CN116794593A - DC energy meter metering error online estimation method based on data driving - Google Patents
DC energy meter metering error online estimation method based on data driving Download PDFInfo
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Abstract
The invention discloses a method for estimating metering error of a direct current energy meter on line based on data driving, which comprises the following steps: collecting a first clock corrected by an electric energy meter in a direct-current power distribution network, and collecting first active electric quantity data and first voltage data in the direct-current power distribution network; detecting abnormal values of the first active electric quantity data and the first voltage data according to normal distribution models corresponding to the first active electric quantity data and the first voltage data respectively, and correcting the abnormal values to obtain second active electric quantity data and second voltage data; according to the second active electric quantity data and the second voltage data, an optimization model for measuring error estimation of the direct current electric energy meter is established, an equivalent variable is introduced to linearly replace an optimization target of the optimization model, a convex optimization model is obtained, and an online measuring error estimated value is obtained by solving, so that operation and maintenance are carried out according to the online measuring error estimated value; the accuracy of the electric energy meter measurement error estimation model in the direct-current power distribution network can be improved, and the model solving efficiency is improved.
Description
Technical Field
The invention relates to the field of error estimation of a direct current ammeter, in particular to a method for online estimation of metering error of a direct current ammeter based on data driving.
Background
Under the driving of a series of policies such as double carbon, construction of a novel power system and the like, large-scale distributed new energy is accessed into the power distribution network. Common distributed new energy sources such as photovoltaic, wind power and energy storage are usually direct current or are converted into direct current after rectification, and an inverter is adopted to be combined into an alternating current power distribution network. In addition, with the recent development of power electronics technology, the overall structure of the load side has also changed greatly. When the AC power distribution system is connected, loads such as an electric automobile, a computer, a mobile phone and the like are required to be provided with an AC/DC device for power supply, and household variable frequency equipment such as an air conditioner, a refrigerator, a washing machine and the like and an energy storage system are also required to pass through the AC/DC/AC device for realizing variable frequency, so that the power supply quality and the power supply reliability are ensured. Under the background, the forms of a direct current power distribution network, an alternating current-direct current series-parallel power distribution network and the like are induced. In the operation of a direct current power distribution network, direct current metering is one of the most important guarantee links, and accurate and reliable direct current metering is particularly critical to the safe and stable operation of the direct current power distribution network. However, the running conditions of the direct current distribution network and the alternating current-direct current series-parallel distribution network are complex and various, direct current loads and power supplies with different properties, such as direct current charging piles, photovoltaic grid connection and the like, have different influences on different working states of the direct current loads, and the voltage and current waveforms under different working conditions are distorted, have obvious differences with ideal direct current load waveforms and influence on the metering accuracy of the direct current electric energy meter. Therefore, the development of the measurement error estimation of the direct current electric energy meter has important significance.
To address this problem, most of the operators currently carry the assay device for field detection. However, the electric energy meter has wide points, time and labor are wasted by means of manual detection, and the feasibility is poor. At present, the electric energy meter has a user electricity consumption data measurement function, the user electricity consumption data essentially reflects the physical characteristics of the operation of the power grid, the on-line estimation of the metering error of the electric energy meter is facilitated through the mining analysis of the user electricity consumption data, and an electric energy meter metering error on-line estimation model based on the law of conservation of electric energy is often adopted in the prior art.
However, at present, an electric energy meter measurement error estimation model based on an electric energy conservation law is mostly applied to an alternating current power distribution network scene, and application research in a direct current power distribution network scene is still lacking. Secondly, the current electric energy meter metering error estimation model of the alternating current power distribution network is obviously influenced by the line loss, and the accuracy of the alternating current electric energy meter metering error estimation is reduced along with the increase of the duty ratio and the change rate of the line loss. In the direct current distribution network, link losses of an AC/DC converter, a DC/DC converter and the like are more obvious except line losses, and the duty ratio is larger. If the typical loss link calculation in the direct current power distribution network is omitted, the error of the original model calculation result is increased or even fails. In addition, the current electric energy meter measurement error estimation model of the alternating current power distribution network is mostly solved by adopting a least square method, the method requires that the number of acquired data time periods is larger than the total number of the electric energy meters, and the application condition is severe.
Disclosure of Invention
The invention aims to overcome the defects in the prior art, and provides a direct current energy meter metering error online estimation method based on data driving, which can improve the accuracy of an energy meter metering error estimation model in a direct current power distribution network and improve the model solving efficiency.
The invention provides a DC energy meter metering error online estimation method based on data driving, which comprises the following steps:
collecting a first clock corrected by an electric energy meter in a direct-current power distribution network, and collecting first active electric quantity data of the same frequency of the total surface of an alternating-current input side and the direct-current electric energy meter in preset time and first voltage data of the total surface of the alternating-current input side in the direct-current power distribution network under the first clock;
detecting abnormal values of the first active electric quantity data and the first voltage data according to a first normal distribution model of the first active electric quantity data and a second normal distribution model of the first voltage data respectively, and correcting the abnormal values to obtain second active electric quantity data and second voltage data respectively;
and establishing an optimization model for measuring error estimation of the direct current electric energy meter according to the second active electric quantity data and the second voltage data, introducing an equivalent variable to linearly replace an optimization target of the optimization model, obtaining a convex optimization model, solving, and obtaining an online measuring error estimated value so as to carry out operation and maintenance according to the online measuring error estimated value.
