COMPUTER-IMPLEMENTED METHOD, SYSTEM AND COMPUTER PROGRAM FOR ELECTRICITY METER READINGS VALIDATION
Description
TECHNICAL FIELD
[0001] The invention relates to a computer-implemented method, system and computer program for electricity meter readings (1) validation, on the basis of which it can be determined whether the readings are plausible or implausible, whereby in certain cases the occurrence of an implausible reading is a prerequisite for detecting a technical malfunction of electricity meters (4) or electricity generator devices (6). The invention relates in particular to the industrial processing of remotely acquired electricity consumption data.
BACKGROUND
[0002] The state of the art is primarily characterized by the fact that it contains the technical infrastructure and related technologies that enable further developments and inventions in the above defined field of technology. In particular, electricity meters (4) and electricity generator devices (6) of different types, wherein meter readings (1) are collected remotely, in-situ or both ways. The term electricity meters (4) is understood to mean electricity meters that operate contain register data (2) or load profile data (3) or both types of data. The term electricity generator devices (6) is understood to alternative power generators, which produce electricity from renewable energy sources, such as, for example, photovoltaic devices. Part of the technique also includes the Description of OBIS code for IEC 62056 standard protocol.
[0003] So far, in the field of remote acquisition and control of electricity consumption, a certain number of technical solutions, systems or methods have been proposed, aimed at the communication of electricity meters (4) with the distribution system server. Such solutions are described, for example, in WO-98/10299, WO-98/10394, EP-A2 0 723 358, WO-99/46564, WO 2003/055031. The solutions are preferably focused on the data transmission system, but are not targeted to control the veracity of the measured and shared data, which is essential to achieve a qualitative industrial result. Possible prior art solutions relating to data veracity include various filters in the data processing process from the data source to the data output, however not algorithms as in the case of the present invention.
SUMMARY
Technical Problem
[0004] Technically, the problem lies in the absence of a mechanism for remote detection of technical problems in electricity meters (4) and electricity generator devices (6), as well as the absence of an automated solution for data quality control, which significantly increases the time and financial costs of collecting and processing meter readings (1). Manual checking implies orders of magnitude higher demands on personnel and/or time to check the received meter readings (1). Uncaught or late captured anomalies lead to adverse consequences, such as late identification of the need for tariff changes by customers, and late identification of technical infrastructure failure.
Solution to Problem
[0005] A computer-implemented method for meter readings (1) validation is proposed as a technical solution to the above technical problem, which provides a flexibly configurable validation of meter readings (1) that are remotely transmitted from the meter so that the validations provide fast and relevant information about the veracity of the meter readings (1). The technical effect of the invention is that, in certain cases, a change in the status of the meter readings (1) enables remote detection of technical malfunctions of electricity metering points (5) or electricity generator devices (6) of different types.
Advantageous Effects of Invention
[0006] The present invention applies for the first time a computer-implemented method for meter readings (1) validation, comprising steps: receiving values of meter readings (1); creating validation classes (8) by selecting at least one validation algorithm (9) from a set of different types of validation algorithms (9); attributing at least one validation class (8) to each electricity tariff (7); implementing the attributed validation class (8) to meter readings (1) to determine whether the values of meter readings (1) are credible or not credible, and reporting the validation results (10).
[0007] The subject invention is an employee invention within the implementation of the research project of SFERA a.s., NFP313020W404 - International Centre of Excellence for Research on Intelligent and Secure Information and Communication Technologies and Systems - Stage II, which aims at industrial research in the field of optimization of data structures of power system elements for modeling and simulation of smart grids and experimental development in the field of tools for modeling and simulation of smart grids.
[0008] A computer-implemented method for meter readings (1) validation is aimed at optimizing the data structures of smart metering system elements, improving data quality, reducing data checking costs, speeding up data checking, and detecting technical problems in the infrastructure. All goals are achieved due to the high degree of automation and the high degree of flexibility of the computer-implemented method for meter readings (1) validation and the validation algorithms themselves (9). The ratio of the number of anomalies captured to the human effort is an order of magnitude higher using an automated method compared to manual inspection. The time required to perform the check is close to zero as validation has become part of the processing of the received data. The advantage of the technical solution is that validations are completed virtually immediately after the meter readings are collected (1), opening up the possibility of speeding up and improving the quality of service in all processes following the collection of meter readings (1).
