Demand determination method and device of electric energy meter, readable storage medium and electric energy meter

Abstract

The invention provides a demand determination method and device of an electric energy meter, a readable storage medium and the electric energy meter, and relates to the technical field of electric metering equipment. The demand determination method comprises the following steps: acquiring an electric energy signal in a target time period; performing signal division processing on the electric energy signal to obtain a plurality of signal segments; determining electric energy data corresponding to each signal segment; determining a tide direction corresponding to the electric energy signal based on the electric energy data; in the plurality of signal segments, determining a first signal segment of which the tidal current direction is forward tidal current and a second signal segment of which the tidal current direction is reverse tidal current; determining forward power in the target time period according to the first signal segment; according to the second signal segment, determining reverse power in the target time period; and determining the demand in the target time period according to the forward power and the reverse power. According to the method and the device, the speed and the timeliness of judging the tidal current direction are improved, so that more accurate electric energy metering and demand calculation are realized, and the accuracy of determining the demand is improved.

Description

Technical Field

[0001] The present application relates to the technical field of electricity metering equipment, and in particular to a method and device for determining the demand of an electric energy meter, a readable storage medium, and an electric energy meter. Background Art

[0002] In related technologies, demand refers to the instantaneous or average power demand that a power system must meet within a specific time period. Accurate demand calculation enables forecasting and regulation of grid demand, thereby reducing peak stress on the grid. Demand calculation requires the maximum average power demand of the system over a specific period, which requires accurate power metering.

[0003] Conventional power metering requires determining the direction of power flow to measure both positive and negative power. This determination relies on voltage and current data from multiple consecutive cycles to determine the power flow direction. This method exhibits significant lag and is slow, leading to inaccurate power measurement and, ultimately, poorly accurate demand calculations. Summary of the Invention

[0004] The present application aims to at least solve the technical problem of poor structural accuracy of demand calculation existing in the prior art or related art.

[0005] To this end, a first aspect of the present application proposes a method for determining the demand of an electric energy meter.

[0006] A second aspect of the present application provides a demand determination device for an electric energy meter.

[0007] A third aspect of the present application provides a demand determination device for an electric energy meter.

[0008] A fourth aspect of the present application provides a readable storage medium.

[0009] A fifth aspect of the present application provides an electric energy meter.

[0010] In view of this, the first aspect of the present application provides a method for determining the demand of an electric energy meter, which method includes: collecting electric energy signals within a target time period; wherein the signal period of the electric energy signal is a first period; performing signal division processing on the electric energy signal to obtain multiple signal segments; wherein the signal period of the multiple signal segments is a second period, and the second period is half a period of the first period; determining the electric energy data corresponding to each signal segment; determining the flow direction corresponding to the electric energy signal based on the electric energy data; among the multiple signal segments, determining the first signal segment with a forward flow direction and the second signal segment with a reverse flow direction; determining the forward power within the target time period based on the first signal segment; determining the reverse power within the target time period based on the second signal segment; and determining the demand within the target time period based on the forward power and the reverse power.

[0011] In this technical solution, the electric energy meter is used to collect electric energy signals within a target time period and measure or convert the collected electric energy signals to obtain corresponding electric energy data. Exemplarily, the electric energy data includes current, voltage, flow direction, power, and demand.

[0012] In related technologies, when performing demand and power calculations, it is necessary to accurately determine the flow direction of the power signal and determine the direction of the power data based on the flow direction. To determine the flow direction, it is common to collect voltage and current data for multiple cycles and then perform flow analysis based on this data to accurately determine the flow direction. This results in a lag in determining the flow direction, making it impossible to promptly reflect the real-time status of the power grid. As a result, the final predicted demand cannot accurately reflect the actual demand of the power grid during that time period.

[0013] In response to the above problems, this application aims to improve the accuracy and timeliness of the tidal flow direction judgment during the demand calculation process. By more accurately judging the tidal flow direction, the accuracy of power metering can be improved, thereby improving the accuracy of demand calculation.

[0014] When the energy meter is operating, it continuously collects and records energy signals within a target time period. After obtaining the energy signal, it is divided into half of the signal cycle to generate multiple half-cycle signal segments. By performing power flow analysis on the energy data in each half-cycle signal segment, it can more quickly determine and identify changes in power flow direction, making power flow direction analysis more timely. This ensures a more accurate measurement of the maximum average power within the target time period, reflecting the actual power demand of the grid during that time period. Demand calculations based on this data can effectively improve the accuracy of demand calculations.

[0015] For example, an electric energy meter collects raw signals and converts the collected current and / or voltage signals into digital signals using a high-precision analog-to-digital converter (ADC). The high-precision ADC ensures that the collected signals have high sampling accuracy and signal resolution, providing a reliable data foundation for subsequent signal processing and feature extraction.

[0016] After obtaining the electric energy signal, the electric energy signal is divided according to half of the electric energy signal cycle to obtain at least two half-cycle signal segments. For example, taking the initial electric energy signal cycle as the first cycle, the initial electric energy signal is divided and processed according to half of the first cycle, that is, the second cycle. The multiple signal segments obtained after processing all have a cycle of the second cycle, and the cycle length of the second cycle is half of the cycle length of the first cycle. After obtaining multiple half-cycle signal segments, power flow analysis is performed based on the electric energy data in each signal segment to obtain power flow analysis results for each half cycle, thereby achieving rapid determination of the power flow direction.

[0017] After obtaining the flow direction, the forward power and reverse power are recorded according to the flow direction to obtain the true average power in the target time period, thereby accurately reflecting the instantaneous occupancy level of the current electricity user on the grid capacity.

