being considered can again be maintained over time.In preferred modes, the threshold criterion can be based on the previous set of one or more monitored parameters. These modes can help provide a threshold criterion for comparison with the difference that is well-suited to the particular electrical installation in question. When the difference is determined to exceed the threshold criterion, the threshold criterion can be updated based on the current set of one or more monitored parameters (which, in a subsequent iteration, can become the previous set of one or more monitored parameters for comparison with a new “current” set of one or more monitored parameters).In these modalities, by iteratively updating the threshold criterion based on particular sets of one or more monitored parameters for which the threshold criterion is exceeded, the suitability of the threshold criterion for comparison with subsequent actual sets of one or more monitored parameters over time can be maintained. Conversely, in preferred modalities, when it is determined that the difference does not exceed the threshold criterion, the threshold criterion may not be updated based on the current set of one or more monitored parameters.In these modalities, by not updating the threshold criterion based on other particular sets of one or more monitored parameters for which the threshold criterion is not exceeded, the processing load placed on the system can be reduced and the threshold criterion can be prevented from deviating over time due to gradual changes in the sets of one or more monitored parameters. In the modalities, the threshold criterion can be derived from (based on or updated based on) the set of one or more monitored parameters in question using a formula, such as a linear or nonlinear (e.g., quadratic) formula. The formula can scale and / or shift the set of one or more monitored parameters in question. As discussed earlier, in some modalities, each set of one or more monitored parameters may comprise a single monitored parameter. In these modalities, the formula can be applied to the single monitored parameter in question. For example, the single monitored parameter can be scaled and / or shifted. However, as discussed earlier, in preferred modalities, each set of one or more monitored parameters may comprise a plurality of monitored parameters.In these preferred modes, the formula can be applied to the magnitude of a vector formed from the set of monitored parameters in question. For example, the magnitude of the vector formed from the set of. The monitored parameters can be scaled and / or shifted. The scale and / or shift value can be preselected to provide any desired monitoring behavior. For example, the scale value can be selected to provide any desired data granularity, and / or the shift value can be selected based on a statistical property (e.g., standard deviation) across a plurality of previous sets of one or more measured parameters. In these methods, when the difference is determined to exceed the threshold criterion, the process may also include determining whether a minimum time period has elapsed between obtaining the current set of one or more monitored parameters and obtaining the previous set. When it is determined that the minimum time period has elapsed, the current set of one or more monitored parameters may be transmitted and / or stored, and / or the threshold criterion may be updated based on the current set of one or more monitored parameters, as described above.However, when it is determined that the minimum time period has not elapsed, the current set of one or more monitored parameters may not be transmitted and / or stored, and / or the threshold criterion may not be updated based on the current set of one or more monitored parameters, regardless of which threshold criterion has been exceeded. These modes can help prevent the system from transmitting and / or storing parameters, and / or updating the threshold criterion, too frequently. The minimum time period can be preset accordingly as needed. In these methods, when it is determined that the difference does not exceed the threshold criterion, the process may also include determining whether or not a maximum time period has elapsed between obtaining the current set of one or more monitored parameters and obtaining the previous set of one or more monitored parameters. When it is determined that the maximum time period has not elapsed, the current set of one or more monitored parameters may not be transmitted and / or may not be stored, and / or the threshold criterion may not be updated based on the current set of one or more monitored parameters, as described above.However, when the maximum time period is determined to have elapsed, the current set of one or more monitored parameters can be transmitted and / or stored, and / or the threshold criterion can be updated based on the current set of one or more monitored parameters, regardless of whether the threshold criterion has been exceeded. These modes can help prevent the system from transmitting and / or storing parameters, and / or updating the threshold criterion, too frequently. The maximum time period can be preset accordingly. The maximum time period can be longer than the minimum time period. In these modes, the sets of one or more monitored parameters may comprise or be based on one or more electrical values of the electrical installation. For