CN117330831A - Electric energy metering method and system for nonlinear load - Google Patents
Electric energy metering method and system for nonlinear load Download PDFInfo
- Publication number
- CN117330831A CN117330831A CN202311079959.4A CN202311079959A CN117330831A CN 117330831 A CN117330831 A CN 117330831A CN 202311079959 A CN202311079959 A CN 202311079959A CN 117330831 A CN117330831 A CN 117330831A
- Authority
- CN
- China
- Prior art keywords
- power
- harmonic
- metering
- data
- current
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 50
- 238000004364 calculation method Methods 0.000 claims abstract description 62
- 238000004458 analytical method Methods 0.000 claims abstract description 34
- 238000012937 correction Methods 0.000 claims abstract description 34
- 238000004088 simulation Methods 0.000 claims abstract description 33
- 238000004422 calculation algorithm Methods 0.000 claims abstract description 29
- 238000005259 measurement Methods 0.000 claims abstract description 16
- 230000007246 mechanism Effects 0.000 claims abstract description 16
- 238000012544 monitoring process Methods 0.000 claims abstract description 8
- 238000005070 sampling Methods 0.000 claims description 22
- 238000001914 filtration Methods 0.000 claims description 16
- 230000007613 environmental effect Effects 0.000 claims description 9
- 230000009466 transformation Effects 0.000 claims description 7
- 230000008859 change Effects 0.000 claims description 6
- 238000007781 pre-processing Methods 0.000 claims description 5
- 238000011426 transformation method Methods 0.000 claims description 5
- 238000013480 data collection Methods 0.000 claims description 3
- 238000013461 design Methods 0.000 claims description 3
- 230000000694 effects Effects 0.000 claims description 3
- 238000002474 experimental method Methods 0.000 claims description 3
- 238000004091 panning Methods 0.000 claims description 3
- 230000002194 synthesizing effect Effects 0.000 claims description 3
- 238000005265 energy consumption Methods 0.000 abstract description 3
- 230000003137 locomotive effect Effects 0.000 description 4
- 230000001052 transient effect Effects 0.000 description 3
- 238000010891 electric arc Methods 0.000 description 2
- 230000005611 electricity Effects 0.000 description 2
- 230000001965 increasing effect Effects 0.000 description 2
- 238000007726 management method Methods 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 238000012935 Averaging Methods 0.000 description 1
- 230000005355 Hall effect Effects 0.000 description 1
- 230000008878 coupling Effects 0.000 description 1
- 238000010168 coupling process Methods 0.000 description 1
- 238000005859 coupling reaction Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000008713 feedback mechanism Effects 0.000 description 1
- 230000006872 improvement Effects 0.000 description 1
- 230000001939 inductive effect Effects 0.000 description 1
- 230000002123 temporal effect Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R22/00—Arrangements for measuring time integral of electric power or current, e.g. electricity meters
- G01R22/06—Arrangements for measuring time integral of electric power or current, e.g. electricity meters by electronic methods
- G01R22/10—Arrangements for measuring time integral of electric power or current, e.g. electricity meters by electronic methods using digital techniques
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R11/00—Electromechanical arrangements for measuring time integral of electric power or current, e.g. of consumption
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R23/00—Arrangements for measuring frequencies; Arrangements for analysing frequency spectra
- G01R23/16—Spectrum analysis; Fourier analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/14—Fourier, Walsh or analogous domain transformations, e.g. Laplace, Hilbert, Karhunen-Loeve, transforms
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00006—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment
- H02J13/00016—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network characterised by information or instructions transport means between the monitoring, controlling or managing units and monitored, controlled or operated power network element or electrical equipment using a wired telecommunication network or a data transmission bus
-
- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
- H02J13/00032—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for
- H02J13/00036—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for the elements or equipment being or involving switches, relays or circuit breakers
Abstract
The invention discloses an electric energy metering method and system for nonlinear load, comprising the following steps: step 1: collecting current and voltage data; step 2: calculating instantaneous power of the collected current and voltage data; step 3: carrying out harmonic analysis on the collected current and voltage data; step 4: based on the geometric topology and parameters of the power system, finite element modeling is carried out, nonlinear load elements are introduced into the model, and actual conditions are simulated; step 5: fitting average active power and reactive power obtained by a virtual power algorithm with results obtained by harmonic analysis and finite element simulation; step 6: and carrying out error correction according to the difference between the actual measurement data and the simulation calculation result, monitoring the load state and the electric energy parameter in real time through a feedback control mechanism, and adjusting the metering method according to the metering error. The invention can more accurately measure the electric energy consumption of the nonlinear load.
Description
Technical Field
The invention relates to the technical field of electric energy metering, in particular to an electric energy metering method and system for nonlinear loads.
