How to obtain measurement data from a meter

Abstract

A method for obtaining measurement data from a meter includes using the meter to measure raw data at one or more measurement locations around the system, receiving a request for measurement data, determining whether the measurement data can be derived from the raw data based on the known measurement capabilities of the meter, and, if it has been determined that the requested measurement data can be derived from the raw data, generating the requested measurement data from the raw data. The method may be particularly suitable for use in utility meters such as smart utility meters, and is not exclusive to use in electricity, gas, or water meters.

Description

Technical Field

[0001] Field The present disclosure relates to a method for obtaining measurement data from a meter for use in a utility meter such as a smart utility meter, and more particularly, but not exclusively, for use in an electric, gas, or water meter.

Background Art

[0002] Background Modern electric meters are capable of supporting tens of thousands of distinct measurement types. Accurately characterizing and differentiating each measurement type is a necessary task for the metering specifications applied to modern meters. Existing metering specifications such as ANSI C12.19, DLMS / COSEM, and IEC 61968-9 each provide a way to specify and differentiate many different measurement types.

[0003] Current practice in metering systems and systems for persisting metered data is to expose only those data types that the meter is configured to calculate and persist or store. However, there are scenarios where processes in downstream systems such as applications running on the meter or head-end equipment benefit from accessing data values of data types that are not persisted or stored but are derivable from the persisted or stored data values. In addition, most calculated data values are determined over several hours overnight and transmitted via the metering network, which generates a large amount of network traffic that needs to be managed.

Summary of the Invention

Means for Solving the Problems

[0004] Summary According to an aspect of the present disclosure, a method for obtaining measurement data from a meter is provided, the method comprising: using the meter to measure raw data at one or more measurement locations around the system; Receiving a request for measurement data, To determine whether measurement data can be derived from raw data based on the known measurement capabilities of the meter, This includes generating the requested measurement data from the raw data, depending on whether it has been determined that the requested measurement data can be derived from the raw data.

[0005] Such a method may eliminate the need to transmit measurement data from the meter to the headend equipment via a network at predetermined times or intervals. Such a method may also, upon request, allow for the acquisition of measurement data of any data type that can be derived from the raw data measured by the meter. In particular, such a method does not require pre-calculation of measurement data of all data types supported by the meter.

[0006] Optionally, the known measurement capabilities of the meter include multiple different measurement types, each measurement type including a corresponding data type that defines a corresponding transformation for generating measurement data from raw data.

[0007] Optionally, each transformation includes a corresponding initial aggregation operation and one or more corresponding functions, the initial aggregation operation being performed on the raw data to form the base data, and the one or more corresponding functions acting on the base data to generate the measured data.

[0008] Optionally, multiple initial aggregation operations corresponding to multiple measurement types are stored in the meter's memory.

[0009] Optionally, generating the requested measurement data from raw data is possible. Based on the requested measurement data, select a measurement type from several measurement types, The meter includes performing an initial aggregation operation on the raw data corresponding to the selected measurement type to determine the base data.

[0010] Optionally, the method includes storing base data in the meter's memory.

[0011] Optionally, multiple functions corresponding to multiple measurement types are stored in the meter's memory.

[0012] Optionally, generating the requested measurement data from raw data is possible. In a meter, the measurement data is derived from base data using one or more functions corresponding to the selected measurement type, This includes transmitting measurement data derived from a meter to a headend device located away from the meter.

[0013] Such a method can avoid any requirement to transmit base data from the meter to the headend equipment at predetermined times or intervals.

[0014] Optionally, multiple functions corresponding to multiple measurement types are stored in the memory of a head-end device located away from the meter.

[0015] Optionally, generating the requested measurement data from raw data is possible. Transmitting base data to head-end equipment located away from the meter, The headend device includes deriving the requested measurement data from base data using one or more functions corresponding to the selected measurement type.

[0016] Such a method avoids any requirement that the meter derive the requested measurement data from base data using one or more functions corresponding to the selected measurement type.

[0017] Optionally, the method includes storing base data in the memory of the headend device.

[0018] Optionally, the method includes publicly presenting or showing a plurality of different measurement types of the known measurement functionality of the meter to the user of the meter and / or the head-end device, so that the user can select which measurement type should be used to derive measurement data from the raw data measured by the meter.

[0019] Optionally, the measurement functionality of the meter includes a plurality of different measurement types supported by the meter, each measurement type including a corresponding measurement point, a corresponding measurement unit, a corresponding data type, and a corresponding measurement type name, the corresponding measurement point defining the corresponding measurement location, the corresponding measurement unit defining the corresponding measurement unit of the measurement data, the corresponding data type defining the corresponding conversion for generating measurement data from raw data, and the corresponding measurement type name being composed of a name associated with the corresponding measurement point, a name associated with the corresponding measurement unit, and a name associated with the corresponding data type.

[0020] Optionally, receiving a request for measurement data includes receiving a request for measurement data of a desired measurement type name.

[0021] Optionally, determining whether measurement data can be derived from raw data based on the known measurement capabilities of the meter includes comparing the desired measurement type name with each measurement type name of the plurality of measurement type names and determining that the measurement data can be derived from raw data in response to determining that the desired measurement type name matches one of the measurement type names.

[0022] Optionally, the measurement functionality of the meter includes a plurality of different codes of measurement specifications, each code being composed of values of code attributes associated with a corresponding measurement point, a corresponding measurement unit, and a corresponding data type.

[0023] Optionally, receiving a request for measurement data includes receiving a request for measurement data of a desired measurement specification code.

[0024] Optionally, determining whether measurement data is derivable from raw data based on the known measurement functionality of the meter includes comparing the desired measurement specification code with each of a plurality of measurement specification codes and determining that the measurement data is derivable from the raw data in response to determining that the desired measurement specification code matches one of the measurement specification codes.

[0025] Optionally, the measurement specification is an IEC 61968-9 measurement specification, and the code for the measurement specification is a reading type code defined according to the IEC 61968-9 measurement specification.