example, the sets of one or more monitored parameters may comprise or be based on one or more voltage values, current values, energy values, frequency values, phase values, and / or harmonic content values, etc. The sets of one or more monitored parameters may comprise or be based on one or more instantaneous values, absolute values, average values (e.g., RMS), maximum values (by CQQfcan / cznz / a / uli example, in a given time period), and / or minimum values (for example, in a given time period), etc. Sets of one or more monitored parameters may comprise or be based on one or more active values, reactive values, complex values, and / or apparent values, etc. In these configurations, the system may include sampling circuitry configured to sample one or more electrical values (e.g., current or voltage) from the electrical installation and provide these sampled electrical values to the processing circuitry. The processing circuitry may be configured to receive these sampled electrical values and derive sets of one or more monitored parameters from them. The sampling circuitry may be configured to sample these electrical values at a frequency of at least 10 kHz, such as at least 25 kHz. As will be seen, a higher frequency may provide greater accuracy, but with the potential disadvantage of increased bandwidth and / or data storage consumption, while a lower frequency may provide less accuracy, but with the potential advantage of reduced bandwidth and / or data storage consumption.The frequencies disclosed in this document have been identified as providing an optimal balance between accuracy and bandwidth consumption when using the data reduction processes described in this document. In these configurations, the sampling circuitry may comprise one or more input data channels configured to sample a respective electrical value (e.g., current or voltage). For example, the sampling circuitry may comprise at least 10, 25, or 50 input data channels configured to sample a respective electrical value. These one or more electrical values may be supplied to the input data channels via a respective connector. Each connector may be connected to a respective electrical sensor (e.g., current or voltage). In these modes, the sampling circuitry may comprise at least two channels of different input data types. For example, the sampling circuitry may comprise one or more input data channels configured to provide a respective current value and one or more input data channels configured to provide a respective voltage value. The sampling circuitry may comprise more current input data channels than voltage data channels. For example, the sampling circuitry may comprise at least 10, 25, or 50 current input data channels and fewer than 5 voltage input data channels (e.g., only one voltage input data channel).In this regard, it has been identified that it is generally desirable to directly monitor current values (for example, to accurately determine the amplitude, frequency, phase, and / or harmonic content of the current for each current data channel), but that multiple voltage values can be estimated from a single voltage value (for example, to roughly determine the power consumption corresponding to each current data channel). Voltage estimation can involve applying an appropriate phase shift to the voltage channel being directly monitored, such as 0°, 120°, or 240° for an ideal three-phase supply. These methods can also help reduce the amount of processing, bandwidth, and / or storage required to monitor the electrical installation. CQQfcan / cznz / a / uιλι In these modes, the mastering circuitry may comprise one or more input data channels (e.g., current) that do not have an amplifier. The sampling circuitry may comprise one or more input data channels (e.g., voltage) that have an amplifier to amplify the electrical value. The amplifier may include an isolation amplifier. In these modes, the sampling circuitry may comprise one or more multiplexers configured to multiplex the plurality of input data channels into a single multiplexed data channel. The sampling circuitry may comprise an analog-to-digital converter (ADC) configured to digitize the multiplexed data channel into a digitized data channel. The processing circuitry may be configured to receive the digitized data channel and derive sets of one or more monitored parameters from it. The processing circuitry may be configured to select (demultiplex) one or more input data channels from the plurality of input data channels and derive sets of one or more monitored parameters from them. In preferred embodiments, the sampling circuitry may comprise a plurality of primary multiplexers, each configured to multiplex a subset of the plurality of input data channels (e.g., current) into a single primary multiplexed data channel. The sampling circuitry may also comprise a secondary multiplexer configured to multiplex the plurality of primary multiplexed data channels into a single secondary multiplexed data channel. The secondary multiplexer may also multiplex one or more unmultiplexed data channels (e.g., voltage) into the single secondary multiplexed data channel. The secondary multiplexer may comprise a higher-speed multiplexer than the primary multiplexer. In these embodiments, the ADC may be configured to digitize the secondary multiplexed data channel into the digitized data channel.Again, the processing circuitry can be configured