[0009] A computer-implemented method for meter readings (1) validation is implemented for practical use as a group of smaller validation algorithms (9), with each algorithm examining values based on different rules. A validation algorithms (9) include: the algorithm Comparison of register data (2) and load profile data (3) (11), the Data integrity check algorithm (12), the Tariff versus Summary Consumption Comparison algorithm (13), the Zero Consumption Check algorithm (14), the Compare Recent Consumption with Previous Consumption algorithm (15), the Accumulation Check algorithm (16), the Plausibility Check algorithm (17), the Electricity meters (4) readout algorithm (18), the Negative Value Check algorithm (19), the User-Modified Consumption Check algorithm (20), the Over-Estimate Check algorithm (21), the Algorithm Check for Exceeding Allowed Number of Self-Deductions (22), the Algorithm Check for Exceeding Allowed Number of Self-Deductions or Estimates (23), the Profile Reserved Capacity Exceedance Check algorithm (25), the Register Reserved Capacity Overrun Check algorithm (26), the Deviation from Expected Deduction Check algorithm (27), the Manual Read Date Check algorithm (28), the Mounting Deduction Check algorithm (29), the Compare Consumption to Standardized Consumption algorithm (30).
[0010] The algorithm Comparison of register data (2) and load profile data (3) (11) compares the values in the register data (2) with the values in the load profile data (3) obtained from the electricity meters (4). The purpose of the algorithm is to compare the profile and register measurements and detect outliers.
[0011] The Data integrity check algorithm (12) checks the integrity of the measured load profile data (3) at the interval between two readings of register data (2) from electricity meters (4). The task of the algorithm is to find the missing measurement in the load profile data (3).
[0012] The Tariff versus Summary Consumption Comparison algorithm (13) compares the consumption in the summary register with the sum of the consumption in the corresponding tariff registers.
[0013] The Zero Consumption Check algorithm (14) identifies zero consumption at electricity metering points (5) under conditions where zero consumption is not expected.
[0014] The Compare Recent Consumption with Previous Consumption algorithm (15) compares the measured consumption with that of the previous reading and identifies unexpected increases or decreases. Consumption is compared relative to the period for which it was measured.
[0015] The Accumulation Check algorithm (16) checks for incremental increases in the accumulation register under conditions where the increase should occur.
[0016] The Plausibility Check algorithm (17) conditions the plausibility of a register with the plausibility of the same register from the preview's deduction.
[0017] The Electricity meters (4) readout algorithm (18) checks that the value in register data (2) is not smaller than the previous reading. In this way, it can detect metronomic meter overflows or detect a significant anomaly that appears to be an overflow of electricity meters (4).
[0018] The Negative Value Check algorithm (19) looks for the occurrence of negative values in readings that indicate a significant anomaly in the measurements.
[0019] The User-Modified Consumption Check algorithm (20) identifies user- modified consumptions and requests their additional reconciliation.
[0020] The Over-Estimate Check algorithm (21) checks the number of consecutive readings with the flag "estimated". Estimates are generated by the system and serve as a full substitute for actual readings. However, the consecutive number of estimates shall not exceed the specified limit.
[0021] The Algorithm Check for Exceeding Allowed Number of Self-Deductions (22) checks the number of consecutive deductions made by the customer. Customers can perform a countdown using the mobile app, but the consecutive count must not exceed the limit. [0022] The Algorithm Check for Exceeding Allowed Number of Self-Deductions or Estimates (23) checks the number of consecutive self-deductions or system estimates. Both types of readings are full substitutes for real measurements, but the consecutive number of readings must not exceed a fixed limit.
[0023] The Utilization Coefficient Check against Maximum Reserved Capacity (24) algorithm compares the consumption for a given period with the maximum allowable consumption derived from the Maximum Reserved Capacity. The maximum reserved capacity determines the maximum instantaneous consumption and is part of the customer's contract with the supplier. The algorithm sets both a minimum and a maximum consumption rate against the maximum reserved capacity.
[0024] The Profile Reserved Capacity Exceedance Check algorithm (25) compares the maximum instantaneous draw recorded in the profile measurements with the Reserved Capacity value. The Reserved Capacity determines the maximum instantaneous consumption and is part of the customer's contract with the supplier.