[0026] Optionally, the measurement specification is an ANSI C12.19 measurement specification, and the code for the measurement specification is a code defined according to the relational table structure of the ANSI C12.19 measurement specification, or

[0027] Optionally, the measurement specification is a COSEM measurement specification, and the code for the measurement specification is a class and / or parameter defined according to the COSEM measurement specification.

[0028] Optionally, the initial aggregation operation includes averaging the raw data over an aggregation time interval.

[0029] Optionally, the initial aggregation operation includes integrating the raw data over an aggregation time interval.

[0030] Optionally, the initial aggregation operation includes selecting an instantaneous raw data value, e.g., the instantaneous raw data value at the end of an aggregation time interval.

[0031] Optionally, the initial aggregation operation includes determining a count of events derived from the raw data over an aggregation time interval.

[0032] Optionally, "raw data" includes raw time series data, "base data" includes base time series data, and "measured data" includes measured time series data.

[0033] Optionally, raw time series data includes one or more arrays of raw time-to-time pairs, base time series data includes one or more arrays of base time-to-time pairs, and measured time series data includes one or more arrays of measured time-to-time pairs.

[0034] Optionally, each of the one or more functions that act on the base data to generate measurement data includes a time series function.

[0035] Optionally, the meter may be configured to be further controlled to measure the flow of electricity, gas, water, or sewage.

[0036] According to one aspect of this disclosure, a method is provided for use in defining measurement types supported by a meter, wherein the meter is configured to measure raw data at a measurement location in the system, the measurement type defines the characteristics of the measurement data that can be derived from the raw data, and the method is This includes defining a measurement type, which includes measurement points, units of measurement, data type, and measurement type name. The measurement point defines the measurement location. The unit of measurement defines the unit of measurement for the measurement data. The data type defines the transformation for generating measured data from raw data. The measurement type name consists of a name associated with the measurement point, a name associated with the unit of measurement, and a name associated with the data type.

[0037] Using such a method, the data type of any measurement type supported by the meter can be clearly defined in terms of conversion.

[0038] Optionally, the transformation defines an initial aggregation operation and one or more functions, the initial aggregation operation is performed on the raw data to form the base data, and the one or more functions act on the base data to generate the measured data.

[0039] Optionally, the meter is configured to perform initial aggregation operations on the raw data, for example, by signal processing of the raw data.

[0040] Optionally, the initial aggregation operation includes averaging the raw data over an aggregation time interval.

[0041] Optionally, the initial aggregation operation includes integrating the raw data over an aggregation time interval.

[0042] Optionally, the initial aggregation operation includes selecting instantaneous raw data values, for example, instantaneous raw data values ​​at the end of the aggregation time interval.

[0043] Optionally, the initial aggregation operation includes determining the count of events derived from the raw data over the aggregation time interval.

[0044] Optionally, "raw data" includes raw time series data, "base data" includes base time series data, and "measured data" includes measured time series data.

[0045] Optionally, raw time series data includes one or more arrays of raw time-to-time pairs, base time series data includes one or more arrays of base time-to-time pairs, and measured time series data includes one or more arrays of measured time-to-time pairs.

[0046] Optionally, each of the one or more functions that act on the base data to generate the measured data includes a time series function. A time series function is a mathematical operation performed on time series data that may contain a list or array of time-versus-value pairs. In practice, an electric meter acts on the data continuously. However, if a time series function is applied to the raw time series data measured by the meter, the mathematical result will be the same. Therefore, it should be understood that such a method treats the raw time series data measured by the meter as a time series object to which one or more time series functions can be applied. Such a method allows specifying the data types supported by the meter by identifying or specifying the initial aggregation operations performed by the meter to generate the base time series data, and by specifying one or more time series functions that are performed on the base time series data to generate the measured time series data.

[0047] Optionally, the method includes defining a measurement specification code corresponding to the measurement type, the measurement specification code consisting of the measurement point, the unit of measurement, and the value of the code attribute associated with the data type.

[0048] Optionally, the measurement specification is the IEC 61968-9 measurement specification, and the measurement specification code is the read type code defined according to the IEC 61968-9 measurement specification.

[0049] Optionally, the measurement specification is the ANSI C12.19 measurement specification, and the measurement specification code is a code defined according to the relational table structure of the ANSI C12.19 measurement specification.

[0050] Optionally, the measurement specification is a COSEM measurement specification, and the measurement specification code is a class and / or parameter defined according to the COSEM measurement specification.

[0051] According to aspects of this disclosure, a method is provided for obtaining measurement data from raw data measured by a meter, the method being: The method used when defining the measurement types supported by the meter, as described above, Receiving a request for measurement data, including the measurement type name and / or measurement specification code, This includes, in response to a request, deriving measurement data from raw data according to a transformation defined by the data type, which corresponds to the measurement type name and / or the measurement specification code.

[0052] Optionally, deriving measurement data from raw data includes performing initial aggregation operations on the raw data to form base data, and then applying one or more functions to the base data to generate measurement data, where one or more functions are defined according to transformations defined by the data type.

[0053] Optionally, the meter is configured to perform initial aggregation operations on the raw data, for example, by signal processing of the raw data.

[0054] The method is optional. The process involves performing an initial aggregation operation on the meter to determine the base data from the raw data measured by the meter, and Using one or more functions in the meter to derive measurement data from base data, This includes transmitting measurement data derived from a meter to a headend device located away from the meter.

[0055] Optionally, one or more functions are stored in the meter's memory.

[0056] The method is optional. The process involves performing an initial aggregation operation on the meter to determine the base data from the raw data measured by the meter, and Transmitting base data from the meter to head-end equipment located away from the meter, This includes using one or more functions in the headend device to derive measurement data from base data.

[0057] Optionally, one or more functions are stored in the headend device's memory.

[0058] According to one aspect of the present disclosure, a method is provided for defining the measurement functionality of a meter, the method comprising defining several different measurement types supported by the meter, each of the several different measurement types being defined in accordance with the method described above.