According to the invention, the abnormal value of the direct-current electric energy meter of the direct-current power distribution network is detected through normal distribution, the abnormal values of the active electric quantity data and the voltage data can be obtained, the abnormal values are corrected, the limit of the data acquisition number can be relieved, enough and complete direct-current electric energy meter data can be obtained, and the accuracy and the reliability of an electric energy meter measurement error estimation model for direct-current power distribution in the direct-current power distribution network are further improved; and the equivalent variable is introduced to linearly replace the optimization target of the optimization model, so that the model solving efficiency can be improved.
Further, the detecting the abnormal value of the first active electric quantity data and the first voltage data according to the first normal distribution model of the first active electric quantity data and the second normal distribution model of the first voltage data respectively includes:
establishing a first normal distribution model according to the first active electric quantity data, wherein if the first active electric quantity is out of a first preset value range of the first normal distribution model, the first active electric quantity is a first abnormal value; the first active power quantity data are obtained according to the difference value of the forward active power quantity and the reverse active power quantity.
Further, the correcting the abnormal value to obtain second active power data and second voltage data respectively includes:
the method comprises the steps of obtaining middle values of front and rear end data of a first abnormal value of first active electric quantity data to replace the first abnormal value, obtaining middle values of front and rear end data of a second abnormal value of first voltage data to replace the second abnormal value, and obtaining second active electric quantity data and second voltage data respectively.
Further, the introducing equivalent variables linearly replaces the optimization targets of the optimization model to obtain a convex optimization model and solves the convex optimization model to obtain an online metering error estimated value, and the method comprises the following steps:
acquiring a first difference value between second active electric quantity data of the total surface of the alternating current input side and an electric quantity value of a loss model; wherein the loss model comprises: the method comprises a line loss model, a conversion loss model of an AC/DC converter and a conversion loss model of a DC/DC converter in front of a DC electric energy meter;
and carrying out linear replacement on the optimization target according to the first difference value, and carrying out linear programming solution on the obtained convex optimization model to obtain an online metering error estimated value.
According to the invention, equivalent variables are used for solving the optimization model comprising the circuit loss model of the direct current power distribution network, the conversion loss model of the AC/DC converter and the conversion loss model of the DC/DC converter in front of the direct current electric energy meter, compared with the traditional model, the influence of high loss ratio and large fluctuation on the accuracy of an evaluation result is effectively reduced by finely quantizing various typical link losses, so that the accuracy of the electric energy meter metering error estimation model in the direct current power distribution network is improved, and the applicability is higher.
Further, the linearly replacing the optimization objective according to the first difference value includes:
introducing a first equivalent variable which is the same as the first difference value into the optimization model, obtaining a second difference value of the first equivalent variable and the electric quantity value of the metering error model of the direct current energy meter, and introducing a second equivalent variable which is the same as the absolute value of the second difference value, so that the optimization target is linearly replaced according to the second equivalent variable.
Further, the first clock after collecting the electric energy meter correction in the direct current power distribution network includes:
collecting second clocks corresponding to electric energy meters in the direct-current power distribution network, and sequentially judging whether the difference value between the second clocks and a third clock of a master station system is larger than a preset threshold value;
and if the difference value between the second clock and the third clock of the master station system is larger than a preset threshold value, clock correction is carried out, and a corrected first clock is correspondingly obtained.
Further, before the first normal distribution model according to the first active power amount data and the second normal distribution model according to the first voltage data, respectively, the method further includes:
detecting the missing value of the first active electric quantity data and the first voltage data respectively, and filling the missing value according to the linear difference value if the values exist at the time adjacent to the front and the rear of the missing value, so as to obtain the first active electric quantity data and the first voltage data without the missing value;
If the missing value is not all the values at the time adjacent to the missing value, the first active electric quantity data and the first voltage data at the time are all abandoned.
Further, the detecting the abnormal value of the first active electric quantity data and the first voltage data according to the first normal distribution model of the first active electric quantity data and the second normal distribution model of the first voltage data respectively, further includes:
and establishing a second normal distribution model according to the first voltage data, and if the voltage data is out of a second preset value range of the second normal distribution model, setting the voltage data as a second abnormal value.
Preferably, the introducing equivalent variables linearly replace the optimization targets of the optimization model, which can be expressed as:
wherein X is t And Y t Respectively obtaining a first equivalent variable and a second equivalent variable at the time t in the optimization target; t (T) a Is direct currentTotal time period number that the energy meter data can collect; r is (r) 0j The unit resistance of the j-th direct current main line is omega/km; l (L) j The length of the j-th direct current main line; η (eta) AC-DCj Conversion efficiency for the jth AC/DC converter; η (eta) DC-DCk The conversion efficiency of the DC/DC converter in front of the kth direct current electric energy meter is obtained; n (N) AC-DC Is the total number of AC/DC converters; n (N) DC-DC The total number of the DC/DC converters in front of the direct current electric energy meter; n (N) m The total number of the direct current electric energy meters is; w (W) 0j,t The data of the second active power quantity at the t moment of the total surface t of the jth alternating current input side; u (U) 0j,t The second voltage data is the j-th alternating current input side total table t moment; w (W) i,t The second active electric quantity data at the moment t of the ith direct current electric energy meter; and->The total electric quantity sum of the alternating current input side, the electric quantity value sum of the line loss model, the electric quantity value sum of the conversion loss model of the AC/DC converter, the electric quantity value sum of the conversion loss model of the DC/DC converter before the DC electric energy meter and the electric quantity value sum of the metering error model of the DC electric energy meter are respectively; epsilon i The metering error rate of the direct current electric energy meter i.
