CN110807711A - Power failure identification method based on electric power big data - Google Patents
Power failure identification method based on electric power big data Download PDFInfo
- Publication number
- CN110807711A CN110807711A CN201911035548.9A CN201911035548A CN110807711A CN 110807711 A CN110807711 A CN 110807711A CN 201911035548 A CN201911035548 A CN 201911035548A CN 110807711 A CN110807711 A CN 110807711A
- Authority
- CN
- China
- Prior art keywords
- power failure
- power
- data
- voltage
- restoration
- 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.)
- Pending
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R19/00—Arrangements for measuring currents or voltages or for indicating presence or sign thereof
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R22/00—Arrangements for measuring time integral of electric power or current, e.g. electricity meters
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
Landscapes
- Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- Theoretical Computer Science (AREA)
- Marketing (AREA)
- Health & Medical Sciences (AREA)
- Development Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Educational Administration (AREA)
- General Business, Economics & Management (AREA)
- Quality & Reliability (AREA)
- Game Theory and Decision Science (AREA)
- Operations Research (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Power Engineering (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The invention provides a power failure identification method based on electric power big data, which comprises the following steps: acquiring the daily operation time of the metering terminal; judging whether the daily running time is less than the preset time or not; if the daily running time is less than the preset time, collecting power failure and restoration alarm information, and acquiring voltage and current data and electric quantity data; and identifying power failure according to the power failure and restoration alarm information, the voltage and current data and the electric quantity data. The invention can conveniently and accurately realize power failure identification.
Description
Technical Field
The invention relates to the technical field of power supply information processing, in particular to a power failure identification method based on electric power big data.
Background
In the power enterprise management process, power supply reliability is an important index, and one of the important indexes for measuring power supply reliability is the number of times of power failure and the length of power failure time. At present, with the development of electric power big data technology and the increasing intellectualization of various metering terminals, the collection and analysis of electric power data are relatively more accurate, the electric power failure identification analysis is carried out by utilizing the electric power big data, the power failure times and the power failure time can be more accurately identified, and therefore a more accurate power supply reliability measurement index is provided.
Disclosure of Invention
The invention provides a power failure identification method based on electric power big data for solving the technical problems, and power failure identification can be conveniently and accurately realized.
The technical scheme adopted by the invention is as follows:
a power failure identification method based on electric power big data comprises the following steps: acquiring the daily operation time of the metering terminal; judging whether the daily running time is less than a preset time or not; if the daily running time is less than the preset time, collecting power failure and power restoration alarm information, and acquiring voltage and current data and electric quantity data; and identifying power failure according to the power failure and restoration alarm information, the voltage and current data and the electric quantity data.
According to stop to answer a telegram and report to the police information, voltage current data and electric quantity data carry out the power failure and discern, specifically include: judging whether the power failure and restoration alarm information is collected or not; if the power failure and restoration alarm information is collected, judging whether the power failure and restoration alarm information is effective or not according to the voltage and current data; if the power failure recovery warning information is effective, determining power failure starting and stopping time according to the power failure recovery warning information; if the power failure recovery warning information is invalid or the power failure recovery warning information is not acquired, determining power failure starting and stopping time according to the voltage and current data; after the power failure starting and stopping time is determined, judging whether the power failure is effective power failure or not according to the electric quantity data; and if the power failure is effective, recording the power failure data of the power failure.
Judging whether the power failure and restoration alarm information is effective according to the voltage and current data, which specifically comprises the following steps: if valid voltage and current curve data exist at a time point immediately after the time point of collecting the power failure warning information, judging that the power failure warning information is invalid, otherwise, judging that the power failure warning information is valid; and if the effective voltage and current curve data exists at the time point immediately before the time point of the power restoration warning information, judging that the power restoration warning information is invalid, otherwise, judging that the power restoration warning information is effective.
Determining the power failure starting and stopping time according to the voltage and current data, and specifically comprising the following steps: and if the three-phase current-voltage curve is abnormal, adding a first preset time length to the moment when the first normal voltage data appears as the power failure moment, and subtracting a second preset time length from the first moment after the normal voltage data is recovered as the power restoration moment.
