CN110687377B - Online monitoring data processing method and device for distributed energy system - Google Patents
Online monitoring data processing method and device for distributed energy system Download PDFInfo
- Publication number
- CN110687377B CN110687377B CN201910969378.5A CN201910969378A CN110687377B CN 110687377 B CN110687377 B CN 110687377B CN 201910969378 A CN201910969378 A CN 201910969378A CN 110687377 B CN110687377 B CN 110687377B
- Authority
- CN
- China
- Prior art keywords
- quality data
- power quality
- electric energy
- monitoring
- monitoring units
- 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.)
- Active
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Remote Monitoring And Control Of Power-Distribution Networks (AREA)
- Supply And Distribution Of Alternating Current (AREA)
Abstract
The application discloses a method and a device for processing online monitoring data of a distributed energy system, after receiving power quality data sent by a plurality of monitoring units at a preset time, arbitrarily selecting one monitoring unit from the plurality of monitoring units as a reference, marking the power quality data sending time of the monitoring unit as the reference as a reference time mark of the preset time, mapping the power quality data sent by other non-reference monitoring units except the monitoring unit as the reference to the reference time mark by utilizing a Newton interpolation algorithm, and carrying out time domain transformation to synchronize the power quality data sent by all the non-reference monitoring units with the power quality data sent by the reference monitoring unit, thereby solving the problem that the power quality data sent by sensors at various measuring points of the existing distributed energy system to a terminal are asynchronous and the accuracy of power quality data analysis of the distributed energy system is influenced, the technical problem of increasing the difficulty of analyzing the power quality data is solved.
Description
Technical Field
The application relates to the technical field of distributed energy data processing, in particular to a distributed energy system online monitoring data processing method and device.
Background
The distributed energy is an energy comprehensive utilization system distributed at a user side, potential influence is generated on the power quality of a power grid after the distributed energy is connected to the power grid, the power quality data of the distributed energy is monitored on line, and the obtained on-line monitoring data is processed and analyzed, so that the distributed energy has important significance.
The existing power grid monitoring And data acquisition are executed by an SCADA (supervisory Control And data acquisition) system, the SCADA system can only acquire voltage And current waveform data And does not have the capacity of analyzing And processing abundant power quality indexes, And due to certain delay in the data acquisition And communication process, the power quality data transmitted from sensors at various measuring points of a distributed energy system to a terminal are asynchronous.
Disclosure of Invention
The application provides a method and a device for processing online monitoring data of a distributed energy system, which are used for solving the technical problems that the quality data of electric energy transmitted to a terminal by sensors at all measuring points of the existing distributed energy system are asynchronous, the accuracy of analysis of the quality data of the electric energy of the distributed energy system is influenced, and the difficulty of analysis of the quality data of the electric energy is increased.
The application provides a distributed energy system online monitoring data processing method in a first aspect, which includes:
receiving power quality data sent by a plurality of monitoring units in a distributed energy system at a preset time, wherein the power quality data is obtained by converting electrical quantity data collected by the monitoring units;
taking any one of the monitoring units as a reference, and marking the sending time of the monitoring unit as a reference time mark of the preset time;
and mapping the electric energy quality data sent by all the non-reference monitoring units to the reference time marks based on a Newton interpolation algorithm, so that the electric energy quality data sent by all the non-reference monitoring units is synchronous with the electric energy quality data sent by the reference monitoring unit.
Optionally, the mapping the power quality data sent by all the non-reference monitoring units to the reference time stamp based on the newton interpolation algorithm, so that the power quality data sent by all the non-reference monitoring units is synchronized with the power quality data sent by the reference monitoring unit, includes:
acquiring point coordinates of the monitoring units in a time domain, wherein the point coordinates comprise time for sending the power quality data and the power quality data;
carrying out difference quotient operation on the time marks of the monitoring units based on the point coordinates to obtain 1-n order difference quotient points;
based on the reference time mark and the 1-n step difference quotient points, respectively mapping the electric energy quality data sent by each non-reference monitoring unit to the reference time mark according to a preset time domain transformation formula, so that the electric energy quality data sent by all the non-reference monitoring units are synchronous with the electric energy quality data sent by the reference monitoring unit.