Preferably, the constraint of the second equivalent variable can be expressed as:
wherein alpha is t A 0-1 variable introduced at time t; m is a preset positive number.
Drawings
FIG. 1 is a schematic flow chart of an online estimation method of metering error of a DC energy meter based on data driving according to an embodiment of the invention;
fig. 2 is a schematic diagram of a topology structure of a simulation model of a dc power distribution network according to an embodiment of the present invention;
FIG. 3 is a graph illustrating an average relative error of online measurement error estimates of each DC electric energy meter according to an embodiment of the present invention;
Fig. 4 is a schematic structural diagram of the data-driven dc energy meter metering error online estimation system provided by the invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, a flow chart of a method for online estimation of metering error of a dc energy meter based on data driving according to an embodiment of the present invention includes steps S11 to S13, specifically:
and S11, acquiring a first clock corrected by the electric energy meter in the direct-current power distribution network, and under the first clock, acquiring first active electric quantity data of the same frequency between the total surface of the alternating-current input side and the direct-current electric energy meter in the direct-current power distribution network and first voltage data of the total surface of the alternating-current input side.
The first clock after the correction of the electric energy meter in the direct-current power distribution network is collected comprises the following steps: collecting second clocks corresponding to electric energy meters in the direct-current power distribution network, and sequentially judging whether the difference value between the second clocks and a third clock of a master station system is larger than a preset threshold value; and if the difference value between the second clock and the third clock of the master station system is larger than a preset threshold value, clock correction is carried out, and a corrected first clock is correspondingly obtained.
It is worth to say that, the remote master station system issues clock acquisition commands to the total table of the alternating current input side of the direct current power distribution network of the target and each direct current electric energy meter successively, and the direct current power distribution network receives the clock acquisition commandsCollecting clock values of each electric energy meter, wherein the clock values comprise: data of 6 dimensions including year, month, day, time, minute and second are recorded as C mi Simultaneously recording the clock value of the master station system when issuing the command each time, and recording the clock value of the master station system as C si . When comparing the clock value of each electric energy meter with the clock value of the master station system, if the difference value between the clock value of the electric energy meter and the clock value of the master station system is not greater than a preset threshold value, issuing a clock correction command to the electric energy meter so that the clock value of the electric energy meter is changed into the clock value of the master station system after the electric energy meter receives the clock correction command; otherwise, the clock value of the electric energy meter is not required to be operated. Namely: if |C mi ―C si |≤t 0 The clock correction instruction is issued to the electric energy meter i, and after the electric energy meter i receives the clock correction instruction, the electric energy meter i modifies the clock value of the electric energy meter i into C si The method comprises the steps of carrying out a first treatment on the surface of the Otherwise, no operation is required.
The method is worthy of explanation, first active electric quantity data of the same frequency of the total surface of the alternating current input side and the direct current electric energy meter in preset time and first voltage data of the total surface of the alternating current input side in the direct current power distribution network are collected; the preset time is the time span of data acquisition. Illustratively, such as: the preset time of 10 days is from 1 st 11 th 2022 to 10 th 11 th 2022. The frequency is a time interval for recording active electric quantity data of each electric energy meter and total surface voltage data of an alternating current input side, and the frequency comprises: 1 minute, 5 minutes or 15 minutes. According to the data recording frequency of the electric energy meter, the time period number which can be acquired by the data of the electric energy meter in one day can be calculated, and the total time period number which can be acquired by the data of the electric energy meter in the set time can be calculated; the total time period number of the data acquisition is larger than the total number of the electric energy meters of the target distribution network.
Preferably, the number of acquirable time periods and the total number of time periods may be expressed as:
T a ＝d×T d ，
the delta t is the time interval of the data recording of the active electric quantity of the electric energy meter and the total voltage of the alternating current input side, and the unit is minutes; d is the time span of data acquisition in days.
And step S12, detecting abnormal values of the first active electric quantity data and the first voltage data according to a first normal distribution model of the first active electric quantity data and a second normal distribution model of the first voltage data respectively, and correcting the abnormal values to obtain second active electric quantity data and second voltage data respectively.
The preprocessing operation of data missing and abnormal value is needed to be carried out on the collected first active power quantity data and first voltage data. Respectively detecting missing values of the collected first active electric quantity data and first voltage data, and filling the missing values by adopting linear interpolation to obtain first active electric quantity data without missing values and first voltage data without missing values; and respectively detecting abnormal values of the first active electric quantity data without the missing values and the first voltage data without the missing values, and correcting the abnormal values by adopting linear interpolation to obtain second active electric quantity data and second voltage data.
Specifically, before the first normal distribution model according to the first active power amount data and the second normal distribution model according to the first voltage data, respectively, the method further includes: detecting the missing value of the first active electric quantity data and the first voltage data respectively, and filling the missing value according to the linear difference value if the values exist at the time adjacent to the front and the rear of the missing value, so as to obtain the first active electric quantity data and the first voltage data without the missing value; if the missing value is not all the values at the time adjacent to the missing value, the first active electric quantity data and the first voltage data at the time are all abandoned.
