Method for obtaining measurement data from meter

Abstract

A method for obtaining measurement data from a meter includes measuring raw data at one or more measurement locations around a system using the meter, receiving a request for the measurement data, determining whether the measurement data can be derived from the raw data based on a known measurement function of the meter, and determining whether the measurement data can be derived from the raw data based on a known measurement function of the meter. And in response to determining 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 applicable to utility meters, such as smart utility meters, and in particular, but not exclusively, to electricity meters, gas meters, or water meters.

Description

TECHNICAL FIELD

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

[0002] Modern electricity meters are capable of supporting thousands of different measurement types. Accurately characterising and distinguishing each measurement type is a task required by any metrology specification applied to modern meters. Existing metrology specifications such as ANSI C12.19, DLMS / COSEM and IEC 61968-9 each provide a method of specifying and distinguishing many different measurement types.

[0003] Current practice in metrology systems and systems that persistently store metrology data only exposes the data types that the meter is configured to calculate and persistently store or store. However, there are scenarios in which an application running on the meter or a process in a downstream system such as a front-end device would benefit from access to data values of a data type that is not persistently stored or stored, but is able to be derived from persistently stored or stored data values. Furthermore, most calculated data values are determined and sent over the metrology network in the hours after midnight. This creates a large amount of network traffic that must be managed. SUMMARY

[0004] According to an aspect of the present disclosure, there is provided a method for obtaining measurement data from a meter, the method comprising:

[0005] measuring raw data at one or more measurement locations around a system using the meter;

[0006] receiving a request for measurement data;

[0007] determining whether the measurement data is derivable from the raw data based on known measurement functions of the meter; and

[0008] generating the requested measurement data from the raw data in response to determining that the requested measurement data is derivable from the raw data.

[0009] Such a method can eliminate the need to send measurement data from a meter to a front-end device over a network at predetermined times or intervals. Such a method can also allow measurement data of any data type to be obtained that is derivable from raw data measured by the meter in response to a request. In particular, such a method does not require all data types of measurement data supported by the meter to be pre-calculated.

[0010] Optionally, the known measurement functions of the meter include a plurality of different measurement types, wherein each measurement type includes a corresponding data type defining a corresponding transformation for generating measurement data from raw data.

[0011] Optionally, each transformation includes a corresponding initial aggregation operation and one or more corresponding functions, wherein the initial aggregation operation is performed on the raw data to generate base data, and wherein the one or more corresponding functions operate on the base data to generate the measurement data.

[0012] Optionally, a plurality of initial aggregation operations corresponding to the plurality of measurement types are stored in a memory of the meter.

[0013] Optionally, generating the requested measurement data from the raw data includes:

[0014] selecting a measurement type from the plurality of measurement types based on the requested measurement data; and

[0015] performing, at the meter, the initial aggregation operation corresponding to the selected measurement type on the raw data to determine the base data.

[0016] Optionally, the method includes storing the base data in a memory of the meter.

[0017] Optionally, a plurality of functions corresponding to the plurality of measurement types are stored in a memory of the meter.

[0018] Optionally, generating the requested measurement data from the raw data includes:

[0019] deriving, at the meter, the measurement data from the base data using the one or more functions corresponding to the selected measurement type; and

[0020] sending the derived measurement data from the meter to a front-end device remote from the meter.

[0021] Such a method can avoid any requirement to send the base data from the meter to the front-end device at a predetermined time or interval.

[0022] Optionally, a plurality of functions corresponding to the plurality of measurement types are stored in a memory of a front-end device remote from the meter.

[0023] Optionally, generating the requested measurement data from the raw data includes:

[0024] sending the base data to a front-end device remote from the meter;

[0025] deriving, at the front-end device, the requested measurement data from the base data using the one or more functions corresponding to the selected measurement type.

[0026] Such a method can avoid any requirement to use one or more functions at the meter corresponding to the selected measurement type to derive the requested measurement data from the base data.

[0027] Optionally, the method comprises storing the base data in a memory of the front-end device.

[0028] Optionally, the method comprises publishing or indicating to a user of the meter and / or the front-end device a plurality of different measurement types of the known measurement functions of the meter to allow the user to select which measurement type should be used to derive the measurement data from the raw data measured by the meter.

[0029] Optionally, the measurement functions of the meter comprise a plurality of different measurement types supported by the meter, each measurement type comprising a corresponding measurement point, a corresponding measurement unit, a corresponding data type and a corresponding measurement type name, wherein the corresponding measurement point defines a corresponding measurement location, the corresponding measurement unit defines a corresponding measurement unit for the measurement data, and the corresponding data type defines a corresponding transformation for generating the measurement data from the raw data, and wherein the corresponding measurement type name is constituted by 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.

[0030] Optionally, receiving the request for the measurement data comprises receiving a request for the measurement data of a desired measurement type name.

[0031] Optionally, determining whether the measurement data is derivable from the raw data based on the known measurement functions of the meter comprises comparing the desired measurement type name with each of a plurality of measurement type names, and in response to determining that the desired measurement type name matches one of the measurement type names, determining that the measurement data is derivable from the raw data.

[0032] Optionally, the measurement functions of the meter comprise a plurality of different codes of the metrological specification, each code being constituted by values of code attributes associated with a corresponding measurement point, a corresponding measurement unit and a corresponding data type.

[0033] Optionally, receiving the request for the measurement data comprises receiving a request for the measurement data of a desired metrological specification code.