Optionally, the obtaining of the point coordinates of the plurality of monitoring units in the time domain, where the point coordinates include the time for sending the power quality data and the power quality data, further includes:
constructing a cloud database formed by point coordinates of the monitoring units in the time domain based on the power quality data;
correspondingly, the acquiring of the point coordinates of the plurality of monitoring units in the time domain specifically includes:
and acquiring the point coordinates of the monitoring units in the time domain from the cloud database.
Optionally, the method further includes:
and solving high-quality power quality data in the synchronized power quality data based on a preset algorithm.
Optionally, the solving of the high-quality power quality data in the synchronized power quality data based on the preset algorithm includes:
acquiring theoretical power quality data, an A/D measurement theoretical error and an A/D measurement actual error of each monitoring unit;
establishing a weighted minimum error function representing high-quality electric energy quality data based on the theoretical electric energy quality data, the A/D measurement theoretical error, the A/D measurement actual error and the synchronized electric energy quality data;
and solving the high-quality power quality data based on the weighted minimum error function.
Optionally, the weighted minimum error function is:
wherein, thetaiFor high-quality power quality data, sigma is the actual error of A/D measurement, sigma' is the theoretical error of A/D measurement,
for the synchronized power quality data,
theoretical error is measured for A/D.
Optionally, the solving the high-quality power quality data based on the weighted minimum error function further includes:
and constructing a power quality precision parameter model based on the high-quality power quality data, and performing state estimation on the plurality of monitoring units.
Optionally, the electric energy quality precision parameter model is as follows:
this application second aspect provides a distributed energy system on-line monitoring data processing apparatus, includes:
the receiving unit is used for receiving electric energy quality data sent by a plurality of monitoring units in the distributed energy system at a preset moment, and the electric energy quality data is obtained by converting electric quantity data collected by the monitoring units;
the reference unit is used for marking the sending time of any monitoring unit as a reference time mark of the preset time by taking any monitoring unit in the plurality of monitoring units as a reference;
and the mapping unit is used for mapping the electric energy quality data sent by all the non-reference monitoring units to the reference time marks based on a Newton interpolation algorithm, so that the electric energy quality data sent by all the non-reference monitoring units are synchronous with the electric energy quality data sent by the reference monitoring unit.
Optionally, the method further includes:
the solving unit is used for solving the high-quality power quality data in the synchronized power quality data based on a preset algorithm;
and the state estimation unit is used for constructing a power quality precision parameter model based on the high-quality power quality data and carrying out state estimation on the monitoring units.
According to the technical scheme, the method has the following advantages:
the application provides a distributed energy system online monitoring data processing method, which comprises the following steps: receiving power quality data sent by a plurality of monitoring units in a distributed energy system at a preset moment, wherein the power quality data is obtained by converting electrical quantity data collected by the monitoring units; taking any one of the monitoring units as a reference, and marking the sending time of any one monitoring unit as a reference time mark of a preset moment; and mapping the power quality data sent by all the non-reference monitoring units to the reference time marks based on a Newton interpolation algorithm, so that the power quality data sent by all the non-reference monitoring units is synchronous with the power quality data sent by the reference monitoring unit. The method for processing the on-line monitoring data of the distributed energy system comprises the steps of receiving power quality data sent by a plurality of monitoring units at a preset time, randomly selecting one monitoring unit from the plurality of monitoring units as a reference, marking the power quality data sending time of the monitoring unit as the reference as a reference time mark of the preset time, mapping the power quality data sent by other non-reference monitoring units except the monitoring unit as the reference under the reference time mark by utilizing a Newton interpolation algorithm, carrying out time domain transformation, synchronizing the power quality data sent by all the non-reference monitoring units with the power quality data sent by the reference monitoring unit, solving the problem that the power quality data sent by sensors at all measuring points of the conventional distributed energy system are asynchronous to a terminal, and influencing the accuracy of power quality data analysis of the distributed energy system, the technical problem of increasing the difficulty of analyzing the power quality data is solved.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the description of the embodiments are briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise.