Background
With the rapid development of power systems, the power grid is no longer simply a simple correspondence of conventional power sources to loads in the past. Today, with the increasing demand for electricity and the changing energy structure, a large number of new nonlinear loads, such as arc furnaces, electric locomotives, electric car charging stations, new energy power stations, etc., are gradually introduced into the power grid. The addition of these new loads brings a rich diversity to the grid, but also brings unprecedented challenges to the metering of electrical energy.
As an indispensable infrastructure of modern society, the stable operation of the electric power system is critical to the normal operation of various industries. However, the metering method designed by the traditional power system is mainly based on a theoretical model under the linear load condition, and is difficult to accurately cope with complex electric energy characteristics caused by nonlinear loads. In this case, the conventional metering method often cannot accurately reflect the actual electricity consumption condition of the nonlinear load, and a large metering error is generated. Therefore, in order to ensure the accuracy of electric energy metering, a new metering method is required.
Disclosure of Invention
In order to solve the above problems, the present invention provides an electric energy metering method and system for nonlinear loads.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows:
in one aspect, the invention discloses a method for metering electrical energy for a nonlinear load, comprising the steps of:
step 1: collecting current and voltage data, and load working state and environment information, filtering and calibrating the collected data, ensuring the quality and accuracy of the data, and determining sampling frequency and duration to adapt to the instantaneous change of nonlinear load;
step 2: calculating instantaneous power of the collected current and voltage data to obtain instantaneous active power and reactive power, and obtaining average active power and reactive power of the load according to an instantaneous power calculation method by using a virtual power algorithm;
step 3: harmonic analysis is carried out on the collected current and voltage data, harmonic components in the system are identified, and a wavelet transformation method is used for converting signals from a time domain to a frequency domain so as to detect each order of harmonic;
step 4: based on the geometric topology and parameters of the power system, finite element modeling is carried out, nonlinear load elements are introduced into the model, actual conditions are simulated, finite element software is used for carrying out simulation calculation on the power system, current and voltage distribution is obtained, and meanwhile harmonic waves introduced by nonlinear loads are considered;
step 5: fitting average active power and reactive power obtained by a virtual power algorithm with results obtained by harmonic analysis and finite element simulation, and correcting a virtual power calculation result by considering the influence of harmonic components introduced by nonlinear load on power;
step 6: and carrying out error correction according to the difference between the actual measurement data and the simulation calculation result, monitoring the load state and the electric energy parameter in real time through a feedback control mechanism, and adjusting the metering method according to the metering error.
Further: the step 1 comprises the following steps:
and (3) data collection: placing a current sensor and a voltage sensor in the power system to acquire current and voltage information of a load connection point;
environmental information collection: collecting environmental information related to a load operating state;
data filtering and calibration: filtering the collected current and voltage data to remove high frequency noise and interference, wherein the filtered current and voltage signals are respectively represented as I (t) and V (t), and in order to eliminate errors caused by sensor nonlinearity and deviation, data calibration is performed according to the following formula:
I calibrated (t)＝a I ·I(t)+b I
V calibrated (t)＝a V ·V(t)+b V
wherein a is I 、b I 、a V 、b V The method is obtained through a calibration experiment;
sampling frequency and duration determination: f (f) sample ＞2f max Wherein f max Is a currentOr the highest frequency component of the voltage signal.
Further: the step 2 comprises the following steps:
instantaneous power calculation:
using already calibrated and filtered current I calibrated (t) and voltage V calibrated (t) data calculate instantaneous power:
the active power P (t) is calculated by the following formula:
P(t)＝V calibratad (t)·I calibrated (t)·cos(θ(t))
where θ (t) is the phase difference between the current and voltage, and P (t) represents the active power at each instant in time;
the reactive power Q (t) is calculated by the following formula:
Q(t)＝V calibrated (t)·I calibrated (t)·sin(θt))
where θ (t) is the phase difference between current and voltage, Q (t) represents reactive power at each instant in time;
average power calculation:
the instantaneous power data is averaged by the sampling points, assuming a total of N sampling points, the average active power Pavg and reactive power Qavg are calculated as follows:
wherein t is i Is the time corresponding to the i-th sampling point.
Further: the step 3 comprises the following steps:
the calibrated and filtered current I calibrated (t) and voltage V calibrated And (t) carrying out wavelet transformation on the data, wherein the transformation formula is as follows:
where x (t) is the input signal, ψ (t) is the wavelet basis function, a is the scale parameter, and b is the panning parameter.