[0059] According to one aspect of this disclosure, a measurement type data object is provided for defining the measurement types supported by the meter, the meter is configured to measure raw data at the measurement location of the system, the measurement type defines the characteristics of the measurement data that can be derived from the raw data, and the measurement type data object is Measurement points and Units of measurement, Data type, A measurement type name consisting of a name associated with a measurement point, a name associated with a unit of measurement, and a name associated with a data type, A measurement type data object where the measurement point defines the measurement location, the measurement unit defines the unit of measurement for the measurement data, and the data type defines the transformation for generating measurement data from raw data.

[0060] Optionally, the meter may be configured to be further controlled to measure the flow of electricity, gas, water, or sewage.

[0061] It should be understood that one or more of the optional features of any one of the aforementioned aspects of the Disclosure may be combined with one or more of the optional features of any other aforementioned aspects of the Disclosure.

[0062] Here, we will explain, with reference to the diagram, a method for obtaining measurement data from the meter, as a purely non-exclusive example. [Brief explanation of the drawing]

[0063] Brief explanation of the drawing [Figure 1] This is a schematic diagram of the weighing system. [Figure 2] This flowchart shows the methods used to determine the measurement functionality of a meter. [Figure 3] Figure 2 is a flowchart that provides a more detailed explanation of the method used to determine the measurement functionality of the meter. [Figure 4A] This is a causal relationship graph that shows the data type conversion from base time series data called "averageBase" to intermediate time series data called "meanAggregateInterval," and the conversion from the intermediate time series data "meanAggregateInterval" to measured time series data called "maxAggregateMacroPeriod." [Figure 4B] Figure 4A shows the plot of the base time series data "averageBase". [Figure 4C] Figure 4A shows a plot of the intermediate time series data "meanAggregateInterval". [Figure 4D] Figure 4A shows a plot of the measured time series data "maxAggregateMacroPeriod". [Figure 5] This is a causal relationship graph illustrating the first alternative data type conversion. [Figure 6] This is a causal relationship graph illustrating the second alternative data type conversion. [Figure 7] This is a causal graph illustrating the third alternative data type conversion. [Figure 8] This is a causal relationship graph illustrating the fourth alternative data type conversion. [Figure 9A]This shows an example set of measurement points for a power meter, and the corresponding values ​​for the cimPhases attribute of the cim code in the IEC 61968-9 measurement specification. [Figure 9B] This shows several different groups of measurement points, each of which includes a different selection of one or more measurement points from the set of measurement points in Figure 9A. [Figure 10A] The first part of an illustrative set of measurement units for power meters, and the corresponding cim code attribute values ​​from the IEC 61968-9 measurement specification are shown. [Figure 10B] Figure 10A shows a second portion of the exemplary set of units of measurement. [Figure 11A] The first part of an illustrative set of data types for power meters, and the corresponding cim code attribute values ​​from the IEC 61968-9 measurement specification are shown. [Figure 11B] The second portion of the exemplary set of data types shown in Figure 11A is presented. [Figure 12] This shows a set of different class / group combinations of measurement point groups (similar to those discussed with reference to Figure 9B), measurement unit classes (similar to those discussed with reference to Figures 10A and 10B), and data type classes (similar to those discussed with reference to Figures 11A and 11B). [Figure 13A] Figure 12 is a screenshot of the first part of the Wolfram Language environment during execution of the Wolfram Language script for the "maximumMacro" class / group combination. [Figure 13B] Figure 12 is a screenshot of the second part of the Wolfram Language environment during execution of the Wolfram Language script for the "maximumMacro" class / group combination. [Figure 13C] Figure 12 is a screenshot of the third part of the Wolfram Language environment during execution of the Wolfram Language script for the "maximumMacro" class / group combination. [Figure 13D]Figure 12 is a screenshot of the fourth part of the Wolfram Language environment during execution of the Wolfram Language script for the "maximumMacro" class / group combination. [Figure 14] Figure 12 shows the selection of measurement type names and CIM codes corresponding to the "maximumMacro" class / group combination. [Modes for carrying out the invention]

[0064] Detailed description of the drawing Referring first to Figure 1, a metering system, shown as a whole, is shown, which includes a plurality of meters 4 and a headend device shown as a whole, shown as 6. The plurality of meters 4 and the headend device 6 are configured to communicate via a network 8, which may be wired and / or wireless. In the specific example of metering system 2 in Figure 1, metering system 2 may optionally be configured to further control the flow of electricity. In other embodiments, it should be understood that metering system 2 may be configured to further control the flow of any utility such as gas, water, or sewage. The meters 4 may be the same or different.

[0065] Referring to Figure 2, a method, collectively shown as 200, is shown for determining the measurement functionality of any one of the meters 4, where the meter 4 is configured to measure raw data at one or more measurement locations around the system, and the measurement functionality of the meter 4 defines the characteristics of the measurement data that can be derived from the raw data. Method 200 is, Identifying a set of different measurement points supported by meter 4 (202), wherein each measurement point defines one or more measurement locations, and for each measurement point in a set of different measurement points, a corresponding name is identified or defined (202), Identifying a set of different units of measurement supported by meter 4 (204), wherein each unit of measurement defines a unit of measurement for measurement data, and for each unit of measurement in a set of different units of measurement, a corresponding name is identified or defined (204), Identifying a set of different data types supported by meter 4 (206), where each data type defines a transformation for generating measurement data from raw data, and for each data type in the set of different data types, identifying or defining a corresponding name (206), For each measurement point, identify the corresponding value for one or more attributes of the measurement specification code (212), For each unit of measurement, identify the corresponding value for each of one or more attributes of the code (214), For each data type, identify the corresponding value for one or more attributes of the code (216), (208) Determining different combinations of measurement points, measurement units, and data types to be selected from different sets of measurement points, different sets of measurement units, and different sets of data types, respectively; and for each combination, determining the corresponding code for the corresponding measurement type and measurement specification, wherein the measurement type includes the corresponding measurement point, the corresponding measurement unit, the corresponding data type, and the corresponding measurement type name, which consists of the name associated with the corresponding measurement point, the name associated with the corresponding measurement unit, and the name associated with the corresponding data type; and the corresponding code for the measurement specification consists of the code attribute values ​​associated with the corresponding measurement point, the corresponding measurement unit, and the corresponding data type.