[0018] For example, when calculating demand, forward and reverse energy are measured separately based on the flow direction. These measurements are then accumulated to calculate the total energy for the target time period. The total energy is then divided by the duration of the target time period to obtain the cycle average power. This cycle average power is then used to calculate the demand for the target time period.

[0019] The power signal is divided into multiple continuous signal segments based on the half-cycle division method, and the flow direction of each signal segment is determined separately. After the flow direction of each signal segment is determined, the signal segment with a forward flow direction is recorded as the first signal segment. The signal segment with a reverse flow direction is recorded as the second signal segment.

[0020] The power measurement results in all the first signal segments are recorded as forward power, and the forward power measurement results in all the first signal segments are accumulated to obtain the total forward power in the target time period.

[0021] Similarly, the power measurement results in all second signal segments are recorded as reverse power, and the reverse power measurement results in all second signal segments are accumulated to obtain the total reverse power in the target time period.

[0022] In some scenarios, it's necessary to determine the net demand. In such scenarios, after obtaining the forward and reverse powers, the forward demand is calculated based on the forward power, and the reverse demand is calculated based on the reverse power. The final demand value = forward demand - reverse demand.

[0023] In other scenarios, independent metering of demand is required, where forward and reverse demand are counted separately. The maximum demand only considers the forward demand value.

[0024] The present application improves the speed and timeliness of determining the direction of the current by dividing the collected electric energy signal into half of its cycle and performing a current analysis based on the electric energy data within the signal segment of the divided half cycle, thereby achieving more accurate electric energy metering and demand calculation, and improving the accuracy of determining the demand.

[0025] In some technical solutions of the present application, optionally, the electric energy signal includes a current signal and a voltage signal; determining the electric energy data corresponding to each signal segment includes: determining the electric energy accumulated value corresponding to each signal segment based on the current signal and voltage signal corresponding to each signal segment.

[0026] In this technical solution, the electric energy data collected by the electric energy meter specifically includes voltage and current signals. After collecting the grid signal, the collected signal is converted into a digital signal through a high-precision analog-to-digital converter to obtain the above-mentioned voltage and current signals.

[0027] Next, the voltage and current signals are segmented based on half of the voltage signal's cycle, yielding signal segments encompassing half the voltage and energy signals. Energy is accumulated for each half-cycle segment to obtain a cumulative energy value for each signal segment. This cumulative energy value represents the energy data corresponding to each signal segment. Because the frequency of the instantaneous power signal is twice that of the current and voltage signals, the half-cycle cumulative energy value allows for more rapid determination of changes in the flow direction.

[0028] The present application performs power flow analysis through the accumulated value of electric energy in a half cycle, and can accurately and quickly obtain the power flow direction of a signal segment, thereby improving the speed and timeliness of power flow detection.

[0029] In some technical solutions of the present application, optionally, the flow direction corresponding to the electric energy signal is determined based on the electric energy data, including: when the accumulated electric energy value is positive, determining the flow direction as a forward flow; or when the accumulated electric energy value is negative, determining the flow direction as a reverse flow.

[0030] In this technical solution, if the accumulated energy value within a half-cycle signal segment is positive, it can be determined that the power flow direction of the power grid in this signal segment is forward flow. If the accumulated energy value within a half-cycle signal segment is negative, it can be determined that the power flow direction of the power grid in this signal segment is reverse flow.

[0031] This method uses the accumulated energy value of half a cycle to determine the direction of the flow, which can quickly determine the change of the flow direction and thus improve the accuracy of energy measurement.

[0032] In some technical solutions of the present application, optionally, the accumulated electric energy value corresponding to each signal segment is determined based on the current signal and voltage signal corresponding to each signal segment, including: determining the instantaneous power signal corresponding to the signal segment based on the current signal and voltage signal; and determining the accumulated electric energy value based on the instantaneous power signal.

[0033] In this technical solution, the electric energy data in each signal segment includes a half-cycle voltage signal and a half-cycle current signal. Assuming that the voltage signal in a signal segment is Vcos(ωt) and the current signal is Icos(ωt+Φ), the instantaneous power can be calculated using the following formula (1):

[0034] P(t)=Vcos(ωt)×Icos(ωt+Φ); (1)

[0035] Where P(t) is the instantaneous power, Vcos(ωt) is the voltage signal, and Icos(ωt+Φ) is the current signal.

[0036] The product and difference formula of the known trigonometric functions is shown in formula (2):

[0037]

[0038] Where A and B represent arbitrary constants.

[0039] From formula (1) and formula (2), the formula for instantaneous power can be simplified to obtain the following formula (3):

[0040]

[0041] Where V is the instantaneous voltage amplitude, I is the instantaneous current amplitude, Φ is the initial phase angle, and ωt is the phase change.

[0042] Formula (3) shows that the frequency of the instantaneous power signal is twice the frequency of the power signal. That is, within one cycle of the current and voltage signals, the frequency of the instantaneous power signal is twice as fast as that of both the current and voltage signals. Therefore, by accumulating electric energy using the instantaneous power signal within a half-cycle, it is possible to quickly determine changes in the flow direction, improve the timeliness of flow direction determination, and thus improve the accuracy of electric energy metering.

[0043] In some technical solutions of the present application, optionally, the accumulated electric energy value is determined based on the instantaneous power signal, including: adding N instantaneous power values to obtain the accumulated electric energy value; wherein the signal segment includes N sampling points, the N sampling points correspond one-to-one to the N instantaneous power values, and N is a positive integer; or, the instantaneous power signal is integrated to obtain the accumulated electric energy value.

[0044] In this technical solution, for example, the electric energy meter periodically samples the power grid discretely. For high-precision electric energy meters, the grid signal can be collected at a frequency of thousands of sampling points per second. The sampled current and voltage signals are stored in the form of discrete sampling points.