Further: the step 4 comprises the following steps:
establishing a geometric topology and parameter model of the power system: constructing a geometric topology and parameter model of the power system from the topology map and parameter information of the power system;
a nonlinear load element is introduced: introducing a nonlinear load element into the power system model;
finite element meshing: dividing a model of the power system into finite element grids;
and (3) simulation calculation: obtaining the distribution condition of current and voltage on different nodes and grids by solving a finite element equation in the electric power system model;
harmonic analysis: on the basis of the simulation calculation result, harmonic analysis is carried out, and harmonic components of current and voltage are extracted so as to obtain amplitude values and phases of different harmonic orders.
Further: the step 5 comprises the following steps:
comprehensive measurement results: average active power P obtained by virtual power algorithm avg And reactive power Q avg Synthesizing results obtained by harmonic analysis and finite element simulation;
correction of harmonic effects on power: the influence of harmonic components introduced by nonlinear loads is reduced by correcting the virtual power calculation result, and the correction formula is as follows:
P corrected -P avg +P harmonic
wherein P is avg Is the average active power obtained by the virtual power algorithm, P harmonic Is the active power correction value introduced by harmonic wave;
fitting and calculating a metering result:
under the condition of considering harmonic wave influence, the corrected virtual power calculation result is used to obtain comprehensive active power P final And reactive power Q final
P final ＝P corrected
Q final ＝Q avg +Q harmonic
Wherein Q is avg Is the average reactive power obtained by the virtual power algorithm, Q harmonic Is the reactive power correction value introduced by the harmonic wave.
Further: the step 6 comprises the following steps:
error correction:
comparing the actual measurement data with the simulation calculation result to determine a metering error, and calculating the difference between the actual power and the calculated power to realize the metering error: assume that the calculation error of the active power is E P The reactive power calculation error is E Q It is possible to obtain:
E P ＝P masured -P final
E Q ＝Q measured -Q final
wherein P is measured And Q measured The active power and the reactive power are obtained by actual measurement;
feedback control mechanism design: based on the metering error, a feedback control mechanism is designed to adjust the metering method so as to better match the actual situation;
and (3) adjusting a metering method: according to the results of the error correction and feedback control mechanism, the previous metering method is adjusted;
feedback control loop: through a feedback control loop, the system can perform error correction and metering method adjustment periodically or according to the requirement.
In another aspect, the present invention discloses an electrical energy metering system for a nonlinear load, comprising:
and the data acquisition and preprocessing module is used for: collecting current and voltage data, and load working state and environment information, filtering and calibrating the collected data, ensuring the quality and accuracy of the data, and determining sampling frequency and duration to adapt to the instantaneous change of nonlinear load;
virtual power calculation module: calculating instantaneous power of the collected current and voltage data to obtain instantaneous active power and reactive power, and obtaining average active power and reactive power of the load according to an instantaneous power calculation method by using a virtual power algorithm;
harmonic analysis module: harmonic analysis is carried out on the collected current and voltage data, harmonic components in the system are identified, and a wavelet transformation method is used for converting signals from a time domain to a frequency domain so as to detect each order of harmonic;
finite element modeling module: based on the geometric topology and parameters of the power system, finite element modeling is carried out, nonlinear load elements are introduced into the model, actual conditions are simulated, finite element software is used for carrying out simulation calculation on the power system, current and voltage distribution is obtained, and meanwhile harmonic waves introduced by nonlinear loads are considered;
and a metering result fitting module: fitting average active power and reactive power obtained by a virtual power algorithm with results obtained by harmonic analysis and finite element simulation, and correcting a virtual power calculation result by considering the influence of harmonic components introduced by nonlinear load on power;
error correction and feedback control module: and carrying out error correction according to the difference between the actual measurement data and the simulation calculation result, monitoring the load state and the electric energy parameter in real time through a feedback control mechanism, and adjusting the metering method according to the metering error.
Compared with the prior art, the invention has the following technical progress:
more accurate power metering: the virtual power algorithm can be used for more accurately calculating the active power and the reactive power of the nonlinear load by combining harmonic analysis, and errors of the virtual power algorithm under the nonlinear condition are reduced by comprehensively considering harmonic components.
Finer load characteristics analysis: the finite element method can simulate the harmonic wave and current distribution condition introduced by the load in a complex power system, and helps to understand the influence of the nonlinear load on the power grid, so that the characteristics of the load are analyzed more deeply.
Better adaptability: the combination of the finite element method and the virtual power algorithm enables the metering method to be better adapted to nonlinear loads of different types and characteristics. More accurate metering results are obtained whether it is an electric arc furnace, an electric locomotive or an electric car charging station.
Providing prediction and warning functions: harmonic analysis can help identify harmonic problems introduced by nonlinear loads, thereby early finding potential power quality problems. This allows system operators to take precautions to avoid grid instability or equipment damage.