Fig. 1 is a schematic flowchart of a method for processing online monitoring data of a distributed energy system according to an embodiment of the present application;
fig. 2 is another schematic flow chart of a method for processing online monitoring data of a distributed energy system according to an embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of an online monitoring data processing apparatus of a distributed energy system according to an embodiment of the present disclosure;
fig. 4 is a system data transmission frame diagram corresponding to the online monitoring data processing method for the distributed energy system in the embodiment of the present application.
Detailed Description
In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
For easy understanding, please refer to fig. 1, the present application provides an embodiment of a method for processing online monitoring data of a distributed energy system, including:
It should be noted that, after the monitoring unit collects the electrical data, the Real Time Real-Time operating system may be used to convert the electrical data into the power quality data by the preset algorithm, where the electrical data may include current data i (t) and voltage data u (t), the power quality data may include grid voltage frequency deviation, supply voltage deviation, THD, three-phase imbalance, and the like, and at the preset Time t, each monitoring unit (QMU) may perform the monitoring operation1，QMU2，…，QMUn) Sending the collected power quality data to a receiving end
The receiving end receives the power quality data
Can then be stored in a cloud database due to different monitoring units (QMU)1，QMU2，…，QMUn) The time mark of the monitoring unit has certain precision and delay, so that the time mark t of the electric energy data sent by the monitoring unit at the preset time t received by the receiving end1,t2,...,tnNot being equal, i.e. t1≠t2≠...≠tnTherefore, the receiving end receives the power quality data of each monitoring unit not synchronously.
And 102, taking any one of the monitoring units as a reference, and marking the sending time of any monitoring unit as a reference time mark of a preset time.
It should be noted that, in the embodiments of the present application, one of the monitoring units, such as QMU, is taken as a reference1The reference time at time t is marked as t1。
And 103, mapping the power quality data sent by all the non-reference monitoring units to the reference time marks based on a Newton interpolation algorithm, so that the power quality data sent by all the non-reference monitoring units is synchronous with the power quality data sent by the reference monitoring unit.
It should be noted that the non-reference monitoring unit (QMU) is used2，…，QMUn) Power quality data of
Mapping to a reference time stamp t by Newton's interpolation algorithm1In the following, the electric energy quality data is realized
To
So that the power quality data sent by all the non-reference monitoring units is synchronous with the power quality data sent by the reference monitoring unit.
The method for processing the on-line monitoring data of the distributed energy system provided by the embodiment of the application comprises the steps of receiving the electric energy quality data sent by a plurality of monitoring units at a preset time, randomly selecting one monitoring unit from the plurality of monitoring units as a reference, marking the electric energy quality data sending time of the monitoring unit as the reference as a reference time mark of the preset time, mapping the electric energy quality data sent by other non-reference monitoring units except the monitoring unit as the reference under the reference time mark by utilizing a Newton interpolation algorithm, carrying out time domain transformation, synchronizing the electric energy quality data sent by all the non-reference monitoring units with the electric energy quality data sent by the reference monitoring unit, solving the problem that the electric energy quality data sent to a terminal by a sensor at each measuring point of the existing distributed energy system are asynchronous and the electric energy quality data analysis accuracy of the electric energy quality data of the distributed energy system is influenced, the technical problem of increasing the difficulty of analyzing the power quality data is solved.
In order to intuitively embody the online monitoring data processing method for the distributed energy system provided in the embodiment of the present application, please refer to fig. 4, where fig. 4 is a system data transmission frame diagram corresponding to the method in the embodiment of the present application, where QMU1, QMU2, and QMU3 are all monitoring units, and certainly, only 3 monitoring units are shown in fig. 4, which does not represent only 3 monitoring units in the system, but also may represent more than 3 monitoring units, and those skilled in the art may increase or decrease the monitoring units as needed in practical application. The DT stands for a data transmission link, and the DMS is a data management cloud (namely a power quality data receiving end). The method comprises the steps that monitoring units are distributed on a common connection point PCC in a distributed energy system, electric energy quality data such as grid voltage frequency deviation, power supply voltage deviation, THD and three-phase unbalance degree at the PCC are obtained, the electric energy quality data are transmitted to a data management cloud end (DMS), and the data management cloud end (DMS) collects the electric energy quality data uploaded by each monitoring unit
And then, the time scale of the whole distributed energy system is unified through a data synchronization link (DS).