[0045] Assume that a signal segment of a half-cycle includes N sampling points. In this case, within this half-cycle signal segment, the current signal includes N current sampling values, and the voltage signal includes N voltage sampling values. When calculating the instantaneous power value, calculations are performed based on the current and voltage values at each sampling point to obtain N instantaneous power values corresponding to the N sampling points. After obtaining these N instantaneous power values, they are accumulated to obtain the accumulated electric energy value for the signal segment of the current half-cycle.

[0046] For example, after obtaining the instantaneous power signal within the signal segment of the half cycle, the instantaneous power signal can also be integrated to obtain the accumulated value of electric energy within a signal segment. For example, the accumulated value of electric energy can be calculated by the following formula (4):

[0047]

[0048] Where E is the accumulated value of electric energy, and T is the period of the electric energy signal, that is, the first period; is the second cycle, v(t) is the voltage signal, i(t) is the current signal, and t is the time.

[0049] In some technical solutions of the present application, optionally, the electric energy signal is an electric energy signal output by the target power grid system, and the method also includes: generating a demand prediction model based on the demand within the target time period; performing demand prediction on the target power grid system through the demand prediction model; and expanding the target power grid system when the demand prediction value corresponding to the demand prediction is greater than the demand threshold.

[0050] In this technical solution, after obtaining the demand for a target time period, this demand is recorded. Once a sufficient amount of demand is recorded, a neural network model is constructed based on this data. The resulting demand forecasting model can use the recorded historical demand changes for different time periods and other energy data collected by the energy meter to predict the demand for the power grid system in the same future time period, thereby achieving demand forecasting.

[0051] Exemplarily, the demand forecasting model may be a forecasting model based on edge intelligent computing.

[0052] Exemplarily, the demand prediction model may be a DMPC prediction model (Distributed Model Predictive Control).

[0053] Exemplarily, the demand prediction model may be a prediction model that combines a fusion ant colony algorithm, Xgboost (non-linear fitting) and a reinforcement learning algorithm.

[0054] The demand forecast reflects the expected grid demand over a specific time period. This forecast represents the instantaneous level of grid capacity utilization expected by electricity users during that time period. When the forecast exceeds the current grid system's demand threshold, it indicates the grid may be at risk of overload during the upcoming period. Therefore, the target grid system is expanded in advance to address this potential excess demand. This reduces the risk of peak electricity user utilization exceeding the grid's capacity limit, potentially impacting the grid and improving the operational reliability and security of the grid system.

[0055] The second aspect of the present application provides a demand determination device for an electric energy meter, which includes: an acquisition module for acquiring electric energy signals within a target time period; wherein the signal period of the electric energy signal is a first period; a processing module for performing signal division processing on the electric energy signal to obtain multiple signal segments; wherein the signal period of the multiple signal segments is a second period, and the second period is half a period of the first period; a determination module for: determining the electric energy data corresponding to each signal segment; determining the flow direction corresponding to the electric energy signal based on the electric energy data; among the multiple signal segments, determining the first signal segment with a forward flow direction and the second signal segment with a reverse flow direction; determining the forward power within the target time period based on the first signal segment; determining the reverse power within the target time period based on the second signal segment; and determining the demand within the target time period based on the forward power and the reverse power.

[0056] In this technical solution, the electric energy meter is used to collect electric energy signals within a target time period and measure or convert the collected electric energy signals to obtain corresponding electric energy data. Exemplarily, the electric energy data includes current, voltage, flow direction, power, and demand.

[0057] In related technologies, when performing demand and power calculations, it is necessary to accurately determine the flow direction of the power signal and determine the direction of the power data based on the flow direction. To determine the flow direction, it is common to collect voltage and current data for multiple cycles and then perform flow analysis based on this data to accurately determine the flow direction. This results in a lag in determining the flow direction, making it impossible to promptly reflect the real-time status of the power grid. As a result, the final predicted demand cannot accurately reflect the actual demand of the power grid during that time period.

[0058] In response to the above problems, this application aims to improve the accuracy and timeliness of the tidal flow direction judgment during the demand calculation process. By more accurately judging the tidal flow direction, the accuracy of power metering can be improved, thereby improving the accuracy of demand calculation.

[0059] When the energy meter is operating, it continuously collects and records energy signals within a target time period. After obtaining the energy signal, it is divided into half of the signal cycle to generate multiple half-cycle signal segments. By performing power flow analysis on the energy data in each half-cycle signal segment, it can more quickly determine and identify changes in power flow direction, making power flow direction analysis more timely. This ensures a more accurate measurement of the maximum average power within the target time period, reflecting the actual power demand of the grid during that time period. Demand calculations based on this data can effectively improve the accuracy of demand calculations.

[0060] For example, an electric energy meter collects raw signals and converts the collected current and / or voltage signals into digital signals using a high-precision analog-to-digital converter (ADC). The high-precision ADC ensures that the collected signals have high sampling accuracy and signal resolution, providing a reliable data foundation for subsequent signal processing and feature extraction.

[0061] After obtaining the electric energy signal, the electric energy signal is divided according to half of the electric energy signal cycle to obtain at least two half-cycle signal segments. For example, taking the initial electric energy signal cycle as the first cycle, the initial electric energy signal is divided and processed according to half of the first cycle, that is, the second cycle. The multiple signal segments obtained after processing all have a cycle of the second cycle, and the cycle length of the second cycle is half of the cycle length of the first cycle. After obtaining multiple half-cycle signal segments, power flow analysis is performed based on the electric energy data in each signal segment to obtain power flow analysis results for each half cycle, thereby achieving rapid determination of the power flow direction.

[0062] After obtaining the flow direction, the forward power and reverse power are recorded according to the flow direction to obtain the true average power in the target time period, thereby accurately reflecting the instantaneous occupancy level of the current electricity user on the grid capacity.