Optimizing energy efficiency in real time: by means of the more accurate metering result, system operators can evaluate the energy consumption of the load more accurately, so that the energy efficiency is optimized in real time when the energy consumption is required, and the energy cost is reduced.
Better load management: by combining a finite element method, more detailed information can be provided in load management and planning, so that a power grid operator can be helped to better analyze the influence of the load and make a more reasonable decision.
The stability of the power system is improved: by deeply analyzing the harmonic problem introduced by the nonlinear load, the influence of the harmonic on the power system can be better known, and corresponding measures are taken to improve the stability of the system.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention.
In the drawings:
FIG. 1 is a flow chart of the present invention.
Detailed Description
The following embodiments may be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments. Embodiments of the present invention will be described below with reference to the accompanying drawings.
As shown in fig. 1, a method for measuring electric energy for a nonlinear load includes the steps of:
step 1: data acquisition and preprocessing
Current and voltage data is collected, as well as load operating status and environmental information. And filtering and calibrating the acquired data to ensure the quality and accuracy of the data. The sampling frequency and duration are determined to accommodate the instantaneous change in the nonlinear load.
Step 2: virtual power calculation
And calculating the instantaneous power of the acquired current and voltage data to obtain instantaneous active power and reactive power. And obtaining the average active power and reactive power of the load according to the instantaneous power calculation method by using a virtual power algorithm.
Step 3: harmonic analysis
And carrying out harmonic analysis on the acquired current and voltage data to identify harmonic components in the system. The signal is converted from the time domain to the frequency domain by wavelet transformation or the like so as to detect each order of harmonic.
Step 4: finite element modeling
Based on the geometric topology and parameters of the power system, finite element modeling is performed, wherein nonlinear load elements such as an electric arc furnace, an electric locomotive and the like are introduced into the model by loads, cables, transformers and the like, and actual conditions are simulated. And (3) performing simulation calculation on the power system by using finite element software to obtain current and voltage distribution, and simultaneously considering harmonic waves introduced by nonlinear loads.
Step 5: comprehensive metering result
And synthesizing the average active power and reactive power obtained by the virtual power algorithm with the results obtained by harmonic analysis and finite element simulation. And correcting the virtual power calculation result by considering the influence of harmonic components introduced by the nonlinear load on the power.
Step 6: error correction and feedback control
And performing error correction according to the difference between the actual measurement data and the simulation calculation result. And designing a feedback control mechanism, monitoring the load state and the electric energy parameter in real time, and adjusting the metering method according to the metering error.
Specifically, step 1 includes:
step 1 involves data acquisition and preprocessing aimed at acquiring high quality current and voltage data while taking into account load operating conditions and environmental information. The following implementation steps are as follows:
and (3) data collection:
a current sensor and a voltage sensor are placed in the power system to obtain current and voltage information of the load connection point. These sensors may operate based on hall effect, inductive coupling, or resistance measurement principles. Data acquisition may be accomplished by an analog-to-digital converter (ADC).
Environmental information collection:
environmental information is collected regarding the load operating conditions, such as temperature, humidity, load type, etc. This may be achieved by a temperature sensor, a humidity sensor, etc.
Data filtering and calibration:
the collected current and voltage data is filtered to remove high frequency noise and interference. Common filtering methods include low pass filtering, median filtering, and the like. The filtered current and voltage signals are denoted as I (t) and V (t), respectively. The data calibration is to eliminate errors caused by sensor nonlinearities and biases. The calibration process may use a linear or nonlinear calibration function:
I calibrated (t)＝a I ·I(t)+b I
V calibrated (t)＝a V ·V(t)+b V
wherein a is I 、b I 、a V 、b V Is a calibration coefficient, and can be obtained through a calibration experiment.
Sampling frequency and duration determination:
sampling frequency f sample Is a parameter that determines the current and voltage data acquisition rates. For nonlinear loads, a sampling frequency high enough to capture transient changes is required. Generally, f is selected sample Meets the Nyquist sampling theorem, i.e., f sample >2f max Wherein f max Is the highest frequency component of the current or voltage signal.
Duration T duration Representing the length of time for each data acquisition. For transient events, a smaller T may be required duration For long-time data acquisition, T can be increased appropriately duration 。
The goal of these steps is to ensure that the current and voltage data obtained from the sensors are accurate, while taking into account load operating conditions and environmental factors. Data filtering and calibration helps to improve data quality, while proper sampling frequency and duration ensure adequate data accuracy to cope with transient variations in nonlinear loading.