The power failure data includes the judgement basis and the power failure start-stop time of this power failure, according to whether this power failure is effective power failure is judged to the electric quantity data, specifically includes: calculating the average value of the electric quantity in the starting and stopping time of the power failure according to the average value of the electric quantity of the third preset time before the power failure time, and comparing the average value of the electric quantity and the electric quantity; and if the average value of the electric quantity in the starting and stopping time of the power failure is smaller than the average value of the electric quantity in the third preset time, judging that the power failure is effective power failure, otherwise, judging that the power failure is ineffective power failure.
According to stop to answer a telegram and report to the police information, voltage current data and electric quantity data carry out the power failure and discern, specifically include: giving corresponding weights to whether the power failure and restoration alarm information, the voltage and current data and the electric quantity data are collected or not; calculating a power failure score according to whether the power failure warning information, the voltage and current data, the electric quantity data and respective corresponding weights are acquired; and judging whether to stop power supply and determining the power failure starting and stopping time according to the power failure score.
Calculating a power failure score value, specifically comprising: assigning values for judging whether the power failure and restoration alarm information, the voltage and current data and the electric quantity data are collected or not; and calculating whether the product of the value of the power failure and the weight thereof, the product of the value of the voltage and the weight thereof and the product of the value of the electric quantity data and the value assigned to the electric quantity data and the product of the weight thereof are acquired or not, and summing the calculated products to obtain the power failure score value.
The invention has the beneficial effects that:
according to the invention, the power failure identification can be conveniently and accurately realized by acquiring the daily running time of the metering terminal, acquiring the power failure and restoration alarm information when the daily running time is less than the preset time, acquiring the voltage and current data and the electric quantity data, and carrying out power failure identification according to the power failure and restoration alarm information, the voltage and current data and the electric quantity data.
Drawings
FIG. 1 is a flow chart of a power outage identification method based on big power data;
fig. 2 is a flowchart of a power outage identification method based on big power data according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, 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 invention.
As shown in fig. 1, the power outage identification method based on the big power data in the embodiment of the present invention includes the following steps:
and S1, acquiring the daily operation time of the metering terminal.
In one embodiment of the invention, the daily operation time defaults to 0 if the data related to the daily operation time is not acquired, and defaults to-10000 if the acquired daily operation time data is invalid. And for the situation that the metering terminal does not have the function of acquiring the daily running time, the daily running time is 0.
And S2, judging whether the daily running time is less than the preset time.
In one embodiment of the present invention, the predetermined time may be 1425 minutes.
And S3, if the daily running time is less than the preset time, acquiring the power failure and restoration alarm information, and acquiring voltage and current data and electric quantity data.
In one embodiment of the invention, the power outage and restoration alarm information comprises power outage alarm information and power restoration alarm information which respectively have corresponding data codes. Wherein, the power failure alarm information and the power restoration alarm information are collected and can be called as double-side alarm; only the power failure alarm information or the power restoration alarm information is collected, which can be called single-side alarm.
In one embodiment of the present invention, the voltage-current data may include a voltage-current curve, and the charge data may be a charge value over a certain period of time.
And S4, power failure identification is carried out according to the power failure and restoration alarm information, the voltage and current data and the electric quantity data.
In an embodiment of the present invention, as shown in fig. 2, after determining that the daily operation time is less than the preset time, the following steps may be performed: judging whether power failure and restoration alarm information is collected or not; if the power failure and restoration alarm information is collected, judging whether the power failure and restoration alarm information is effective or not according to the voltage and current data; if the power failure and power restoration warning information is effective, determining the power failure starting and stopping time according to the power failure and power restoration warning information; if the power failure recovery warning information is invalid or the power failure recovery warning information is not acquired, determining the power failure starting and stopping time according to the voltage and current data; after the power failure starting and stopping time is determined, judging whether the power failure is effective power failure or not according to the electric quantity data; and if the power failure is effective, recording the power failure data of the power failure.
