CN104269844B - A kind of state of electric distribution network estimation abnormality recognition method and its device - Google Patents

Abstract

A distribution network state estimation abnormality identification method and a device thereof relate to the field of distribution automation. At present, the efficiency of manual search for problems is low, the cycle is long, and there are shortcomings such as incomplete identification of problems, which cannot effectively improve the pass rate of distribution network measurement. The invention includes the following steps: automatically read the power grid model and section from the SCADA system at regular intervals, generate real-time network topology, process the data by using the distribution network state estimation algorithm, identify unqualified measurements, and identify unqualified measurements according to preset rules. For the equipment that causes abnormal measurement, determine the owner of the equipment, send a text message to the equipment owner, and notify the operating personnel in time to deal with it. The technical solution reduces manual proofreading and inspection links, reduces costs and improves efficiency.

Description

A method and device for identifying anomalies in distribution network state estimation

technical field

The invention relates to the field of distribution automation, in particular to a method and device for identifying an abnormal method of distribution network state estimation.

Background technique

At present, during the operation of the distribution automation system, due to the influence of various links such as acquisition devices, sub-stations, and channels, there are deviations and errors between the collected measurements and the actual measurements. For example, data distortion caused by channel interference, transformers or Damaged measuring equipment leads to dead data, and untimely system maintenance leads to reverse problems in the measurement direction. Currently, these problems can only be solved by manually timing to the substation site for comparison. The on-site comparison method can be searched and identified Some measurement data problems, such as dead data, cannot be detected on site for problems such as wrong measurement directions, and the efficiency of manual search for problems is low, the cycle is long, and there are shortcomings such as incomplete identification of problems, which cannot effectively improve the configuration. Grid measurement pass rate.

Contents of the invention

In view of this, the present invention provides a distribution network state estimation abnormality identification method and its device, so as to realize the purpose of quickly finding problems. To achieve the above object, the present invention takes the following technical solutions:

A distribution network state estimation abnormal identification method, characterized in that it includes the following steps:

1) Automatically read the grid model and section from the SCADA system at regular intervals;

2) Generate real-time network topology;

3) Use the distribution network state estimation algorithm to process the data;

4) Identify the unqualified measurement, and identify the equipment that causes abnormal measurement according to the preset rules;

5) Determine the device owner and send a text message to the device owner.

Using a common file method, automatically read the grid model and section from the network device or automation system, reconstruct the grid model, determine the real-time network topology, process the data with the state estimation algorithm, identify unqualified measurements, According to the set rules, determine the equipment that causes measurement abnormalities, send notifications to relevant personnel, and guide inspections to troubleshoot defects.

As a further improvement and supplement to the above technical solutions, the present invention also includes the following additional technical features.

Preferably, when the grid model and section are automatically read regularly from the SCADA system, the FTP technology is used to regularly read the grid model and section.

When automatically reading the grid model and section from the SCADA system regularly, the grid model and section used are based on the CIM/E format.

When the distribution network state estimation algorithm is used to process the data, according to the distribution transformer capacity as the relative proportion of the loads in the unobservable area, the total measured load in the unobservable area is distributed to each distribution transformer. Distribution network power flow calculation, based on which the network loss in each unobservable area is estimated, and then the total load in the unobservable area is corrected to obtain an estimated value.

Unqualified measurement includes one or more of transformer active power unbalance, bus active power unbalance, line active power unbalance, line active power death data, line active power jump data, and transformer active power death data.

A distribution network state estimation abnormal identification device, characterized in that it includes:

The power grid model and section reading unit uses the RJ-45 network port to directly read the power grid model and section files to determine the real-time network topology and power flow status;

The state estimation and abnormal identification unit is used for state estimation and calculation; the grid model and section reading unit is connected to the state estimation and abnormal identification unit through the EMAC interface;

A defect notification unit, including a communication chip, which is equipped with a GSM sending function;

Power supply, used to provide 3.3V DC.

Beneficial effects: This technical solution establishes a complete chain of reading, calculation, identification, and notification from the power grid model and measurement data, and realizes automatic discovery and information transmission of measurement problems, and has the following advantages:

First of all, it effectively solves the problem that relevant personnel cannot find inaccurate measurement data in a timely and comprehensive manner, reduces manual proofreading and inspection links, reduces costs, and improves efficiency.

Secondly, a distribution network state estimation method that distributes loads in proportion is provided, which solves the problem of insufficient practicability of state estimation in the case of incomplete distribution network measurement data, makes the measurement problems of estimated state discovery more comprehensive, and promotes The qualified rate of measurement has been effectively improved.

Description of drawings

Fig. 1 is a schematic diagram of the present invention;

Fig. 2 is a schematic structural diagram provided by an embodiment of the present invention.

In Figure 1: 1. Read model and section; 2. Reconstruct network model; 3. Perform state estimation; 4. Identify abnormal equipment; 5. Abnormal notification.

In Fig. 2: 1. Model and section reading unit; 2. State estimation unit; 3. Defect notification unit; 4. Power supply.

Detailed ways

In order to enable those skilled in the art to understand and implement the present invention, the embodiments of the present invention are now described with reference to the accompanying drawings. Obviously, the described embodiments are only some of the embodiments of the present application, not all of them. Based on the embodiments of the present application, all other embodiments obtained by persons of ordinary skill in the art without creative work , should all belong to the protection scope of this application.

The invention discloses a method for identifying anomalies in distribution network state estimation, the steps of which are shown in Figure 1:

1. Read the grid model and section.

Regularly read the power grid model and section through the common file method;

The grid model and section files can be in CIM/E format. Grid CIM/E is a file format expressing grid model and measurement data. Its modeling aspect inherits CIM/XML, which defines grid equipment Model class objects, each class object contains its own application attributes and their topological relationships.

CIM is a set of public information models defined by the International Electrotechnical Commission (IEC, International Electrotechnical Commission), which includes all the main objects of the power enterprise, and represents power system resources by providing an object class and attribute and the relationship between them. standard method.

More specifically, FTP technology can be used to read grid models and sections in CIM/E format on network resources, and FTP paths and accounts can be initialized and set through the interface.

It should be noted that it is necessary to analyze the network topology based on the CIM-based power grid model and convert it into a node-branch model to determine the state of the power flow.

The network topology analysis described above mainly converts the equipment connection relationship model based on the connection point-switch-branch into a network calculation model based on the topology point-branch according to the opening/closing state of the switch/knife switch

The real-time power flow state is mainly based on the network topology and switch measurement in the CIM/E format to reproduce the power grid working conditions.

The timing can be read in a manner of 10-15 minutes.

The network resources include SCADA data file servers.

2. State estimation.

The data is processed using an improved proportional distribution state estimation algorithm. Compared with the transmission network, the distribution network is generally in the form of a radial or weak ring network, with many branches, large branch impedance ratio, and incomplete measurement. Therefore, it is not appropriate to directly use the state estimation method of the transmission network. In view of the current situation of weak distribution network measurement configuration, the state estimation algorithm of proportional allocation of capacity is adopted, and the distribution transformer capacity is used as the relative proportion of loads in the unobservable area to distribute the total measurement load in the unobservable area to each Distribution transformers, on this basis, carry out a power flow calculation of the distribution network, and estimate the network loss of each unobservable area based on this, and then correct the total load in the unobservable area to obtain an estimated value.

The state estimation is based on the statistical characteristics of the measurement error, and the estimated value is calculated by the method of mathematical statistics. Its function is to improve the data accuracy and maintain the consistency of the data, and provide credible real-time power flow data for network analysis.

3. Bad measurement identification.

Use the state estimation results to automatically find bad measurements. The bad measurements mainly refer to the fact that the measured values do not match the real values or the deviation is too large to be used, mainly including:

Deviation measurement, use active and reactive power measurement values to check current measurement, and find possible bad measurements of active power, reactive power, voltage, and gear position.

Measurement direction, based on the measurement area balance check, to find possible wrong direction of flow

Switch identification: Use switch branch active power flow calculation and expert database to find possible wrong switch remote signals.

After the bad measurement is identified, the bad measurement is output in CIM/E mode.

4. Identification of dead data and transition data.

Use the results of state estimation to automatically discover dead data and jump data. The dead data is data that no longer changes due to various reasons such as acquisition devices or channels; jump data refers to data that suddenly occurs larger changes, and these data are actually unlikely to undergo major changes.

The dead data is mainly the data that no longer changes, which can only be found through the cumulative comparison of multiple consecutive sections.

The jump data is mainly the mutation data found after comparing multiple consecutive sections.

After the column data and jump data are identified, they are output in CIM/E mode.

5. Abnormal equipment identification.

According to the measurement position, type, quantity, etc., identify the relationship with primary equipment, channels, and sensors, and identify equipment that may cause abnormalities. For example, when it is found that a substation switch has a bad measurement, but the measurements of the switch accessories are normal, it can be explained that the bad measurement may be caused by the acquisition sensor of the switch

6. Defect notification.

When the abnormal equipment is identified, it will automatically send a text message to the automation personnel to guide the operation personnel to inspect

The above description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention will not be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

As shown in Figure 2, a device corresponding to a distribution network state estimation abnormality identification method includes:

1. Grid model and section reading unit.

Use the RJ-45 network port to directly read the grid model and section files to determine the real-time network topology and power flow status.