[0025] The Register Reserved Capacity Overrun Check algorithm (26) compares the maximum instantaneous draw recorded in the register readout with the Reserved Capacity value. The Reserved Capacity determines the maximum instantaneous off-take and is part of the customer's contract with the supplier.
[0026] The Deviation from Expected Deduction Check algorithm (27) checks that the deduction is within the range of the expected state, which is derived from the supplier's prediction.
[0027] The Manual Read Date Check algorithm (28) identifies an incorrectly recorded read date by the manual meter reading device.
[0028] The Mounting Deduction Check algorithm (29) checks if the mounting deduction has zero consumption.
[0029] The Compare Consumption to Standardized Consumption algorithm (30) compares consumption against a standardized consumption defined by the owner of the electricity meters (4).
[0030] The validation algorithms (9) in the computer-implemented method for meter readings (1) validation operate on data obtained from electricity meters (4), such as contain register data (2) and load profile data (3) or both. Contain register data (2) express the current cumulative consumption according to the electricity meters (4) - it is a single number. Load profile data (3) is made up of a progressive measurement of consumption, for example a record every 15 minutes. The different validation algorithms (9) can be divided into basic groups: algorithms that validate contain register data (2); algorithms that validate load profile data (3); algorithms that validate contain register data (2) load and profile data (3). All constants are configurable. It is possible to set the validation algorithm (9), validation class (8), validation interval, etc., in the form of a list of individual validation algorithms.
[0031] To automate the technical solution, a data-processing system comprising means for carrying out the steps of computer-implemented method for meter readings (1) validation is created by the applicant. A data-processing system is designed for the data management of smart metering systems, providing for the collection and management of the meter readings (1), the evaluation of the data, the generation of surrogate values and the provision of data to external entities in accordance with the processes of the liberalized electricity market. Included in a data-processing system is a computer program comprising instructions which, when the program is executed by a computer, cause the computer to carry out the steps of the method for meter readings (1) validation.
[0032] A data-processing system comprising list of types of validation algorithms (9). Types of validation algorithms (9) are model s/templates that have their own validation logic programmed. Validation algorithms (9) are created in the data-processing system based on types of validation algorithms (9) in that each validation algorithm (9) has its own set of tolerances and thresholds defined. Due to this, measurements of two electricity metering points (5) can be validated using the same validation logic but with different tolerances.
[0033] To simplify the assignment of the necessary validation algorithms (9) for electricity metering points (5), validation classes (8) are used. Validation class (8) is an editable set of validation algorithms (9). The meter readings (1) of each electricity metering point (5) are validated just on the basis of the validation algorithms (9) contained in validation class (8). The validation class (8) contains any plurality of validation algorithms (9) and may be assigned to any plurality of electricity metering points (5).
[0034] The key to the choice of validation algorithms (9) for electricity metering points (5) is in most cases the electricity tariff (7). It is for this reason that the automatic creation of validation classes (8) and also the automatic assignment of validation classes (8) to new electricity metering points (5) based on the electricity tariff (7) of the electricity metering points (5) works.
[0035] The automatic definition of the validation class (8) takes place on the basis of electricity tariffs (7) registered in the data-processing system. If a new electricity tariff (7) is created, a new validation class (8) is automatically created with a name derived from the respective tariff. The validation class (8) is automatically populated with validation algorithms (9) according to the selected key when it is created.
[0036] When a new electricity metering point (5) is created, the data-processing system is provided with the establishment of the electricity metering points (5), the definition of the main attributes of the electricity metering points (5) together with electricity tariff (7), the setting of the binding entities (device, assembly, and subsequent automatic assignment of the validation class (8) based on the electricity tariff (7). The automatic assignment of validation class (8) at the creation of new electricity metering points (5) is performed by firstly creating a new electricity tariff (7) or synchronizing the new electricity tariff (7) to the data-processing system, secondly ensuring the creation of a new validation class (8) based on the newly created electricity tariff (7), and thirdly performing the automatic assignment of the validation algorithms (9) to the validation class (8) based on the key: electricity tariff (7) plus electricity metering points type (5).
