CN112200485A - Power dispatching real-time data quality improving method based on multi-source arbitration - Google Patents

Power dispatching real-time data quality improving method based on multi-source arbitration Download PDF

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CN112200485A
CN112200485A CN202011160778.0A CN202011160778A CN112200485A CN 112200485 A CN112200485 A CN 112200485A CN 202011160778 A CN202011160778 A CN 202011160778A CN 112200485 A CN112200485 A CN 112200485A
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晋银峰
戴则梅
唐元合
孙世明
邰曈
钱涵佳
孙惠
于雷
马洁
史宁波
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Nari Technology Co Ltd
NARI Nanjing Control System Co Ltd
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NARI Nanjing Control System Co Ltd
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Abstract

The invention discloses a power dispatching real-time data quality improving method based on multi-source arbitration. Belonging to the technical field of power grids; the method comprises the following specific steps: 1. determining a plurality of data sources for acquiring an object; 2. determining the rationality of each data source; 3. comparing the numerical difference between the data sources; 4. and sequencing according to the preset data source priority, and selecting the effective data source with the highest priority as the result of the multi-source decision. The method realizes the analysis and screening of the multi-source data, solves the problem of effective identification of abnormal data, improves the reliability of real-time data, and makes full use of cross information in power grid dispatching by using the multi-source arbitration method, so that the method is suitable for the requirements of larger scale, higher accuracy and higher reliability in the future.

Description

Power dispatching real-time data quality improving method based on multi-source arbitration
Technical Field
The invention relates to the technical field of power grids, in particular to a power dispatching real-time data quality improving method based on multi-source arbitration.
Background
In an electric power dispatching automation system, real-time data of electric power dispatching is an important basis for safe production and dispatching automation of electric power command, and the quality of the real-time data directly influences the safe, economic, stable and reliable operation of a power grid. The real-time data acquisition process is as follows: data collected by a data collection unit (RTU) of each plant station is transmitted to a data collection and monitoring control (SCADA) system through a data collection and exchange subsystem (generally called as a 'preposed subsystem'), the SCADA system performs screening, discrimination and other operations on the transmitted original data (raw data) to obtain a processing result (cooked data), and the processing result is written into a storage medium or transmitted in a message form and provided for external application. In this case, the system may have a plurality of different data sources (called "point multi-sources") for the same acquisition object (e.g. active power of a line), the data sources are generally consistent but have more or less different data quality, and when one or more of the data sources is abnormal due to some unexpected reasons, how to select an optimal source as the final data of the measurement object to improve the real-time data quality also becomes a major problem.
At present, the domestic discrimination of real-time data of multi-source measuring points adopts a processing mode of judging abnormity, namely, which data source is abnormal is filtered and removed. The method can quickly and accurately judge the explicit abnormal conditions (such as unchanged data or errors caused by communication channel interruption), but has low identification degree on abnormal data, cannot effectively judge suspicious data, and cannot meet the quality requirement on real-time data under a future large-scale power grid.
Disclosure of Invention
Aiming at the problems, the invention provides a power scheduling real-time data quality improving method based on multi-source arbitration.
The technical scheme of the invention is as follows: a power dispatching real-time data quality improving method based on multi-source arbitration specifically comprises the following steps:
step (1.1), determining a plurality of data sources of the acquisition object according to the acquisition device and system construction;
step (1.2), carrying out reasonable inspection on the data source according to the reasonable upper and lower limits and the qualified rate of the data, and marking the data source which fails to pass as invalid through the inspection;
step (1.3), error data screening is realized by comparing the numerical difference between the remaining data sources which are not marked as invalid, and the data source with larger error is marked as invalid;
and (1.4) sorting the data sources which are left after error data screening and are not marked as invalid according to a preset data source priority, and selecting the valid data source with the highest priority as a final determination decision result of the multi-source decision.
Further, in step (1.1), the data sources include real-time data, peer end, state estimation, WAMS and 5 backup data sources sent by the pre-subsystem.
Further, in the step (1.2), a data source reasonable check is performed according to the reasonable upper and lower limits and the qualified rate of the data, and the specific step of marking the failed data source as invalid through the check is as follows:
(1) judging reasonable upper and lower limits for each data source, and marking the data sources close to the reasonable range as invalid;
(2) and judging the state estimation convergence mark and the measurement qualified rate for the state estimation data, and marking the state estimation source as invalid if the calculation is not converged or the measurement qualified rate is lower than 90%.
Further, in the step (1.3), error data screening is realized by comparing the numerical difference between the remaining data sources which are not marked as invalid, and the specific step of marking the data source with larger error as invalid is that; screening out abnormal measurement by adopting a coarse error data judgment criterion, and marking the abnormal measurement as invalid; through a comparison algorithm, error values of a plurality of data sources under a common condition are counted, then a median value is found in the plurality of sources, the difference value between the numerical value of each source and the median value is calculated, and finally data with the difference value larger than an empirical value are removed.
Further, aiming at the whole process of reasonably checking the data source in the step (1.2), screening error data in the step (1.3) and finally determining a decision result in the step (1.4), all intermediate calculation results are stored in a log or an alarm event so as to be convenient for back check afterwards.
The invention has the beneficial effects that: the invention provides a power dispatching real-time data quality improving method based on multi-source arbitration, which comprises the steps of firstly determining the rationality of each data for multi-source real-time data, removing data source data outside reasonable upper and lower limits, secondly comparing the numerical difference among all effective data sources, screening abnormal data through a comparison algorithm (such as a Dixon criterion or a Grabas criterion), and finally carrying out priority sorting on the rest data sources according to experience to select the effective data source with the highest priority as the result of the multi-source arbitration. According to the method, abnormal data are effectively screened out and suspicious data are judged by consuming more computing resources, so that the data source of the point measuring object is more reliable, the real-time data quality is further improved, and the accuracy and reliability of the data in the power grid dispatching system are guaranteed.
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FIG. 1 is a flow chart of the architecture of the present invention;
fig. 2 is a schematic diagram of an embodiment of the present invention.
Detailed Description
In order to more clearly illustrate the technical solution of the present invention, the following detailed description is made with reference to the accompanying drawings:
as depicted in fig. 1; a power dispatching real-time data quality improving method based on multi-source arbitration specifically comprises the following steps:
step (1.1), determining a plurality of data sources of the acquisition object according to the acquisition device and system construction;
step (1.2), carrying out reasonable inspection on the data source according to the reasonable upper and lower limits and the qualified rate of the data, and marking the data source which fails to pass as invalid through the inspection;
step (1.3), error data screening is realized by comparing the numerical difference between the remaining data sources which are not marked as invalid, and the data source with larger error is marked as invalid;
and (1.4) sorting the data sources which are left after error data screening and are not marked as invalid according to a preset data source priority, and selecting the valid data source with the highest priority as a final determination decision result of the multi-source decision.
Further, in step (1.1), the data sources generally include real-time data uploaded by the pre-subsystem, peer end, state estimation, WAMS, and 5 backup data sources.
Further, in the step (1.2), a data source reasonable check is performed according to the reasonable upper and lower limits and the qualified rate of the data, and the specific step of marking the failed data source as invalid through the check is as follows:
(1) judging reasonable upper and lower limits for each data source, and marking the data sources close to the reasonable range as invalid;
(2) and judging the state estimation convergence mark and the measurement qualified rate for the state estimation data, and marking the state estimation source as invalid if the calculation is not converged or the measurement qualified rate is lower than 90%.
Further, in step (1.3), error data screening is implemented by comparing the numerical difference between the remaining data sources which are not marked as invalid, and the specific step of marking the data source with larger error as invalid is as follows: removing abnormal measurement by using coarse error data judgment criterion (such as Dixon criterion or Grabas criterion), and marking the abnormal measurement as invalid; through a comparison algorithm, the number of error values of a plurality of data sources in general is counted (an empirical value, such as 0.5, can be set by using parameters), then a median value is found from the plurality of sources, the difference value between the numerical value of each source and the median value is calculated, and finally data with the difference value larger than the empirical value is removed.
Further, aiming at the whole process of reasonably checking the data source in the step (1.2), screening error data in the step (1.3) and finally determining a decision result in the step (1.4), all intermediate calculation results are stored in a log or an alarm event so as to be convenient for back check afterwards.
As shown in fig. 2, fig. 2 is a data flow chart of a power scheduling real-time data quality improving method based on multi-source arbitration, and it can be seen from the figure that real-time data is uploaded to a current subsystem to trigger a flow of multi-source arbitration; taking the active tie line as an example, the existing data sources are as follows: 1. preamble, 2, peer: and the line opposite side measurement has the inverse function, 3, state estimation, 4, WAMS, 5 and standby modulation. After entering a multi-source arbitration process, firstly, judging reasonable upper and lower limits for each data source, and marking the data source in a more reasonable range as invalid; and for the state estimation data, judging a state estimation convergence mark and a measurement qualified rate, and marking the state estimation source as invalid if the calculation is not converged or the measurement qualified rate is lower than 90%. Secondly, comparing the numerical difference among the data sources; the coarse error data determination criteria (e.g., dixon criteria or grassroots criteria) are used to screen out the abnormal measurements and mark the abnormal measurements as invalid. The comparison algorithm can also use a simple median error algorithm, firstly, the error of a plurality of data sources under the common condition is counted (an empirical value, such as 0.5, can be set by using parameters), then, a median value is found from the plurality of sources, the difference value between each source and the median value is calculated, and the data with the error larger than the empirical value is removed. Finally, selecting the effective data source with the highest priority according to the priority sequence of the local end, the opposite end, the state estimation, the WAMS and the standby regulation, and outputting the data to the SCADA system; in addition, as shown in fig. 1, in the multi-source arbitration process, all intermediate calculation results need to be stored in a log or an alarm event, such as reasonable data source inspection, error data screening, and final decision result determination, so as to perform back-check afterwards.
The above examples do not limit the invention in any way, and all technical solutions obtained by means of equivalent substitution or equivalent transformation fall within the scope of protection of the invention.

Claims (5)

1. A power dispatching real-time data quality improving method based on multi-source arbitration is characterized by comprising the following specific steps:
step (1.1), determining a plurality of data sources of the acquisition object according to the acquisition device and system construction;
step (1.2), carrying out reasonable inspection on the data source according to the reasonable upper and lower limits and the qualified rate of the data, and marking the data source which fails to pass as invalid through the inspection;
step (1.3), error data screening is realized by comparing the numerical difference between the remaining data sources which are not marked as invalid, and the data source with larger error is marked as invalid;
and (1.4) sorting the data sources which are left after error data screening and are not marked as invalid according to a preset data source priority, and selecting the valid data source with the highest priority as a final determination decision result of the multi-source decision.
2. The method according to claim 1, wherein in step (1.1), the data sources include real-time data sent by the front-end subsystem, peer-to-peer, state estimation, WAMS, and 5 backup data sources.
3. The method according to claim 1, wherein in the step (1.2), the reasonable inspection of the data source is performed according to the reasonable upper and lower limits and the qualified rate of the data, and the specific step of marking the failed data source as invalid by the inspection is:
(1) judging reasonable upper and lower limits for each data source, and marking the data sources close to the reasonable range as invalid;
(2) and judging the state estimation convergence mark and the measurement qualified rate for the state estimation data, and marking the state estimation source as invalid if the calculation is not converged or the measurement qualified rate is lower than 90%.
4. The method according to claim 1, wherein in step (1.3), error data screening is implemented by comparing the numerical difference between the remaining data sources that are not marked as invalid, and the specific step of marking the data source with a larger error as invalid is; screening out abnormal measurement by adopting a coarse error data judgment criterion, and marking the abnormal measurement as invalid; through a comparison algorithm, error values of a plurality of data sources under a common condition are counted, then a median value is found in the plurality of sources, the difference value between the numerical value of each source and the median value is calculated, and finally data with the difference value larger than an empirical value are removed.
5. The method according to claim 1, wherein all intermediate calculation results are saved in a log or an alarm event for the whole process of reasonably checking the data source in step (1.2), screening error data in step (1.3) and finally determining the decision result in step (1.4) so as to perform back check afterwards.
CN202011160778.0A 2020-10-27 2020-10-27 Power dispatching real-time data quality improving method based on multi-source arbitration Pending CN112200485A (en)

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Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105046344A (en) * 2015-05-15 2015-11-11 北京科东电力控制系统有限责任公司 Primary station data quality optimizing method for intelligent power grid dispatching technical support system

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105046344A (en) * 2015-05-15 2015-11-11 北京科东电力控制系统有限责任公司 Primary station data quality optimizing method for intelligent power grid dispatching technical support system

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Application publication date: 20210108