2. State estimation and abnormal identification unit.

The ARM926 processor chip is used for state estimation calculation; the ARM microprocessor is a 32-bit microprocessor with high performance and low power consumption.

The grid model and section reading unit is connected with the state estimation and abnormal identification unit through the EMAC interface.

3. Defect notification unit.

The OMAP730 GSM/GPRS communication chip of Ti Company is used. This chip has high-speed WLAN, GPIO port, embedded ARM926TEJ processor, the highest frequency is 200MHZ; it has 16kB instruction cache, 8Kb data cache, and GSM sending function.

4. Power supply.

Provides 3.3V DC to other power supplies.

The above description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention will not be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims (6)

1. A distribution network state estimation abnormal identification method is characterized in that comprising the following steps: 1) Automatically read the grid model and section from the SCADA system at regular intervals; 2) Generate real-time network topology; 3) Use the distribution network state estimation algorithm to process the data; 4) Identify the unqualified measurement, and identify the equipment that causes abnormal measurement according to the preset rules; 5) Determine the owner of the device, and send a text message or WeChat to the owner of the device; Using a common file method, automatically read the grid model and section from the network device or automation system, reconstruct the grid model, determine the real-time network topology, process the data with the state estimation algorithm, identify unqualified measurements, According to the set rules, determine the equipment that causes the abnormal measurement, send a notification to the relevant personnel, and guide the patrol to check for defects; The identification methods include: A) bad measurement identification, Use the state estimation results to automatically find bad measurements. The bad measurements include that the measured values are inconsistent with the real values or the deviation is too large to be used, including: Deviation measurement, use active and reactive power measurement values to check current measurement, and find possible bad measurement of active power, reactive power, voltage and gear position; Measurement direction, based on the measurement area balance check, to find possible wrong direction of flow Switch identification: Use switch branch active power flow calculation and expert database to find possible wrong switch remote signals; After the bad measurement is identified, output the bad measurement in CIM/E mode; B) Identification of dead data and transition data; Use the state estimation results to automatically discover dead data and jump data. The dead data is data that no longer changes due to various reasons in the acquisition device or channel; jump data refers to sudden large changes in data , and these data are actually unlikely to change greatly; The dead data includes the data that can no longer be changed, which can only be found through the cumulative comparison of multiple consecutive sections; The jump data includes mutation data found after comparing multiple consecutive sections; After the column data and jump data are identified, output them in CIM/E mode; C) Abnormal equipment identification; According to the relationship between the measurement location, type and quantity identification and the primary equipment, channels and sensors, identify the equipment that may cause abnormalities; The measurement may be caused by the acquisition sensor of this switch. 2. A distribution network state estimation abnormality identification method according to claim 1, characterized in that: when automatically reading the grid model and section from the SCADA system regularly, the FTP technology is used to regularly read the grid model and section. 3. A distribution network state estimation abnormality identification method according to claim 1, characterized in that: when the grid model and section are automatically read regularly from the SCADA system, the grid model and section used are based on the CIM/E format. 4. A distribution network state estimation anomaly identification method according to claim 1, characterized in that: when the distribution network state estimation algorithm is used to process the data, the distribution transformer capacity is used as the relative load between loads in the unobservable area The proportion of the total measured load in the unobservable area is distributed to each distribution transformer. On this basis, a power flow calculation of the distribution network is carried out, and the network loss of each unobservable area is estimated based on this, and then the load in the unobservable area is calculated. The total is corrected to obtain an estimate. 5. A distribution network state estimation abnormality identification method according to claim 1, characterized in that: unqualified measurements include transformer active power unbalance, bus active power unbalance, line active power unbalance, line active dead data, line One or more of active power jump data and transformer active dead data. 6. A distribution network state estimation abnormal identification device, which adopts a distribution network state estimation abnormal identification method according to any one of claims 1-5 to perform distribution network state estimation abnormal identification; it is characterized in that it includes: The power grid model and section reading unit uses the RJ-45 network port to directly read the power grid model and section files to determine the real-time network topology and power flow status; The state estimation and abnormal identification unit is used for state estimation and calculation; the grid model and section reading unit is connected to the state estimation and abnormal identification unit through the EMAC interface; A defect notification unit, including a communication chip, which is equipped with a GSM sending function; Power supply, used to provide 3.3V DC.