[0063] For example, when calculating demand, forward and reverse energy are measured separately based on the flow direction. These measurements are then accumulated to calculate the total energy for the target time period. The total energy is then divided by the duration of the target time period to obtain the cycle average power. This cycle average power is then used to calculate the demand for the target time period.

[0064] The power signal is divided into multiple continuous signal segments based on the half-cycle division method, and the flow direction of each signal segment is determined separately. After the flow direction of each signal segment is determined, the signal segment with a forward flow direction is recorded as the first signal segment. The signal segment with a reverse flow direction is recorded as the second signal segment.

[0065] The power measurement results in all the first signal segments are recorded as forward power, and the forward power measurement results in all the first signal segments are accumulated to obtain the total forward power in the target time period.

[0066] Similarly, the power measurement results in all second signal segments are recorded as reverse power, and the reverse power measurement results in all second signal segments are accumulated to obtain the total reverse power in the target time period.

[0067] In some scenarios, it's necessary to determine the net demand. In such scenarios, after obtaining the forward and reverse powers, the forward demand is calculated based on the forward power, and the reverse demand is calculated based on the reverse power. The final demand value = forward demand - reverse demand.

[0068] In other scenarios, independent metering of demand is required, where forward and reverse demand are counted separately. The maximum demand only considers the forward demand value.

[0069] The present application improves the speed and timeliness of determining the direction of the current by dividing the collected electric energy signal into half of its cycle and performing a current analysis based on the electric energy data within the signal segment of the divided half cycle, thereby achieving more accurate electric energy metering and demand calculation, and improving the accuracy of determining the demand.

[0070] The third aspect of the present application provides a device for determining the demand of an electric energy meter, comprising: a memory for storing programs or instructions; a processor for implementing the steps of the method for determining the demand of an electric energy meter provided in any of the above technical solutions when executing the programs or instructions, thereby also being able to achieve all the same technical effects. To avoid repetition, they will not be described here.

[0071] The fourth aspect of the present application provides a readable storage medium on which a program or instruction is stored. When the program or instruction is executed by the processor, the steps of the method for determining the demand of an electric energy meter provided in any of the above technical solutions are implemented, and thus all the same technical effects can be achieved. To avoid repetition, they will not be repeated here.

[0072] The fifth aspect of the present application provides an electric energy meter, including an electric energy meter demand determination device as provided in any of the above technical solutions, and / or a readable storage medium as provided in any of the above technical solutions, so that all the same technical effects can be achieved. To avoid repetition, they will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the description of the embodiments in conjunction with the following drawings, in which:

[0074] Figure 1 A flow chart showing a method for determining demand of an electric energy meter according to some embodiments of the present application is shown;

[0075] Figure 2 A logic diagram showing a method for determining demand of an electric energy meter according to some embodiments of the present application is shown;

[0076] Figure 3 A structural block diagram of a device for determining demand for an electric energy meter according to some embodiments of the present application is shown;

[0077] Figure 4 A structural block diagram of a device for determining demand of an electric energy meter according to some embodiments of the present application is shown. DETAILED DESCRIPTION

[0078] In order to more clearly understand the above-mentioned objects, features and advantages of the present application, the present application is further described in detail below in conjunction with the accompanying drawings and specific embodiments. It should be noted that the embodiments of the present application and the features therein can be combined with each other in the absence of conflict.

[0079] In the following description, many specific details are set forth to facilitate a full understanding of the present application. However, the present application may also be implemented in other ways different from those described herein. Therefore, the scope of protection of the present application is not limited to the specific embodiments disclosed below.

[0080] Refer to the following Figures 1 to 4 The present invention describes a method and device for determining the demand of an electric energy meter, a readable storage medium, and an electric energy meter according to some embodiments of the present application.

[0081] In some embodiments of the present application, a method for determining the demand of an electric energy meter is provided. Figure 1 A flow chart showing a method for determining the demand of an electric energy meter according to some embodiments of the present application is shown. Figure 1 As shown, the demand determination methods include:

[0082] Step 102: collecting an electric energy signal within a target time period; wherein the signal period of the electric energy signal is a first period;

[0083] Step 104: performing signal segmentation processing on the electric energy signal to obtain a plurality of signal segments; wherein the signal periods of the plurality of signal segments are all the second period, and the second period is half the period of the first period;

[0084] Step 106, determining the power data corresponding to each signal segment;

[0085] Step 108, determining the power flow direction corresponding to the power signal based on the power data;

[0086] Step 110, determining, from the plurality of signal segments, a first signal segment in which the tidal current direction is a forward tidal current and a second signal segment in which the tidal current direction is a reverse tidal current;

[0087] Step 112, determining the forward power within the target time period based on the first signal segment;

[0088] Step 114: determining the reverse power within the target time period based on the second signal segment;

[0089] Step 116: Determine the demand within the target time period based on the forward power and the reverse power.

[0090] In this embodiment, the electric energy meter is used to collect electric energy signals within a target time period and measure or convert the collected electric energy signals to obtain corresponding electric energy data. For example, the electric energy data includes current, voltage, flow direction, power, and demand.

[0091] In related technologies, when performing demand and power calculations, it is necessary to accurately determine the flow direction of the power signal and determine the direction of the power data based on the flow direction. To determine the flow direction, it is common to collect voltage and current data for multiple cycles and then perform flow analysis based on this data to accurately determine the flow direction. This results in a lag in determining the flow direction, making it impossible to promptly reflect the real-time status of the power grid. As a result, the final predicted demand cannot accurately reflect the actual demand of the power grid during that time period.

[0092] In response to the above problems, this application aims to improve the accuracy and timeliness of the tidal flow direction judgment during the demand calculation process. By more accurately judging the tidal flow direction, the accuracy of power metering can be improved, thereby improving the accuracy of demand calculation.