After the power failure and power restoration warning information is collected, if the time point of collecting the power failure warning information is a time point immediately after the current point, for example, 15 minutes of the current point has valid voltage and current curve data, the power failure warning information is judged to be invalid, and otherwise, the power failure warning information is judged to be valid; and if the effective voltage and current curve data exists at the time point immediately before the time point of the power restoration warning information, judging that the power restoration warning information is invalid, otherwise, judging that the power restoration warning information is effective. For the condition that the power failure alarm information and the power restoration alarm information are both effective, the method can be called as effective bilateral alarm; the condition that only the power failure alarm information or the power restoration alarm information is effective can be called as effective single-side alarm. If effective alarms are received for multiple times within 15 minutes, the first alarm information is taken for subsequent processing.
When the power failure and power restoration alarm information is judged to be effective, namely the power failure alarm information and the power restoration alarm information are both effective, the power failure starting and stopping time can be determined according to the time information carried by the power failure alarm information and the power restoration alarm information, namely the time for sending the power failure alarm information and the time for sending the power restoration alarm information.
When the power restoration stopping warning information is judged to be invalid or the power restoration stopping warning information is not acquired, if the three-phase current voltage curve is abnormal, adding a first preset time length to the time when the first normal voltage data appears as a power failure time, and subtracting a second preset time length from the first time when the normal voltage data is recovered as a power restoration time. The three-phase current-voltage curve is not counted as power failure as long as one phase is normal, and the load data is judged to be abnormal if the value of the load data is 0 or null or less than 60% of a rated value (the current is less than 60% of the starting current, and the starting current value is 10% of the rated current). In one embodiment of the present invention, the first preset time period and the second preset time period may be 8 minutes each. For the case of unilateral alarm, specifically, if only the power failure alarm information is acquired or only the power failure alarm information is valid, the time obtained by subtracting 8 minutes from the first time point with curve data within three days after the time point of acquiring the power failure alarm information can be used as the power restoration time; if only the power restoration alarm information is collected or only the power restoration alarm information is valid, the time of adding 8 minutes to the latest time point with curve data within three days before the time point of collecting the power restoration alarm information can be used as the power failure time.
After the power failure starting and stopping time is determined, the average value of the electric quantity in the power failure starting and stopping time can be calculated according to the average value of the electric quantity of the third preset time before the power failure time, the average value of the electric quantity in the power failure starting and stopping time is compared with the average value of the electric quantity of the third preset time, if the average value of the electric quantity in the power failure starting and stopping time is smaller than the average value of the electric quantity of the third preset time, the power failure is judged to be effective power failure, and if. In a specific embodiment of the present invention, the third preset duration is three days. In addition, whether the power failure is effective power failure or not can be judged according to the power failure time length, specifically, if the power failure time length is within 44 minutes to 72 hours, the power failure is judged to be effective power failure, and if the power failure time length is less than 44 minutes or exceeds 72 hours, the power failure is judged to be ineffective power failure.
The recorded power failure data comprises judgment basis (including double-side alarm, single-side alarm and curve abnormity) of the power failure and power failure starting and stopping time, and the power failure data can be stored in a database.
In addition, in the case where one identification object has a plurality of metering terminals, for example, when one transformer corresponds to a plurality of electric energy meters, if it is identified that no effective power failure occurs according to any one electric energy meter, it is determined that no power failure occurs; if an effective power outage is identified according to the plurality of electric energy meters, the power outage start-stop time can be the intersection of the power outage times determined according to the plurality of electric energy meters. The single-phase electric energy meter does not participate in the judgment of the curve data, and the auxiliary meter, the metering point which does not participate in the system analysis object model and the metering point with incomplete rated current and voltage data do not participate in the power failure identification.
In another embodiment of the invention, after the daily running time is judged to be less than the preset time, corresponding weights are given to whether the power failure and power restoration warning information, the voltage and current data and the power quantity data are collected or not, a power failure score value is calculated according to whether the power failure and power restoration warning information, the voltage and current data and the power quantity data are collected or not and the corresponding weights, and whether power failure occurs or not and power failure starting and stopping time is determined according to the power failure score value.