[0066] As shown in detail in Figure 3, determining different combinations of measurement points, units of measurement, and data types (208) is, (208a) to define a set of different measurement point groups, wherein each measurement point group includes a different selection of one or more measurement points from a set of different measurement points, Associating each unit of measurement in a different set of units of measurement with a corresponding unit of measurement class (208b), Associating each data type in a set of different data types with a corresponding data type class (208c), Defining a set of different class / group combinations, where each of the different class / group combinations includes a different combination of measurement point groups, measurement unit classes, and data type classes (208d), (208e) For each class / group combination from a set of different class / group combinations, determine all possible combinations of i) a measurement point associated with the class / group combination, ii) a unit of measurement associated with the class / group combination, and iii) a data type associated with the class / group combination; and for each combination, determine the corresponding measurement type and the corresponding code for the measurement specification, wherein the measurement type includes the corresponding measurement point, the corresponding unit of measurement, the corresponding data type, and the corresponding measurement type name, which consists of the name associated with the corresponding measurement point, the name associated with the corresponding unit of measurement, and the name associated with the corresponding data type; and the corresponding code for the measurement specification consists of the code attribute values ​​associated with the corresponding measurement point, the corresponding unit of measurement, and the corresponding data type.

[0067] Here, the steps of the second method 200 will be described in more detail below, referring to Figures 4A to 14, and for specific cases of power meters, referring to the reading type code or CIM code of the IEC 61968-9 measurement specification.

[0068] Figure 4A illustrates how data types define the transformation for generating measured data from raw data. Each meter 4 performs initial signal processing on the raw data to generate base data. Specifically, the raw data measured by any one of the meters 4 includes raw time series data (i.e., an array of raw time-vs. pairs to which a time series function can be applied), and each meter 4 performs initial signal processing on the raw time series data to generate base time series data. Generally, base data represents a first aggregation of the raw data. The interval used for aggregating the raw data to generate base data is not specified, as it may vary across systems. There are several types of base data defined by the initial signal processing performed by the meter 4. Base data can represent the mean of sampled values ​​over an interval, the integral of sampled values ​​over an interval, instantaneous measurements (often samples at the end of an interval), or counts of events over an interval. These different types of base data are treated independently, as different time series functions are applicable to each type.

[0069] The data type defines a time series function or sequence of time series functions that are applied to base time series data to generate measured time series data. For example, Figures 4A to 4D illustrate transformations defined by the data type from base time series data containing mean values ​​at 1-minute intervals. The base time series data is first transformed into intermediate time series data containing mean values ​​averaged over 15-minute intervals, and then into monthly maximum measured time series data. More specifically, Figure 4A is a causal graph illustrating the transformation from 1-minute averaged base time series data called "averageBase" shown in Figure 4B to 15-minute averaged intermediate time series data called "meanAggregateInterval" shown in Figure 4C, using the first time series function "TimeSeriesAggregate[input, 15min, Mean]", and the transformation from the intermediate time series data "meanAggregateInterval" to monthly maximum measured time series data called "maxAggregateMacroPeriod" shown in Figure 4D, using the second time series function "TimeSeriesAggregate[input, Month, Max]". Therefore, in order to specify the data types supported by a given meter 4, it is necessary to identify the base time series data generated by meter 4 and specify the transformations performed on the base time series data. Figures 5, 6, 7, and 8 show four alternative causal relationship graphs illustrating the associated transformations for mean-based, integral-based, instantaneous-based, and count-based time series data, respectively. It should be understood that the causal relationship graphs in Figures 4A, 5, 6, 7, and 8 are not exhaustive and represent only some of the most common data types supported by meter 4.

[0070] Referring here to Figure 9A, an exemplary set of different measurement points for a power meter and the corresponding values ​​of the cimPhases attribute of the cim code in the IEC 61968-9 measurement specification are shown. It should be understood that the different measurement points in Figure 9A are derived from the meter manufacturer's specifications. However, neither the cim code attribute nor its value is specified in the meter manufacturer's specifications. Therefore, the cim code attribute and its value are derived using engineering knowledge from the units of measurement specified in the meter manufacturer's specifications. It should also be understood that the different measurement points shown in Figure 9A are not necessarily exhaustive. Figure 9B shows several different measurement point groups, each measurement point group containing a different selection of one or more measurement points from the set of different measurement points in Figure 9A. Each measurement point group is defined using engineering knowledge and should be understood to represent a common group of measurement locations encountered in a power distribution system. It should also be understood that the different measurement point groups shown in Figure 9B are not necessarily exhaustive.

[0071] Referring here to Figures 10A and 10B, an exemplary set of different units of measurement for a power meter and the corresponding cim code attribute values ​​in the IEC 61968-9 measurement specification are shown. It should be understood that the different units of measurement in Figures 10A and 10B are derived from the meter manufacturer's specifications. However, neither the cim code attributes nor their values ​​are specified in the meter manufacturer's specifications. Therefore, the cim code attributes and their values ​​are derived using engineering knowledge from the units of measurement specified in the meter manufacturer's specifications. It should also be understood that the different units of measurement shown in Figures 10A and 10B are not exhaustive. It should also be understood that each unit of measurement is assigned to a corresponding unit of measurement class using engineering knowledge. For example, in Figures 10A and 10B, all units of measurement are assigned to the unit of measurement class "threePhaseEnergy". Each unit of measurement class is defined using engineering knowledge, and it should be understood that all units of measurement related to the same unit of measurement class are closely related. While all measurement units in Figures 10A and 10B are assigned to the measurement unit class "threePhaseEnergy," it should be understood that in reality, an exemplary set of different measurement units may include many more measurement units than those shown in Figures 10A and 10B, and that different measurement units may be assigned to different measurement unit classes. Specifically, measurement units may be assigned to measurement unit classes that include "threePhaseEnergy," "threePhasePower," "calculatedNetEnergy," "demandTimestamp," and "powerFactor."