[0093] When the energy meter is operating, it continuously collects and records energy signals within a target time period. After obtaining the energy signal, it is divided into half of the signal cycle to generate multiple half-cycle signal segments. By performing power flow analysis on the energy data in each half-cycle signal segment, it can more quickly determine and identify changes in power flow direction, making power flow direction analysis more timely. This ensures a more accurate measurement of the maximum average power within the target time period, reflecting the actual power demand of the grid during that time period. Demand calculations based on this data can effectively improve the accuracy of demand calculations.

[0094] For example, an electric energy meter collects raw signals and converts the collected current and / or voltage signals into digital signals using a high-precision analog-to-digital converter (ADC). The high-precision ADC ensures that the collected signals have high sampling accuracy and signal resolution, providing a reliable data foundation for subsequent signal processing and feature extraction.

[0095] After obtaining the electric energy signal, the electric energy signal is divided according to half of the electric energy signal cycle to obtain at least two half-cycle signal segments. For example, taking the initial electric energy signal cycle as the first cycle, the initial electric energy signal is divided and processed according to half of the first cycle, that is, the second cycle. The multiple signal segments obtained after processing all have a cycle of the second cycle, and the cycle length of the second cycle is half of the cycle length of the first cycle. After obtaining multiple half-cycle signal segments, power flow analysis is performed based on the electric energy data in each signal segment to obtain power flow analysis results for each half cycle, thereby achieving rapid determination of the power flow direction.

[0096] After obtaining the flow direction, the forward power and reverse power are recorded according to the flow direction to obtain the true average power in the target time period, thereby accurately reflecting the instantaneous occupancy level of the current electricity user on the grid capacity.

[0097] For example, when calculating demand, forward and reverse energy are measured separately based on the flow direction. These measurements are then accumulated to calculate the total energy for the target time period. The total energy is then divided by the duration of the target time period to obtain the cycle average power. This cycle average power is then used to calculate the demand for the target time period.

[0098] The power signal is divided into multiple continuous signal segments based on the half-cycle division method, and the flow direction of each signal segment is determined separately. After the flow direction of each signal segment is determined, the signal segment with a forward flow direction is recorded as the first signal segment. The signal segment with a reverse flow direction is recorded as the second signal segment.

[0099] The power measurement results in all the first signal segments are recorded as forward power, and the forward power measurement results in all the first signal segments are accumulated to obtain the total forward power in the target time period.

[0100] Similarly, the power measurement results in all second signal segments are recorded as reverse power, and the reverse power measurement results in all second signal segments are accumulated to obtain the total reverse power in the target time period.

[0101] In some scenarios, it's necessary to determine the net demand. In such scenarios, after obtaining the forward and reverse powers, the forward demand is calculated based on the forward power, and the reverse demand is calculated based on the reverse power. The final demand value = forward demand - reverse demand.

[0102] In other scenarios, independent metering of demand is required, where forward and reverse demand are counted separately. The maximum demand only considers the forward demand value.

[0103] The present application improves the speed and timeliness of determining the direction of the current by dividing the collected electric energy signal into half of its cycle and performing a current analysis based on the electric energy data within the signal segment of the divided half cycle, thereby achieving more accurate electric energy metering and demand calculation, and improving the accuracy of determining the demand.

[0104] In some embodiments of the present application, optionally, the electric energy signal includes a current signal and a voltage signal; determining the electric energy data corresponding to each signal segment includes: determining the electric energy accumulated value corresponding to each signal segment based on the current signal and voltage signal corresponding to each signal segment.

[0105] In this embodiment, the electric energy data collected by the electric energy meter specifically includes voltage signals and current signals. After collecting the grid signal, the collected signal is converted into a digital signal by a high-precision analog-to-digital converter to obtain the above-mentioned voltage signal and current signal.

[0106] Next, the voltage and current signals are segmented based on half of the voltage signal's cycle, yielding signal segments encompassing half the voltage and energy signals. Energy is accumulated for each half-cycle segment to obtain a cumulative energy value for each signal segment. This cumulative energy value represents the energy data corresponding to each signal segment. Because the frequency of the instantaneous power signal is twice that of the current and voltage signals, the half-cycle cumulative energy value allows for more rapid determination of changes in the flow direction.

[0107] The present application performs power flow analysis through the accumulated value of electric energy in a half cycle, and can accurately and quickly obtain the power flow direction of a signal segment, thereby improving the speed and timeliness of power flow detection.

[0108] In some embodiments of the present application, optionally, the flow direction corresponding to the electric energy signal is determined based on the electric energy data, including: when the accumulated electric energy value is a positive value, determining the flow direction as a forward flow; or when the accumulated electric energy value is a negative value, determining the flow direction as a reverse flow.

[0109] In this embodiment, if the accumulated electric energy value within a half-cycle signal segment is a positive value, it can be determined that the power flow direction of the power grid within this signal segment is a forward power flow. If the accumulated electric energy value within a half-cycle signal segment is a negative value, it can be determined that the power flow direction of the power grid within this signal segment is a reverse power flow.

[0110] This method uses the accumulated energy value of half a cycle to determine the direction of the flow, which can quickly determine the change of the flow direction and thus improve the accuracy of energy measurement.

[0111] In some embodiments of the present application, optionally, the accumulated electric energy value corresponding to each signal segment is determined based on the current signal and voltage signal corresponding to each signal segment, including: determining the instantaneous power signal corresponding to the signal segment based on the current signal and voltage signal; and determining the accumulated electric energy value based on the instantaneous power signal.