It is worth to say that, when the first active electric quantity data or the first voltage data at a certain acquisition time is missing, if the data exist at the time adjacent to the time before and after the time, the linear interpolation method is adopted to fill the data missing, otherwise, the data of all the electric energy meters at the time are all discarded.
The method for detecting the abnormal value of the first active electric quantity data and the first voltage data according to a first normal distribution model of the first active electric quantity data and a second normal distribution model of the first voltage data respectively comprises the following steps: establishing a first normal distribution model according to the first active electric quantity data, wherein if the first active electric quantity is out of a first preset value range of the first normal distribution model, the first active electric quantity is a first abnormal value; the first active power quantity data are obtained according to the difference value of the forward active power quantity and the reverse active power quantity. Furthermore, the method further comprises: and establishing a second normal distribution model according to the first voltage data, and if the voltage data is out of a second preset value range of the second normal distribution model, setting the voltage data as a second abnormal value.
Preferably, the abnormal value detection is performed on the collected first active power data and the first voltage data by adopting a 3-sigma criterion.
For example, when the abnormal value detection is performed on the first active power data by using the 3-sigma criterion, the normal distribution mean and standard deviation of the first active power data may be expressed as:
wherein W is i,t For the first active electric quantity data of the electric energy meter i at the moment T, T a As the number of total time periods,and the average value and standard deviation of a curve corresponding to the first active electric quantity data of the electric energy meter i in the set time are obtained.
For example, the detection of the abnormal value of the first active power amount data may be expressed as:
wherein W is i,t The first active power data of the electric energy meter i at the time t,and the average value and standard deviation of a curve corresponding to the first active electric quantity data of the electric energy meter i in the set time are obtained.
It is worth to say that, according to the mean value and standard deviation of the curve corresponding to the total voltage data of the ac input side, the detection of the abnormal value of the first voltage data can be obtained by adopting the 3-sigma criterion. When the first active electric quantity data or the first voltage data is judged to be abnormal, abnormal values are removed, and a linear interpolation method is adopted for filling.
It is worth to say that the first active electric quantity data of the same frequency of the total surface of the alternating current input side of the direct current power distribution network and each direct current electric energy meter in the set time is composed of a forward active electric quantity part and a reverse active electric quantity part.
Preferably, the first active power quantity data may be expressed as:
wherein W is i,t The active power value of the direct current electric energy meter i is t time periods;the positive and negative active power values of the direct current electric energy meter i at the t time interval are respectively obtained.
Filling the abnormal value to obtain second active electric quantity data and second voltage data respectively, wherein the method comprises the following steps of: the method comprises the steps of obtaining middle values of front and rear end data of a first abnormal value of first active electric quantity data to replace the first abnormal value, obtaining middle values of front and rear end data of a second abnormal value of first voltage data to replace the second abnormal value, and obtaining second active electric quantity data and second voltage data respectively.
Preferably, the linear interpolation of the first outlier of the first active power quantity and the linear interpolation of the second outlier of the first voltage data may be expressed as:
wherein W is i,t The second active electric quantity data after linear interpolation is carried out on the first abnormal value of the total surface i of the direct current input side at the moment t, U 0j,t And exchanging second voltage data after linear interpolation corresponding to the first abnormal value of the total table j of the input side at the moment t.
And S13, establishing an optimization model for estimating the metering error of the direct-current electric energy meter according to the second active electric quantity data and the second voltage data, introducing an equivalent variable to linearly replace an optimization target of the optimization model, obtaining a convex optimization model, solving, and obtaining an online metering error estimated value so as to operate and maintain according to the online metering error estimated value.
Introducing equivalent variables to linearly replace an optimization target of the optimization model to obtain a convex optimization model and solving to obtain an online metering error estimated value, wherein the method comprises the following steps of: acquiring a first difference value between the second active electric quantity data of the alternating current input side and an electric quantity value of a loss model; wherein the loss model comprises: the method comprises a line loss model, a conversion loss model of an AC/DC converter and a conversion loss model of a DC/DC converter in front of a DC electric energy meter; and carrying out linear replacement on the optimization target according to the first difference value, and carrying out linear programming solution on the obtained convex optimization model to obtain an online metering error estimated value.
Preferably, the line loss model of the dc distribution network may be expressed as:
wherein r is 0j The unit resistance of the j-th direct current main line is omega/km; l (L) j Is the length of the j-th direct current main line.
Since the conversion loss of the AC/DC converter is linearly related to the AC side input power as a whole, the AC/DC converter loss model of the DC distribution network can be preferably expressed as:
ΔW AC-DCj,t ＝W 0j,t ×(1―η AC-DCj )，
wherein eta AC-DCj The conversion efficiency of the jth AC/DC converter.
The DC/DC converter has a conversion loss that is linear with the DC side input power as a whole. In a direct current power distribution network, the direct current electric energy meter is configured differently under different load metering scenes, and the direct current electric energy meter can be roughly divided into two scenes: 1) The direct current electric energy meter measures the loss value of the DC/DC converter, such as distributed photovoltaic, energy storage and the like; 2) The direct current electric energy meter does not measure the loss value of the DC/DC converter, and the loss value of the DC/DC converter comprises an electric automobile charging pile.
Preferably, for the case that the DC/DC converter loss value is not measured by the DC electric energy meter, the loss model of the DC/DC converter before the DC electric energy meter may be expressed as:
wherein eta DC-DCk The conversion efficiency of the DC/DC converter in front of the kth direct current electric energy meter. It should be noted that, because of the multiple voltage levels in the DC distribution network, part of the distributed power source or the power load can be directly connected to the grid without a DC/DC converter, and the corresponding η is the same DC-DCi Taken as 1.