[0037] For specific electricity metering points (5) the data-processing system offers the possibility to manually modify the validation class (8) or replace it completely. When editing, the user has the possibility to change the list of validation algorithms (9) assigned to the validation class (8). Customizing validation class (8) starts with searching for electricity metering points (5) using filters, then identifying validation class (8), opening the edit validation class (8) of the electricity metering point (5) and assigning and/or removing in validation algorithm (9) from/to validation class (8). In this case, the change will affect all electricity metering points (5) that work with the given validation class (8). With a full replacement, the user has the possibility to create his own validation class (8) to which he assigns validation algorithms (9) as needed. The thus created validation class (8) is then assigned to the selected electricity metering points (5).
[0038] The technical solution is a complex solution where the configuration validation algorithms (9) (setting threshold or configuration values) are independent of each other. The practicality of this solution lies in the combination of the following facts: the selection of a suitable design pattern for implementation is enabled, and it is enabled to define a set of validation algorithms (9) for the validation of meter readings (1).
[0039] The uniqueness of the solution lies in the fact that by demonstrating the unreliability of meter readings (1) due to the progress of certain validation algorithms (9), it is possible to easily detect the failure of electricity meters (4) or electricity generator devices (6). The failure of electricity meters (4) or electricity generator devices (6) is detected in the case of reporting the validation results (10) with at least one non-reliable value based on the Plausibility Check algorithm (17) or the Electricity meters (4) readout algorithm (18). A device fault is also demonstrated by reporting the validation results (10) with a repeat occurrence of an invalid value based on the validation results when performing the algorithm Comparison of register data (2) and load profile data (3) (11), the Tariff versus Summary Consumption Comparison algorithm (13), the Zero Consumption Check algorithm (14).
[0040] "Types of validation algorithms" is a model of a particular validation algorithm (9). It is programmed to contain the business logic and/or mathematical formula upon which to validate meter readings (1). Within the types of validation algorithms, its parameter types and constraints for each parameter are also defined. Multiple validation algorithms (9) (multiple instances) can be created from each Types of validation algorithms (9), and each can have different values set in its parameters.
[0041] "Validation algorithm (9)" is an instance of the validation type. A validation algorithm (9) is thus defined by an algorithm type and a custom parameter set.
[0042] "Validation classes (8)" is an editable set of validation algorithms (9). The class is used to associate itself with an electricity metering point (5) to ensure that the data- processing system for that electricity metering point (5) executes the validation algorithms (9) that the validation classes (8)" contains.
[0043] "Electricity metering points (5)" means electricity consumption points with an electricity meter.
[0044] "Electricity tariff (7)" means the off-take tariff based on a contract between the user of electricity metering points (5) and the electricity supplier.
BRIEF DESCRIPTION OF DRAWINGS
[0045] The invention is explained in more detail by means of a figure.
Fig. 1
The figure schematically illustrates the data flows in the automated validation flow within the validation class (8). Each validation class (8) represents a set of selected validation algorithms (9), namely algorithms (11) to (30), these validations are independent of each other. The input data in this case is a set of meter readings (1) from electricity meters (4) on electricity metering points (5) or electricity generator devices (6), which are intended for validation. The output is a data stream, which in this case contains a set of meter readings (1) together with the reporting of the validation results (10). A computer-implemented method for meter readings (1) validation allows easy extension of the validation of meter readings (1) by new validation algorithms (9). The configurations of the validation algorithms (9) (setting threshold or configuration values) are also independent of each other.
DESCRIPTION OF EMBODIMENTS
Example 1
[0046] In this example of a particular embodiment of the subject invention, methods of data matching are illustrated, which are implemented by the algorithm Comparison of register data (2) and load profile data (3) (11).
[0047] Validation of 15-minute profiles is done by comparing the REGISTRE values against the Active Download/Work profiles. The comparison is made between Register 1.8. ©(positive active energy (total) and Profile P+ (1.5.0) (positive active demand). The reference value is the value from the register. First, the monthly consumption (kWh) has to be calculated from the register values as follows 1.8.0. xx - 1.8.0. yy, where xx is the first memory register and yy is the second memory register. A comparison should then be made, e.g. a difference of values, between the consumption value from the registers, according to the above formula, and the consumption value from the profile. The values from the profile are plausible if the deviation between the register and the profile is within tolerance, i.e. it does not differ by more than % (±0.5 %) or by more than 10 kWh. Then all values from the profile will have the status VALID for the given month. Otherwise, if the variation is greater than the allowed variation, all values from the profile for that month will have the status INVALID. The % Tolerance value is a parameter configurable from the application level. The Tolerance value in kWh is a parameter configurable from the application level. If the accumulation is also within a month, the period between two valid accumulations for both registers and profiles is used for comparison.