The data transmission link (DT) in fig. 4 adopts a C/S distributed mode, and may specifically include the following links:
multi-machine networking: establishing a special communication network or using a 4G/5G networking by utilizing a network communication protocol (TCP/IP) to construct a distributed energy system multi-machine communication network, wherein the distributed energy system multi-machine communication network comprises a data management cloud (DMS) and each monitoring unit;
data acquisition: a monitoring unit is arranged at the PCC position in the distributed energy system and the monitoring unit samples with the sampling frequency f through an A/D acquisition cardsSampling the electrical quantity u (t), i (t) at PCC;
inter-process communication: after the monitoring unit collects the electric quantity data, the PCI bus data transmission from the collection card to the terminal DMA is realized by utilizing an RT operating system, and the electric quantities u (t), i (t) are converted into electric quantities by a specified algorithmPower quality data
Network communication: according to the established communication network, the power quality data is transmitted
Transmitting from the monitoring unit communication port to a data management cloud (DMS) communication port;
data storage: receiving power quality data by data management cloud (DMS)
And then storing the data in a cloud database in a preset storage mode.
For easy understanding, please refer to fig. 2, another embodiment of a method for processing online monitoring data of a distributed energy system is provided, including:
It should be noted that step 201 in this embodiment of the present application is the same as step 101 in the previous embodiment, and is not described herein again.
It should be noted that step 202 in the present embodiment is the same as step 102 in the previous embodiment, and is not described herein again.
And 203, constructing a cloud database formed by point coordinates of the monitoring units in the time domain based on the power quality data.
And 204, acquiring point coordinates of the monitoring units in the time domain from the cloud database, wherein the point coordinates comprise time for sending the power quality data and the power quality data.
It should be noted that the present application is illustrativeIn the examples, the power quality data is
Storing the data by point coordinates in time domain
The point coordinates in the time domain can be expressed as
Where n is the number of points, related to the interpolation accuracy, ti,jRefers to the current time mark t of the ith monitoring unitiAnd forward j time stamp tjThe difference, i.e. ti,j＝ti-tj。
And 205, performing difference quotient operation on the time marks of the monitoring units based on the point coordinates to obtain 1-n order difference quotient points.
It should be noted that, the obtained point coordinates are subjected to difference quotient on the time mark to obtain a difference quotient point
The specific calculation formula is as follows:
continuously differentiating the calculation results of the first order difference quotient points to finally obtain the n order difference quotient points
The calculation formula is as follows:
therefore, the calculation result of the 1-n step quotient point can be obtained.
And step 206, respectively mapping the power quality data sent by each non-reference monitoring unit to the reference time mark based on the reference time mark and the 1-n step difference quotient point according to a preset time domain transformation formula, so that the power quality data sent by all the non-reference monitoring units are synchronous with the power quality data sent by the reference monitoring unit.
It should be noted that, in the embodiment of the present application, the power quality data is implemented according to a preset time domain transformation formula
To
The preset time domain transformation formula of the time domain transformation is as follows:
the time scale unification of the whole distributed energy system can be realized through the electric energy quality data after time domain transformation, the technical problems that the electric energy quality data analysis accuracy of the distributed energy system is influenced and the electric energy quality data analysis difficulty is increased due to the fact that the electric energy quality data are asynchronous are solved.
Because the sensor measurement information at the present stage is remote measurement, the power quality data itself may have system errors and human errors, and the accuracy of the power quality data needs to be judged according to the accuracy and the test state of the sensor, therefore, as a further improvement to the embodiment of the present application, in the embodiment of the present application, after step 206, the method may further include:
and step 207, solving high-quality power quality data in the synchronized power quality data based on a preset algorithm.
It should be noted that, in step 207, the specific process is to obtain theoretical power quality data, an a/D measurement theoretical error, and an a/D measurement actual error of each monitoring unit; establishing a weighted minimum error function representing high-quality power quality data based on theoretical power quality data, an A/D measurement theoretical error, an A/D measurement actual error and the synchronized power quality data; and solving the quality data of the high-quality electric energy based on the weighted minimum error function.