[0034] Optionally, determining whether the measurement data is derivable from the raw data based on the known measurement functions of the meter comprises comparing the desired metrological specification code with each of a plurality of metrological specification codes, and in response to determining that the desired metrological specification code matches one of the metrological specification codes, determining that the measurement data is derivable from the raw data.

[0035] Optionally, the metering specification is an IEC 61968-9 metering specification, and the code of the metering specification is a reading type code defined according to the IEC 61968-9 metering specification,

[0036] Optionally, the metering specification is an ANSI C12.19 metering specification, and the code of the metering specification is a code defined according to the relationship table structure of the ANSI C12.19 metering specification, or

[0037] Optionally, the metering specification is a COSEM metering specification, and the code of the metering specification is a class and / or parameter defined according to the COSEM metering specification.

[0038] Optionally, the initial aggregation operation comprises averaging the raw data over the aggregation time interval.

[0039] Optionally, the initial aggregation operation comprises integrating the raw data over the aggregation time interval.

[0040] Optionally, the initial aggregation operation comprises selecting a transient raw data value, for example a transient raw data value at the end of the aggregation time interval.

[0041] Optionally, the initial aggregation operation comprises determining a count of events derived from the raw data over the aggregation time interval.

[0042] Optionally, the raw data comprises raw time series data, the base data comprises base time series data, and the measurement data comprises measurement time series data.

[0043] Optionally, the raw time series data comprises one or more arrays of raw time-value pairs, the base time series data comprises one or more arrays of base time-value pairs, and the measurement time series data comprises one or more arrays of measurement time-value pairs.

[0044] Optionally, each of the one or more functions operating on the base data to generate the measurement data comprises a time series function.

[0045] Optionally, the meter is configured to meter and optionally also to control the flow of electricity, gas, water or sewage.

[0046] According to an aspect of the present disclosure, there is provided a method for defining a measurement type supported by a meter, wherein the meter is configured for measuring raw data at a measurement location of a system, wherein the measurement type defines a characteristic of measurement data derivable from the raw data, and wherein the method comprises:

[0047] defining a measurement type, the measurement type comprising a measurement point, a measurement unit, a data type and a measurement type name,

[0048] wherein the measurement point defines the measurement location,

[0049] wherein the measurement unit defines a measurement unit for the measurement data,

[0050] wherein the data type defines a transformation for generating the measurement data from the raw data, and

[0051] wherein the measurement type name is composed of a name associated with the measurement point, a name associated with the measurement unit, and a name associated with the data type.

[0052] Such a method can be used to explicitly define the data type of any measurement type supported by a meter in terms of a transformation.

[0053] Optionally, the transformation defines an initial aggregation operation and one or more functions, wherein the initial aggregation operation is performed on the raw data to form base data, and wherein the one or more functions operate on the base data to generate the measurement data.

[0054] Optionally, the meter is configured to perform the initial aggregation operation on the raw data, e.g. by signal processing of the raw data.

[0055] Optionally, the initial aggregation operation comprises averaging the raw data over an aggregation time interval.

[0056] Optionally, the initial aggregation operation comprises integrating the raw data over an aggregation time interval.

[0057] Optionally, the initial aggregation operation comprises selecting an instantaneous raw data value, e.g. the instantaneous raw data value at the end of the aggregation time interval.

[0058] Optionally, the initial aggregation operation comprises determining a count of events derived from the raw data over an aggregation time interval.

[0059] Optionally, the raw data comprises raw time series data, the base data comprises base time series data, and the measurement data comprises measurement time series data.

[0060] Optionally, the raw time series data comprises one or more arrays of raw time-value pairs, the base time series data comprises one or more arrays of base time-value pairs, and the measurement time series data comprises one or more arrays of measurement time-value pairs.

[0061] Optionally, operating on the base data to generate each of the one or more functions of measurement data comprises a time series function. A time series function is a mathematical operation performed on time series data, which can comprise a list or array of time-value pairs. In practice, a meter continuously operates on data. However, the mathematical result would be the same if a time series function were applied to the raw time series data measured by the meter. Thus, it will be appreciated that such a method treats the raw time series data measured by the meter as a time series object on which one or more time series functions can be applied. Such a method enables the data type supported by the meter to be specified by identifying or specifying the initial aggregation operation performed by the meter to generate the base time series data, and by specifying one or more time series functions performed on the base time series data to generate the measurement time series data.

[0062] Optionally, the method comprises defining a code of the metrological specification corresponding to the measurement type, wherein the code of the metrological specification consists of values of code attributes associated with the measurement point, the measurement unit and the data type.

[0063] Optionally, the metrological specification is an IEC 61968-9 metrological specification, and the code of the metrological specification is a reading type code defined according to the IEC 61968-9 metrological specification.

[0064] Optionally, the metrological specification is an ANSI C12.19 metrological specification, and the code of the metrological specification is a code defined according to the relational table structure of the ANSI C12.19 metrological specification.

[0065] Optionally, the metrological specification is a COSEM metrological specification, and the code of the metrological specification is a class and / or parameter defined according to the COSEM metrological specification.

[0066] According to an aspect of the present disclosure, there is provided a method for obtaining measurement data from raw data measured by a meter, the method comprising:

[0067] a method for defining a measurement type supported by a meter as described above;

[0068] receiving a request for measurement data of the measurement type name and / or measurement data of the metrological specification code; and

[0069] in response to the request, deriving the measurement data from the raw data according to the transformation defined by the data type corresponding to the measurement type name and / or corresponding to the metrological specification code.

[0070] Optionally, deriving the measurement data from the raw data comprises performing an initial aggregation operation on the raw data to form the 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 in accordance with a transformation defined by the data type.

[0071] Optionally, the meter is configured to perform the initial aggregation operation on the raw data, e.g. by signal processing of the raw data.

[0072] Optionally, the method comprises:

[0073] performing an initial aggregation operation on the raw data measured by the meter at the meter to determine the base data at the meter;

[0074] deriving the measurement data from the base data at the meter using the one or more functions; and

[0075] sending the derived measurement data from the meter to a head-end device remote from the meter.

[0076] Optionally, the one or more functions are stored in a memory of the meter.

[0077] Optionally, the method comprises:

[0078] performing an initial aggregation operation on the raw data measured by the meter at the meter to determine the base data at the meter;

[0079] sending the base data from the meter to a head-end device remote from the meter; and

[0080] deriving the measurement data from the base data at the head-end device using the one or more functions.

[0081] Optionally, the one or more functions are stored in a memory of the head-end device.

[0082] According to an aspect of the disclosure, there is provided a method for defining a measurement function of a meter, the method comprising defining a plurality of different measurement types supported by the meter, wherein each measurement type of the plurality of different measurement types is defined in accordance with the method as described above.

[0083] According to an aspect of the disclosure, there is provided a measurement type data object for defining a measurement type supported by a meter, wherein the meter is configured for measuring raw data at a measurement location of a system, wherein the measurement type defines characteristics of measurement data derivable from the raw data, and wherein the measurement type data object comprises:

[0084] a measurement point;

[0085] measurement unit;

[0086] data type; and

[0087] a measurement type name consisting of a name associated with the measurement point, a name associated with the measurement unit, and a name associated with the data type,

[0088] wherein the measurement point defines the measurement location, the measurement unit defines the measurement unit for the measurement data, and the data type defines a transformation for generating the measurement data from the raw data.

[0089] Optionally, the meter is configured to meter and optionally also control the flow of electricity, gas, water, or sewage.

[0090] It will be appreciated that any one or more of the optional features of any one of the foregoing aspects of the disclosure can be combined with any one or more of the optional features of any one of the other foregoing aspects of the disclosure. BRIEF DESCRIPTION OF DRAWINGS

[0091] A method for obtaining measurement data from a meter will now be described by way of non-limiting example only with reference to the accompanying drawings in which:

[0092] Figure 1 is a schematic diagram of a metering system;

[0093] Figure 2 is a flow chart illustrating a method for determining the measurement function of a meter;

[0094] Figure 3 is a flow chart illustrating in more detail the method for determining the measurement function of a meter Figure 2

[0095] Figure 4A is a causal diagram depicting the data type transformation of base time series data, referred to as “averageBase”, into intermediate time series data, referred to as “meanAggregateInterval”, and the transformation of the intermediate time series data “meanAggregateInterval” into measurement time series data, referred to as “maxAggregateMacroPeriod”;

[0096] Figure 4B is a plot of the base time series data “averageBase” of Figure 4A

[0097] Figure 4C is a plot of the base time series data “averageBase” of Figure 4A ​​a plot of the intermediate time series data "meanAggregateInterval" of

[0098] Figure 4D is Figure 4A a plot of the measurement time series data "maxAggregateMacroPeriod" of

[0099] Figure 5 is a causal graph depicting a first alternative data type transformation;

[0100] Figure 6 is a causal graph depicting a second alternative data type transformation;

[0101] Figure 7 is a causal graph depicting a third alternative data type transformation;

[0102] Figure 8 is a causal graph depicting a fourth alternative data type transformation;

[0103] Figure 9A shows an example set of measurement points of an electric meter and corresponding values of the cimPhases attribute of the cim code of the IEC 61968-9 metering specification;

[0104] Figure 9B shows a plurality of different measurement point groups, each measurement point group comprising Figure 9A a different selection of one or more measurement points of the set of measurement points of

[0105] Figure 10A shows a first part of an example set of measurement units of an electric meter and values of corresponding cim code attributes of the IEC 61968-9 metering specification;

[0106] Figure 10B shows a second part of the example set of measurement units of Figure 10A

[0107] Figure 11A shows a first part of an example set of data types of an electric meter and values of corresponding cim code attributes of the IEC 61968-9 metering specification;

[0108] Figure 11B shows a second part of the example set of data types of Figure 11A

[0109] Figure 12 shows measurement point groups (similar to those discussed with reference to Figure 9B measurement unit categories (similar to those discussed with reference to Figure 10A and Figure 10B data type categories (similar to those discussed with reference to Figure 11A ​​and Figure 11B a set of different category / group combinations of those discussed above;

[0110] Figure 13A is a screenshot of a first portion of a Wolfram Language environment during execution of a Wolfram Language script for the "maximumMacro" category / group combination of Figure 12

[0111] Figure 13B is a screenshot of a second portion of a Wolfram Language environment during execution of a Wolfram Language script for the "maximumMacro" category / group combination of Figure 12

[0112] Figure 13C is a screenshot of a third portion of a Wolfram Language environment during execution of a Wolfram Language script for the "maximumMacro" category / group combination of Figure 12

[0113] Figure 13D is a screenshot of a fourth portion of a Wolfram Language environment during execution of a Wolfram Language script for the "maximumMacro" category / group combination of Figure 12

[0114] shows a selection of measurement type names and cim codes corresponding to the "maximumMacro" category / group combination of Figure 14 Figure 12 DETAILED DESCRIPTION

[0115] Referring initially to Figure 1 , a metering system, generally designated 2, is shown that includes a plurality of meters 4 and a headend device, generally designated 6. The plurality of meters 4 and the headend device 6 are configured to communicate across a network 8, which can be wired and / or wireless. In the specific example of the metering system 2 of Figure 1 , the metering system 2 can be configured to meter and possibly also control the flow of electricity. It will be appreciated that in other embodiments, the metering system 2 can be configured to meter and possibly also control the flow of any utility, such as gas, water, sewage, etc. The meters 4 can be the same or different.