Based on the law of conservation of electric energy, a multi-element linear equation set considering the balance of the supplied electric quantity, the lost electric quantity and the load electric quantity in each period of the direct-current power distribution network is established according to a line loss model, a conversion loss model of an AC/DC converter and a conversion loss model of a DC/DC converter in front of the direct-current electric energy meter, and an optimization model for metering error estimation of the direct-current electric energy meter is established according to the multi-element linear equation set.
According to the invention, the original model is converted into the convex optimization model, and the linear programming method is adopted for solving, so that the model solving efficiency can be effectively improved, the global optimal solution can be obtained by solving, meanwhile, the limitation of the traditional least square method on the data acquisition quantity of the electric energy meter is relieved, the model solving efficiency can be improved, and the accuracy of the electric energy meter measurement error estimation model in the direct-current power distribution network can be improved by carrying out parameter change through equivalent variables.
Preferably, the system of multiple linear equations can be expressed as:
wherein ε i,t For the metering error rate of the direct current electric energy meter i at the moment t, N AC-DC N is the total number of the AC/DC converters DC-DC The total number of the DC/DC converters in front of the direct current electric energy meter; andthe total electric quantity sum of the input total surface at the alternating current side, the electric quantity value sum of the line loss model, the electric quantity value sum of the conversion loss model of the AC/DC converter, the electric quantity value sum of the conversion loss model of the DC/DC converter before the DC electric energy meter and the electric quantity value sum of the metering error model of the DC electric energy meter are respectively; r is (r) 0j The unit resistance of the j-th direct current main line is omega/km; l (L) j The length of the j-th direct current main line; η (eta) AC-DCj Conversion efficiency for the jth AC/DC converter; η (eta) DC-DCk The conversion efficiency of the DC/DC converter in front of the kth direct current electric energy meter is obtained; n (N) m To take the total number of the DC energy meter.
Preferably, the objective function of the optimization model of the dc ammeter measurement error estimate may be expressed as:
s.t.-∞≤ε i ≤+∞，
wherein T is a The total time period number is the total time period number which can be acquired by the data of the direct current electric energy meter; epsilon i For the metering error rate of the direct current electric energy meter i at the time t, the range is [ - ++infinity, ++infinity]Between N AC-DC N is the total number of the AC/DC converters DC-DC The total number of the DC/DC converters in front of the direct current electric energy meter; And->The total electric quantity sum of the alternating current input side, the electric quantity value sum of the line loss model, the electric quantity value sum of the conversion loss model of the AC/DC converter, the electric quantity value sum of the conversion loss model of the DC/DC converter before the DC electric energy meter and the electric quantity value sum of the metering error model of the DC electric energy meter are respectively; r is (r) 0j The unit resistance of the j-th direct current main line is omega/km; l (L) j The length of the j-th direct current main line; η (eta) AC-DCj Conversion efficiency for the jth AC/DC converter; η (eta) DC-DCk The conversion efficiency of the DC/DC converter in front of the kth direct current electric energy meter is obtained; n (N) m To take the total number of the DC energy meter.
According to the invention, equivalent variables are used for solving the optimization model comprising the circuit loss model of the direct current power distribution network, the conversion loss model of the AC/DC converter and the conversion loss model of the DC/DC converter in front of the direct current electric energy meter, compared with the traditional model, the influence of high loss ratio and large fluctuation on the accuracy of an evaluation result is effectively reduced by finely quantizing various typical link losses, so that the accuracy of the electric energy meter metering error estimation model in the direct current power distribution network is improved, and the applicability is higher.
Performing linear replacement on the optimization target according to the first difference value, including: introducing a first equivalent variable which is the same as the first difference value into the optimization model, obtaining a second difference value of the first equivalent variable and the electric quantity value of the metering error model of the direct current energy meter, and introducing a second equivalent variable which is the same as the absolute value of the second difference value, so that the optimization target is linearly replaced according to the second equivalent variable.
Preferably, the introducing equivalent variables linearly replace the optimization targets of the optimization model, which can be expressed as:
wherein X is t And Y t And the first equivalent variable and the second equivalent variable are respectively the absolute value term at the moment t in the optimization target.
Preferably, the constraint of the second equivalent variable can be expressed as:
wherein alpha is t A 0-1 variable introduced at time t; m is a preset positive number.
According to the invention, the abnormal value of the direct-current electric energy meter of the direct-current power distribution network is detected through normal distribution, the abnormal value of the active electric quantity data and the voltage data can be obtained, the abnormal value is filled, the limit of the data acquisition number can be relieved, enough and complete direct-current electric energy meter data can be obtained, and the accuracy and the reliability of an electric energy meter measurement error estimation model for direct-current power distribution in the direct-current power distribution network are improved; and the equivalent variable is introduced to linearly replace the optimization target of the optimization model, so that the model solving efficiency can be improved.