Under the condition of not considering the current monitoring unit, solving a QMU (quality metric Unit) of the monitoring unit according to a power flow equation of the distributed energy systemiTheoretical power quality data of
And A/D measurement theoretical error sigma 'due to A/D measurement accuracy'i(ii) a Monitoring unit QMUiMeasured synchronized power quality data as
And the actual error sigma of the A/D measurement due to the precision of the A/D measurementiAnd satisfies the formula:
establishing a weighted minimum error function S (theta)i) The concrete formula is as follows:
by a weighted least squares function S (θ)i) Solving to obtain high-quality electric energy quality data thetaiThe method comprises the following steps:
by establishing a weighted minimum error function S (theta)i) And solving to obtain high-quality electric energy quality data thetaiThe method can improve the precision of the power quality data and purify the power quality data on the premise of fully considering the system error, the human error and the random error generated by the sensor precision of the power quality data, thereby greatly increasing the reliability of the power quality dataAnd obtaining representative and reliable high-quality power quality data.
As a further improvement to the embodiment of the present application, in the online monitoring data processing method for a distributed energy system provided in the embodiment of the present application, after step 207, the method may further include:
and 208, constructing a power quality precision parameter model based on the high-quality power quality data, and performing state estimation on the plurality of monitoring units.
Specifically, the electric energy quality precision parameter model is as follows:
state estimation (state estimation) is a method for estimating the internal state of a dynamic system based on available metrology data. The data obtained by measuring the input and output of the system can only reflect the external characteristics of the system, and the dynamic law of the system needs to be described by internal (generally, the direct measurement cannot be carried out) state variables. State estimation is therefore of great importance for understanding and controlling a system. In the embodiment of the application, the power quality precision parameter model is constructed, the running state of the monitoring unit is effectively evaluated according to the model calculation result, the larger the model calculation result value is, the better the running state of the monitoring unit is, the higher the measurement precision is, the more accurate the measured power quality data is, and the data support can be provided for improving the power quality of the distributed energy system.
For easy understanding, please refer to fig. 3, the present application provides an embodiment of a distributed energy system online monitoring data processing apparatus, including:
the receiving unit 301 is configured to receive power quality data sent by a plurality of monitoring units in the distributed energy system at a preset time, where the power quality data is obtained by converting electrical quantity data collected by the monitoring units.
The reference unit 302 is configured to mark a sending time of any one of the plurality of monitoring units as a reference time mark of a preset time, with the reference of any one of the plurality of monitoring units.
The mapping unit 303 is configured to map the power quality data sent by all the non-reference monitoring units to the reference time stamp based on a newton interpolation algorithm, so that the power quality data sent by all the non-reference monitoring units is synchronized with the power quality data sent by the reference monitoring unit.
The method can also comprise the following steps:
and the solving unit 304 is configured to solve the high-quality power quality data in the synchronized power quality data based on a preset algorithm.
And the state estimation unit 305 is configured to construct a power quality precision parameter model based on the high-quality power quality data, and perform state estimation on the plurality of monitoring units.
Specifically, the mapping unit 303 is specifically configured to:
acquiring point coordinates of a plurality of monitoring units in a time domain, wherein the point coordinates comprise time for sending power quality data and the power quality data;
carrying out difference quotient operation on the time marks of the monitoring units based on the point coordinates to obtain 1-n order difference quotient points;
and respectively mapping the power quality data sent by each non-reference monitoring unit to the reference time mark based on the reference time mark and the 1-n step difference quotient points according to a preset time domain transformation formula, so that the power quality data sent by all the non-reference monitoring units are synchronous with the power quality data sent by the reference monitoring unit.
Specifically, the method may further include:
and the database construction unit 306 is configured to construct a cloud database composed of point coordinates of the monitoring unit in the time domain based on the power quality data.
The database construction unit 306 provides the mapping unit 303 with a query basis of the point coordinates of the plurality of monitoring units in the time domain.
Specifically, the state estimation unit 305 is specifically configured to:
acquiring theoretical power quality data, an A/D measurement theoretical error and an A/D measurement actual error of each monitoring unit;
establishing a weighted minimum error function representing high-quality power quality data based on theoretical power quality data, an A/D measurement theoretical error, an A/D measurement actual error and the synchronized power quality data, wherein the weighted minimum error function is as follows:
wherein, thetaiFor high-quality power quality data, sigma is the actual error of A/D measurement, sigma' is the theoretical error of A/D measurement,
for the synchronized power quality data,
measuring theoretical error for A/D;
and solving the high-quality power quality data based on the weighted minimum error function.