[0048] Comparison of REGISTRE values against the Active Consumption/Power PROFILE. The comparison is made between Register 1.6.0 (positive active maximum demand) and Profile P+ (1.5.0) (positive active demand). The reference value is the value from the register. The comparison will be made with the 1.6.0 register according to the date of the peak. The value of the 1.6.0 register shall be compared against the P+ profile at the time of the peak recorded in the 1.6.0 register. It shall also be compared whether there is a higher value stored in the P+ profile in the accounting period. The values from the profile are plausible if the deviation between the 1.6.0 peak register and the P+ profile is within tolerance, i.e. it does not differ by more than 0,01kW (±0,01kW). In that case all values from the profile will have a status of VALID for that month. Otherwise, if the deviation is greater than the tolerance, all values from the profile for that month will have a status of INVALID. The Tolerance value in kW is a parameter configurable from the application level. If the accumulation is also within a month, the period between two valid accumulations for both registers and profiles is used for comparison.
[0049] Comparison of REGISTRE values against PROFILE Active Supply/Consumption. The comparison is made between Register 2.8. ©(negative active energy, total) and Profile P-(2.5.0) (negative active demand). The reference value is the value from the register. First, the monthly consumption (kWh) has to be calculated from the register values as follows 2.8.0. xx - 2.8.0. yy, where xx is the first memory register and yy is the second memory register. A comparison should then be made, e.g. a difference of values, between the consumption value from the registers, according to the above formula, and the consumption value from the profile. The values from the profile are plausible if the deviation between the register and the profile is within tolerance, i.e. it does not differ by more than % (±0.5 %) or by more than 10 kWh. Then all values from the profile will have the status VALID for that month. Otherwise, if the variation is greater than the allowed variation, all values from the profile for that month will have a status of INVALID. The % Tolerance value is a parameter configurable from the application level. The Tolerance value in kWh is a parameter configurable from the application level. If the accumulation is also within a month, the period between two valid accumulations for both registers and profiles is used for comparison.
[0050] Comparison of REGISTRE values against PROFILE Active Delivery /Performance. The comparison is made between Register 2.6. ©(negative active maximum demand) and Profile P-(2.5.0) (negative active demand). The reference value is the value from the register. The comparison will be made according to the peak date of the 2.6.0 register. The value of register 2.6.0 shall be compared against profile P- at the time of the maximum recorded in register 2.6.0. At the same time, it shall be compared whether there is a higher value stored in the P- profile in the settlement period. The values from the profile are plausible if the deviation between the 2.6.0 peak register and the P- profile is within tolerance, i.e. it does not differ by more than 0,01kW (±0,01kW). In that case all values from the profile will have the status of VALID for that month. Otherwise, if the deviation is greater than the tolerance, all values from the profile for that month will have a status of INVALID. The Tolerance value in kW is a parameter configurable from the application level. If the accumulation is also within a month, the period between two valid accumulations for both registers and profiles is used for comparison.
[0051] Comparison of REGISTRE values versus PROFILE Reactive Download/ Inductive. The comparison will be made between Register 5.8.0 (reactive energy in I quadrant) and Profile QI (5.5.0) (reactive demand in the last completed demand period in I quadrant). The reference value is the value from the register. First, the monthly consumption (kVArh) has to be calculated from the register values as follows 5.8.0. xx - 5.8.0. yy, where xx is the first memory register and yy is the second memory register. A comparison should then be made, e.g. a difference of values, between the power consumption value from the registers, according to the above formula, and the power consumption value from the profile. The values from the profile are plausible if the deviation between the register and the profile is within tolerance, i.e., does not differ by more than 1% (±1%) or by more than 10 kVArh. In that case, all values from the profile will have a VALID status for that month. Otherwise, if the variation is greater than the allowed variation, all values from the profile for that month will have a status of INVALID. The % Tolerance value is a parameter configurable from the application level. Tolerance value in kVArh is a parameter configurable from the application level. If the accumulation is also within a month, the period between two valid accumulations for both registers and profiles is used for comparison.