For example, to verify the effectiveness of the method of the present invention, a DC power distribution network simulation model is constructed, see FIG. 2The topological structure diagram of the direct current power distribution network simulation model provided by the embodiment of the invention is that in the diagram, 20 load branches, 10 distributed photovoltaic branches, 10 electric automobile charging load branches and 5 energy storage device branches are arranged in the direct current power distribution network. A total of 1 ac input side total and 45 dc power meters were configured. For the branch of the distributed photovoltaic and energy storage device, the DC electric energy meter measures the loss value of the DC/DC converter; for low-power direct current load and electric automobile charging load, the direct current electric energy meter does not measure the loss value of the DC/DC converter. Resistor r of unit length of DC main line 0 And the length L is 200m and 0.0754 ohm/km, the Matlab platform is based on which the power flow simulation calculation of the direct-current distribution network is carried out, the injected active power of the alternating-current input side is obtained and is used as the active power curve of the total surface of the alternating-current input side, and the active power of the total surface of the alternating-current input side and each direct-current electric energy meter are multiplied by the time interval to obtain the active power reference curve.
Preferably, the conversion efficiency η of the AC/DC converter AC-DC Conversion efficiency eta of the DC/DC converter in front of the direct current electric energy meter is 0.95 DC-DC 0.92.
In 45 direct current electric energy meters, the standard curves of the active electric energy meters 5, 25 and 35 are overlapped with normal distribution random error values with the average value of 0 and the standard deviation of 5% of the standard curve of the active electric energy, and the standard deviation of 1% of the standard curve of the active electric energy meters are overlapped with normal distribution random error values with the average value of 0 to form new active electric energy curves of the direct current electric energy meters. Based on the curve, an optimization model of the metering error estimation of the direct current electric energy meter is established, and the online metering error estimation value of each electric energy meter is obtained through solving. And evaluating the accuracy of the calculation result of the optimization model of the DC ammeter metering error estimation according to the average relative error of the DC ammeter online metering error estimation value and the superimposed random error value.
Preferably, the average relative error may be expressed as:
wherein ε i 、κ i The measurement error estimated value and the superimposed random error value of the ith direct current electric energy meter are respectively obtained.
Referring to fig. 3, a schematic diagram of an average relative error of an online measurement error estimation value of each dc electric energy meter according to an embodiment of the present invention is shown, in which average relative errors of 45 dc electric energy meters are in a range of 0,4%, and it can be seen that according to the online measurement error estimation method of the dc electric energy meter based on data driving of the present invention, accuracy of a measurement error estimation model of the electric energy meter in a dc power distribution network can be improved.
Referring to fig. 4, a schematic structural diagram of an online estimation system for measuring errors of a dc energy meter based on data driving according to the present invention includes: a data acquisition module 41, a preprocessing module 42 and an online estimation module 43.
It should be noted that, the data acquisition module 41 is mainly configured to acquire first active power data and first voltage data of each electric energy meter, and transmit the acquired data to the preprocessing module 42; after the preprocessing module 42 obtains the collected data, preprocessing the missing value and the abnormal value to obtain second active power data and second voltage data, and transmitting the second active power data and the second voltage data to the online estimation module 43; after receiving the second active power data and the second voltage data, the online estimation module 43 establishes an optimization model of the measurement error estimation of the direct current electric energy meter, and solves the optimization model to obtain an online measurement error estimation value, so that operation and maintenance are performed according to the online measurement error estimation value.
The data collection module 41 is configured to collect a first clock after correction of the electric energy meter in the dc power distribution network, and collect, under the first clock, first active power data of the same frequency between the ac input side total surface and the dc electric energy meter in the dc power distribution network in a preset time, and first voltage data of the ac input side total surface.
The first clock after the correction of the electric energy meter in the direct-current power distribution network is collected comprises the following steps: collecting second clocks corresponding to electric energy meters in the direct-current power distribution network, and sequentially judging whether the difference value between the second clocks and a third clock of a master station system is larger than a preset threshold value; and if the difference value between the second clock and the third clock of the master station system is larger than a preset threshold value, clock correction is carried out, and a corrected first clock is correspondingly obtained.
The preprocessing module 42 is configured to detect an abnormal value of the first active power data and the first voltage data according to a first normal distribution model of the first active power data and a second normal distribution model of the first voltage data, and correct the abnormal value to obtain second active power data and second voltage data, respectively.
The method for detecting the abnormal value of the first active electric quantity data and the first voltage data according to a first normal distribution model of the first active electric quantity data and a second normal distribution model of the first voltage data respectively comprises the following steps: establishing a first normal distribution model according to the first active electric quantity data, wherein if the first active electric quantity is out of a first preset value range of the first normal distribution model, the first active electric quantity is a first abnormal value; the first active power quantity data are obtained according to the difference value of the forward active power quantity and the reverse active power quantity. Furthermore, the method further comprises: and establishing a second normal distribution model according to the first voltage data, and if the voltage data is out of a second preset value range of the second normal distribution model, setting the voltage data as a second abnormal value.
Filling the abnormal value to obtain second active electric quantity data and second voltage data respectively, wherein the method comprises the following steps of: the method comprises the steps of obtaining middle values of front and rear end data of a first abnormal value of first active electric quantity data to replace the first abnormal value, obtaining middle values of front and rear end data of a second abnormal value of first voltage data to replace the second abnormal value, and obtaining second active electric quantity data and second voltage data respectively.
It is noted that before the first normal distribution model according to the first active power amount data and the second normal distribution model according to the first voltage data, the method further includes: detecting the missing value of the first active electric quantity data and the first voltage data respectively, and filling the missing value according to the linear difference value if the values exist at the time adjacent to the front and the rear of the missing value, so as to obtain the first active electric quantity data and the first voltage data without the missing value; if the missing value is not all the values at the time adjacent to the missing value, the first active electric quantity data and the first voltage data at the time are all abandoned.