The rule for calculating the power failure score value is as follows: assigning values for whether power failure and restoration alarm information, voltage and current data and electric quantity data are acquired; and calculating whether the product of the value of the power failure and the weight of the power failure alarm information, the product of the value of the voltage and current data and the weight of the voltage and current data and the value of the electric quantity data assignment and the product of the weight of the voltage and current data are acquired or not, and summing the calculated products to obtain a power failure score.
Specifically, a preset time period may be intercepted, and first, whether the power failure warning information and the voltage-current curve are abnormal or not are acquired within the preset time period is judged, and an electric quantity value within the preset time period is acquired. And assigning 1 to the collected power failure and restoration alarm information, assigning 1 to the voltage and current curve if abnormity occurs, and assigning the electric quantity value as electric quantity value data. Then, according to the respective corresponding weights, for example, the weight of collected power failure and power failure alarm information is a, the weight of not collected power failure and power failure alarm information is 1-a, the weight of abnormal voltage and current curve is b, the weight of abnormal voltage and current curve is 1-b, and the weight of electric quantity value is c, the power failure scoring value is calculated. Taking the collected power failure and restoration alarm information, the occurrence of abnormality of the voltage and current curve and the electric quantity value as E as an example, the power failure score value P is a + b + E. And finally, judging whether the power failure score is larger than a preset score, and if so, judging that the power failure occurs in the preset time period. When the power failure of a plurality of continuous preset time periods is judged, the power failure starting and stopping time can be determined simultaneously. It should be appreciated that the smaller the preset time period, the higher the accuracy of the power outage identification.
In summary, according to the power failure identification method based on the large electric power data in the embodiment of the invention, by acquiring the daily operation time of the metering terminal, acquiring the power failure and power restoration alarm information when the daily operation time is less than the preset time, acquiring the voltage and current data and the electric quantity data, and performing power failure identification according to the power failure and power restoration alarm information, the voltage and current data and the electric quantity data, the method can conveniently and accurately realize power failure identification.
In the description of the present invention, the terms "first" and "second" are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implying any number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. The meaning of "plurality" is two or more unless specifically limited otherwise.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (7)
1. A power failure identification method based on electric power big data is characterized by comprising the following steps:
(1) acquiring the daily operation time of the metering terminal;
(2) judging whether the daily running time is less than a preset time or not;
(3) if the daily running time is less than the preset time, collecting power failure and power restoration alarm information, and acquiring voltage and current data and electric quantity data;
(4) and identifying power failure according to the power failure and restoration alarm information, the voltage and current data and the electric quantity data.
2. The power outage identification method based on the big power data as claimed in claim 1, wherein in the step (4), the power outage identification is performed according to the power outage and restoration alarm information, the voltage and current data and the power quantity data, and specifically includes:
(2-1) judging whether the power failure and restoration alarm information is acquired or not;
(2-2) if the power failure and restoration alarm information is collected, judging whether the power failure and restoration alarm information is effective or not according to the voltage and current data;
(2-3) if the power failure and power restoration warning information is valid, determining power failure starting and stopping time according to the power failure and power restoration warning information;
(2-4) if the power failure and restoration alarm information is invalid or the power failure and restoration alarm information is not acquired, determining power failure starting and stopping time according to the voltage and current data;
(2-5) after the power failure starting and stopping time is determined, judging whether the power failure is effective power failure or not according to the electric quantity data;
and (2-6) if the power failure is effective, recording the power failure data of the power failure.
3. The power outage identification method based on the big power data as claimed in claim 2, wherein in the step (2-2), determining whether the power outage and restoration alarm information is valid according to the voltage and current data specifically includes:
(3-1) if valid voltage and current curve data exist at a time point immediately after the time point of collecting the power failure warning information, judging that the power failure warning information is invalid, otherwise, judging that the power failure warning information is valid;
and (3-2) if valid voltage and current curve data exist at a time point immediately before the time point of the power restoration warning information, judging that the power restoration warning information is invalid, and otherwise, judging that the power restoration warning information is valid.
4. The power outage identification method based on the big power data as claimed in claim 2, wherein in the step (2-4), the power outage starting and ending time is determined according to the voltage and current data by the following method: and if the three-phase current-voltage curve is abnormal, adding a first preset time length to the moment when the first normal voltage data appears as the power failure moment, and subtracting a second preset time length from the first moment after the normal voltage data is recovered as the power restoration moment.
5. The method for identifying a power outage based on big power data as claimed in claim 2, wherein the power outage data includes a criterion of the power outage and a power outage start-stop time, and in the step (2-5), whether the power outage is an effective power outage is determined according to the power data, and the specific method is as follows:
(5-1) calculating the average value of the electric quantity in the starting and stopping time of the power failure according to the average value of the electric quantity in a third preset time before the power failure time, and comparing the average value of the electric quantity and the electric quantity;
(5-2) if the average value of the electric quantity in the starting and stopping time of the power failure is smaller than the average value of the electric quantity in the third preset time, judging that the power failure is effective power failure, and otherwise, judging that the power failure is ineffective power failure.
6. The power failure identification method based on the big power data as claimed in claim 1, wherein the power failure identification is performed according to the power failure and restoration alarm information, the voltage and current data and the power quantity data, and the specific method is as follows:
giving corresponding weights to whether the power failure and restoration alarm information, the voltage and current data and the electric quantity data are collected or not;
calculating a power failure score according to whether the power failure warning information, the voltage and current data, the electric quantity data and respective corresponding weights are acquired;
and judging whether to stop power supply and determining the power failure starting and stopping time according to the power failure score.
7. The power failure identification method based on the big power data as claimed in claim 6, wherein the power failure score value is calculated by the following specific method:
assigning values for judging whether the power failure and restoration alarm information, the voltage and current data and the electric quantity data are collected or not;
and calculating whether the product of the value of the power failure and the weight thereof, the product of the value of the voltage and the weight thereof and the product of the value of the electric quantity data and the value assigned to the electric quantity data and the product of the weight thereof are acquired or not, and summing the calculated products to obtain the power failure score value.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911035548.9A CN110807711A (en) | 2019-10-29 | 2019-10-29 | Power failure identification method based on electric power big data |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911035548.9A CN110807711A (en) | 2019-10-29 | 2019-10-29 | Power failure identification method based on electric power big data |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110807711A true CN110807711A (en) | 2020-02-18 |
Family
ID=69489384
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911035548.9A Pending CN110807711A (en) | 2019-10-29 | 2019-10-29 | Power failure identification method based on electric power big data |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110807711A (en) |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103926485A (en) * | 2014-03-26 | 2014-07-16 | 国家电网公司 | Power failure event judging method based on electric energy collecting terminal |
| JP2016153739A (en) * | 2015-02-20 | 2016-08-25 | 株式会社Ｎｔｔファシリティーズ | Power supply system, power supply quality monitoring device, power supply monitoring method, and program |
| KR20180004581A (en) * | 2016-07-04 | 2018-01-12 | 엘에스산전 주식회사 | Device of monitoring a reactive power compensation system and method thereof |
| CN108764596A (en) * | 2018-03-28 | 2018-11-06 | 广州供电局有限公司 | The monitoring method and monitoring system of the power failure of metering automation system |
| CN108805412A (en) * | 2018-05-18 | 2018-11-13 | 广东电网有限责任公司 | Arrester evaluating apparatus based on big data analysis and method |
| CN109239487A (en) * | 2018-08-28 | 2019-01-18 | 中能瑞通（北京）科技有限公司 | A kind of user's use energy quality evaluating method and system based on electricity consumption data |
| CN110196366A (en) * | 2019-06-04 | 2019-09-03 | 鼎信信息科技有限责任公司 | Route stops send a telegram in reply state identification method, device, computer equipment and storage medium |
-
2019
- 2019-10-29 CN CN201911035548.9A patent/CN110807711A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103926485A (en) * | 2014-03-26 | 2014-07-16 | 国家电网公司 | Power failure event judging method based on electric energy collecting terminal |
| JP2016153739A (en) * | 2015-02-20 | 2016-08-25 | 株式会社Ｎｔｔファシリティーズ | Power supply system, power supply quality monitoring device, power supply monitoring method, and program |
| KR20180004581A (en) * | 2016-07-04 | 2018-01-12 | 엘에스산전 주식회사 | Device of monitoring a reactive power compensation system and method thereof |
| CN108764596A (en) * | 2018-03-28 | 2018-11-06 | 广州供电局有限公司 | The monitoring method and monitoring system of the power failure of metering automation system |
| CN108805412A (en) * | 2018-05-18 | 2018-11-13 | 广东电网有限责任公司 | Arrester evaluating apparatus based on big data analysis and method |
| CN109239487A (en) * | 2018-08-28 | 2019-01-18 | 中能瑞通（北京）科技有限公司 | A kind of user's use energy quality evaluating method and system based on electricity consumption data |
| CN110196366A (en) * | 2019-06-04 | 2019-09-03 | 鼎信信息科技有限责任公司 | Route stops send a telegram in reply state identification method, device, computer equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108879654B (en) | Remote diagnosis method based on abnormal remote measurement of abnormal equipment | |
| CN110571925B (en) | Method for analyzing power quality by using data of power distribution network monitoring terminal | |
| CN115796708B (en) | Big data intelligent quality inspection method, system and medium for engineering construction | |
| EP3972084A2 (en) | Systems and methods for monitoring energy-related data in an electrical system | |
| CN111666273B (en) | Meter reading system data validity analysis method and device | |
| CN109374995A (en) | Low-voltage distribution system, aging circuit and oppose electricity-stealing monitoring method and correspondence system | |
| CN109450089B (en) | Transformer area low voltage identification method and device and terminal equipment | |
| US11397212B2 (en) | Identification of cause of failure in a power storage system | |
| CN117220441A (en) | Information monitoring intelligent early warning method based on panoramic monitoring | |
| CN113238890B (en) | Current sampling loop abnormity diagnosis method and device based on dynamic record data | |
| CN113297033A (en) | Vehicle electric control system health assessment method and system based on cloud monitoring data | |
| CN111413564B (en) | Supercapacitor failure early warning method, system and equipment | |
| CN117349624A (en) | Electric power energy monitoring method, system, terminal equipment and storage medium | |
| CN110807711A (en) | Power failure identification method based on electric power big data | |
| CN115358336A (en) | Power utilization abnormity detection method and device and electronic equipment | |
| Tang et al. | An aging-and load-insensitive method for quantitatively detecting the battery internal-short-circuit resistance | |
| CN109375145A (en) | No-voltage fault monitoring method and device based on phase three-wire three meter equipment | |
| CN109507628B (en) | Reverse polarity fault monitoring method and device based on three-phase four-wire meter equipment | |
| CN107450030B (en) | Communication storage battery telemetry data processing method, device and system | |
| CN111751732A (en) | Electric quantity calculation method based on self-adaptive Gaussian convolution component method | |
| CN116990578B (en) | Direct current detection method and system based on intelligent power | |
| CN117458722B (en) | Data monitoring method and system based on electric power energy management system | |
| CN117124857B (en) | Insulation abnormality identification method and device, readable storage medium and electric automobile | |
| CN115423250B (en) | Analysis method for household transformer relation of transformer area | |
| CN113447712B (en) | Method for discovering electricity stealing of special variable metering device through multi-dimensional combination |
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 | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20210702 Address after: 510700 3rd, 4th and 5th floors of building J1 and 3rd floor of building J3, No.11 Kexiang Road, Science City, Luogang District, Guangzhou City, Guangdong Province Applicant after: ELECTRIC POWER Research Institute CHINA SOUTHERN POWER GRID Address before: 510670 No.11 Kexiang Road, Science City, Luogang District, Guangzhou City, Guangdong Province Applicant before: ELECTRIC POWER Research Institute CHINA SOUTHERN POWER GRID Applicant before: POWER GRID TECHNOLOGY RESEARCH CENTER. CHINA SOUTHERN POWER GRID |
|
| TA01 | Transfer of patent application right | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20200218 |
|
| RJ01 | Rejection of invention patent application after publication |