Specifically, the electric energy quality precision parameter model is as follows:
in the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions in the embodiments of the present application.
Claims (6)
1. A distributed energy system online monitoring data processing method is characterized by comprising the following steps:
receiving power quality data sent by a plurality of monitoring units in a distributed energy system at a preset time, wherein the power quality data is obtained by converting electrical quantity data collected by the monitoring units;
taking any one of the monitoring units as a reference, and marking the sending time of the monitoring unit as a reference time mark of the preset time;
mapping the electric energy quality data sent by all the non-reference monitoring units to the reference time marks based on a Newton interpolation algorithm, so that the electric energy quality data sent by all the non-reference monitoring units are synchronous with the electric energy quality data sent by the reference monitoring units, and the method comprises the steps of obtaining point coordinates of the plurality of monitoring units in a time domain, wherein the point coordinates comprise the time for sending the electric energy quality data and the electric energy quality data;
carrying out difference quotient operation on the time marks of the monitoring units based on the point coordinates to obtain 1-n order difference quotient points;
respectively mapping the electric energy quality data sent by each non-reference monitoring unit to the reference time mark based on the reference time mark and the 1-n step difference quotient point according to a preset time domain transformation formula, so that the electric energy quality data sent by all the non-reference monitoring units are synchronous with the electric energy quality data sent by the reference monitoring unit;
solving high-quality power quality data in the synchronized power quality data based on a preset algorithm;
the method for solving the high-quality power quality data in the synchronized power quality data based on the preset algorithm comprises the following steps:
acquiring theoretical power quality data, an A/D measurement theoretical error and an A/D measurement actual error of each monitoring unit;
establishing a weighted minimum error function representing high-quality electric energy quality data based on the theoretical electric energy quality data, the A/D measurement theoretical error, the A/D measurement actual error and the synchronized electric energy quality data;
solving the high-quality power quality data based on the weighted minimum error function;
the weighted minimum error function is:
wherein, thetaiFor high-quality power quality data, sigma is the actual error of A/D measurement, sigma' is the theoretical error of A/D measurement,
for the synchronized power quality data,
the data is theoretical power quality data.
2. The method for processing the online monitoring data of the distributed energy system according to claim 1, wherein the obtaining of the point coordinates of the plurality of monitoring units in the time domain includes a time for sending the power quality data and the power quality data, and further includes:
constructing a cloud database formed by point coordinates of the monitoring units in the time domain based on the power quality data;
correspondingly, the acquiring of the point coordinates of the plurality of monitoring units in the time domain specifically includes:
and acquiring the point coordinates of the monitoring units in the time domain from the cloud database.
3. The method for processing the online monitoring data of the distributed energy system according to claim 1, wherein the solving the high-quality power quality data based on the weighted minimum error function further comprises:
and constructing a power quality precision parameter model based on the high-quality power quality data, and performing state estimation on the plurality of monitoring units.
4. The method for processing the on-line monitoring data of the distributed energy system according to claim 3, wherein the electric energy quality precision parameter model is as follows:
5. the utility model provides a distributed energy system on-line monitoring data processing apparatus which characterized in that includes:
the receiving unit is used for receiving electric energy quality data sent by a plurality of monitoring units in the distributed energy system at a preset moment, and the electric energy quality data is obtained by converting electric quantity data collected by the monitoring units;
the reference unit is used for marking the sending time of any monitoring unit as a reference time mark of the preset time by taking any monitoring unit in the plurality of monitoring units as a reference;
the mapping unit is used for mapping the electric energy quality data sent by all the non-reference monitoring units to the reference time marks based on a Newton interpolation algorithm, so that the electric energy quality data sent by all the non-reference monitoring units are synchronous with the electric energy quality data sent by the reference monitoring units, and is specifically used for acquiring point coordinates of the plurality of monitoring units in a time domain, wherein the point coordinates comprise the time for sending the electric energy quality data and the electric energy quality data; carrying out difference quotient operation on the time marks of the monitoring units based on the point coordinates to obtain 1-n order difference quotient points; respectively mapping the electric energy quality data sent by each non-reference monitoring unit to the reference time mark based on the reference time mark and the 1-n step difference quotient point according to a preset time domain transformation formula, so that the electric energy quality data sent by all the non-reference monitoring units are synchronous with the electric energy quality data sent by the reference monitoring unit;
the solving unit is used for solving the high-quality power quality data in the synchronized power quality data based on a preset algorithm;
the solving unit is specifically used for acquiring theoretical power quality data, A/D measurement theoretical errors and A/D measurement actual errors of each monitoring unit;
establishing a weighted minimum error function representing high-quality electric energy quality data based on the theoretical electric energy quality data, the A/D measurement theoretical error, the A/D measurement actual error and the synchronized electric energy quality data;
solving the high-quality power quality data based on the weighted minimum error function;
the weighted minimum error function is:
wherein, thetaiFor high-quality power quality data, sigma is the actual error of A/D measurement, sigma' is the theoretical error of A/D measurement,
for the synchronized power quality data,
the data is theoretical power quality data.