to receive the digitized data channel and derive sets of one or more monitored parameters from it. The processing circuitry can also be configured to select (demultiplex) one or more input data channels from the plurality of input data channels and derive sets of one or more monitored parameters from them. In these modes, the system may include transmission circuitry configured to transmit sets of one or more monitored parameters. These sets may be transmitted via a wired and / or wireless interface. They may also be transmitted to one or more remote system servers. Alternatively, or additionally, the sets may be stored locally within the system's electronic storage. This electronic storage may comprise one or more memories accessible to the processing circuitry. In one embodiment, the method may comprise operating in a first mode of operation in which the threshold criteria are not used, and then operating in a second mode of operation in which the threshold criteria are used. In other embodiments, the method may comprise operating in a first mode of operation in which the first threshold criteria are used, and then operating in a second CQQtrQn / cznz / a / uli mode of operation in which the second threshold criteria are used, the second threshold criteria being higher than the first threshold criteria. In either of these modes, the first mode of operation may allow the electrical installation to be initially analyzed at a higher data granularity, for example, to build a model for the electrical installation, while the second mode of operation may allow the electrical installation to continue being analyzed, but at a lower data granularity, for example, using the electrical installation model. In terms of modalities, the electrical installation may comprise a domestic, commercial or industrial installation, such as an electrical installation for a dwelling (house or apartment block), office, school, college, university, hotel, hospital, shop, restaurant, station, airport, manufacturing plant, etc. As will be seen, the method described herein can encompass carrying out any of the functional steps performed by the system (e.g., by the processing circuitry). Similarly, the system (e.g., the processing circuitry) described herein can be configured accordingly to perform any of the functional steps of the method described herein. By way of example only, the embodiments of the present invention will now be described in detail with reference to the accompanying drawings in which: Figure 1 shows a physical schematic of a system for monitoring parameters of an electrical installation according to a modality of the present invention; Figure 2 is a schematic illustration of the system in Figure 1; Figure 3 is a data reduction method according to an embodiment of the present invention; Figure 4 is a data reduction method according to another embodiment of the present invention; Figures 5A to 5D show graphical illustrations of the monitored parameter sets and the threshold criterion used in the method of Figure 4; and Figure 6 is a data reduction method according to yet another embodiment of the present invention. Figures 1 and 2 show features of a system 10 mounted on a printed circuit board (PCB) for monitoring parameters of an electrical installation, such as a domestic, commercial, or industrial installation. The system 10 is powered by a power supply unit 11. The system 10 comprises various sampling circuits that sample electrical values from the electrical installation. In this embodiment, the sampling circuitry includes fifty-four current input data channels 12 for sampling respective current values from the electrical installation through a pair of respective connectors that can be connected to a respective current sensor coil. The fifty-four current input data channels 12 are arranged in nine subsets of six current input data channels each.In this mode, the sampling circuitry also includes a single input voltage data channel 13 for sampling. CQQtrQn / cznz / a / uli a voltage value from the electrical installation through a pair of additional connectors that can be connected to a voltage sensor. The voltage value is amplified and isolated using an isolation amplifier 14. The single voltage input data channel 13 is used to derive an approximate voltage value for each of the current input data channels 12. The sampling circuitry further comprises a plurality of primary multiplexers 15, each of which multiplexes a subset of current input data channels into a single respective primary multiplexed current data channel.The sampling circuitry further includes an arrangement 16 having a secondary high-speed multiplexer 16a that multiplexes the plurality of primary multiplexed current data channels and the voltage data channel into a single secondary multiplexed data channel, and a high-speed ADC 16b that digitizes the secondary multiplexed data channel into a digitized data channel. In this configuration, the sampling circuitry can sample electrical values at a frequency of at least 25 kHz. The system 10 further comprises processing circuitry 17 that receives the digitized data channel, selects (demultiplexes) one or more input data channels from the plurality of input data channels, and derives sets of one or more monitored parameters from them.In this mode, the processing circuitry 17 performs phase / frequency detection 18a, voltage phase correction 18b, energy consumption