[0112] In this embodiment, the electric energy data in each signal segment includes a half-cycle voltage signal and a half-cycle current signal. Assuming that the voltage signal in a signal segment is Vcos(ωt) and the current signal is Icos(ωt+Φ), the instantaneous power can be calculated using the following formula (1):

[0113] P(t)=Vcos(ωt)×Icos(ωt+Φ); (1)

[0114] Where P(t) is the instantaneous power, Vcos(ωt) is the voltage signal, and Icos(ωt+Φ) is the current signal.

[0115] The product and difference formula of the known trigonometric functions is shown in formula (2):

[0116]

[0117] Where A and B represent arbitrary constants.

[0118] From formula (1) and formula (2), the formula for instantaneous power can be simplified to obtain the following formula (3):

[0119]

[0120] Where V is the instantaneous voltage amplitude, I is the instantaneous current amplitude, Φ is the initial phase angle, and ωt is the phase change.

[0121] Formula (3) shows that the frequency of the instantaneous power signal is twice the frequency of the power signal. That is, within one cycle of the current and voltage signals, the frequency of the instantaneous power signal is twice as fast as that of both the current and voltage signals. Therefore, by accumulating electric energy using the instantaneous power signal within a half-cycle, it is possible to quickly determine changes in the flow direction, improve the timeliness of flow direction determination, and thus improve the accuracy of electric energy metering.

[0122] In some embodiments of the present application, optionally, determining the accumulated electric energy value based on the instantaneous power signal includes: adding N instantaneous power values to obtain the accumulated electric energy value; wherein the signal segment includes N sampling points, the N sampling points correspond one-to-one to the N instantaneous power values, and N is a positive integer; or, integrating the instantaneous power signal to obtain the accumulated electric energy value.

[0123] In this embodiment, the electric energy meter periodically and discretely samples the power grid. For high-precision electric energy meters, the power grid signal can be sampled at a frequency of thousands of sampling points per second. The sampled current and voltage signals are stored in the form of discrete sampling points.

[0124] Assume that a signal segment of a half-cycle includes N sampling points. In this case, within this half-cycle signal segment, the current signal includes N current sampling values, and the voltage signal includes N voltage sampling values. When calculating the instantaneous power value, calculations are performed based on the current and voltage values at each sampling point to obtain N instantaneous power values corresponding to the N sampling points. After obtaining these N instantaneous power values, they are accumulated to obtain the accumulated electric energy value for the signal segment of the current half-cycle.

[0125] For example, after obtaining the instantaneous power signal within the signal segment of the half cycle, the instantaneous power signal can also be integrated to obtain the accumulated value of electric energy within a signal segment. For example, the accumulated value of electric energy can be calculated by the following formula (4):

[0126]

[0127] Where E is the accumulated value of electric energy, and T is the period of the electric energy signal, that is, the first period; is the second cycle, v(t) is the voltage signal, i(t) is the current signal, and t is the time.

[0128] In some embodiments of the present application, optionally, the electric energy signal is an electric energy signal output by the target power grid system, and the method also includes: generating a demand prediction model based on the demand within the target time period; performing demand prediction on the target power grid system through the demand prediction model; and expanding the target power grid system when the demand prediction value corresponding to the demand prediction is greater than the demand threshold.

[0129] In this embodiment, after obtaining the demand for the target time period, this demand is recorded. Once a sufficient amount of demand is recorded, a neural network model is constructed based on this data. The resulting demand forecasting model can predict the future demand of the power grid system for the same time period based on the recorded historical demand changes in different time periods and other energy data collected by the energy meter, thereby achieving demand forecasting.

[0130] Exemplarily, the demand forecasting model may be a forecasting model based on edge intelligent computing.

[0131] Exemplarily, the demand prediction model may be a DMPC prediction model (Distributed Model Predictive Control).

[0132] Exemplarily, the demand prediction model may be a prediction model that combines a fusion ant colony algorithm, Xgboost (non-linear fitting) and a reinforcement learning algorithm.

[0133] The demand forecast reflects the expected grid demand over a specific time period. This forecast represents the instantaneous level of grid capacity utilization expected by electricity users during that time period. When the forecast exceeds the current grid system's demand threshold, it indicates the grid may be at risk of overload during the upcoming period. Therefore, the target grid system is expanded in advance to address this potential excess demand. This reduces the risk of peak electricity user utilization exceeding the grid's capacity limit, potentially impacting the grid and improving the operational reliability and security of the grid system.

[0134] In some embodiments of the present application, Figure 2 A logic diagram of a method for determining the demand of an electric energy meter according to some embodiments of the present application is shown. Figure 2As shown in the figure, during the demand calculation process, a high-precision ADC is first used to collect voltage and current signals. These signals are divided into half-cycle segments, yielding multiple half-cycle signal segments. Next, feature extraction and algorithm processing are performed on each half-cycle segment to obtain characteristic parameters such as the instantaneous value, effective value, and phase difference of the voltage and current. Based on these extracted characteristic parameters, a pre-set judgment algorithm is used to quickly determine changes in the flow direction. The energy meter then records the positive and negative demand based on the flow direction.

[0135] Preprocessing algorithm 1 calculates characteristic parameters such as the instantaneous value, effective value, and phase difference of voltage and current. Preprocessing algorithm 2 calculates the power flow direction based on the characteristic parameters such as the instantaneous value, effective value, and phase difference of voltage and current.