[0072] Referring here to Figures 11A and 11B, an exemplary set of different data types for a power meter and the corresponding cim code attribute values ​​in the IEC 61968-9 measurement specification are shown. It should be understood that the different data types in Figures 11A and 11B are derived from the meter manufacturer's specifications. However, neither the cim code attributes nor their values ​​are specified in the meter manufacturer's specifications. Therefore, the cim code attributes and their values ​​are derived using engineering knowledge from the data types specified in the meter manufacturer's specifications. It should also be understood that the different data types shown in Figures 11A and 11B are not exhaustive. It should also be understood that each data type is assigned to a corresponding data type class using engineering knowledge. For example, in Figures 11A and 11B, the data types are assigned to different data type classes, including "integratedMacro", "accumlutatingMacro", "mme", "maneVA", "minimumMacro", "maximumMacro", and "manMacro". It should be understood that each data type class is defined using engineering knowledge, and that all data types belonging to the same data type class are closely related.

[0073] Referring here to Figure 12, a set of different class / group combinations of measurement point groups (similar to those discussed with reference to Figure 9B), measurement unit classes (similar to those discussed with reference to Figures 10A and 10B), and data type classes (similar to those discussed with reference to Figures 11A and 11B) is shown. It should be understood that the different class / group combinations shown in Figure 12 are derived from the engineering knowledge of the operation of the power meter in step 208d of Method 200 in Figure 3. It should also be understood that the set of different class / group combinations shown in Figure 12 is not necessarily exhaustive.

[0074] Figures 13A to 13D are screenshots of different parts of the Wolfram Language environment during the execution of a Wolfram Language script, for one case of the class / group combination from Figure 12 called "maximumMacro," which corresponds to the combination of the measurement point group "oneThroughFour," the measurement unit class "threePhasePower," and the data type class "maximumMacro." Different measurement points and corresponding cim codes corresponding to the measurement point group "oneThroughFour," different measurement units and corresponding cim codes corresponding to the measurement unit class "threePhasePower," and different data types and corresponding cim codes corresponding to the data type class "maximumMacro" are loaded into the Wolfram Language environment as shown in Figure 13A. All different members of the "maximumMacro" data type class, the "threePhasePower" measurement unit class, and the "oneThroughFour" measurement point group are enumerated as shown in Figure 13B. Next, all possible combinations of different measurement points and corresponding CIM codes corresponding to the measurement point group "oneThroughFour", different measurement units and corresponding CIM codes corresponding to the measurement unit class "threePhasePower", and different data types and corresponding CIM codes corresponding to the data type class "maximumMacro" are generated. The possible combinations of different measurement points corresponding to the measurement point group "oneThroughFour", different measurement units corresponding to the measurement unit class "threePhasePower", and different data types corresponding to the data type class "maximumMacro" are shown in Figure 13C. As shown in Figure 13D, for each combination of measurement point, measurement unit, and data type class, a measurement type name is then generated or constructed from the name associated with the corresponding measurement point, the name associated with the corresponding measurement unit, and the name associated with the corresponding data type.

[0075] Next, the measurement type name and cim code for each combination of different measurement points corresponding to the measurement point group "oneThroughFour", different measurement units corresponding to the measurement unit class "threePhasePower", and different data types corresponding to the data type class "maximumMacro" corresponding to the "maximumMacro" class / group combination are stored. Figure 14 shows a small selection of the measurement type names and cim codes for each combination of different measurement points corresponding to the measurement point group "oneThroughFour", different measurement units corresponding to the measurement unit class "threePhasePower", and different data types corresponding to the data type class "maximumMacro" corresponding to the "maximumMacro" class / group combination. Figure 14 also shows the corresponding "cimDescription" for each combination, which is generated simply by converting the numeric cim code value into a string enumeration as defined in the IEC 61968-9 measurement specification. Accordingly, it should be understood that the measurement type name and "cimDescription" are equivalent for each combination. Figure 14 does not show all measurement type names and CIM codes corresponding to the "maximumMacro" class / group; it should be understood that there may be hundreds of measurement type names and CIM codes corresponding to the "maximumMacro" class / group.

[0076] Next, using a Wolfram Language script, all measurement type names and CIM codes for all other class / group combinations defined in Figure 12 are generated and stored to define the functionality of meter 4 and the corresponding set of CIM codes.

[0077] It should be understood that the method described above, used to determine the measurement functionality of a meter, can not only define the functionality of the meter more completely than the manufacturer's meter specifications, but can also define the CIM code for each measurement type. Furthermore, those skilled in the art will understand that essentially the same method can be used to define the measurement functionality of a meter in terms of the codes of measurement specifications other than IEC 61968-9, for example, in terms of the codes of ANSI C12.19 or COSEM.

[0078] Furthermore, using the same method, it may be possible to define corresponding codes for each measurement type for multiple measurement specifications, such as multiple measurement specifications selected from IEC 61968-9, ANSI C12.19, and COSEM measurement specifications, thereby enabling the direct construction and maintenance of mappings across different measurement specifications. For example, the method is: For each measurement point, identify or define a value corresponding to each of one or more attributes of the further code of the further measurement specification, For each unit of measurement, identify or define a value corresponding to each of one or more attributes of the further code of the further measurement specification, For each data type, identify or define a value corresponding to each of one or more attributes of the further code of the further measurement specification, This may include determining a corresponding further code for each combination of measurement point, measurement unit, and data type, which consists of values ​​of further code attributes associated with the corresponding measurement point, corresponding measurement unit, and corresponding data type.

[0079] Further measurement specifications may be IEC 61968-9 measurement specifications, and further codes for further measurement specifications may be read type codes defined according to IEC 61968-9 measurement specifications.

[0080] Further measurement specifications may be ANSI C12.19 measurement specifications, and the codes for these further measurement specifications may be codes defined according to the relational table structure of the ANSI C12.19 measurement specifications.

[0081] Further measurement specifications may be COSEM measurement specifications, and further codes of these further measurement specifications may be classes and / or parameters defined according to the COSEM measurement specifications.

[0082] Such a method may be used to determine the interoperability between the meter 4 and the headend device 6, where the functionality of the headend device 6 is defined using codes of a given measurement specification. For example, for a headend device 6 having functionality defined as multiple codes of a given measurement specification, the method used to identify the interoperability between the headend device 6 and the meter 4 of the weighing system 2 is: Using the method described above, determine the code associated with the measurement functionality of meter 4 for the same given measurement specifications, This involves comparing the code associated with the known functionality of the headend device 6 with the determined code associated with the determined measurement functionality of the meter 4, This may include determining, based on the results of the comparison, whether the headend device 6 and the meter 4 are mutually operable.

[0083] Using the determined measurement type and / or the determined measurement specification code, it is possible to determine whether the desired measurement type is supported by the meter and to obtain measurement data of the desired measurement type from the raw data measured by the meter.

[0084] For example, a method for obtaining measurement data from raw data measured by a meter is: To receive a request for measurement data, including the desired measurement type name and / or the desired code for the measurement specification, The meter determines whether a desired measurement type is supported by comparing the desired measurement type name with each of the determined measurement type names among a set of determined measurement type names, and / or the desired measurement specification code with each of the determined measurement specification codes among a set of determined measurement specification codes. This may include determining that a desired measurement type name matches one of the determined measurement type names, and / or that a desired measurement specification code matches one of the determined measurement specification codes, and deriving measurement data from raw data according to a transformation defined by the data type corresponding to the determined measurement type name that matches the desired measurement type name, and / or according to a transformation defined by the data type corresponding to the determined measurement specification code that matches the desired measurement specification code.

[0085] It should be understood that when meter 4 or headend device 6 receives a request for a specific measurement type, the measurement data is determined by first performing an initial aggregation operation on the raw data in the meter to calculate the base data. As previously mentioned with reference to the causal relationship graph examples in Figures 4A, 5, 6, 7, and 8, the sequence of time series functions that must be applied to calculate the requested measurement data from the base data is defined by a sequence of time series functions that traverses from the base data vertex of the relevant causal relationship graph to the requested measurement data vertex of the relevant causal relationship graph. As discussed above, the method can completely define the functionality of the meter. In other words, the method can define all measurement types supported by the meter, thereby making it possible to derive measurement data for all measurement types supported by the meter from the raw data measured by the meter.

[0086] Meter 4 can derive measurement data from base data using a related sequence of time-series functions, and the derived measurement data can be transmitted from meter 4 to headend device 6. This may require meter 4 to calculate, persist, or store base data and measurement data, but may avoid any requirement for meter 4 to transmit base data to headend device 6.

[0087] Alternatively, base data may be transmitted from meter 4 to headend device 6, which may derive measurement data from the base data using a sequence of relevant time-series functions. This may require meter 4 to calculate, persist, and store the base data, and that the base data be transmitted from meter 4 to headend device 6, but it may avoid any requirement on meter 4 to derive measurement data from the base data.

[0088] The method may include disclosing or indicating the determined measurement types to the users of the meter 4 and / or headend device 6 so that the users can select which one or more measurement types should be used to derive measurement data from the raw data measured by the meter 4.

[0089] Those skilled in the art will understand that the method described above can be used to generate a model for defining the measurement functionality of a meter, and that the meter is configured to measure raw data at one or more measurement locations around the system, the model defines the characteristics of the measurement data that can be derived from the raw data, and the model includes several different measurement type data objects, each measurement type data object is, Corresponding measurement points, Corresponding units of measurement, Corresponding data types, It includes a corresponding measurement type name, which consists of the name associated with the corresponding measurement point, the name associated with the corresponding unit of measurement, and the name associated with the corresponding data type, The corresponding measurement point defines the corresponding measurement location, the corresponding measurement unit defines the measurement unit of the corresponding measurement data, and the corresponding data type defines the corresponding transformation for generating the corresponding measurement data from the corresponding raw data.

[0090] Those skilled in the art will understand that various modifications are possible to any of the above methods. For example, although the above method used to determine the measuring functionality of a meter is described in relation to an electric meter 4 and metering system 2, those skilled in the art will understand that a similar method may be used to determine the measuring functionality of a meter in relation to any utility meter 4 and metering system 2, such as gas, water, or sewage.

[0091] While several specific initial aggregation operations for determining base data from raw data are described above, the described initial aggregation operations are not necessarily exhaustive, and other initial aggregation operations are possible. For example, instead of base data representing instantaneous measurements at the end of the aggregation interval, base data may represent instantaneous measurements at any defined time within the aggregation interval, such as at the beginning or in the middle of the aggregation interval.

[0092] The various sequences of time series functions described with reference to Figures 4A to 8 are not necessarily exhaustive.

[0093] The various measurement points described with reference to Figure 9A are not necessarily exhaustive. The various measurement point groups described with reference to Figure 9B are not necessarily exhaustive. The various units of measurement described with reference to Figures 10A and 10B are not necessarily exhaustive. The various classes of units of measurement described with reference to Figures 10A and 10B are not necessarily exhaustive. The various data types described with reference to Figures 11A and 11B are not necessarily exhaustive. The various classes of data types described with reference to Figures 11A and 11B are not necessarily exhaustive.

[0094] It should be understood that the embodiments of this disclosure are illustrative only and the claims are not limited to the embodiments. Those skilled in the art will be able to modify the embodiments of this disclosure and contemplate alternative forms to the embodiments that are included within the scope of the appended claims. Each feature described above and / or shown in any of the appended drawings may be incorporated into any embodiment, either alone or in any suitable combination with any other features described and / or shown in the drawings. In particular, those skilled in the art will understand that one or more features of the embodiments described above and / or shown in any of the appended drawings may produce an effect or provide an advantage when used separately from one or more other features of the same embodiment, and that different combinations of features other than the specific combinations of features of the embodiments described above and / or shown in any of the appended drawings are possible.

[0095] Those skilled in the art will understand that in the foregoing description and the attached claims, positional terms such as “above,” “alongside,” and “side” are made with reference to the attached drawings. These terms are used for ease of reference and are not intended to be inherently limiting. These terms should be understood to refer to the object as it is oriented as shown in the attached drawings.

[0096] The use of the terms “equipped with” or “including” when used in relation to the features of an embodiment does not exclude other features or steps. The use of the terms “one (a)” or “one (an)” when used in relation to the features of an embodiment of the present disclosure does not exclude the possibility that the embodiment may include more than one such feature.

[0097] The use of reference numerals in the claims should not be construed as limiting the scope of the claims.

Claims

1. A method for obtaining measurement data from a meter, wherein the method is Using the aforementioned meter, raw data is measured at one or more measurement locations around the system, Receiving a request for measurement data, The determination of whether the measurement data can be derived from the raw data is based on the known measurement functionality of the meter, In response to the determination that the requested measurement data can be derived from the raw data, the requested measurement data is generated from the raw data. A method that includes this.

2. The method according to claim 1, wherein the known measurement functionality of the meter includes a plurality of different measurement types, each measurement type including a corresponding data type that defines a corresponding transformation for generating the measurement data from the raw data.

3. The method according to claim 2, wherein each transformation includes a corresponding initial aggregation operation and one or more corresponding functions, the initial aggregation operation being performed on the raw data to form base data, and the one or more corresponding functions acting on the base data to generate the measurement data.

4. The method according to claim 3, wherein the plurality of initial aggregation operations corresponding to the plurality of measurement types are stored in the memory of the meter.

5. Generating the requested measurement data from the raw data is Based on the requested measurement data, a measurement type is selected from the plurality of measurement types. In the meter, the initial aggregation operation corresponding to the selected measurement type is performed on the raw data to determine the base data, The method according to claim 3 or 4, including the method described in claim 3 or 4.

6. The method according to any one of claims 3 to 5, comprising storing the base data in the memory of the meter.

7. The method according to any one of claims 3 to 6, wherein the plurality of functions corresponding to the plurality of measurement types are stored in the memory of the meter.

8. Generating the requested measurement data from the raw data is In the meter, the measurement data is derived from the base data using one or more functions corresponding to the selected measurement type. The measurement data derived from the meter is transmitted to a headend device located away from the meter. The method according to any one of claims 3 to 7, including the method described in any one of claims 3 to 7.

9. The method according to any one of claims 3 to 6, wherein the plurality of functions corresponding to the plurality of measurement types are stored in the memory of a headend device located away from the meter.

10. Generating the requested measurement data from the raw data is The base data is transmitted to a head-end device located away from the meter. The headend device derives the requested measurement data from the base data using one or more functions corresponding to the selected measurement type, The method according to any one of claims 3 to 6 or 9, including the following:

11. The method according to claim 9 or 10, further comprising storing the base data in the memory of the headend device.

12. The initial aggregation operation described above is: The raw data is averaged over an aggregated time interval. Integrating the aforementioned raw data over an aggregated time interval, Selecting instantaneous raw data values, for example, instantaneous raw data values ​​at the end of the aggregation time interval, or To determine the number of events derived from the raw data over the aggregated time interval, The method according to any one of claims 3 to 11, including the method described in any one of claims 3 to 11.

13. The method according to any one of claims 3 to 12, wherein the raw data includes raw time series data, the base data includes base time series data, and the measurement data includes measurement time series data.

14. The method according to claim 13, wherein the raw time series data comprises one or more arrays of raw time-converted pairs, the base time series data comprises one or more arrays of base time-converted pairs, and the measured time series data comprises one or more arrays of measured time-converted pairs.

15. The method according to any one of claims 3 to 14, wherein each of the one or more functions that act on the base data to generate the measurement data includes a time series function.

16. The method according to any one of claims 2 to 11, comprising disclosing or indicating to the user of the meter and / or the headend device the plurality of different measurement types of the known measurement functionality of the meter so that the user can select which measurement type should be used to derive the measurement data from the raw data measured by the meter.

17. The measurement functionality of the meter includes a plurality of different measurement types supported by the meter, each measurement type including a corresponding measurement point, a corresponding unit of measurement, a corresponding data type, and a corresponding measurement type name, wherein the corresponding measurement point defines the corresponding measurement location, the corresponding unit of measurement defines the corresponding unit of measurement of the measurement data, the corresponding data type defines the corresponding transformation for generating the measurement data from the raw data, and the corresponding measurement type name consists of a name associated with the corresponding measurement point, a name associated with the corresponding unit of measurement, and a name associated with the corresponding data type. Receiving the aforementioned request for measurement data includes receiving a request for measurement data of a desired measurement type name, Determining whether the measurement data can be derived from the raw data based on the known measurement function of the meter involves comparing the desired measurement type name with each of the multiple measurement type names, and determining that the measurement data can be derived from the raw data if it is determined that the desired measurement type name matches one of the measurement type names. The method according to any one of claims 1 to 16, including the method described in any one of claims 1 to 16.

18. The measurement functionality of the meter includes a plurality of different codes of measurement specifications, each code consisting of a value of a code attribute associated with the corresponding measurement point, the corresponding unit of measurement, and the corresponding data type. Receiving the aforementioned request for measurement data includes receiving a request for measurement data of a desired measurement specification code. Determining whether the measurement data can be derived from the raw data based on the known measurement functionality of the meter involves comparing the desired measurement specification code with each of the plurality of measurement specification codes, and determining that the measurement data can be derived from the raw data if it is determined that the desired measurement specification code matches one of the measurement specification codes. The method according to any one of claims 1 to 17, including the method described in any one of claims 1 to 17.

19. The measurement specification is the IEC 61968-9 measurement specification, and the code in the measurement specification is a read type code defined in accordance with the IEC 61968-9 measurement specification. The measurement specification is an ANSI C12.19 measurement specification, and the code of the measurement specification is a code defined according to the relational table structure of the ANSI C12.19 measurement specification, or The measurement specification is a COSEM measurement specification, and the code of the measurement specification is a class and / or parameter defined according to the COSEM measurement specification. The method according to claim 18.

20. The method according to any one of claims 1 to 19, wherein the meter is optionally configured to be further controlled to measure the flow of electricity, gas, water, or sewage.

21. A method used to define the measurement types supported by a meter, wherein the meter is configured to measure raw data at a measurement location in the system, the measurement type defines the characteristics of the measurement data that can be derived from the raw data, and the method is This includes defining a measurement type, which includes measurement points, units of measurement, data type, and measurement type name. The aforementioned measurement point defines the measurement location, The unit of measurement defines the unit of measurement of the measurement data, The aforementioned data type defines a transformation for generating the measurement data from the raw data, A method wherein the measurement type name comprises a name associated with the measurement point, a name associated with the measurement unit, and a name associated with the data type.

22. The method according to claim 21, wherein the transformation defines an initial aggregation operation and one or more functions, the initial aggregation operation is performed on the raw data to form base data, and the one or more functions act on the base data to generate the measurement data.

23. The method according to claim 22, wherein the meter is configured to perform the initial aggregation operation on the raw data, for example, by signal processing of the raw data.

24. The initial aggregation operation described above is: The raw data is averaged over an aggregated time interval. Integrating the aforementioned raw data over an aggregated time interval, Selecting instantaneous raw data values, for example, instantaneous raw data values ​​at the end of the aggregation time interval, or To determine the number of events derived from the raw data over the aggregated time interval, The method according to claim 22 or 23, including the method described in claim 22 or 23.

25. The method according to any one of claims 22 to 24, wherein the raw data includes raw time series data, the base data includes base time series data, and the measurement data includes measurement time series data.

26. The method according to claim 25, wherein the raw time series data comprises one or more arrays of raw time-converted pairs, the base time series data comprises one or more arrays of base time-converted pairs, and the measured time series data comprises one or more arrays of measured time-converted pairs.

27. The method according to any one of claims 22 to 26, wherein each of the one or more functions that act on the base data to generate the measurement data includes a time series function.

28. The method according to any one of claims 21 to 27, comprising defining a code for a measurement specification corresponding to the measurement type, wherein the code for the measurement specification comprises the measurement point, the measurement unit, and the value of a code attribute associated with the data type.

29. The measurement specification is the IEC 61968-9 measurement specification, and the code in the measurement specification is a read type code defined in accordance with the IEC 61968-9 measurement specification. The measurement specification is an ANSI C12.19 measurement specification, and the code of the measurement specification is a code defined according to the relational table structure of the ANSI C12.19 measurement specification, or The method according to claim 28, wherein the measurement specification is a COSEM measurement specification, and the code of the measurement specification is a class and / or parameter defined according to the COSEM measurement specification.

30. A method for obtaining measurement data from raw data measured by a meter, wherein the method is: A method for defining the measurement type supported by a meter, according to any one of claims 21 to 29, Receiving a request for measurement data for the aforementioned measurement type name and / or measurement specification code, In response to the above request, the measurement data is derived from the raw data according to the conversion defined by the data type corresponding to the measurement type name and / or the measurement specification code, Methods that include...

31. The method according to claim 30, wherein deriving the measurement data from the raw data comprises performing an initial aggregation operation on the raw data to form base data, and applying one or more functions to the base data to generate the measurement data, wherein the one or more functions are defined according to the transformation defined by the data type.

32. The method according to claim 31, wherein the meter is configured to perform the initial aggregation operation on the raw data, for example, by signal processing of the raw data.

33. In the meter, the initial aggregation operation is performed on the raw data measured by the meter to determine the base data in the meter. The meter uses one or more functions to derive the measurement data from the base data, The measurement data derived from the meter is transmitted to a headend device located away from the meter. The method according to claim 31 or 32, including the method described in claim 31 or 32.

34. The method according to claim 33, wherein the one or more functions are stored in the memory of the meter.

35. In the meter, the initial aggregation operation is performed on the raw data measured by the meter to determine the base data in the meter. The base data from the meter is transmitted to a headend device located away from the meter. In the headend device, the measurement data is derived from the base data using one or more functions, The method according to claim 31 or 32, including the method described in claim 31 or 32.

36. The method according to claim 35, wherein the one or more functions are stored in the memory of the headend device.

37. A method for defining the measurement functionality of a meter, the method comprising defining a plurality of different measurement types supported by the meter, each of the plurality of different measurement types being defined according to the method of any one of claims 21 to 29.

38. A measurement type data object for defining the measurement types supported by a meter, wherein the meter is configured to measure raw data at a measurement location in the system, the measurement type defines the characteristics of the measurement data that can be derived from the raw data, and the measurement type data object is Measurement points and Units of measurement, Data type, A measurement type name comprising the name associated with the measurement point, the name associated with the measurement unit, and the name associated with the data type, A measurement type data object in which the measurement point defines the measurement location, the measurement unit defines the measurement unit of the measurement data, and the data type defines the transformation for generating the measurement data from the raw data.

39. A method used to define a measurement type supported by a meter, according to any one of claims 21 to 29, wherein the method is a method for obtaining measurement data from a meter, according to any one of claims 30 to 36, the method is a method for defining the measurement functionality of a meter, according to claim 37, or a measurement type data object, according to claim 38, wherein the meter is configured to measure and optionally further control the flow of electricity, gas, water, or sewage.

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