[0052] Comparison of REGISTRE values against PROFILES Reactive Consumption/ Capacity. The comparison is made between Register 6.8.0 (reactive energy in II quadrant) and Profile Q2 (6.5.0) (reactive demand in the last completed demand period in II quadrant). The reference value is the value from the register. First, the monthly consumption (kVArh) has to be calculated from the register values as follows 6.8.0. xx - 6.8.0. yy, where xx is the first memory register and yy is the second memory register. A comparison should then be made, e.g. a difference of values, between the power consumption value from the registers, according to the above formula, and the power consumption value from the profile. The values from the profile are plausible if the deviation between the register and the profile is within tolerance, i.e., does not differ by more than 1% (±1%) or by more than 10 kVArh. In that case, all values from the profile will have a VALID status for that month. Otherwise, if the variation is greater than the allowed variation, all values from the profile for that month will have a status of INVALID. The % Tolerance value is a parameter configurable from the application level. Tolerance value in kVArh is a parameter configurable from the application level. If the accumulation is also within a month, the period between two valid accumulations for both registers and profiles is used for comparison. [0053] Comparison of REGISTRE values against PROFILE Reactive Delivery/ Inductive. The comparison is made between Register 7.8.0(reactive energy in III quadrant) and Profile Q3 (7.5.0) (reactive demand in the last completed demand period in III quadrant). The reference value is the value from the register. First, the monthly consumption (kVArh) has to be calculated from the register values as follows 7.8.0. xx - 7.8.0. yy, where xx is the first memory register and yy is the second memory register. A comparison should then be made, e.g. a difference of values, between the power consumption value from the registers, according to the above formula, and the power consumption value from the profile. The values from the profile are plausible if the deviation between the register and the profile is within tolerance, i.e., does not differ by more than 1% (±1%) or by more than 10 kVArh. In that case, all values from the profile will have a VALID status for that month. Otherwise, if the variation is greater than the allowed variation, all values from the profile for that month will have a status of INVALID. The % Tolerance value is a parameter configurable from the application level. Tolerance value in kVArh is a parameter configurable from the application level. If the accumulation is also within a month, the period between two valid accumulations for both registers and profiles is used for comparison.
[0054] Comparison of REGISTRE values against PROFILE Reactive Supply/Capacity. The comparison is made between Register 8.8.0 (reactive energy in IV quadrant) and Profile Q4 (8.5.0) (reactive demand in the last completed demand period in IV quadrant). The reference value is the value from the register. First, the monthly consumption (kVArh) has to be calculated from the register values as follows 8.8.0. xx - 8.8.0. yy, where xx is the first memory register and yy is the second memory register. A comparison should then be made, e.g. a difference of values, between the power consumption value from the registers, according to the above formula, and the power consumption value from the profile. The values from the profile are plausible if the deviation between the register and the profile is within tolerance, i.e., does not differ by more than 1% (±1%) or by more than 10 kVArh. In that case, all values from the profile will have a VALID status for that month. Otherwise, if the variation is greater than the allowed variation, all values from the profile for that month will have a status of INVALID. The % Tolerance value is a parameter configurable from the application level. Tolerance value in kVArh is a parameter configurable from the application level. If the accumulation is also within a month, the period between two valid accumulations for both registers and profiles is used for comparison.
[0055] Comparison of REGISTRE values against PROFILES Active work subscription High tariff. The comparison will be made between Register 1.8.2 (positive active energy in high tariff) and Profile P+ (1.5.0) (positive active demand). The reference value is the value from the register. The comparison will be made between Register 1.8.2 (current accumulation versus previous accumulation) versus the sum of the measured values (kWh) in Profile P+ (1.5) according to the time stamp concerning the currently assigned electricity tariff (7). If the deviation is greater than 1% (parameter) the measured value 1.8.2 will be marked as INVALID. The Tolerance value in kW (parameter) is adjustable from the application level. If the accumulation is also within a month, the period between two valid accumulations for the registers in each period is used for comparison.
[0056] Comparison of REGISTRE values against PROFILES Active work subscription Low tariff. The comparison is made between Register 1.8.3 (positive active energy in low tariff) and Profile P+ (1.5.0) (positive active demand). The reference value is the value from the register. The comparison shall be made between Register 1.8.3 (current accumulation against previous accumulation) against the sum of the measured values (kWh) in Profile P+ (1.5) according to the time stamp with respect to the currently assigned electricity tariff (7). If the deviation is greater than 1% (parameter) the measured value 1.8.3 will be marked as INVALID. The Tolerance value in kW (parameter) is adjustable from the application level. If the accumulation is also within a month, the period between two valid accumulations for the registers in each period is used for comparison.
[0057] Comparison of REGISTRE values against PROFILE Consumption/Performance of maximum reserved capacity. The comparison will be made between Register 1.2.0 (positive active cumulative maximum demand) and Profile P+ (1.5.0) (positive active demand). The reference value is the value from the register. The comparison will be the difference of the registers current value versus the previous value in register’s 1.2.0. The value will be compared against the maximum of the P+ profile in the period being compared. If the deviation in % (parameter) is greater than the specified deviation the value in register 1.2.0 will be flagged as INVALID. The % Tolerance value (parameter) is adjustable from the application level. If the accumulation is also within a month, the period between two valid accumulations for the registers is used for comparison.
[0058] Comparison of the values of REGISTER against the PROFILE Delivery/performance of the maximum reserved capacity. The comparison will be made between Register 2.6.0 (negative active maximum demand) and Profile P-(2.5.0) (negative active demand). The reference value is the value from the register. The comparison will be made according to the date of the peak in the 2.6.0 register. The value of register 2.6.0 shall be compared against profile P- at the time of the maximum recorded in 2.6.0. It will also be compared if there is no higher value stored in the P- profile in the accounting period, in which case the value will be INVALID. The Tolerance value in % (parameter) is configurable from the application level. If the accumulation is also within a month, the period between two valid accumulations for the registers is used for comparison.
[0059] Comparison of REGISTRE values against PROFILE Supply/performance of maximum reserved capacity. The comparison will be made between Register 2.2.0 (negative active cumulative maximum demand) and Profile P-(2.5.0) (negative active demand). The reference value is the value from the register. The comparison will be the difference of the registers current value versus the previous one in the value of register 2.2.0. The value will be compared against the maximum of the P- profile in the period being compared. If the deviation in % (parameter) is greater than the specified deviation, the value in the 2.2.0 register will be marked as INVALID. The Tolerance value in % (parameter) is adjustable from the application level. If the accumulation is also within a month, the period between two valid accumulations for the registers is used for comparison.
[0060] The example shows how to compare the values in the algorithm Comparison of register data (2) and load profile data (3) (11). Similar logic based on configurations is used to compare values in the other validation algorithm (9) according to the relevance of the comparing value. Based on the result of the comparison of values after all validation algorithms (9) within the validation class (8) have been executed, if the report of the validation results (10) contains the result that the value of the meter readings (1) is marked as EQUAL in relation to all validation algorithms (9), the meter readings (1) are considered to be of good quality and can be used for the purpose of billing and meeting the legislative requirements of data reporting by the electricity market processes without any doubt on their quality.
Example 2
[0061] In this example of a particular embodiment of the invention, a method of using a computer-implemented method for meter readings (1) validation using a data-processing system with a demonstrated technical effect is described. A data-processing system, after obtaining electricity meter readings (1) from electricity metering points (5) within an assigned validation class (8), performs a validation algorithm (9) of comparing registers and profiles, wherein it compares one or more values according to Example 1, wherein the report of the validation results (10) the value of the meter readings (1) is marked as INVALID. After the 15-minute interval is completed and the data is re-validated, the report of the validation results (10) value of the meter readings (1) is repeatedly marked as INVALID. A data- processing system includes a warning notice of the need for in-situ inspection or service of the electricity meters (4). Alternatively, it is possible to use a data-processing system for a warning notice of the need for in-situ inspection or service of the electricity generator devices (6), for example, photovoltaic devices.
INDUSTRIAL APPLICABILITY
[0062] The invention can be used in any enterprise whose activity is related to the operation of smart metering systems and is aimed at collecting meter readings (1) from electricity meters (4) on electricity metering points (5) or electricity generator devices (6), storing them in a consolidated form, evaluating their quality, providing for the generation of surrogate readings and providing meter readings (1) to other internal and external systems. The invention can also be used for businesses and households operating electricity generator devices (6), which produce electricity from renewable energy sources. A computer- implemented method for meter readings (1) validation is a technical solution for reliably determining the quality of meter readings (1) with their subsequent use for the purpose of billing and fulfilling the obligation to report meter readings (1) in accordance with electricity market processes, also detect or take precautions against the occurrence of a fault on electricity metering points (5) or electricity generator devices (6).