The online estimation module 43 is configured to establish an optimization model for estimating the metering error of the dc electric energy meter according to the second active electric quantity data and the second voltage data, introduce an equivalent variable to linearly replace an optimization target of the optimization model, obtain a convex optimization model, and solve the convex optimization model to obtain an online metering error estimation value, so that operation and maintenance are performed according to the online metering error estimation value.
Introducing equivalent variables to linearly replace an optimization target of the optimization model to obtain a convex optimization model and solving to obtain an online metering error estimated value, wherein the method comprises the following steps of: taking a first difference value between second active electric quantity data of the total table of the alternating current input side and an electric quantity value of a loss model; wherein the loss model comprises: the method comprises a line loss model, a conversion loss model of an AC/DC converter and a conversion loss model of a DC/DC converter in front of a DC electric energy meter; and carrying out linear replacement on the optimization target according to the first difference value, and carrying out linear programming solution on the obtained convex optimization model to obtain an online metering error estimated value.
Performing linear replacement on the optimization target according to the first difference value, including: introducing a first equivalent variable which is the same as the first difference value into the optimization model, obtaining a second difference value of the first equivalent variable and the electric quantity value of the metering error model of the direct current energy meter, and introducing a second equivalent variable which is the same as the absolute value of the second difference value, so that the optimization target is linearly replaced according to the second equivalent variable.
Preferably, the introduction of equivalent variables to linearly replace the optimization objective of the optimization model can be expressed as:
Wherein X is t And Y t Respectively obtaining a first equivalent variable and a second equivalent variable at the time t in the optimization target; t (T) a The total time period number is the total time period number which can be acquired by the data of the direct current electric energy meter; r is (r) 0j The unit resistance of the j-th direct current main line is omega/km; l (L) j The length of the j-th direct current main line; η (eta) AC-DCj Conversion efficiency for the jth AC/DC converter; η (eta) DC-DCk The conversion efficiency of the DC/DC converter in front of the kth direct current electric energy meter is obtained; n (N) AC-DC Is the total number of AC/DC converters; n (N) DC-DC The total number of DC/DC converters of the direct current electric energy meter; n (N) m The total number of the direct current electric energy meters is; w (W) 0j,t The data of the second active power quantity at the t moment of the total surface t of the jth alternating current input side; u (U) 0j,t The second voltage data is the j-th alternating current input side total table t moment; w (W) i,t The second active electric quantity data at the moment t of the ith direct current electric energy meter; and->The total electric quantity sum of the alternating current input side, the electric quantity value sum of the line loss model, the electric quantity value sum of the conversion loss model of the AC/DC converter, the electric quantity value sum of the conversion loss model of the DC/DC converter before the DC electric energy meter and the electric quantity value sum of the metering error model of the DC electric energy meter are respectively; epsilon i The metering error rate of the direct current electric energy meter i.
Preferably, the constraint of the second equivalent variable can be expressed as:
Wherein alpha is t A 0-1 variable introduced at time t; m isA preset positive number.
According to the invention, the metering error estimation model of the direct-current electric energy meter of the direct-current power distribution network is realized by considering various typical link losses. Compared with the traditional model, the method has the advantages that loss values of all links are quantized finely, so that the influence of high loss ratio and large fluctuation on the accuracy of the estimated result is effectively reduced. And an equivalent variable is introduced, an original model is converted into a convex optimization model, and the model is solved by adopting a linear programming method, so that the model solving efficiency can be effectively improved, the global optimal solution is obtained by solving, and meanwhile, the limitation of the traditional least square method on the data acquisition quantity of the electric energy meter is relieved.
The invention also provides a computer terminal device, comprising: one or more processors; a memory coupled to the processor for storing one or more programs; the one or more programs, when executed by the one or more processors, cause the one or more processors to implement the data-driven direct current energy meter metering error online estimation method.
The invention also provides a computer readable storage medium, on which a computer program is stored, which when being executed by a processor, implements the data-driven direct current energy meter metering error online estimation method.
It will be appreciated by those skilled in the art that embodiments of the present application may also be provided including a computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The foregoing is merely a preferred embodiment of the present invention, and it should be noted that modifications and variations could be made by those skilled in the art without departing from the technical principles of the present invention, and such modifications and variations should also be regarded as being within the scope of the invention.
Claims (10)
1. The method for online estimation of the metering error of the direct current energy meter based on data driving is characterized by comprising the following steps of:
collecting a first clock corrected by an electric energy meter in a direct-current power distribution network, and collecting first active electric quantity data of the same frequency of the total surface of an alternating-current input side and the direct-current electric energy meter in preset time and first voltage data of the total surface of the alternating-current input side in the direct-current power distribution network under the first clock;
detecting abnormal values of the first active electric quantity data and the first voltage data according to a first normal distribution model of the first active electric quantity data and a second normal distribution model of the first voltage data respectively, and correcting the abnormal values to obtain second active electric quantity data and second voltage data respectively;
and establishing an optimization model for measuring error estimation of the direct current electric energy meter according to the second active electric quantity data and the second voltage data, introducing an equivalent variable to linearly replace an optimization target of the optimization model, obtaining a convex optimization model, solving, and obtaining an online measuring error estimated value so as to carry out operation and maintenance according to the online measuring error estimated value.
2. The method of on-line estimation of metering errors of a data-driven dc energy meter according to claim 1, wherein the detecting abnormal values of the first active electric quantity data and the first voltage data according to a first normal distribution model of the first active electric quantity data and a second normal distribution model of the first voltage data, respectively, comprises:
Establishing a first normal distribution model according to the first active electric quantity data, wherein if the first active electric quantity is out of a first preset value range of the first normal distribution model, the first active electric quantity is a first abnormal value; the first active power quantity data are obtained according to the difference value of the forward active power quantity and the reverse active power quantity.
3. The online estimation method of metering error of a dc energy meter based on data driving according to claim 1, wherein the correcting the abnormal value to obtain the second active power data and the second voltage data respectively comprises:
the method comprises the steps of obtaining middle values of front and rear end data of a first abnormal value of first active electric quantity data to replace the first abnormal value, obtaining middle values of front and rear end data of a second abnormal value of first voltage data to replace the second abnormal value, and obtaining second active electric quantity data and second voltage data respectively.
4. The online estimation method of the metering error of the direct current energy meter based on data driving according to claim 1, wherein the introducing the equivalent variable linearly replaces the optimization target of the optimization model to obtain a convex optimization model and solves the convex optimization model to obtain an online metering error estimated value comprises the following steps:
Acquiring a first difference value between second active electric quantity data of the total surface of the alternating current input side and an electric quantity value of a loss model; wherein the loss model comprises: the method comprises a line loss model, a conversion loss model of an AC/DC converter and a conversion loss model of a DC/DC converter in front of a DC electric energy meter;
and carrying out linear replacement on the optimization target according to the first difference value, and carrying out linear programming solution on the obtained convex optimization model to obtain an online metering error estimated value.
5. The online data-driven dc energy meter metering error estimation method of claim 4, wherein the linearly replacing the optimization objective according to the first difference value comprises:
introducing a first equivalent variable which is the same as the first difference value into the optimization model, obtaining a second difference value of the first equivalent variable and the electric quantity value of the metering error model of the direct current energy meter, and introducing a second equivalent variable which is the same as the absolute value of the second difference value, so that the optimization target is linearly replaced according to the second equivalent variable.
6. The online estimation method of metering error of a direct current energy meter based on data driving according to claim 1, wherein the collecting the corrected first clock of the energy meter in the direct current power distribution network comprises:
Collecting second clocks corresponding to electric energy meters in the direct-current power distribution network, and sequentially judging whether the difference value between the second clocks and a third clock of a master station system is larger than a preset threshold value;
and if the difference value between the second clock and the third clock of the master station system is larger than a preset threshold value, clock correction is carried out, and a corrected first clock is correspondingly obtained.
7. The data-driven dc energy meter metering error online estimation method according to claim 1, further comprising, before the first normal distribution model according to the first active power amount data and the second normal distribution model according to the first voltage data, respectively:
detecting the missing value of the first active electric quantity data and the first voltage data respectively, and filling the missing value according to the linear difference value if the values exist at the time adjacent to the front and the rear of the missing value, so as to obtain the first active electric quantity data and the first voltage data without the missing value;
if the missing value is not all the values at the time adjacent to the missing value, the first active electric quantity data and the first voltage data at the time are all abandoned.
8. The method of on-line estimation of metering errors of a data-driven dc energy meter according to claim 2, wherein the detecting abnormal values of the first active electric quantity data and the first voltage data according to a first normal distribution model of the first active electric quantity data and a second normal distribution model of the first voltage data, respectively, further comprises:
And establishing a second normal distribution model according to the first voltage data, and if the voltage data is out of a second preset value range of the second normal distribution model, setting the voltage data as a second abnormal value.
9. The online estimation method of metering error of direct current energy meter based on data driving according to claim 1, wherein the introducing equivalent variable performs linear replacement on the optimization target of the optimization model, which can be expressed as:
wherein X is t And Y t Respectively obtaining a first equivalent variable and a second equivalent variable at the time t in the optimization target; t (T) a The total time period number is the total time period number which can be acquired by the data of the direct current electric energy meter; r is (r) 0j The unit resistance of the j-th direct current main line is omega/km; l (L) j The length of the j-th direct current main line; η (eta) AC-DCj Conversion efficiency for the jth AC/DC converter; η (eta) DC-DCk The conversion efficiency of the DC/DC converter in front of the kth direct current electric energy meter is obtained; n (N) AC-DC Is the total number of AC/DC converters; n (N) DC-DC The total number of the DC/DC converters in front of the direct current electric energy meter; n (N) m The total number of the direct current electric energy meters is; w (W) 0j,t The data of the second active power quantity at the t moment of the total surface t of the jth alternating current input side; u (U) 0j,t The second voltage data is the j-th alternating current input side total table t moment; w (W) i,t The second active electric quantity data at the moment t of the ith direct current electric energy meter; And->The total electric quantity sum of the alternating current input side, the electric quantity value sum of the line loss model, the electric quantity value sum of the conversion loss model of the AC/DC converter, the electric quantity value sum of the conversion loss model of the DC/DC converter before the DC electric energy meter and the electric quantity value sum of the metering error model of the DC electric energy meter are respectively; epsilon i The metering error rate of the direct current electric energy meter i.
10. The data-driven direct current energy meter metering error online estimation method according to claim 9, wherein the constraint of the second equivalent variable can be expressed as:
wherein alpha is t A 0-1 variable introduced at time t; m is a preset positive number.
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