[0116] Referring to Figure 2 , a method, generally designated 200, for use in determining a measurement function of any of the meters 4 is shown, wherein the meters 4 are configured for measuring raw data at one or more measurement locations around a system, and wherein the measurement function of the meters 4 defines a characteristic of measurement data that is able to be derived from the raw data. The method 200 includes:​​​​​

[0117] identifying 202 a set of different measurement points supported by the meter 4, each measurement point defining one or more measurement locations, and identifying or defining a corresponding name for each measurement point in the set of different measurement points;

[0118] identifying 204 a set of different measurement units supported by the meter 4, each measurement unit defining a measurement unit for measurement data, and identifying or defining a corresponding name for each measurement unit in the set of different measurement units;

[0119] identifying 206 a set of different data types supported by the meter 4, each data type defining a transformation for generating measurement data from raw data, and identifying or defining a corresponding name for each data type in the set of different data types;

[0120] for each measurement point, identifying 212 a corresponding value for each of one or more attributes of a metering specification code;

[0121] for each measurement unit, identifying 214 a corresponding value for each of one or more attributes of a code;

[0122] for each data type, identifying 216 a corresponding value for each of one or more attributes of a code; and

[0123] determining 208 different combinations of measurement points, measurement units and data types selected from the set of different measurement points, the set of different measurement units and the set of different data types, respectively, and for each combination determining a corresponding measurement type and a corresponding code of a metering specification, wherein the measurement type comprises the corresponding measurement point, the corresponding measurement unit, the corresponding data type and a corresponding measurement type name consisting 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 wherein the corresponding code of the metering specification consists of the code attribute values associated with the corresponding measurement point, the corresponding measurement unit and the corresponding data type.

[0124] As shown in more detail in Figure 3 determining 208 the different combinations of measurement points, measurement units and data types comprises:

[0125] defining 208a a set of different measurement point groups, each measurement point group comprising a different selection of one or more measurement points in the set of different measurement points;

[0126] associating 208b each measurement unit in the set of different measurement units with a corresponding measurement unit category;

[0127] each data type in the set of different data types is associated 208c with a corresponding data type category;

[0128] a set of different category / group combinations is defined 208d, each different category / group combination comprising a different combination of a measurement point group, a measurement unit category and a data type category; and

[0129] for each category / group combination in the set of different category / group combinations, all possible combinations of i) measurement points associated with the category / group combination; ii) measurement units associated with the category / group combination; and iii) data types associated with the category / group combination are determined 208e, and for each combination a corresponding measurement type and a corresponding code of metrological specification are determined, wherein the measurement type comprises the corresponding measurement points, the corresponding measurement units, the corresponding data types, and a corresponding measurement type name consisting of the names associated with the corresponding measurement points, the names associated with the corresponding measurement units, the names associated with the corresponding data types, and wherein the corresponding code of metrological specification consists of the code attribute values associated with the corresponding measurement points, the corresponding measurement units, and the corresponding data types.

[0130] Reference will now be made to the following drawings Figures 4A-14 The steps of the second method 200 will now be described in more detail for the specific case of an electricity meter for which the reading type code or cim code of the IEC 61968-9 metrological specification is used for reference.

[0131] Figure 4A It is shown how the data type defines a transformation for generating the measurement data from the raw data. Each meter 4 performs initial signal processing on the raw data to generate base data. In particular, the raw data measured by any one of the meters 4 comprises raw time series data (i.e. an array of raw time-value 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. Overall, the base data represents a first aggregation of the raw data. The interval for the aggregation of the raw data to generate the base data can differ between systems and is therefore unspecified. There are several types of base data defined by the initial signal processing performed by the meters 4. The base data can represent an average of the sampled values over an interval, an integral of the sampled values over an interval, an instantaneous measurement (typically a sample at the end of the interval) or a count of events over an interval. These different types of base data are processed independently as different time series functions are applied to each type.

[0132] The data type defines a time series function or a sequence of time series functions that are applied to the base time series data to generate the measurement time series data. For example, Figures 4A-4DTransformations defined by data types from base time series data comprising average values at one minute intervals are shown. The base time series data is first transformed into intermediate time series data comprising average values averaged over 15 minute intervals, and then into monthly maximum measured time series data. More specifically, Figure 4A is a causal graph that depicts the transformation of one minute average base time series data, referred to as "averageBase", shown in Figure 4B to fifteen minute average intermediate time series data, referred to as "meanAggregateInterval", shown in Figure 4C and the transformation of the intermediate time series data "meanAggregateInterval" to monthly maximum measured time series data, referred to as "maxAggregateMacroPeriod", shown in Figure 4D using a second time series function "TimeSeriesAggregate[input, Month, Max]". Thus, 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 the meter 4, and to specify the transformations performed on the base time series data. Figure 5 , Figure 6 , Figure 7 and Figure 8 show four alternative causal graphs that illustrate the associated transformations for average, integral, instantaneous and count base time series data, respectively. It should be understood that Figure 4A , Figure 5 , Figure 6 , Figure 7 and Figure 8 the causal graphs of are not exhaustive, but rather they represent some of the most common data types supported by meters 4.