Specifically, step 2 includes:
step 2 relates to the application of a virtual power algorithm for calculating the instantaneous active and reactive power of the nonlinear load and calculating the average active and reactive power from these data. The following steps are realized:
instantaneous power calculation:
using already calibrated and filtered current I calibrated (t) and voltage V calibrated (t) data calculate instantaneous power:
the active power P (t) is calculated by the following formula:
P(t)＝V calibrated (t)·I calibrated (t)·cos(θ(t))
where θ (t) is the phase difference between the current and voltage, and P (t) represents the active power at each instant in time;
the reactive power Q (t) is calculated by the following formula:
Q(t)＝V calibrated (t)·I calibrated (t)·sin(θ(t))
where θ (t) is the phase difference between the current and voltage, and Q (t) represents the reactive power at each instant in time.
Average power calculation (virtual power algorithm):
using the instantaneous power data, a power waveform over a time sequence can be obtained. However, this waveform may be unstable when the temporal variation is large. In order to obtain a smoother average power, the averaging may be performed by sampling points. Assuming a total of N sampling points, the average active power P avg And reactive power Q avg The calculation is as follows:
wherein t is i Is the time corresponding to the i-th sampling point.
The steps can obtain the instantaneous active power and the reactive power of the load by calculating the instantaneous power and applying a virtual power algorithm, and calculate the average active power and the reactive power by an average method. This provides the basis data for subsequent metering and analysis.
Specifically, step 3 includes:
the calibrated and filtered current I calibrated (t) and voltage V calibrated And (t) carrying out wavelet transformation on the data, wherein the transformation formula is as follows:
where x (t) is the input signal, ψ (t) is the wavelet basis function, a is the scale parameter, and b is the panning parameter.
The signal is decomposed into wavelet coefficients of different frequencies and scales, and the wavelet coefficient map can be used to analyze the presence of harmonic components. The high frequency wavelet coefficients typically represent high frequency components, possibly harmonics. Peaks in the wavelet coefficient map may represent harmonic orders.
Wavelet transform methods can help identify and analyze harmonic problems introduced by nonlinear loads. This method allows a more detailed knowledge of the characteristics of the signal in the time-frequency domain, thereby locating and analyzing the harmonic components more accurately.
Specifically, step 4 includes:
establishing a geometric topology and parameter model of the power system:
and constructing a geometric topology and a parameter model of the power system from the topology map and the parameter information of the power system. This includes components such as generators, transformers, loads, cables, etc.
A nonlinear load element is introduced:
nonlinear load elements, such as arc furnaces, electric locomotives, etc., are introduced into the power system model. This can be achieved by an equivalent circuit model of the nonlinear element taking into account the current-voltage characteristics of the element.
Finite element meshing:
the model of the power system is partitioned into a finite element mesh. The fine granularity of the grid depends on the required accuracy and simulation complexity.
And (3) simulation calculation:
and obtaining the distribution condition of the current and the voltage on different nodes and grids by solving a finite element equation in the electric power system model. Such distribution information can be used to analyze current and voltage conditions in the system, including harmonics introduced by nonlinear loads.
Harmonic analysis:
and on the basis of the simulation calculation result, harmonic analysis is carried out to extract harmonic components of current and voltage. Harmonic analysis can be performed using FFT or the like to obtain the amplitude and phase of the different harmonic orders.
In this step, the finite element method combines modeling and simulation of the power system, and can more accurately analyze harmonic problems introduced by nonlinear loads.
Specifically, step 5 includes:
comprehensive measurement results:
average active power P obtained by virtual power algorithm avg And reactive power Q avg And the result obtained by harmonic analysis and finite element simulation is combined to obtain a more accurate metering result.
Correction of harmonic effects on power:
harmonic components introduced by nonlinear loading may affect the power metering result, especially when there is a phase difference between current and voltage, which can be taken into account by modifying the virtual power calculation result. Harmonic introduced reactive power typically results in an underestimation of the actual power, while the active power may be affected by the phase difference.
And (3) correcting the formula:
the formula for correcting the virtual power calculation will vary depending on the particular harmonic impact situation. In this embodiment, the correction method is to correct the active power and the reactive power according to the power influence introduced by the harmonic, and calculate the corrected active power Pcorrected as:
P corrected ＝P avg +P harmonic
wherein P is avg Is the average active power obtained by the virtual power algorithm, P harmonic Is the active power correction value introduced by the harmonic wave.
Fitting and calculating a metering result:
under the condition of considering harmonic wave influence, the corrected virtual power calculation result is used to obtain comprehensive active power P final And reactive power Q final
P final ＝P corrected
Q final ＝Q avg +Q harrmonic
Wherein Q is avg Is the average reactive power obtained by the virtual power algorithm, Q harmonic Is the reactive power correction value introduced by the harmonic wave.
The goal of this step is to correct and optimize the metering result by comprehensively considering the results of virtual power calculation, harmonic analysis and finite element simulation to obtain a more accurate power metering of the nonlinear load.