6. The distributed energy system online monitoring data processing device according to claim 5, further comprising:
and the state estimation unit is used for constructing a power quality precision parameter model based on the high-quality power quality data and carrying out state estimation on the monitoring units.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910969378.5A CN110687377B (en) | 2019-10-12 | 2019-10-12 | Online monitoring data processing method and device for distributed energy system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910969378.5A CN110687377B (en) | 2019-10-12 | 2019-10-12 | Online monitoring data processing method and device for distributed energy system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN110687377A CN110687377A (en) | 2020-01-14 |
| CN110687377B true CN110687377B (en) | 2021-07-30 |
Family
ID=69112509
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910969378.5A Active CN110687377B (en) | 2019-10-12 | 2019-10-12 | Online monitoring data processing method and device for distributed energy system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110687377B (en) |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH1123629A (en) * | 1997-07-07 | 1999-01-29 | Chubu Electric Power Co Inc | Method for measuring harmonic of power system |
| KR20090126127A (en) * | 2008-06-03 | 2009-12-08 | 삼성중공업 주식회사 | Apparatus and method of voltage control |
| CN201615930U (en) * | 2009-11-16 | 2010-10-27 | 深圳市华力特电气股份有限公司 | Online electrical energy quality monitoring instrument and electrical energy quality monitoring system |
| CN102053202A (en) * | 2009-11-10 | 2011-05-11 | 北京博电新力电力***仪器有限公司 | Smart grid-oriented power quality monitoring system and method |
| CN103116096A (en) * | 2013-01-24 | 2013-05-22 | 广东电网公司电力科学研究院 | Integration unit for electric energy quality monitoring and synchronous sampling method of integration unit |
| CN103353756A (en) * | 2013-05-27 | 2013-10-16 | 武汉理工大学 | Method for monitoring underway ship in real time based on AIS and VTS information integration |
| CN103454491A (en) * | 2013-08-15 | 2013-12-18 | 江苏科技大学 | Intelligent electric meter and power quality detection method |
| CN103792419A (en) * | 2014-03-04 | 2014-05-14 | 济南大学 | Synchronous sampling method achieving hybrid access of analog quantity and digital quantity |
| CN103869162A (en) * | 2014-03-05 | 2014-06-18 | 湖南大学 | Dynamic signal phasor measurement method based on time domain quasi-synchronization |
| CN106296019A (en) * | 2016-08-17 | 2017-01-04 | 云南电网有限责任公司电力科学研究院 | Region energy quality comprehensive assessment method and system |
| CN208999510U (en) * | 2018-10-30 | 2019-06-18 | 云南电网有限责任公司信息中心 | A kind of distributed power system power quality information collecting device |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108459295B (en) * | 2018-04-25 | 2019-05-10 | 国网山西省电力公司计量中心 | CVT on-line monitoring system and method based on distributed data acquisition processing |
-
2019
- 2019-10-12 CN CN201910969378.5A patent/CN110687377B/en active Active
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH1123629A (en) * | 1997-07-07 | 1999-01-29 | Chubu Electric Power Co Inc | Method for measuring harmonic of power system |
| KR20090126127A (en) * | 2008-06-03 | 2009-12-08 | 삼성중공업 주식회사 | Apparatus and method of voltage control |
| CN102053202A (en) * | 2009-11-10 | 2011-05-11 | 北京博电新力电力***仪器有限公司 | Smart grid-oriented power quality monitoring system and method |
| CN201615930U (en) * | 2009-11-16 | 2010-10-27 | 深圳市华力特电气股份有限公司 | Online electrical energy quality monitoring instrument and electrical energy quality monitoring system |
| CN103116096A (en) * | 2013-01-24 | 2013-05-22 | 广东电网公司电力科学研究院 | Integration unit for electric energy quality monitoring and synchronous sampling method of integration unit |