[0136] In some embodiments of the present application, a device for determining demand of an electric energy meter is provided. Figure 3 FIG. 1 shows a structural block diagram of a device for determining the demand of an electric energy meter according to some embodiments of the present application. Figure 3 As shown, the demand determination device 300 includes: an acquisition module 302, which is used to acquire electric energy signals within a target time period; wherein the signal period of the electric energy signal is a first period; a processing module 304, which is used to perform signal division processing on the electric energy signal to obtain multiple signal segments; wherein the signal period of multiple signal segments is the second period, and the second period is half a period of the first period; a determination module 306, which is used to: determine the electric energy data corresponding to each signal segment; determine the flow direction corresponding to the electric energy signal based on the electric energy data; among the multiple signal segments, determine the first signal segment with a forward flow direction and the second signal segment with a reverse flow direction; determine the forward power within the target time period based on the first signal segment; determine the reverse power within the target time period based on the second signal segment; and determine the demand within the target time period based on the forward power and the reverse power.

[0137] In this embodiment, the electric energy meter is used to collect electric energy signals within a target time period and measure or convert the collected electric energy signals to obtain corresponding electric energy data. For example, the electric energy data includes current, voltage, flow direction, power, and demand.

[0138] In related technologies, when performing demand and power calculations, it is necessary to accurately determine the flow direction of the power signal and determine the direction of the power data based on the flow direction. To determine the flow direction, it is common to collect voltage and current data for multiple cycles and then perform flow analysis based on this data to accurately determine the flow direction. This results in a lag in determining the flow direction, making it impossible to promptly reflect the real-time status of the power grid. As a result, the final predicted demand cannot accurately reflect the actual demand of the power grid during that time period.

[0139] In response to the above problems, this application aims to improve the accuracy and timeliness of the tidal flow direction judgment during the demand calculation process. By more accurately judging the tidal flow direction, the accuracy of power metering can be improved, thereby improving the accuracy of demand calculation.

[0140] When the energy meter is operating, it continuously collects and records energy signals within a target time period. After obtaining the energy signal, it is divided into half of the signal cycle to generate multiple half-cycle signal segments. By performing power flow analysis on the energy data in each half-cycle signal segment, it can more quickly determine and identify changes in power flow direction, making power flow direction analysis more timely. This ensures a more accurate measurement of the maximum average power within the target time period, reflecting the actual power demand of the grid during that time period. Demand calculations based on this data can effectively improve the accuracy of demand calculations.

[0141] For example, an electric energy meter collects raw signals and converts the collected current and / or voltage signals into digital signals using a high-precision analog-to-digital converter (ADC). The high-precision ADC ensures that the collected signals have high sampling accuracy and signal resolution, providing a reliable data foundation for subsequent signal processing and feature extraction.

[0142] After obtaining the electric energy signal, the electric energy signal is divided according to half of the electric energy signal cycle to obtain at least two half-cycle signal segments. For example, taking the initial electric energy signal cycle as the first cycle, the initial electric energy signal is divided and processed according to half of the first cycle, that is, the second cycle. The multiple signal segments obtained after processing all have a cycle of the second cycle, and the cycle length of the second cycle is half of the cycle length of the first cycle. After obtaining multiple half-cycle signal segments, power flow analysis is performed based on the electric energy data in each signal segment to obtain power flow analysis results for each half cycle, thereby achieving rapid determination of the power flow direction.

[0143] After obtaining the flow direction, the forward power and reverse power are recorded according to the flow direction to obtain the true average power in the target time period, thereby accurately reflecting the instantaneous occupancy level of the current electricity user on the grid capacity.

[0144] For example, when calculating demand, forward and reverse energy are measured separately based on the flow direction. These measurements are then accumulated to calculate the total energy for the target time period. The total energy is then divided by the duration of the target time period to obtain the cycle average power. This cycle average power is then used to calculate the demand for the target time period.

[0145] The power signal is divided into multiple continuous signal segments based on the half-cycle division method, and the flow direction of each signal segment is determined separately. After the flow direction of each signal segment is determined, the signal segment with a forward flow direction is recorded as the first signal segment. The signal segment with a reverse flow direction is recorded as the second signal segment.

[0146] The power measurement results in all the first signal segments are recorded as forward power, and the forward power measurement results in all the first signal segments are accumulated to obtain the total forward power in the target time period.

[0147] Similarly, the power measurement results in all second signal segments are recorded as reverse power, and the reverse power measurement results in all second signal segments are accumulated to obtain the total reverse power in the target time period.

[0148] In some scenarios, it's necessary to determine the net demand. In such scenarios, after obtaining the forward and reverse powers, the forward demand is calculated based on the forward power, and the reverse demand is calculated based on the reverse power. The final demand value = forward demand - reverse demand.

[0149] In other scenarios, independent metering of demand is required, where forward and reverse demand are counted separately. The maximum demand only considers the forward demand value.

[0150] The present application improves the speed and timeliness of determining the direction of the current by dividing the collected electric energy signal into half of its cycle and performing a current analysis based on the electric energy data within the signal segment of the divided half cycle, thereby achieving more accurate electric energy metering and demand calculation, and improving the accuracy of determining the demand.

[0151] In some embodiments of the present application, a device for determining demand of an electric energy meter is provided. Figure 4 FIG. 1 shows a structural block diagram of a device for determining the demand of an electric energy meter according to some embodiments of the present application. Figure 4 As shown, the demand determination device 400 includes: a memory 402 for storing programs or instructions; a processor 404 for implementing the steps of the demand determination method for an electric energy meter provided in any of the above embodiments when executing the programs or instructions, thereby also being able to achieve all the same technical effects. To avoid repetition, they are not described here.

[0152] In some embodiments of the present application, a readable storage medium is provided on which a program or instruction is stored. When the program or instruction is executed by a processor, the steps of the method for determining the demand of an electric energy meter provided in any of the above embodiments are implemented, and thus all the same technical effects can be achieved. To avoid repetition, they will not be described here.

[0153] In some embodiments of the present application, an electric energy meter is provided, including a demand determination device for the electric energy meter as provided in any of the above embodiments, and / or a readable storage medium as provided in any of the above embodiments, so that all the same technical effects can be achieved. To avoid repetition, they will not be described here.

[0154] The methods may be implemented in various ways depending on the specific features and / or example applications. For example, the methods may be implemented through a combination of hardware, firmware, and / or software. For example, in a hardware implementation, the processor may be implemented in one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, electronic devices, other equipment units for performing the above functions, and / or combinations thereof.

[0155] A computer-readable storage medium may be a tangible device that can retain and store instructions for use by an instruction execution device. A computer-readable storage medium may be, but is not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the above. A non-exhaustive list of more specific examples of computer-readable storage media includes: a portable computer floppy disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM) or flash memory, a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory card, a floppy disk, an encoding mechanical device (such as a punched card or a groove having a raised structure with instructions recorded thereon), and any suitable combination of the above. The computer-readable storage medium used herein should not be understood as a transmission signal itself, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagated through waveguides or other transmission media, or electrical signals transmitted through wires.

[0156] In the description of this application, the term "plurality" refers to two or more, unless otherwise expressly defined. The orientation or positional relationship indicated by the terms "upper" and "lower" is based on the orientation or positional relationship described in the accompanying drawings, and is only for the convenience of describing this application and simplifying the description, and does not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on this application; the terms "connect", "install", "fixed", etc. should be understood in a broad sense. For example, "connection" can be a fixed connection, a detachable connection, or an integral connection; it can be directly connected or indirectly connected through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0157] In the description of this application, the terms "one embodiment," "some embodiments," "specific embodiments," etc., mean that the specific features, structures, materials, or characteristics described in conjunction with that embodiment or example are included in at least one embodiment or example of this application. In this application, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described can be combined in any suitable manner in any one or more embodiments or examples.

[0158] The above description is merely a preferred embodiment of the present application and is not intended to limit the present application. Various modifications and variations are possible for those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present application shall be included within the scope of protection of the present application.

Claims

1. A method for determining the demand of an electric energy meter, characterized in that: The demand determination method includes: Collecting an electric energy signal within a target time period; wherein the signal period of the electric energy signal is a first period; Performing signal division processing on the electric energy signal to obtain a plurality of signal segments; wherein the signal periods of the plurality of signal segments are all the second period, and the second period is half the period of the first period; Determining electric energy data corresponding to each of the signal segments; determining a power flow direction corresponding to the power signal based on the power data; Determining, from the plurality of signal segments, a first signal segment in which the tidal current direction is a forward tidal current and a second signal segment in which the tidal current direction is a reverse tidal current; determining, based on the first signal segment, the forward power within the target time period; determining, according to the second signal segment, the reverse power within the target time period; Demand within the target time period is determined according to the forward power and the reverse power.

2. The demand determination method according to claim 1, characterized in that: The electric energy signal includes a current signal and a voltage signal; The determining of the electric energy data corresponding to each of the signal segments includes: The electric energy accumulated value corresponding to each signal segment is determined according to the current signal and the voltage signal corresponding to each signal segment.

3. The demand determination method according to claim 2, characterized in that: The determining the power flow direction corresponding to the power signal based on the power data includes: When the accumulated electric energy value is positive, determining the flow direction as a forward flow; Alternatively, when the accumulated electric energy value is a negative value, the flow direction is determined to be a reverse flow.

4. The demand determination method according to claim 2, characterized in that: Determining the electric energy accumulated value corresponding to each signal segment according to the current signal and the voltage signal corresponding to each signal segment includes: determining an instantaneous power signal corresponding to the signal segment according to the current signal and the voltage signal; The electrical energy accumulated value is determined based on the instantaneous power signal.

5. The demand determination method according to claim 4, characterized in that: The determining the electric energy accumulated value based on the instantaneous power signal includes: Adding N instantaneous power values to obtain the accumulated electric energy value; wherein the signal segment includes N sampling points, the N sampling points correspond one-to-one to the N instantaneous power values, and N is a positive integer; Alternatively, the instantaneous power signal is integrated to obtain the accumulated electric energy value.

6. The demand determination method according to any one of claims 1 to 5, characterized in that: The electric energy signal is an electric energy signal output by the target power grid system, and the method further includes: generating a demand forecast model based on the demand within the target time period; Performing demand forecasting on the target power grid system using the demand forecasting model; When the demand prediction value corresponding to the demand prediction is greater than the demand threshold, the target power grid system is expanded.

7. A device for determining the demand of an electric energy meter, characterized in that: The demand determination device comprises: An acquisition module, configured to acquire an electric energy signal within a target time period; wherein the signal period of the electric energy signal is a first period; a processing module, configured to perform signal division processing on the electric energy signal to obtain a plurality of signal segments; wherein the signal periods of the plurality of signal segments are all a second period, and the second period is a half period of the first period; Identify modules for: Determining electric energy data corresponding to each of the signal segments; determining a power flow direction corresponding to the power signal based on the power data; Determining, from the plurality of signal segments, a first signal segment in which the tidal current direction is a forward tidal current and a second signal segment in which the tidal current direction is a reverse tidal current; determining, based on the first signal segment, the forward power within the target time period; determining, according to the second signal segment, the reverse power within the target time period; Demand within the target time period is determined according to the forward power and the reverse power.

8. A device for determining the demand of an electric energy meter, characterized in that: include: Memory, used to store programs or instructions; A processor, configured to implement the steps of the demand determination method according to any one of claims 1 to 6 when executing the program or instructions.

9. A readable storage medium having a program or instruction stored thereon, characterized in that: When the program or instruction is executed by a processor, the steps of the demand determination method according to any one of claims 1 to 6 are implemented.

10. An electric energy meter, characterized in that: include: The demand determination device for an electric energy meter according to claim 7 or 8; and / or The readable storage medium according to claim 9.

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