Specifically, step 6 includes:
step 6 involves error correction and feedback control to ensure accuracy of the metering result and to adjust according to the metering error under real-time monitoring. The following implementation steps are as follows:
error correction:
the actual measurement data is compared with the simulated calculation results to determine the metrology error, periodically or as needed. This may be achieved by calculating the difference between the actual power and the calculated powerAnd different to achieve the aim. Assume that the calculation error of the active power is E P The reactive power calculation error is E Q It is possible to obtain:
E P ＝P measured -P final
E Q ＝Q measured -Q final
wherein P is measured And Q measured Is the actual measured active power and reactive power.
Feedback control mechanism design:
based on the metering error, a feedback control mechanism is designed to adjust the metering method to better match the actual situation. This may be achieved by changing the calculation parameters, adjusting the filtering strategy, or optimizing the correction formula.
And (3) adjusting a metering method:
the previous metering method is adjusted according to the results of the error correction and feedback control mechanisms. For example, parameters of the virtual power algorithm may be adaptively adjusted according to the magnitude of the error, or thresholds in the harmonic analysis may be modified.
Feedback control loop:
a feedback control loop is designed so that the system can make error correction and metrology adjustments periodically or as needed. This will ensure that the metering method is always consistent with the actual situation and can accommodate variations in different operating conditions.
The goal of step 6 is to establish a feedback mechanism between the actual measured data and the simulated calculation to correct the metrology error and dynamically adjust the metrology method to obtain a more accurate metrology result.
In another aspect, the present invention also discloses an electric energy metering system for nonlinear load, which is characterized by comprising:
and the data acquisition and preprocessing module is used for: collecting current and voltage data, and load working state and environment information, filtering and calibrating the collected data, ensuring the quality and accuracy of the data, and determining sampling frequency and duration to adapt to the instantaneous change of nonlinear load;
virtual power calculation module: calculating instantaneous power of the collected current and voltage data to obtain instantaneous active power and reactive power, and obtaining average active power and reactive power of the load according to an instantaneous power calculation method by using a virtual power algorithm;
harmonic analysis module: harmonic analysis is carried out on the collected current and voltage data, harmonic components in the system are identified, and a wavelet transformation method is used for converting signals from a time domain to a frequency domain so as to detect each order of harmonic;
finite element modeling module: based on the geometric topology and parameters of the power system, finite element modeling is carried out, nonlinear load elements are introduced into the model, actual conditions are simulated, finite element software is used for carrying out simulation calculation on the power system, current and voltage distribution is obtained, and meanwhile harmonic waves introduced by nonlinear loads are considered;
and a metering result fitting module: fitting average active power and reactive power obtained by a virtual power algorithm with results obtained by harmonic analysis and finite element simulation, and correcting a virtual power calculation result by considering the influence of harmonic components introduced by nonlinear load on power;
error correction and feedback control module: and carrying out error correction according to the difference between the actual measurement data and the simulation calculation result, monitoring the load state and the electric energy parameter in real time through a feedback control mechanism, and adjusting the metering method according to the metering error.
Finally, it should be noted that: the foregoing description is only a preferred embodiment of the present invention, and the present invention is not limited thereto, but it is to be understood that modifications and equivalents of some of the technical features described in the foregoing embodiments may be made by those skilled in the art, although the present invention has been described in detail with reference to the foregoing embodiments. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.
Claims (8)
1. A method of metering electrical energy for a nonlinear load, comprising the steps of:
step 1: collecting current and voltage data, and load working state and environment information, filtering and calibrating the collected data, ensuring the quality and accuracy of the data, and determining sampling frequency and duration to adapt to the instantaneous change of nonlinear load;
step 2: calculating instantaneous power of the collected current and voltage data to obtain instantaneous active power and reactive power, and obtaining average active power and reactive power of the load according to an instantaneous power calculation method by using a virtual power algorithm;
step 3: harmonic analysis is carried out on the collected current and voltage data, harmonic components in the system are identified, and a wavelet transformation method is used for converting signals from a time domain to a frequency domain so as to detect each order of harmonic;
step 4: based on the geometric topology and parameters of the power system, finite element modeling is carried out, nonlinear load elements are introduced into the model, actual conditions are simulated, finite element software is used for carrying out simulation calculation on the power system, current and voltage distribution is obtained, and meanwhile harmonic waves introduced by nonlinear loads are considered;
step 5: fitting average active power and reactive power obtained by a virtual power algorithm with results obtained by harmonic analysis and finite element simulation, and correcting a virtual power calculation result by considering the influence of harmonic components introduced by nonlinear load on power;
step 6: and carrying out error correction according to the difference between the actual measurement data and the simulation calculation result, monitoring the load state and the electric energy parameter in real time through a feedback control mechanism, and adjusting the metering method according to the metering error.