| CN103353756A (en) * | 2013-05-27 | 2013-10-16 | 武汉理工大学 | Method for monitoring underway ship in real time based on AIS and VTS information integration |
| CN103454491A (en) * | 2013-08-15 | 2013-12-18 | 江苏科技大学 | Intelligent electric meter and power quality detection method |
| CN103792419A (en) * | 2014-03-04 | 2014-05-14 | 济南大学 | Synchronous sampling method achieving hybrid access of analog quantity and digital quantity |
| CN103869162A (en) * | 2014-03-05 | 2014-06-18 | 湖南大学 | Dynamic signal phasor measurement method based on time domain quasi-synchronization |
| CN106296019A (en) * | 2016-08-17 | 2017-01-04 | 云南电网有限责任公司电力科学研究院 | Region energy quality comprehensive assessment method and system |
| CN208999510U (en) * | 2018-10-30 | 2019-06-18 | 云南电网有限责任公司信息中心 | A kind of distributed power system power quality information collecting device |
Non-Patent Citations (1)
| Title |
|---|
| 适用于电能质量监测分析的合并单元插值算法研究;李博等;《第九届电能质量研讨会论文集》;20180628;正文第302、309-311页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN110687377A (en) | 2020-01-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111026927B (en) | Low-voltage transformer area running state intelligent monitoring system | |
| CN111624544B (en) | Method and related device for identifying household transformer relation of transformer area | |
| CN105137231A (en) | Power quality monitoring method and system | |
| CN107886171B (en) | PMU data-based breaker state online diagnosis method and system | |
| CN104217127B (en) | A kind of PMU dynamic datas simulation-generation method | |
| CN109472231B (en) | Transformer substation harmonic source positioning method and device and computer readable storage medium | |
| JPWO2008126240A1 (en) | Synchronous phasor measuring device and phase angle difference measuring device between buses using the same | |
| CN106302019A (en) | A kind of substation data communication network shutdown processes the test system and method for time | |
| CN107741577A (en) | A kind of Source of Gateway Meter degree of accuracy on-line monitoring and analysis method and system | |
| CN110187193B (en) | Dielectric loss monitoring system and method based on total-station voltage transformer stability judgment | |
| CN115878958B (en) | Transformer oil temperature prediction method, device, equipment and storage medium | |
| CN115618654B (en) | Identification method and device for out-of-tolerance electric energy meter | |
| CN111679150A (en) | Online analysis system and method for transmission line loss | |
| CN115685046A (en) | Mutual inductor metering abnormity identification method, device, equipment and storage medium | |
| CN115113125A (en) | Correction system of multichannel arbitrary waveform generator | |
| EP3048566A1 (en) | Information processing device and information processing method | |
| CN110417834B (en) | Multi-substation data section transmission method and system with time scale measurement | |
| CN110687377B (en) | Online monitoring data processing method and device for distributed energy system | |
| CN116595395B (en) | Inverter output current prediction method and system based on deep learning | |
| CN113449928A (en) | Wind field power prediction method, system, server and computer readable storage medium | |
| CN104076317A (en) | Power harmonic-caused electronic-type electric energy meter metering error analyzing and correcting system | |
| CN103217581B (en) | The method and system of line parameter circuit value identification is realized based on stable state telemetry | |
| CN107703342A (en) | A kind of high-precision transient analyser and its transient arithmetic | |
| CN203981771U (en) | A kind of instrument | |
| CN110780114A (en) | Transformer area theoretical line loss analysis method and readable storage medium |
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 | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |