CN116611816A - Power distribution network line loss statistical method - Google Patents
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Abstract
The application provides a distribution network line loss statistical method, and belongs to the technical field of distribution network line loss management. Comprising the following steps: acquiring basic data and historical data of a power distribution network; identifying abnormal line loss caused by insufficient surface bottom acquisition precision in the main network, and counting abnormal causes of the line loss of the main network; utilizing historical power failure data to check the medium-voltage distribution network line change relation; identifying and repairing the missing surface and bottom data of the power distribution network; and counting the line loss condition and the abnormal condition, and outputting a counting result. The application can automatically summarize the line loss condition, and the user can download and visualize the effective information, thereby reducing the workload of line loss management personnel; the application counts the line loss condition and the abnormal condition, outputs the statistical result in the modes of a data table, a visual chart and the like, can more intuitively display the condition and the abnormal condition of the line loss rate, is beneficial to the analysis, evaluation and decision of the line loss condition by power management staff, and adopts corresponding measures to optimize and improve the line loss.
Description
Technical Field
The application belongs to the technical field of power distribution network line loss management, and particularly relates to a power distribution network line loss statistical method.
Background
In the process of electric energy transmission, on one hand, various elements have certain resistance and reactance, and electromagnetic and electrothermal energy conversion can occur when electric quantity flows through the elements, so that some unavoidable losses are caused; on the other hand, various users at the distribution end use the electric power, and meanwhile, certain electric energy loss and loss are inevitably caused by the condition of the equipment, the economical efficiency of the operation mode or some electricity stealing and leakage behaviors. The line loss is the combination of various losses during the transmission and use of electric energy.
The intelligent and lean management of line loss is an important work of national network companies, is also a core factor influencing loss reduction, and in recent years, the line loss data acquisition technology is mature, and although the current service system can calculate the line loss according to the power supply quantity and the sales quantity, the analysis function, the intelligent judgment function and the like of the service system need to be further perfected.
Disclosure of Invention
The application aims to solve the technical problem of providing a power distribution network line loss statistical method aiming at the defects in the prior art.
In order to solve the technical problems, the application adopts the following technical scheme:
a power distribution network line loss statistical method, comprising:
acquiring basic data and historical data of a power distribution network;
identifying abnormal line loss caused by insufficient surface bottom acquisition precision in the main network, and counting abnormal causes of the line loss of the main network;
utilizing historical power failure data to check the medium-voltage distribution network line change relation;
identifying and repairing the missing surface and bottom data of the power distribution network;
and counting the line loss condition and the abnormal condition, and outputting a counting result.
Further, the method for identifying the abnormal line loss caused by insufficient surface bottom acquisition precision in the main network comprises the following steps:
acquiring a correction interval of the line loss rate according to the theoretical line loss rate;
if the theoretical line loss rate exceeds the line loss rate upper and lower limit intervals and the correction interval is overlapped with the line loss rate upper and lower limit intervals, judging that the cause of the line loss abnormality is due to insufficient surface bottom acquisition precision;
the correction interval isWherein Sigma delta represents the sum of multiplying power of all elements in the same circuit, a represents the input electric quantity of the circuit, and x% represents the theoretical line loss rate of the current circuit;
the upper limit interval and the lower limit interval of the line loss rate are preset intervals for judging whether the line loss is abnormal or not.
Further, the method for verifying the medium voltage distribution network cable change relation by using the historical power outage data comprises the following steps:
acquiring historical power outage data of a medium-voltage distribution network, and screening a power outage generating station area or line and a corresponding power outage time period;
acquiring a station area file corresponding to a station stopping area or a line from a line loss system;
and acquiring current and voltage data of a metering point corresponding to the radio stopping area in a power failure time period, judging that the line change relation is normal if the current and voltage data have null values, and judging that the line change relation is abnormal if the current and voltage data have null values.
Further, the repair method for the missing table bottom data comprises the following steps: and acquiring the meter base data from the electricity acquisition system again according to the number of the metering point, and if the meter base data cannot be acquired, supplementing the meter base data by using the average value of the electricity consumption of the metering point in the recent days.
Further, the basic data comprise inherent attribute data, archive data and operation data of the power distribution network.
Further, the history data includes power outage data in recent years and load conduction data of 96 points daily in recent years.
Further, the statistical result is output in a data table and a visual mode.
The line loss rate is taken as an important index of a power supply enterprise, the basic management level can be reflected, the operation cost of the enterprise is directly influenced, the loss of electric energy in a line can be effectively reduced by reducing the line loss rate, and the economic benefit of the enterprise is improved. The comprehensive line loss rate can be directly used for measuring the operation management level of a power grid management enterprise, and can also be used as a main basis for guiding the upgrading and transformation of the power grid.
With the development of intelligent distribution networks, the national network companies perfect a plurality of systems such as electricity collection information, PMS, marketing business and the like through power supply units of all levels, and an integrated electric quantity and line loss system based on the system data is also gradually built. The integrated electric quantity and line loss system synchronously collects the power supply quantity and the synchronous sales electric quantity, realizes synchronous management of the electric quantity and the line loss, and has relatively stable synchronous line loss rate, and tends to be consistent with the structural characteristics and the load change condition of the power grid. Through carrying out accurate management and control to the line loss in the distribution network, the problem that influences the line loss can be timely found and timely solution. With the application of the integrated electric quantity and line loss system, the line loss management of a power supply unit is gradually enhanced, and the line loss rate is gradually reduced.
At present, the line loss level of a main network with the voltage level of 35kV and above is generally lower, and the international advanced level is reached; the medium-low voltage distribution network with the voltage of 10kV or below still has higher line loss level due to the complex grid structure, large load fluctuation and the like, which not only causes certain economic loss for power enterprises, but also influences the power supply quality to a certain extent.
Although the line loss level of the main network with the voltage level of 35kV and above is low, the line loss abnormality is caused by the reasons of load change, line charging, equipment failure and the like in the operation of the power grid, and the existing line loss system judges partial abnormality reasons after calculating the line loss abnormality. However, the equipment fault may include line loss abnormality caused by insufficient accuracy of the surface bottom, the existing line loss system cannot accurately identify the line loss, the abnormality type is misjudged as other types, and interference is caused to statistics and subsequent treatment of the line loss by a power supply unit.
In addition, the line loss level of the 10kV power distribution network is higher and mainly comprises technical factors such as overlarge power supply radius of the power distribution network, unreasonable power distribution network architecture, low equipment efficiency and the like, and non-technical management factors such as metering acquisition abnormality, abnormal power consumption behavior, line loss statistical errors and the like existing on a user side.
Aiming at the problems, the application focuses on analyzing the factors such as the line loss abnormality caused by the insufficient surface bottom precision in the main network line loss, the surface bottom deficiency in the non-technical line loss, the line change relation abnormality and the like.
Part of information of the distribution network structure is manually checked and registered, and the process is time-consuming and labor-consuming, and is easy to negligence and error, so that abnormal registration of the linear transformation relationship in the service system is easy to cause. The line transformer relation is a relation between distribution transformer of a distribution network area and a 10kV line to which the distribution transformer belongs, and belongs to one of distribution network topological structures. The carding of the line change relation is an important link for ensuring the stable operation of the distribution network, and the correctness of the line change relation has very important significance for the calculation of the network loss of the distribution network, the rush repair of the fault of the distribution network and the like, and the accuracy of the line loss calculation is affected by the wrong line change relation. Therefore, the verification of the line change relation of the medium-voltage distribution network is necessary.
In the prior art, the line change verification is performed by using the power grid operation data. If the distribution transformer outlet voltage is utilized for calculation, the correlation coefficient between the distribution transformer voltage curves is calculated based on the distribution transformer outlet voltage, and the correctness of the linear transformation relation is verified through the magnitude of the correlation coefficient. Because the electricity utilization habits of a large number of low-voltage transformer area users in the line are similar, the correlation coefficient of the 10kV distribution transformer outlet voltage is easy to be very close, and the misjudgment is easy to be caused by a method for checking the line transformation relation by using the correlation coefficient of the outlet voltage. The basic idea is to use the change characteristics of the bias correlation coefficient to judge the attribution relation of all the areas in the line, collect and analyze the big data of the power distribution network operation based on the computer, and use the condition that the total electric energy input by the line in the line change relation and the electric energy consumed by all the areas of the line accord with the electric energy conservation relation to judge the correctness of the line change relation.
But the linear transformation relation verification based on the power grid operation data needs to collect a large amount of power grid data, and has complex algorithm and high realization cost. In order to overcome the above drawbacks, the present inventors have proposed a method for performing a linear relation check using historical power outage data. The method is based on the basic principle that three-phase information does not have numerical values in a fault power failure time range, and the linear transformation relation is judged by judging whether corresponding acquisition points in a power failure time period of a transformer area have readings or not.
Compared with the prior art, the application has the following beneficial effects:
the application can automatically collect line loss conditions, users can download and visualize effective information, the line loss statistical workload of 2 hours per day is compressed to be within 1 minute, the workload of line loss data processing is reduced by more than 90 percent, and the workload of line loss management personnel is reduced. The application counts the line loss condition and the abnormal condition, outputs the statistical result in the modes of a data table, a visual chart and the like, can more intuitively display the condition and the abnormal condition of the line loss rate, is beneficial to the analysis, evaluation and decision of the line loss condition by power management staff, and adopts corresponding measures to optimize and improve the line loss.
The application can count the line loss abnormality cause of the main network line, identify the line loss rate abnormality caused by insufficient acquisition precision of the upper and lower table bottoms, and accurately judge the abnormality of the line loss rate. According to the application, a correction interval of the line loss rate is obtained by combining the sum of all element multiplying powers in the same line according to the theoretical line loss rate, and if the theoretical line loss rate exceeds the upper limit interval and the lower limit interval of the line loss rate and the correction interval is overlapped with the upper limit interval and the lower limit interval of the line loss rate, the cause of the line loss abnormality is judged to be due to insufficient surface bottom acquisition precision. The problem of misjudgment of the line loss rate is corrected, and the accuracy and the judgment result of the line loss are improved.
The method and the device for verifying the linear transformation relationship in the medium-voltage distribution network can ensure the accuracy and the matching performance of the linear transformation relationship. According to the method, historical power failure data of the medium-voltage distribution network are obtained, and a power failure generating station area or line and a corresponding power failure time period are screened; acquiring a station area file corresponding to a station stopping area or a line from a line loss system; and acquiring current and voltage data of a metering point corresponding to the radio stopping area in a power failure time period, judging that the line change relation is normal if the current and voltage data have null values, and judging that the line change relation is abnormal if the current and voltage data have null values. By checking the linear transformation relation, the influence of the abnormal linear transformation relation on the linear loss rate calculation can be eliminated, and the accuracy of the linear loss rate calculation and the reliability of the evaluation result are improved.
According to the application, by checking whether each metering point in the line loss system has the phenomenon of missing table bottom data or not and automatically repairing the missing table bottom data, the workload of manual checking and repairing can be reduced, and the integrity and accuracy of the table bottom data are improved. The repaired surface data are used when the line loss rate is recalculated, so that the accuracy of calculating the line loss rate can be improved.
Drawings
The present application will be described in further detail with reference to the accompanying drawings.
Fig. 1: a flow chart of the present application;
fig. 2: in the step S2, a misjudgment line loss correction schematic diagram is provided;
fig. 3: in the step S3, a plot line variation normal statistical chart is obtained;
fig. 4: and (4) performing a bottom-of-table deletion repair statistical graph in the step S4.
Detailed Description
For a better understanding of the present application, the content of the present application will be further clarified below with reference to the examples and the accompanying drawings, but the scope of the present application is not limited to the following examples only. In the following description, numerous specific details are set forth in order to provide a more thorough understanding of the present application. It will be apparent, however, to one skilled in the art that the application may be practiced without one or more of these details.
Referring to fig. 1-4, an objective of the present embodiment is to provide a method for counting line losses of a power distribution network. As shown in fig. 1, the statistical method includes:
and S1, acquiring basic data and historical data of the power distribution network.
The step of obtaining basic data for line loss statistics mainly comprises the following steps:
intrinsic attribute data: element data in the line, etc.;
archive data: user basic information, line basic information, station area basic information and metering point information;
operation data: indication value of total electric energy of a metering point, voltage value of the metering point, current value of the metering point, electric quantity, line loss value, line loss rate, operation information of a transformer and the like. The operation data is day data of recent days.
The basic data are automatically obtained from a line loss system (such as an integrated electric quantity and line loss system or other synchronous line loss systems), an electricity acquisition system, a PMS system (equipment operation lean management system), a TMR system (electric energy metering system), a D5000 scheduling command system and other power grid systems.
Meanwhile, historical data such as power outage data (power outage equipment, a power outage area, a power outage line, power outage time and the like) in recent years, load conduction data (acquisition point numbers, currents, voltages and the like) at 96 time points every day in recent years, daily electricity consumption of each metering point in recent days and the like are obtained. The historical data can be automatically obtained from power grid systems such as an electricity acquisition system.
And S2, counting the line loss abnormality cause of the main network line.
When the current line loss system acquires the line loss rate of a main power grid such as 35kV, whether the line loss rate is abnormal or not is determined according to whether the line loss rate is within a preset upper limit interval and a preset lower limit interval, but part of abnormal line loss rate is caused by insufficient upper and lower surface bottom precision, the existing line loss system cannot identify the reason for the abnormal line loss rate, the misjudgment of the line loss rate of the main power grid occurs, and the summarization and judgment results of the line loss are affected.
The meter bottom data refer to the electric energy usage recorded on a metering point (ammeter), and the lower meter bottom is initial meter bottom data, namely the reading at the beginning of a metering period; the upper table bottom is the end table bottom data, i.e. the reading at the end of the metering cycle. The difference between the upper and lower meter bottoms is the electric energy consumption in the metering period, and the line loss rate can be calculated according to the electric energy consumption. When the upper and lower table bottom accuracy is insufficient (as the table bottom data is missing), the calculated line loss rate will be abnormal.
Referring to the schematic diagram of fig. 2, in fig. 2, the line loss ratio is calculated from the line loss coefficient at the left end 2022, 8 months and 24 days, and the line loss ratio is 1.12, and exceeds the line loss ratio. The line loss rate abnormality is caused by insufficient accuracy of the table bottom on the day, but the line loss system does not recognize the exact cause of the abnormality.
Therefore, the step identifies the cause of the abnormal line loss rate in the current line loss system and judges whether the situation of insufficient upper and lower table bottom acquisition precision exists or not; if so, the misjudgment problem of the line loss rate is corrected.
Specifically, the method comprises the following steps:
s21, acquiring a correction interval of the line loss rate according to the theoretical line loss rate.
Correction intervalWhere Σδ represents the sum of the multiplying powers of all the elements in the same line, a represents the line input power, x% represents the theoretical line loss rate of the current line (i.e., the line loss rate calculated from the power supply amount and the power selling amount), and Y represents the corrected line loss rate discrimination section. The multiplying power of an element refers to the ratio between the rated capacity and the actual running capacity of each electrical element (such as a transformer, a power transmission line and the like), and reflects the actual load degree of the element.
Referring to fig. 2, the theoretical line loss rate of 2022, 8 months and 24 days is 1.12, and the correction interval calculated by combining the line basic data is 1.12±0.88, i.e. the lower limit of the correction interval is 0.24, and the upper limit is 2.
S22, judging whether the line loss abnormal cause is insufficient in surface bottom acquisition precision according to the correction interval.
If the theoretical line loss rate exceeds the line loss rate upper and lower limit intervals and the correction interval coincides with the line loss rate upper and lower limit intervals, judging that the cause of the line loss abnormality is due to insufficient surface bottom acquisition precision.
When the situation of insufficient transmission precision of the surface bottom is identified, the subsequent step S4 can correct the problem of partial surface bottom data missing.
Meanwhile, step S2 also displays the correction process related data in a visual chart manner.
And S3, checking the transformation relation of the medium-voltage distribution network cable.
The line change relation is the association relation between the line and the transformer in the distribution network. The calculation of the line loss rate involves parameters of the line and the transformer, such as resistance, reactance, capacity and the like, and if the line transformation relation is abnormal, the parameter mismatch or wrong parameter input is caused, so that the accuracy of the calculation of the line loss rate is affected.
At present, most 10kV lines in urban areas have complex structures, the line transformer verification difficulty is high, and the calculation and evaluation errors of medium-voltage line loss rate are large. Therefore, the linear transformation relation in the medium-voltage distribution network is verified in the step.
When a certain area has power failure, the data such as voltage, current and the like recorded by the metering point in the area should be null, and the step is to check the linear transformation relation according to the data. Specifically, the method comprises the following steps:
s31, acquiring power failure data of the medium-voltage distribution network.
And (3) screening the power outage occurrence areas or lines and the corresponding power outage time periods according to the power outage historical data obtained in the step (S1).
S32, acquiring file data of the radio stopping area from the line loss system.
If the power failure occurs, acquiring file data of a station area under the line in the line loss system according to the information such as the serial number of the power failure line from the existing line loss system of the power grid. If the power failure occurs, the file data of the corresponding station area is obtained from the existing line loss system of the power grid according to the information such as the serial number of the power failure station area.
S33, checking the linear transformation relation according to the current and voltage data of the metering point corresponding to the station stopping area in the power failure time period.
And acquiring metering points corresponding to the radio stopping area according to the area file data. And (3) extracting current and voltage data of the metering point corresponding to the station stopping area in the power failure time from the load guiding historical data obtained in the step (S1), judging that the line change relation is normal if null value exists in the current and voltage data in the power failure time period, and otherwise, judging that the line change relation is abnormal.
Meanwhile, step S3 also displays the abnormal area of the linear relation in a visual chart mode. As shown in fig. 3, in this step S3, a site area having an abnormal line change relation can be screened, and the accuracy of line loss rate calculation can be improved by correcting the line change relation.
And S4, identifying and repairing the loss of the bottom of the distribution network.
The metering point in the power grid often causes a problem of bottom missing due to equipment faults, unstable equipment installation, data transmission errors and the like. The loss of the surface bottom can affect the accuracy of the calculated line loss rate in the existing line loss system due to the lack of accurate user power consumption data.
At present, the surface bottom loss rate of a part of medium-voltage distribution network is more than 5%, and the traditional method needs to manually check whether the surface bottom is lost or not, thereby wasting time and labor. Therefore, the step adopts measures to automatically judge whether the data of the table bottom is missing or not, and automatically complement the missing data of the table bottom. Specifically, the method comprises the following steps:
s41, checking whether each metering point in the line loss system has a phenomenon of missing data of the table base.
Firstly, acquiring electric quantity data, upper and lower table bottom data, multiplying power data and archive data of each metering point in a line loss system. And traversing the acquired upper and lower table base data, and judging whether the table base missing phenomenon exists.
S42, repairing the surface data.
And if the table bottom data is missing, re-acquiring the table bottom data from the electricity acquisition system according to the number of the metering point.
If the upper and lower table base data acquired in the electricity acquisition system are still missing or the data acquisition fails, the average value of the electricity consumption of the metering point in the recent days acquired in the step S1 is used for complement, and meanwhile, a label is added to the data to remind a worker of paying attention.
S43, recalculating the line loss rate by using the repaired surface-bottom data.
When the surface data is completed, the missing electric quantity can be directly calculated according to the completed data, then the missing electric quantity is added with the total electric quantity of each corresponding line in the line loss system on the same day, and the line loss rate is calculated again on the basis.
Meanwhile, step S4 also displays the data related to the identification and repair of the sole missing in a visual chart manner. FIG. 4 is a schematic diagram of the result of identifying and repairing the table base data.
S5, counting line loss conditions and abnormal conditions (including line loss abnormality, line change relation abnormality and the like), generating a data table, and outputting a statistical result in a visual mode.
According to the application, the historical line loss data of the power distribution network can be counted and analyzed.
Finally, it is noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present application, and that other modifications and equivalents thereof by those skilled in the art should be included in the scope of the claims of the present application without departing from the spirit and scope of the technical solution of the present application.
Claims (7)
1. A power distribution network line loss statistical method is characterized in that: comprising the following steps:
acquiring basic data and historical data of a power distribution network;
identifying abnormal line loss caused by insufficient surface bottom acquisition precision in the main network, and counting abnormal causes of the line loss of the main network;
utilizing historical power failure data to check the medium-voltage distribution network line change relation;
identifying and repairing the missing surface and bottom data of the power distribution network;
and counting the line loss condition and the abnormal condition, and outputting a counting result.
2. The power distribution network line loss statistical method according to claim 1, wherein: the method for identifying the abnormal line loss caused by insufficient surface bottom acquisition precision in the main network comprises the following steps:
acquiring a correction interval of the line loss rate according to the theoretical line loss rate;
if the theoretical line loss rate exceeds the line loss rate upper and lower limit intervals and the correction interval is overlapped with the line loss rate upper and lower limit intervals, judging that the cause of the line loss abnormality is due to insufficient surface bottom acquisition precision;
the correction interval isWherein Sigma delta represents the sum of multiplying power of all elements in the same circuit, a represents the input electric quantity of the circuit, and x% represents the theoretical line loss rate of the current circuit;
the upper limit interval and the lower limit interval of the line loss rate are preset intervals for judging whether the line loss is abnormal or not.
3. The power distribution network line loss statistical method according to claim 1, wherein: the method for verifying the medium-voltage distribution network line change relation by using the historical power failure data comprises the following steps:
acquiring historical power outage data of a medium-voltage distribution network, and screening a power outage generating station area or line and a corresponding power outage time period;
acquiring a station area file corresponding to a station stopping area or a line from a line loss system;
and acquiring current and voltage data of a metering point corresponding to the radio stopping area in a power failure time period, judging that the line change relation is normal if the current and voltage data have null values, and judging that the line change relation is abnormal if the current and voltage data have null values.
4. The power distribution network line loss statistical method according to claim 1, wherein: the repair method for the missing table bottom data comprises the following steps: and acquiring the meter base data from the electricity acquisition system again according to the number of the metering point, and if the meter base data cannot be acquired, supplementing the meter base data by using the average value of the electricity consumption of the metering point in the recent days.
5. The power distribution network line loss statistical method according to claim 1, wherein: the basic data comprise inherent attribute data, archive data and operation data of the power distribution network.
6. The power distribution network line loss statistical method according to claim 1, wherein: the history data includes power outage data in recent years and load conduction data of 96 points daily in recent years.
7. The power distribution network line loss statistical method according to claim 1, wherein: the statistical result is output in a data table and a visual mode.
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