2. A method of metering electrical energy for a nonlinear load according to claim 1, wherein said step 1 comprises:
and (3) data collection: placing a current sensor and a voltage sensor in the power system to acquire current and voltage information of a load connection point;
environmental information collection: collecting environmental information related to a load operating state;
data filtering and calibration: filtering the collected current and voltage data to remove high frequency noise and interference, wherein the filtered current and voltage signals are respectively represented as I (t) and V (t), and in order to eliminate errors caused by sensor nonlinearity and deviation, data calibration is performed according to the following formula:
I calibrated (t)＝a I ·I(t)+b I
V calibrated (t)＝a V ·V(t)+b V
wherein a is I 、b I 、a V 、b V Is a calibration coefficient, and can be obtained through a calibration experiment;
sampling frequency and duration determination: f (f) sample >2f max Wherein f max Is the highest frequency component of the current or voltage signal.
3. A method of metering electrical energy for a nonlinear load in accordance with claim 2, wherein said step 2 comprises:
instantaneous power calculation:
using already calibrated and filtered current I calibrated (t) and voltage V calibrated (t) data calculate instantaneous power:
the active power P (t) is calculated by the following formula:
P(t)＝V calibrated (t)·I calibrated (t)·cos(θ(t))
where θ (t) is the phase difference between the current and voltage, and P (t) represents the active power at each instant in time;
the reactive power Q (t) is calculated by the following formula:
Q(t)＝V calibrated (t)·I calibrated (t)·sin(θ(t))
where θ (t) is the phase difference between current and voltage, Q (t) represents reactive power at each instant in time;
average power calculation:
the instantaneous power data is averaged by the sampling points,assuming a total of N sampling points, the average active power P avg And reactive power Q avg The calculation is as follows:
wherein t is i Is the time corresponding to the i-th sampling point.
4. A method of metering electrical energy for a nonlinear load in accordance with claim 3, wherein said step 3 comprises:
the calibrated and filtered current I calibrated (t) and voltage V calibrated And (t) carrying out wavelet transformation on the data, wherein the transformation formula is as follows:
where x (t) is the input signal, ψ (t) is the wavelet basis function, a is the scale parameter, and b is the panning parameter.
5. The method of power metering for nonlinear loads according to claim 4, wherein said step 4 comprises:
establishing a geometric topology and parameter model of the power system: constructing a geometric topology and parameter model of the power system from the topology map and parameter information of the power system;
a nonlinear load element is introduced: introducing a nonlinear load element into the power system model;
finite element meshing: dividing a model of the power system into finite element grids;
and (3) simulation calculation: obtaining the distribution condition of current and voltage on different nodes and grids by solving a finite element equation in the electric power system model;
harmonic analysis: on the basis of the simulation calculation result, harmonic analysis is carried out, and harmonic components of current and voltage are extracted so as to obtain amplitude values and phases of different harmonic orders.
6. The method of claim 5, wherein said step 5 comprises:
comprehensive measurement results: average active power P obtained by virtual power algorithm avg And reactive power Q avg Synthesizing results obtained by harmonic analysis and finite element simulation;
correction of harmonic effects on power: the influence of harmonic components introduced by nonlinear loads is reduced by correcting the virtual power calculation result, and the correction formula is as follows:
P corrected ＝P avg +P harmonic
wherein P is avg Is the average active power obtained by the virtual power algorithm, P harmonic Is the active power correction value introduced by harmonic wave;
fitting and calculating a metering result:
under the condition of considering harmonic wave influence, the corrected virtual power calculation result is used to obtain comprehensive active power P final And reactive power Q final
P final ＝P corrected
Q final ＝Q avg +Q harmonic
Wherein Q is avg Is the average reactive power obtained by the virtual power algorithm, Q harmonic Is the reactive power correction value introduced by the harmonic wave.
7. The method of power metering for nonlinear loads according to claim 6, wherein said step 6 comprises:
error correction:
actual measurement data and analog meterThe calculation results are compared to determine a metering error by calculating the difference between the actual power and the calculated power: assuming that the calculation error of the active power is EP and the calculation error of the reactive power is E Q It is possible to obtain:
E P ＝P measured -P final
E Q ＝Q measured -Q final
wherein P is measured And Q measured The active power and the reactive power are obtained by actual measurement;
feedback control mechanism design: based on the metering error, a feedback control mechanism is designed to adjust the metering method so as to better match the actual situation;
and (3) adjusting a metering method: according to the results of the error correction and feedback control mechanism, the previous metering method is adjusted;
feedback control loop: through a feedback control loop, the system can perform error correction and metering method adjustment periodically or according to the requirement.