calculations 18c, harmonic content calculations 18d, and a data reduction process 18e. The system 10 further comprises transmission circuitry 19 that wirelessly transmits monitored parameters to a remote server according to the data reduction process 18e. The data reduction process 18e will now be described in more detail with reference to Figures 3 to 6. Figure 3 illustrates a data reduction method. In this method, in step 31, a threshold offset value (a) is set to 1 and a threshold scale value (β) is set to 0.01. Then, in step 32, a single monitored parameter (p) is determined (e.g., measured, calculated, or derived). Next, in step 33, the current monitored parameter (p) is transmitted to the remote server (“publish p”). The current monitored parameter (p) is then treated as a previous monitored parameter (V), and a threshold criterion is established in the form of a threshold value (T) using a linear formula such that T = β + a. Then, in step 34, a new current monitored parameter (p) is determined. Finally, in step 35, the magnitude of the difference between the current monitored parameter (p) and the previous monitored parameter (V) is compared to the threshold value (T).If the difference exceeds the threshold, the method returns to step 33, in which the current monitored parameter (p) is transmitted to the remote server (“publish p”), the current monitored parameter (p) is now considered to be the previous monitored parameter (V), and the threshold value (T) is updated such that T = βν + a. The method then proceeds to step 34. However, if the difference does not exceed the threshold, the method returns directly to step 34 without transmitting the current monitored parameter and without updating either the previous monitored parameter (V) or the threshold value (T). The method then proceeds to step 35, and so on through successive iterations. An example of the method in Figure 3 is illustrated in the following table, in which the monitored parameter is the actual energy and in which the initial published actual energy was 3.4 watts. CQQfcan / cznz / a / uιλι Iteration Current real energy (P) Previous real energy (V) Threshold value T PV difference Publish p? Published Value 1 3.2 3.4 1.034 -0.2 No 2 3.8 3.4 1.034 0.4 No 3 4.0 3.4 1.034 0.6 No 4 5.2 3.4 1.034 1.8 Yes 5.2 5 961.2 5.2 1.052 956.0 Yes 961.2 6 966.1 961.2 10.612 4.9 No 7 960.1 961.2 10.612 -1.1 No 8 952.2 961.2 10.612 -9.0 No 9 955.5 961.2 10.612 -5.7 No 10 1712.9 961.2 10.612 751.7 Yes 1712.9 CQQtrQn / cznz / a / uιλι As shown above, only three values are published instead of ten. Consequently, this data reduction method provides a way to properly monitor a variable electrical parameter of an electrical installation while also helping to reduce data bandwidth consumption. Figure 4 illustrates another data reduction method. In this method, in step 41, a threshold offset value (a) is reset to 1 and a threshold scale value (β) is reset to 0.01. Then, in step 42, a vector of a plurality of monitored parameters (P) is determined (e.g., measured, calculated, or derived). Next, in step 43, the current vector of monitored parameters (P) is transmitted to the remote server (“publish P”). The current vector of monitored parameters (P) is then treated as a previous vector of monitored parameters (X), and a threshold criterion is set in the form of a threshold value (T) using a linear formula such that T = β | X| + a. Finally, in step 44, a new current vector of the plurality of monitored parameters (P) is determined.Next, in step 45, the magnitude of the vector difference between the current monitored parameter vector (P) and the previous monitored parameter vector (X) is compared to the threshold value (T). If the difference exceeds the threshold, the method returns to step 43, in which the current monitored parameter vector (P) is transmitted to the remote server (“publish P”), the current monitored parameter vector (P) is now considered to be the previous monitored parameter vector (X), and the threshold value (T) is updated such that T = β|X| + a. The method then proceeds again to step 44. However, if the difference does not exceed the threshold, the method returns directly to step 44 without transmitting the current monitored parameter vector (P) and without updating either the previous monitored parameter vector (X) or the threshold value (T). The method then proceeds to step 45 again, and so on.Consequently, this data reduction method 40 provides a way in which to properly monitor a set of a plurality of variable electrical parameters of an electrical installation while also helping to reduce data bandwidth consumption. Figures 5A to 5D are a graphical illustration of the monitored parameter sets and the threshold criterion used in the method of Figure 4. Figure 5A illustrates a current vector P formed from two monitored parameters, a previous vector X formed from the two monitored parameters, and a vector difference PX between the current vector P and the previous vector X. Figure 5B then illustrates a hypothetical threshold region defined by the threshold T with respect to the previous vector X. Figure 5C then illustrates a vector difference PX that falls within the hypothetical threshold region defined by the threshold T, that is, in which the magnitude of the vector difference |PX| is less than T. On the other hand, Figure 5D illustrates a vector difference PX that extends beyond the hypothetical threshold region defined by the threshold T, that is, in which the magnitude of the vector difference |PX| is greater than T.In these examples, the monitored parameter sets comprise a first in-phase harmonic H1 and a first quadrature harmonic H1, so the corresponding vectors are two-dimensional. In this sense, each current harmonic can be represented as a vector with a magnitude and an angle relative to the voltage. Consequently, the "first in-phase harmonic" is the vector component of the first current harmonic that is in phase with the voltage, and the "first quadrature harmonic" is the vector component of the first current harmonic that is orthogonal to the voltage. However, as will be seen, sets of different monitored parameters with more than two dimensions can be used in a similar way. For example, two or more voltage values, current values, energy values, frequency values, phase values, and / or harmonic content values, etc., could be considered together as a multidimensional vector of monitored parameters. Figure 6 illustrates yet another data reduction method. In this modality, in step 61, a threshold offset value (a) and a threshold scale value (β) are again set to reasonable values. For example, the scale value (β) can be selected to provide a desired data granularity, and the offset value (a) can be selected to be two standard deviations across pluralities of measured parameter sets. However, if desired, other selection criteria can be used for the threshold offset value (a) and the threshold scale value (β). Then, in step 62, a vector of a plurality of monitored parameters (P) is determined (e.g., measured, calculated, or derived).Next, in step 63, the current vector of monitored parameters (P) is transmitted to the remote server (“publish P”). Then, the current vector of monitored parameters (P) is treated as a previous vector of monitored parameters (X), and a threshold criterion is established in the form of a threshold value (T) using a linear formula such that T = β | X| + a. Next, in step 64, a new current vector of the plurality of monitored parameters (P) is determined. Then, in step 65, the magnitude of the difference between the current vector of monitored parameters (P) and the previous vector of monitored parameters (X) is compared to the threshold value (T). If the difference exceeds the threshold, the method proceeds to step 66, in which it is determined whether a minimum time period (LB) has elapsed between obtaining the current vector of monitored parameters (P) and obtaining the previous vector of monitored parameters (X).In this mode, the minimum time period (LB) is 5 seconds, although other minimum time periods could be used as needed. CQQfcan / cznz / a / uli desire. If the minimum time period (LB) has elapsed, the method returns to step 63, in which the current monitored parameter vector (P) is transmitted to the remote server (“publish P”), the current monitored parameter vector (P) is now considered to be the previous monitored parameter vector (X), and the threshold value (T) is updated such that T = β | X | + a, according to Figure 4. However, in this mode, if the minimum time period (LB) has not elapsed, the method returns directly to step 64 without transmitting the current monitored parameter vector (P) and without updating the previous monitored parameter vector (X) or the threshold value (T). This can help prevent the system from transmitting and updating the threshold criterion too frequently.Considering step 65 again, if the difference does not exceed the threshold, the method proceeds to step 67, in which it is determined whether a maximum time period (UB) has elapsed between obtaining the current monitored parameter vector (P) and obtaining the previous monitored parameter vector (X). In this mode, the maximum time period (UB) is 1800 seconds, although other maximum time periods could be used as desired. If the maximum time period (UB) has not elapsed, the method returns directly to step 64 without transmitting the current monitored parameter vector (P) and without updating the previous monitored parameter vector (X) or the threshold value (T), according to Figure 4.However, if the maximum time period (UB) has elapsed, the method reverts to step 63, in which the current monitored parameter vector (P) is transmitted to the remote server (“publish P”), the current monitored parameter vector (P) is now considered to be the previous monitored parameter vector (X), and the threshold value (T) is updated such that T = β|X| + a. This can help prevent the system from transmitting and updating the threshold criterion at a very low frequency. In any of the modes described in Figures 3 to 6, System 10 can operate in a first mode in which threshold criteria are not used to determine whether or not to transmit the measured parameters. This allows the electrical installation to be initially analyzed at a higher data granularity to build a model of the electrical installation. Subsequently, System 10 can operate in a second mode in which threshold criteria are used, allowing the electrical installation to continue being analyzed using the electrical installation model but at a much lower data granularity. In other modes, the first mode of operation can instead use lower threshold criteria than the second mode of operation, for example, by adjusting the scale and / or phase value appropriately for the respective modes of operation.

Claims

1. A method for monitoring parameters of an electrical installation, the method comprising: performing a plurality of successive iterations of a process in which a difference between a current set of one or more monitored parameters of the electrical installation and a previous set of one or more monitored parameters of the electrical installation is compared with a threshold criterion; wherein, when it is determined that the difference exceeds the threshold criterion, the current set of one or more monitored parameters is transmitted and / or stored; and wherein, when it is determined that the difference does not exceed the threshold criterion, the current set of one or more monitored parameters is not transmitted and / or stored.

2. A method according to claim 1, wherein the threshold criterion comprises a single threshold value.

3. A method according to claim 1 or 2, wherein the difference being compared to the threshold criterion comprises or is based on a modulo of a difference between the current set of one or more monitored parameters and the previous set of one or more monitored parameters.

4. A method according to any of claims 1 to 3, wherein each of the sets of one or more monitored parameters comprises a single monitored parameter.

5. A method according to claim 4, wherein the difference being compared to the threshold criterion comprises or is based on a scalar difference between a current monitored parameter and a previous monitored parameter.

6. A method according to any of claims 1 to 3, wherein each of the sets of one or more monitored parameters comprises a plurality of monitored parameters.

7. A method according to claim 6, wherein the difference being compared to the threshold criterion comprises or is based on a vector difference between a vector formed from the current set of monitored parameters and a vector formed from the previous set of monitored parameters.

8. A method according to any of the preceding claims, wherein the threshold criterion is based on the previous set of one or more monitored parameters.

9. A method according to any of the preceding claims, wherein when it is determined that the difference exceeds the threshold criterion, the threshold criterion is updated based on the current set of one or more monitored parameters.

10. A method according to any of the preceding claims, wherein when it is determined that the difference does not exceed the threshold criterion, the threshold criterion is not updated based on the current set of one or more monitored parameters.

11. A method according to any of claims 8 to 10, wherein the threshold criterion is derived from the set of one or more monitored parameters in question using a formula. CQQfcan / cznz / a / uli 12. A method according to claim 11, wherein the formula scales and / or shifts the set of one or more monitored parameters in question.

13. A method according to claim 12, when dependent on claim 6, wherein the formula scales and / or shifts a module of a vector formed from the set of monitored parameters in question.

14. A method according to any of the preceding claims, wherein, when it is determined that the difference exceeds the threshold criterion, the method further comprises: determining whether or not a minimum time period has elapsed between obtaining the current set of one or more monitored parameters and obtaining the previous set of one or more monitored parameters; wherein, when it is determined that the minimum time period has elapsed, the current set of one or more monitored parameters is transmitted and / or stored; and wherein, when it is determined that the minimum time period has not elapsed, the current set of one or more monitored parameters is not transmitted and / or stored.

15. A method according to any of the preceding claims, wherein, when it is determined that the difference does not exceed the threshold criterion, the method further comprises: determining whether or not a maximum time period has elapsed between obtaining the current set of one or more monitored parameters and obtaining the previous set of one or more monitored parameters; wherein, when it is determined that the maximum time period has not elapsed, the current set of one or more monitored parameters is not transmitted and / or stored; and wherein, when it is determined that the maximum time period has elapsed, the current set of one or more monitored parameters is transmitted and / or stored.

16. A method according to any of claims 1 to 15, wherein the method comprises operating in a first mode of operation in which the threshold criteria are not used and then operating in a second mode of operation in which the threshold criteria are used.

17. A method according to any of claims 1 to 15, wherein the method comprises operating in a first mode of operation in which the first threshold criteria are used and then operating in a second mode of operation in which the second threshold criteria are used, the second threshold criteria being higher than the first threshold criteria.

18. A method according to any of the preceding claims, wherein the electrical installation comprises a domestic, commercial or industrial installation.

19. A method according to any of the preceding claims, wherein the electrical installation comprises an electrical installation for a house, office, school, college, university, hotel, hospital, shop, restaurant, station, airport or manufacturing plant.

20. A system for monitoring parameters of an electrical installation, the system comprising: processing circuitry configured to perform a plurality of successive iterations of a process in which a difference between a current set of one or more monitored parameters of the electrical installation and a previous set of one or more monitored parameters of the electrical installation is compared to a threshold criterion; wherein, when the processing circuitry determines that the difference exceeds the threshold criterion, the processing circuitry is configured to transmit and / or store the current set of one or more monitored parameters; and wherein, when the processing circuitry determines that the difference does not exceed the threshold criterion, the processing circuitry is configured not to transmit and / or store the current set of one or more monitored parameters; and