[0133] Referring now to Figure 9A , an example set of different measurement points for an electricity meter and corresponding values for the cimPhases attribute of the cim code of the IEC 61968-9 metering specification are shown. It should be understood that Figure 9A the different measurement points in Figure 9A are not necessarily exhaustive. Figure 9B shows a plurality of different measurement point groups, each comprising Figure 9Adifferent selections of one or more of the different measurement points in the set of different measurement points. It should be appreciated that each measurement point group is defined using engineering knowledge and represents a common group of measurement locations encountered by electrical distribution systems. It should also be appreciated that, Figure 9B the different measurement point groups shown in

[0134] Reference is now made to Figure 10A and Figure 10B showing an example set of different measurement units for an electric meter and the values of the corresponding cimCode attributes of the IEC 61968-9 metering specification. It should be appreciated that, Figure 10A and Figure 10B the different measurement units in Figure 10A and Figure 10B are derived from the meter manufacturer’s specification. However, neither the cimCode attributes nor their values are specified in the meter manufacturer’s specification. Accordingly, the cimCode attributes and their values are derived from the measurement units specified in the meter manufacturer’s specification using engineering knowledge. It should also be appreciated that, Figure 10A and Figure 10B the different measurement units shown in Figure 10A and Figure 10B are not exhaustive. It should also be appreciated that each measurement unit is assigned to a corresponding measurement unit category using engineering knowledge. For example, in Figure 11A and Figure 11B all of the measurement units are assigned to the measurement unit category “threePhaseEnergy”. It should be appreciated that each measurement unit category is defined using engineering knowledge and that all measurement units related to the same measurement unit category are closely related. It should also be appreciated that although

[0135] Reference is now made to Figure 11A and Figure 11B showing an example set of different data types for an electric meter and the values of the corresponding cimCode attributes of the IEC 61968-9 metering specification. It should be appreciated that, Figure 11A and Figure 11BThe different data types in 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 from the data types specified in the meter manufacturer's specifications using engineering knowledge. It should also be understood that Figure 11A and Figure 11B The different data types shown in are not exhaustive. It should also be understood that engineering knowledge is used to assign each data type to a corresponding data type category. For example, in Figure 12 and Figure 9B In

[15] , data types are assigned to different data type categories, including "integratedMacro", "accumlutatingMacro", "mme", "meanVA", "minimumMacro", "maximumMacro", and "meanMacro". It should be understood that each data type category is defined using engineering knowledge, and all data types associated with the same data type category are closely related.

[0136] Now refer to Figure 10A , shows a set of measurement points (similar to the reference Figure 10B discussed), measurement unit categories (similar to those in reference Figure 11A and Figure 11B discussed) and data type categories (similar to those in reference Figure 12 and Figure 3 It should be understood that Figure 12 The different category / group combinations shown in Figures 13A-13D The method 200 step 208d is derived from the engineering knowledge of the operation of the electric meter. It should also be understood that Figure 12 The set of different category / group combinations shown in is not necessarily exhaustive.

[0137] Figure 13A Is for those from Figure 13Bcorresponding to the measurement point group "oneThroughFour", the different measurement units corresponding to the measurement unit category "threePhasePower", and the different data types corresponding to the data type category "maximumMacro" are read into the Wolfram Language environment as shown in Figure 13C Figure 13D The different members of the "maximumMacro" data type category, the "threePhasePower" measurement unit category, and the "oneThroughFour" measurement point group are listed as shown in Figure 13D All possible combinations of the different measurement points corresponding to the measurement point group "oneThroughFour", the different measurement units corresponding to the measurement unit category "threePhasePower", and the different data types corresponding to the data type category "maximumMacro" are then generated. The possible combinations of the different measurement points corresponding to the measurement point group "oneThroughFour", the different measurement units corresponding to the measurement unit category "threePhasePower", and the different data types corresponding to the data type category "maximumMacro" are shown in Figure 14 Figure 14 For each combination of measurement point, measurement unit, and data type category, 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 as shown in

[0138] The measurement type names and cim codes for each combination of the different measurement points corresponding to the measurement point group "oneThroughFour", the different measurement units corresponding to the measurement unit category "threePhasePower", and the different data types corresponding to the data type category "maximumMacro" corresponding to the "maximumMacro" category / group combination are then stored. Figure 14A small selection of measurement type names and cim codes for each combination corresponding to different measurement points of the measurement point group "oneThroughFour", different measurement units of the measurement unit class "threePhasePower", and different data types of the data type class "maximumMacro" in combination with the "maximumMacro" class / group are shown. Figure 12 A corresponding "cimDescription" for each combination is also shown, where the cimDescription is generated by simply transforming the numerical cim code values into their string enumerations, as defined by the IEC 61968-9 metering specification. Thus, it will be appreciated that the measurement type name and the "cimDescription" are equivalent for each combination. It will be appreciated that, Figure 4A All measurement type names and cim codes corresponding to the "maximumMacro" class / group are not shown, and there can be hundreds of measurement type names and cim codes corresponding to the "maximumMacro" class / group.

[0139] The Wolfram language script is then used to generate and store all measurement type names and cim codes corresponding to all other class / group combinations defined in the Figure 5 IEC 61968-9 metering specification, in order to define the functionality of the meter 4 and the corresponding set of cim codes.

[0140] It will be appreciated that the above-described method for determining the measurement functionality of a meter not only can define the functionality of the meter more comprehensively than the manufacturer's meter specification, but also can define the corresponding cim codes for each measurement type. Furthermore, it will be appreciated by those of ordinary skill in the art that essentially the same method can be used to define the measurement functionality of a meter according to the codes of metering specifications other than the IEC 61968-9 metering specification, such as according to the codes of the ANSI C12.19 metering specification, or according to the codes of the COSEM metering specification.

[0141] Furthermore, the same method can be used to define the corresponding codes for each measurement type for multiple metering specifications, such as multiple metering specifications selected from the IEC 61968-9 metering specification, the ANSI C12.19 metering specification, and the COSEM metering specification, thereby allowing direct mappings to be created and maintained across different metering specifications. For example, the method can include:

[0142] identifying or defining a corresponding value for each of one or more attributes of an additional code for an additional metering specification for each measurement point;

[0143] for each data type, identifying or defining a corresponding value for each of one or more attributes of the further code of the further metrology specification; and

[0144] for each data type, identifying or defining a corresponding value for each of one or more attributes of the further code of the further metrology specification; and

[0145] for each combination of measurement point, measurement unit and data type, determining a corresponding further code of the further metrology specification, the corresponding further code of the further metrology specification consisting of values of further code attributes associated with the corresponding measurement point, the corresponding measurement unit and the corresponding data type.

[0146] The further metrology specification can be an IEC 61968-9 metrology specification, and the further code of the further metrology specification can be a reading type code defined according to the IEC 61968-9 metrology specification.

[0147] The further metrology specification can be an ANSI C12.19 metrology specification, and the further code of the further metrology specification can be a code defined according to the relationship table structure of the ANSI C12.19 metrology specification.

[0148] The further metrology specification can be a COSEM metrology specification, and the further code of the further metrology specification can be a class and / or parameter defined according to the COSEM metrology specification.

[0149] Such a method can be used to determine interoperability between a meter 4 and a front-end device 6, where the functionality of the front-end device 6 is defined using codes of a given metrology specification. For example, for a front-end device 6 having functionality defined as a plurality of codes of a given metrology specification, a method for identifying interoperability between a meter 4 of a metrology system 2 and the front-end device 6 can comprise:

[0150] determining, using the method as described above, a code associated with a measurement function of the meter 4 for the same given metrology specification;

[0151] comparing the code associated with the known functionality of the front-end device 6 and the determined code associated with the determined measurement function of the meter 4; and

[0152] determining whether the front-end device 6 and the meter 4 are interoperable based on a result of the comparison.

[0153] The determined measurement type and / or the determined metrology specification code can be used to determine whether a meter supports a desired measurement type, and to obtain measurement data of the desired measurement type from raw data measured by the meter.

[0154] For example, a method for obtaining measurement data from raw data measured by a meter can comprise:

[0155] receiving a request for measurement data of a desired measurement type name and / or measurement data of a desired code of a metering specification;

[0156] determining whether the meter supports the desired measurement type by comparing the desired measurement type name to each of the determined plurality of measurement type names and / or by comparing the desired metering specification code to each of the determined plurality of metering specification codes; and

[0157] in response to determining that the desired measurement type name matches one of the determined measurement type names and / or the desired metering specification code matches one of the determined metering specification codes, deriving the measurement data from the raw data according to a transformation defined by a data type corresponding to the determined measurement type name that matches the desired measurement type name and / or according to a transformation defined by a data type corresponding to the determined metering specification code that matches the desired metering specification code.

[0158] It will be appreciated that when a meter 4 or a front-end device 6 receives a request for a particular measurement type, the measurement data is determined by first performing an initial aggregation operation on the raw data at the meter to calculate base data. As previously described with reference to the examples of the causal graphs of Figure 6 、 Figure 7 、 Figure 8 、 Figures 4A-8 and Figure 9A , the sequence of time series functions that must be applied to calculate the requested measurement data from the base data is defined by the sequence of time series functions that are traversed from the base data vertex of the relevant causal graph to the requested measurement data vertex of the relevant causal graph. As described above, this approach can define the functionality of the meter completely. In other words, this approach can define all of the measurement types that the meter supports, thereby allowing measurement data for all of the measurement types that the meter supports to be derived from the raw data measured by the meter.

[0159] The meter 4 can use the relevant sequence of time series functions to derive the measurement data from the base data, and the derived measurement data can be sent from the meter 4 to the front-end device 6. This can require the meter 4 to calculate and persist store or store the base data and the measurement data, but can avoid any requirement for the meter 4 to send the base data to the front-end device 6.

[0160] Alternatively, the base data can be sent from the meter 4 to the headend device 6, and the headend device 6 can use the relevant sequence of time series functions to derive the measurement data from the base data. This can require the meter 4 to calculate and persist store or store the base data, and require the base data to be sent from the meter 4 to the headend device 6, but can avoid any requirement for the meter 4 to derive the measurement data from the base data.

[0161] The method can comprise publishing or indicating the determined measurement types to a user of the meter 4 and / or the headend device 6 to allow the user to select which measurement type or types should be used to derive the measurement data from the raw data measured by the meter 4.

[0162] The person of ordinary skill in the art will appreciate that the above-described methods can be used to generate a model for defining a measurement function of a meter, wherein the meter is configured for measuring raw data at one or more measurement locations around a system, wherein the model defines characteristics of measurement data that is derivable from the raw data, and wherein the model comprises a plurality of different measurement type data objects, wherein each measurement type data object comprises:

[0163] a corresponding measurement point;

[0164] a corresponding measurement unit;

[0165] a corresponding data type; and

[0166] a corresponding measurement type name consisting 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,

[0167] wherein the corresponding measurement point defines the corresponding measurement location, the corresponding measurement unit defines a unit of measurement for the corresponding measurement data, and the corresponding data type defines a corresponding transformation for generating the corresponding measurement data from corresponding raw data.

[0168] The person of ordinary skill in the art will also appreciate that various modifications can be made to any of the above-described methods. For example, although the above-described methods for determining a measurement function of a meter are described in the context of a metering system 2 and meter 4 for electricity, the person of ordinary skill in the art will appreciate that similar methods can be used to determine a measurement function of a meter in the context of a metering system 2 and meter 4 for any utility, such as gas, water, sewage, etc.

[0169] Although 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, rather than the base data representing instantaneous measurement values at the end of the aggregation interval, the base data can represent instantaneous measurement values at any defined time within the aggregation interval, such as at the beginning or middle of the aggregation interval.

[0170] Reference is made to Figure 9B The different sequences of time series functions described are not necessarily exhaustive.

[0171] Reference is made to Figure 10A The different measurement points described are not necessarily exhaustive. Reference is made to Figure 10B The different measurement point groups described are not necessarily exhaustive. Reference is made to Figure 10A And Figure 10B The different measurement units described are not necessarily exhaustive. Reference is made to Figure 11A And Figure 11B The different measurement unit categories described are not necessarily exhaustive. Reference is made to Figure 11A And Figure 11B The different data types described are not necessarily exhaustive. Reference is made to ​ And ​ The different data type categories described are not necessarily exhaustive.

[0172] It will be appreciated that embodiments of the disclosure are illustrative only and that the claims are not limited to these embodiments. A person skilled in the art will be able to modify the embodiments of the disclosure and envisage alternatives falling within the ambit of the claims. Each feature described above and / or shown in any of the figures can be combined with any other feature(s) whether or not those features are described or shown together in any of the figures. In particular, a person skilled in the art will appreciate that one or more features of the above described and / or shown in any of the figures can produce an effect or provide an advantage when used together with one or more other features of the same embodiment and that different combinations of the features of the above described and / or shown in any of the figures can also be possible.

[0173] A person skilled in the art will appreciate that in the preceding description and appended claims, reference is made to positional terms such as “above”, “along”, “side” etc. with reference to the figures. These terms are used for ease of reference but are not intended to be limiting in nature. These terms are to be understood as referring to the objects when in the orientation as shown in the figures.

[0174] The use of the term "include" or "includes" when used about features of the embodiments does not exclude other features or steps. The use of the term "a" or "an" when used about features of the embodiments of the disclosure does not exclude the possibility that the embodiments can include a plurality of such features.

[0175] The use of reference signs in the claims should not be construed as limiting the scope of the claims by the reference signs in the claims.

Claims

1. A method for obtaining measurement data from a meter, the method comprising: measuring raw data at one or more measurement locations around the system using the instrument; receiving a request for measurement data; determining whether the measurement data can be derived from the raw data based on known measurement capabilities of the meter; as well as In response to determining that the requested measurement data is derivable from the raw data, the requested measurement data is generated from the raw data.

2. The method according to claim 1, wherein The known measurement functionality of the meter comprises a plurality of different measurement types, wherein each measurement type comprises a corresponding data type defining 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, wherein the initial aggregation operation is performed on the raw data to generate base data, and wherein the one or more corresponding functions operate on the base data to generate the measurement data.

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

5. The method according to claim 3 or 4, wherein: Generating the requested measurement data from the raw data comprises: selecting a measurement type from the plurality of measurement types based on the requested measurement data; and The initial aggregation operation corresponding to the selected measurement type is performed on the raw data at the meter to determine the base data.

6. A 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 a memory of the meter.

8. The method according to any one of claims 3 to 7, wherein Generating the requested measurement data from the raw data comprises: deriving the measurement data from the base data at the meter using one or more functions corresponding to the selected measurement type; and The derived measurement data is sent from the meter to a front-end device remote from the meter.

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 a memory of a front-end device remote from the meter.

10. The method according to any one of claims 3 to 6 or 9, wherein Generating the requested measurement data from the raw data comprises: sending the basic data to a front-end device far away from the meter; The requested measurement data is derived from the base data at the front-end device using one or more functions corresponding to the selected measurement type.

11. The method according to claim 9 or 10, comprising storing the basic data in the memory of the front-end device.

12. The method according to any one of claims 3 to 11, wherein The initial aggregation operation includes: averaging the raw data over an aggregation time interval; integrating the raw data over an aggregation time interval; Select an instantaneous raw data value, such as the instantaneous raw data value at the end of the aggregation time interval; or A count of events derived from the raw data within an aggregation time interval is determined.

13. The method according to any one of claims 3 to 12, wherein The original data includes original time series data, the basic data includes basic 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-value pairs, the base time series data comprises one or more arrays of base time-value pairs, and the measured time series data comprises one or more arrays of measured time-value pairs.

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

16. The method according to any one of claims 2 to 11 comprises publishing or indicating the multiple different measurement types of the known measurement functions of the meter to a user of the meter and / or the front-end device to allow the user to select which measurement type should be used to derive the measurement data from the raw data measured by the meter.

17. A method according to any preceding claim, wherein: 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, wherein the corresponding measurement point defines a corresponding measurement location, the corresponding measurement unit defines a corresponding measurement unit for the measurement data, and the corresponding data type defines a corresponding transformation for generating the measurement data from the raw data, and wherein the corresponding measurement type name consists 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, Wherein, receiving a request for measurement data comprises receiving a request for measurement data of a desired measurement type name, and Wherein, determining whether the measurement data can be derived from the raw data based on the known measurement function of the meter includes: comparing the expected measurement type name with each measurement type name in the multiple measurement type names, and in response to determining that the expected measurement type name matches one of the measurement type names, determining that the measurement data can be derived from the raw data.

18. A method according to any one of the preceding claims, wherein The measurement function of the meter includes a plurality of different codes of the metrological specification, each code consisting of a value of a code attribute associated with a corresponding measurement point, a corresponding measurement unit and a corresponding data type, wherein receiving the request for measurement data comprises receiving a request for measurement data of a desired metrology specification code, Wherein, determining whether the measurement data can be derived from the raw data based on the known measurement function of the meter includes: comparing the expected measurement specification code with each of the multiple measurement specification codes, and in response to determining that the expected measurement specification code matches one of the measurement specification codes, determining that the measurement data can be derived from the raw data.

19. The method according to claim 18, in, The metrology specification is the IEC 61968-9 metrology specification, and the metrology specification code is a read type code defined according to the IEC 61968-9 metrology specification, 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, or The metrology specification is a COSEM metrology specification, and the metrology specification code is a category and / or parameter defined according to the COSEM metrology specification.

20. A method according to any one of the preceding claims, wherein The meter is configured to meter and optionally also control the flow of electricity, gas, water or sewage.

21. A method for defining measurement types supported by a meter, wherein: The meter is configured for measuring raw data at a measurement location of the system, wherein the measurement type defines characteristics of measurement data derivable from the raw data, and wherein the method comprises: Define a measurement type, which includes a measurement point, a measurement unit, a data type, and a measurement type name. wherein the measurement point defines the measurement position, wherein the measurement unit defines the measurement unit used for the measurement data, wherein the data type defines a transformation for generating the measurement data from the raw data, and The measurement type name consists of 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, wherein the initial aggregation operation is performed on the raw data to form base data, and wherein the one or more functions operate 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 method according to claim 22 or 23, wherein The initial aggregation operation includes: averaging the raw data over an aggregation time interval; integrating the raw data over an aggregation time interval; Select an instantaneous raw data value, such as the instantaneous raw data value at the end of the aggregation time interval; or A count of events derived from the raw data within an aggregation time interval is determined.

25. The method according to any one of claims 22 to 24, wherein The original data includes original time series data, the basic data includes basic 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-value pairs, the base time series data comprises one or more arrays of base time-value pairs, and the measured time series data comprises one or more arrays of measured time-value pairs.

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

28. The method according to any one of claims 21 to 27, comprising defining a code of a metrology specification corresponding to the measurement type, wherein the code of the metrology specification consists of values ​​of code attributes associated with the measurement point, the measurement unit and the data type.

29. The method according to claim 28, wherein The metrology specification is the IEC 61968-9 metrology specification, and the metrology specification code is a read type code defined according to the IEC 61968-9 metrology specification, 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, or The metrology specification is a COSEM metrology specification, and the metrology specification code is a category and / or parameter defined according to the COSEM metrology specification.

30. A method for obtaining measurement data from raw data measured by an instrument, the method comprising: A method for defining measurement types supported by a meter according to any one of claims 21 to 29; receiving a request for measurement data of the measurement type name and / or measurement data of the metrology specification code; as well as In response to the request, the measurement data is derived from the raw data according to the transformation defined by the data type corresponding to the measurement type name and / or corresponding to the metrology specification code.

31. The method according to claim 30, wherein Deriving the measurement data from the raw data includes 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. The method according to claim 31 or 32, comprising: performing the initial aggregation operation on raw data measured by the meter at the meter to determine the base data at the meter; deriving the measurement data from the base data at the meter using the one or more functions; as well as The derived measurement data is sent from the meter to a front-end device remote from the meter.

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

35. The method according to claim 31 or 32, comprising: performing the initial aggregation operation on raw data measured by the meter at the meter to determine the base data at the meter; sending the basic data from the meter to a front-end device remote from the meter; as well as The measurement data is derived from the base data using the one or more functions at the front-end device.

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

37. A method for defining measurement functionality of a meter, the method comprising defining a plurality of different measurement types supported by the meter, wherein: Each measurement type of the plurality of different measurement types is defined according to the method of any one of claims 21 to 29.

38. A measurement type data object for defining a measurement type supported by a meter, wherein: The meter is configured for measuring raw data at a measurement location of a system, wherein the measurement type defines characteristics of measurement data that can be derived from the raw data, and wherein the measurement type data object comprises: Measuring point; Units of measurement; the type of data; and a measurement type name consisting of a name associated with the measurement point, a name associated with the measurement unit, and a name associated with the data type, Therein, the measurement point defines the measurement location, the measurement unit defines the measurement unit used for the measurement data, and the data type defines a transformation used to generate the measurement data from the raw data.

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

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