8. An electrical energy metering system for a nonlinear load, comprising:
and the data acquisition and preprocessing module is used for: collecting current and voltage data, and load working state and environment information, filtering and calibrating the collected data, ensuring the quality and accuracy of the data, and determining sampling frequency and duration to adapt to the instantaneous change of nonlinear load;
virtual power calculation module: calculating instantaneous power of the collected current and voltage data to obtain instantaneous active power and reactive power, and obtaining average active power and reactive power of the load according to an instantaneous power calculation method by using a virtual power algorithm;
harmonic analysis module: harmonic analysis is carried out on the collected current and voltage data, harmonic components in the system are identified, and a wavelet transformation method is used for converting signals from a time domain to a frequency domain so as to detect each order of harmonic;
finite element modeling module: based on the geometric topology and parameters of the power system, finite element modeling is carried out, nonlinear load elements are introduced into the model, actual conditions are simulated, finite element software is used for carrying out simulation calculation on the power system, current and voltage distribution is obtained, and meanwhile harmonic waves introduced by nonlinear loads are considered;
and a metering result fitting module: fitting average active power and reactive power obtained by a virtual power algorithm with results obtained by harmonic analysis and finite element simulation, and correcting a virtual power calculation result by considering the influence of harmonic components introduced by nonlinear load on power;
error correction and feedback control module: and carrying out error correction according to the difference between the actual measurement data and the simulation calculation result, monitoring the load state and the electric energy parameter in real time through a feedback control mechanism, and adjusting the metering method according to the metering error.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311079959.4A CN117330831A (en) | 2023-08-24 | 2023-08-24 | Electric energy metering method and system for nonlinear load |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311079959.4A CN117330831A (en) | 2023-08-24 | 2023-08-24 | Electric energy metering method and system for nonlinear load |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117330831A true CN117330831A (en) | 2024-01-02 |
Family
ID=89281905
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311079959.4A Pending CN117330831A (en) | 2023-08-24 | 2023-08-24 | Electric energy metering method and system for nonlinear load |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117330831A (en) |
-
2023
- 2023-08-24 CN CN202311079959.4A patent/CN117330831A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| De Angelis et al. | Uncertainty characterization of a practical system for broadband measurement of battery EIS | |
| WO2012108993A1 (en) | Non-linearity calibration using an internal source in an intelligent electronic device | |
| AU2012214770A1 (en) | Non-linearity calibration using an internal source in an intelligent electronic device | |
| CN109900959B (en) | Method for extracting harmonic component in dynamic sinusoidal distortion signal | |
| Pogliano et al. | Software platform for PMU algorithm testing | |
| Artale et al. | Measurement of Simplified Single-and Three-Phase Parameters for Harmonic Emission Assessment Based on IEEE 1459-2010 | |
| CN103229062A (en) | Method for measurement of total harmonic distortion | |
| CN108896944B (en) | Laboratory calibrator of synchronous measuring device and synchronous phasor measuring method thereof | |
| KR20100021964A (en) | Apparatus for measuring the impedance of the high power energy devices by the digital lock in amplifier and method for the same | |
| CN117330831A (en) | Electric energy metering method and system for nonlinear load | |
| CN109581045A (en) | A kind of m-Acetyl chlorophosphonazo power measurement method meeting IEC standard frame | |
| Sun et al. | PMU placement for dynamic state tracking of power systems | |
| Tentzerakis et al. | Measurement of wind farm harmonic emissions | |
| Gallo et al. | On the Measurement of Power Electronic Devices' Frequency Coupling Admittance | |
| CN115639400A (en) | High-precision alternating current electric energy metering method | |
| CN113156358B (en) | Method and system for analyzing abnormal line loss of overhead transmission line | |
| CN108334822B (en) | Kalman and modified wavelet transform filtering method based on electric vehicle charging nonlinear load characteristics | |
| Xu et al. | Study on the estimation of utility harmonic impedance based on minimum norm of impedance difference | |
| CN115754886A (en) | Electric energy meter metering compensation method, storage medium and electric energy meter | |
| Redondo et al. | A strategy for improving the accuracy of flicker emission measurement from wind turbines | |
| CN108982967A (en) | A kind of network of ship parameter real time monitoring system and method | |
| Baccigalupi et al. | An improved error model of data acquisition systems | |
| Acunto et al. | A new bidimensional histogram for the dynamic characterization of ADCs | |
| Kocewiak et al. | Harmonic analysis of wind turbines including measurements, data analysis and modelling | |
| JP3620930B2 (en) | Power system characteristic estimation apparatus and characteristic estimation method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |