CN109738723A - A kind of electric energy meter three-phase automatic identification method - Google Patents

A kind of electric energy meter three-phase automatic identification method Download PDF

Info

Publication number
CN109738723A
CN109738723A CN201811647847.3A CN201811647847A CN109738723A CN 109738723 A CN109738723 A CN 109738723A CN 201811647847 A CN201811647847 A CN 201811647847A CN 109738723 A CN109738723 A CN 109738723A
Authority
CN
China
Prior art keywords
phase
voltage
electric energy
area
energy meter
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.)
Granted
Application number
CN201811647847.3A
Other languages
Chinese (zh)
Other versions
CN109738723B (en
Inventor
段盼
胡蓓
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Chongqing University of Science and Technology
Chongqing University of Post and Telecommunications
Original Assignee
Chongqing University of Science and Technology
Chongqing University of Post and Telecommunications
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Chongqing University of Science and Technology, Chongqing University of Post and Telecommunications filed Critical Chongqing University of Science and Technology
Priority to CN201811647847.3A priority Critical patent/CN109738723B/en
Publication of CN109738723A publication Critical patent/CN109738723A/en
Application granted granted Critical
Publication of CN109738723B publication Critical patent/CN109738723B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Landscapes

  • Supply And Distribution Of Alternating Current (AREA)
  • Remote Monitoring And Control Of Power-Distribution Networks (AREA)

Abstract

The present invention relates to a kind of electric energy meter three-phase automatic identification methods, belong to power distribution network electric parameter measurement application field.First on the basis of existing platform area accurate data, a voltage loss model is established.It is then based on voltage loss model and user's end data, area's Source of Gateway Meter voltage and three-phase are put into effect in estimation.Estimated voltage and virtual voltage are finally subjected to correlation analysis, integrated decision-making goes out the three-phase of user's electric energy meter to be identified, and provides the two related coefficient, so that administration of power networks ability is improved, the operation for promoting grid health stable.

Description

A kind of electric energy meter three-phase automatic identification method
Technical field
The invention belongs to power distribution network electric parameter measurement application fields, are related to a kind of electric energy meter three-phase automatic identification method.
Background technique
In daily management mission of the Utilities Electric Co. to power distribution network, often it is related to and the affiliated platform Qu Xiangguan of user's electric energy meter The problem of, such as when remote bill control, clock school.Accurately identify that platform area belonging to user's electric energy meter can be realized the battalion of fining It sells and effectively consumption reduction detracts.
Currently, the platform area identification of user relies primarily on PLC technology, need to send carrier signal from concentrator, then User terminal connects measuring tool and measures, and not only workload is very big, but also is easy the interference by electromagnetic signal.
Data according to defined in " the DL/T645-2007 multifunctional electric energy meter communication protocol " of in December, 2007 publication Exchange agreement can acquire various status informations when operation of power networks in real time.If can make full use of these collected operations Data analyze power distribution network, efficiently identify out the platform area of user's electric energy meter, it will substantially reduce Utilities Electric Co. administrator The work difficulty of member, improves the operational efficiency of power grid.
Summary of the invention
In view of this, the purpose of the present invention is to provide a kind of electric energy meter three-phase automatic identification methods.By in existing platform On the basis of area's accurate data, a voltage loss model is established.It is then based on voltage loss model, utilizes synchronization user The voltage value of area's Source of Gateway Meter phase is put into effect in the performance number of the voltage of electric energy meter, performance number and platform area Source of Gateway Meter phase, estimation.Most Afterwards, by calculating the voltage estimated value of several moment platforms area Source of Gateway Meter and the Spearman rank correlation coefficient of voltage actual value, come Determine the three-phase of user's electric energy meter to be identified.
In order to achieve the above objectives, the invention provides the following technical scheme:
A kind of electric energy meter three-phase automatic identification method, it is characterised in that: method includes the following steps:
S1: using known correct platform area data acquire the voltage of several moment platforms area's Source of Gateway Meter and user's electric energy meter with Performance number;
S2: a voltage loss model is established using collected voltage and performance number;
S3: voltage loss model and user's electric energy meter data to be identified are utilized, each critical point Tai Qu of each moment is estimated The voltage and three-phase of the every phase of table;
S4: the data of estimated value and actual value based on the every phase voltage of moment platform area Source of Gateway Meter calculate theirs Spearman rank correlation coefficient;
S5: using the Spearman rank correlation coefficient of actual value and estimated value, integrated decision-making user's electric energy meter to be identified Three-phase.
Further, the step S1 specifically:
Every 1~15 minute in certain number of days, user's electric energy meter voltage V of synchronous acquisitionu, power WuWith the user Electric energy meter corresponds to platform area Source of Gateway Meter in the voltage V of corresponding phaset, power Wt;Finally according to the collected data, a training is constructed Data set D (Wu Vu,Wt,Vt)。
Further, the step S2 specifically:
S21: by collected training dataset D use zero-mean value standardization method normalized, eliminate them it Between dimension, obtain new training dataset D*Specific conversion formula are as follows:
S22: according to gradient descent method principle, by making objective function Local Minimum, to obtain the ginseng of voltage loss model Number (k0,k1,k2,k3);Objective function are as follows:
Wherein, λ is regularization parameter, and m is training dataset D*The sample size of middle acquisition,Wt (i),Vt (i)Point It Wei not training set D*In i-th of sample.
Further, the S3 specifically:
S31: every 1~15 minute in certain number of days, the primary user's electric energy meter voltage V to be identified of synchronous acquisitionux, power WuxWith each area's Source of Gateway Meter each phase voltage Vt, power Wt;Finally according to the collected data, 3 × k number evidence is constructed Collect Tij(Wux Vux,Wtij,Vtij);Wherein, k is the total quantity in platform area, and i is platform area number, one in j A, B, C phase;
S32: by data set TijIn every data according in S21 mean value and variance standardize;
S33: according to voltage loss model, each each phase in area is estimated in the voltage value at corresponding moment and three Phase;The specific formula of voltage loss model are as follows:
Wherein, V 'tijI-th area's Source of Gateway Meter is represented in the voltage estimated value of j phase, Vux、WuxRespectively represent use to be identified Family electric energy meter voltage and power, Wtij V′tijI-th area's Source of Gateway Meter is represented in the power of j phase.
Further, the S4 specifically:
S41: by each data set TijThe voltage estimated value and actual value of obtained i-th area jth phase are respectively from small To big sequence, corresponding rank R is calculatediAnd Qi
S42: according to calculated rank, Spearman rank correlation coefficient, specific formula are calculated are as follows:
Further, the S5 specifically:
S51: calculated three correlation coefficient rs in i-th area are takeniA、riB、riCIn maximum value square be used as platform area Degree of correlation ri 2
S52: Ruo Tai area degree of correlation ri 2Less than γ1, then i-th area is removed from alternative platform area;Wherein, 0≤r2≤ 1, ri 2It is stronger closer to 1 user's electric energy meter and i-th area's correlation;γ1For threshold value, rule of thumb obtain;
S53: in remaining alternative platform area, the maximum r of the degree of correlation is foundi 2, then user's electric energy meter to be identified just with platform Area's Source of Gateway Meter three is consistent;
S54: it if can not finally be matched to suitable three-phase data, is analyzed again after obtaining more data;It repeats Step S3 to S5 identifies more user's electric energy meters, no longer needs to building loss of voltage model.
The beneficial effects of the present invention are:
First, can measure the function of voltage and power by electric energy meter, the method for maintenance data analysis is automatically identified The three-phase of user's electric energy meter reduces cost without adding additional special equipment;
Secondly, it can be achieved that the identification of across platform area, effectively solves the problems, such as Utilities Electric Co.'s archives typing mistake, improves the standard of statistics True rate.
Detailed description of the invention
In order to keep the purpose of the present invention, technical scheme and beneficial effects clearer, the present invention provides following attached drawing and carries out Illustrate:
Fig. 1 is a kind of electric energy meter three-phase automatic identification method flow chart;
Fig. 2 is user's electric energy meter three-phase comprehensive decision diagram to be identified.
Specific embodiment
Below in conjunction with attached drawing, a preferred embodiment of the present invention will be described in detail.
Fig. 1 is a kind of electric energy meter three-phase automatic identification method flow chart, and Fig. 2 is that user's electric energy meter three-phase comprehensive to be identified is determined Plan figure.It is as shown in the figure: a kind of electric energy meter three-phase automatic identification method provided by the invention, comprising the following steps:
S1: using known correct platform area data acquire the voltage of several moment platforms area's Source of Gateway Meter and user's electric energy meter with Performance number;
S2: a voltage loss model is established using collected voltage and performance number;
S3: voltage loss model and user's electric energy meter data to be identified are utilized, each critical point Tai Qu of each moment is estimated The voltage and three-phase of the every phase of table;
S4: the data of estimated value and actual value based on the every phase voltage of moment platform area Source of Gateway Meter calculate theirs Spearman rank correlation coefficient;
S5: using the Spearman rank correlation coefficient of actual value and estimated value, integrated decision-making user's electric energy meter to be identified Three-phase.
Further, in the step S1 using known correct platform area data acquire certain several moment platforms area's Source of Gateway Meter with The voltage of user's electric energy meter and performance number method particularly includes: every 1~15 minute in certain number of days, synchronous acquisition is once used Family electric energy meter voltage Vu, power WuPlatform area Source of Gateway Meter is corresponded to user's electric energy meter in the voltage V of corresponding phaset, power Wt.Most Afterwards according to the collected data, a training dataset D (W is constructedu Vu,Wt,Vt);
Further, a voltage loss model is established using the voltage and performance number of acquisition in the S2, including following Specific steps:
S21: by collected training dataset D use zero-mean value standardization method normalized, eliminate them it Between dimension, obtain new training dataset D*Specific conversion formula are as follows:
S22: according to gradient descent method principle, by making objective function Local Minimum, to obtain the ginseng of voltage loss model Number (k0,k1,k2,k3);
Further, the objective function in the S22 is
Wherein, λ is regularization parameter, and m is training dataset D*The sample size of middle acquisition,Wt (i),Vt (i)Point It Wei not training set D*In i-th of sample.
Further, voltage loss model and user's electric energy meter data to be identified are utilized in the step S3, are estimated each The voltage of each every phase of area's Source of Gateway Meter of moment, comprising the following specific steps
S31: every 15 minutes in 30 days, the primary user's electric energy meter voltage V to be identified of synchronous acquisitionux, power WuxWith it is every Voltage V of the area the Ge Tai Source of Gateway Meter in each phaset, power Wt.Finally according to the collected data, 3 × k number of building is according to collection Tij (Wux Vux,Wtij,Vtij).Wherein, k is the total quantity in platform area, and i is platform area number, one in j A, B, C phase;
S32: by data set TijIn every data according in S21 mean value and variance standardize;
S33: according to voltage loss model, each each phase in area is estimated in the voltage value at corresponding moment.Voltage damage Consume the specific formula of model are as follows:
Wherein, V 'tijI-th area's Source of Gateway Meter is represented in the voltage estimated value of j phase, Vux、WuxRespectively represent use to be identified Family electric energy meter voltage and power, Wtij V′tijI-th area's Source of Gateway Meter is represented in the power of j phase.
Further, the estimated value based on certain every phase voltage of several moment platforms area Source of Gateway Meter in the step S4 and actual value Data calculate their Spearman rank correlation coefficient, comprising the following specific steps
S41: by each data set TijThe voltage estimated value and actual value of obtained i-th area jth phase are respectively from small To big sequence, corresponding rank R is calculatediAnd Qi
S42: according to calculated rank, Spearman rank correlation coefficient, specific formula are calculated are as follows:
Further, the S5 specifically:
S51: calculated three correlation coefficient rs in i-th area are takeniA、riB、riCIn maximum value square be used as platform area Degree of correlation ri 2
S52: Ruo Tai area degree of correlation ri 2Less than γ1, then i-th area is removed from alternative platform area;Wherein, 0≤r2≤ 1, ri 2It is stronger closer to 1 user's electric energy meter and i-th area's correlation;γ1For threshold value, rule of thumb obtain;
S53: in remaining alternative platform area, the maximum r of the degree of correlation is foundi 2, then user's electric energy meter to be identified just with platform Area's Source of Gateway Meter three is consistent;S54: it if can not finally be matched to suitable three-phase data, is carried out again after obtaining more data Analysis;Step S3 to S5 is repeated, more user's electric energy meters are identified, no longer needs to building loss of voltage model.
Method of the present embodiment based on ridge regression and Spearman rank correlation, proposes a kind of electric energy meter three-phase automatic identification Method can not only effectively identify the three-phase of user's electric energy meter, can also provide corresponding related coefficient, to provide accurate Three-phase identification, promote power grid security effectively run.
Finally, it is stated that preferred embodiment above is only used to illustrate the technical scheme of the present invention and not to limit it, although logical It crosses above preferred embodiment the present invention is described in detail, however, those skilled in the art should understand that, can be Various changes are made to it in form and in details, without departing from claims of the present invention limited range.

Claims (6)

1. a kind of electric energy meter three-phase automatic identification method, it is characterised in that: method includes the following steps:
S1: the voltage and power of several moment platforms area's Source of Gateway Meter Yu user's electric energy meter are acquired using known correct platform area data Value;
S2: a voltage loss model is established using collected voltage and performance number;
S3: voltage loss model and user's electric energy meter data to be identified are utilized, it is every to estimate each area's Source of Gateway Meter of each moment The voltage and three-phase of phase;
S4: the data of estimated value and actual value based on the every phase voltage of moment platform area Source of Gateway Meter calculate theirs Spearman rank correlation coefficient;
S5: using the Spearman rank correlation coefficient of actual value and estimated value, the three-phase of integrated decision-making user's electric energy meter to be identified.
2. a kind of electric energy meter three-phase automatic identification method according to claim 1, it is characterised in that: the step S1 is specific Are as follows:
Every 1~15 minute in certain number of days, user's electric energy meter voltage V of synchronous acquisitionu, power WuWith user's electric energy Table corresponds to platform area Source of Gateway Meter in the voltage V of corresponding phaset, power Wt;Finally according to the collected data, a training data is constructed Collect D (Wu Vu,Wt,Vt)。
3. a kind of electric energy meter three-phase automatic identification method according to claim 1, it is characterised in that: the step S2 is specific Are as follows:
S21: collected training dataset D is used to the method normalized of zero-mean value standardization, is eliminated between them Dimension obtains new training dataset D*Specific conversion formula are as follows:
S22: according to gradient descent method principle, by making objective function Local Minimum, to obtain the parameter (k of voltage loss model0, k1,k2,k3);Objective function are as follows:
Wherein, λ is regularization parameter, and m is training dataset D*The sample size of middle acquisition,Wt (i),Vt (i)Respectively Training set D*In i-th of sample.
4. a kind of electric energy meter three-phase automatic identification method according to claim 1, it is characterised in that: the S3 specifically:
S31: every 1~15 minute in certain number of days, the primary user's electric energy meter voltage V to be identified of synchronous acquisitionux, power WuxWith Voltage V of each area's Source of Gateway Meter in each phaset, power Wt;Finally according to the collected data, 3 × k number of building is according to collection Tij (Wux Vux,Wtij,Vtij);Wherein, k is the total quantity in platform area, and i is platform area number, one in j A, B, C phase;
S32: by data set TijIn every data according in S21 mean value and variance standardize;
S33: according to voltage loss model, each each phase in area is estimated in the voltage value and three-phase at corresponding moment;Electricity Press the specific formula of loss model are as follows:
Wherein, V 'tijI-th area's Source of Gateway Meter is represented in the voltage estimated value of j phase, Vux、WuxRespectively represent user's electric energy to be identified Table voltage and power, Wtij V′tijI-th area's Source of Gateway Meter is represented in the power of j phase.
5. a kind of electric energy meter three-phase automatic identification method according to claim 1, it is characterised in that: the S4 specifically:
S41: by each data set TijVoltage estimated value and the actual value difference of obtained i-th area jth phase are from small to large Sequence, calculates corresponding rank RiAnd Qi
S42: according to calculated rank, Spearman rank correlation coefficient, specific formula are calculated are as follows:
6. a kind of electric energy meter three-phase automatic identification method according to claim 1, it is characterised in that: the S5 specifically:
S51: calculated three correlation coefficient rs in i-th area are takeniA、riB、riCIn maximum value square be used as platform Qu Xiangguan Spend ri 2
S52: Ruo Tai area degree of correlation ri 2Less than γ1, then i-th area is removed from alternative platform area;Wherein, 0≤r2≤ 1, ri 2 It is stronger closer to 1 user's electric energy meter and i-th area's correlation;γ1For threshold value, rule of thumb obtain;
S53: in remaining alternative platform area, the maximum r of the degree of correlation is foundi 2, then user's electric energy meter to be identified is just closed with platform area Oral thermometer three is consistent;
S54: it if can not finally be matched to suitable three-phase data, is analyzed again after obtaining more data;Repeat step S3 to S5 identifies more user's electric energy meters, no longer needs to building loss of voltage model.
CN201811647847.3A 2018-12-29 2018-12-29 Three-phase automatic identification method for electric energy meter Active CN109738723B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201811647847.3A CN109738723B (en) 2018-12-29 2018-12-29 Three-phase automatic identification method for electric energy meter

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201811647847.3A CN109738723B (en) 2018-12-29 2018-12-29 Three-phase automatic identification method for electric energy meter

Publications (2)

Publication Number Publication Date
CN109738723A true CN109738723A (en) 2019-05-10
CN109738723B CN109738723B (en) 2021-02-09

Family

ID=66362828

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201811647847.3A Active CN109738723B (en) 2018-12-29 2018-12-29 Three-phase automatic identification method for electric energy meter

Country Status (1)

Country Link
CN (1) CN109738723B (en)

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109857975A (en) * 2018-12-29 2019-06-07 重庆邮电大学 A kind of electric energy meter platform area and three-phase automatic identification method
CN111487488A (en) * 2020-03-24 2020-08-04 国网冀北电力有限公司电力科学研究院 Intelligent station area outdoor transformer identification method based on grey correlation analysis
CN112485748A (en) * 2020-10-15 2021-03-12 国网江苏省电力有限公司南京供电分公司 Phase-to-phase judgment method for single-phase electric meter
CN112611997A (en) * 2020-12-01 2021-04-06 国网河南省电力公司电力科学研究院 Online verification method and system for hitching relation of platform area gateway table

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103116098A (en) * 2013-01-25 2013-05-22 重庆大学 Household appliance operating state identification method based on cross correlation coefficient
CN104218570A (en) * 2014-08-21 2014-12-17 国家电网公司 Method and system for online evaluating overall measuring errors of electric energy measuring device
CN107220906A (en) * 2017-05-31 2017-09-29 国网上海市电力公司 Multiple Time Scales multiplexing electric abnormality analysis method based on electricity consumption acquisition system
CN107493277A (en) * 2017-08-10 2017-12-19 福建师范大学 The online method for detecting abnormality of big data platform based on maximum information coefficient
CN108303606A (en) * 2018-01-02 2018-07-20 国网江西省电力有限公司电力科学研究院 A kind of distribution transformer capacity online evaluation method
CN108519514A (en) * 2018-04-24 2018-09-11 宁波三星医疗电气股份有限公司 Taiwan area phase recognition methods based on Pearson correlation coefficient algorithm
CN108683180A (en) * 2018-05-07 2018-10-19 国网河南省电力公司电力科学研究院 A kind of three-phase low-voltage power distribution network topology rebuilding method
CN108805457A (en) * 2018-06-19 2018-11-13 宁波迦南智能电气股份有限公司 A kind of electric energy meter taiwan area recognition methods of high accuracy

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103116098A (en) * 2013-01-25 2013-05-22 重庆大学 Household appliance operating state identification method based on cross correlation coefficient
CN104218570A (en) * 2014-08-21 2014-12-17 国家电网公司 Method and system for online evaluating overall measuring errors of electric energy measuring device
CN107220906A (en) * 2017-05-31 2017-09-29 国网上海市电力公司 Multiple Time Scales multiplexing electric abnormality analysis method based on electricity consumption acquisition system
CN107493277A (en) * 2017-08-10 2017-12-19 福建师范大学 The online method for detecting abnormality of big data platform based on maximum information coefficient
CN108303606A (en) * 2018-01-02 2018-07-20 国网江西省电力有限公司电力科学研究院 A kind of distribution transformer capacity online evaluation method
CN108519514A (en) * 2018-04-24 2018-09-11 宁波三星医疗电气股份有限公司 Taiwan area phase recognition methods based on Pearson correlation coefficient algorithm
CN108683180A (en) * 2018-05-07 2018-10-19 国网河南省电力公司电力科学研究院 A kind of three-phase low-voltage power distribution network topology rebuilding method
CN108805457A (en) * 2018-06-19 2018-11-13 宁波迦南智能电气股份有限公司 A kind of electric energy meter taiwan area recognition methods of high accuracy

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
HILA NACHLIELI等: "Measuring the Quality of Quality Measures", 《IEEE TRANSACTIONS ON IMAGE PROCESSING》 *
杨光盛等: "基于CRITIC 和理想点法的计量设备运行质量评估", 《电力系统保护与控制》 *
胡蓓等: "低压电网远程抄表效益", 《农网自动化》 *

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN109857975A (en) * 2018-12-29 2019-06-07 重庆邮电大学 A kind of electric energy meter platform area and three-phase automatic identification method
CN109857975B (en) * 2018-12-29 2023-04-07 重庆邮电大学 Electric energy meter area and three-phase automatic identification method
CN111487488A (en) * 2020-03-24 2020-08-04 国网冀北电力有限公司电力科学研究院 Intelligent station area outdoor transformer identification method based on grey correlation analysis
CN112485748A (en) * 2020-10-15 2021-03-12 国网江苏省电力有限公司南京供电分公司 Phase-to-phase judgment method for single-phase electric meter
CN112485748B (en) * 2020-10-15 2023-10-24 国网江苏省电力有限公司南京供电分公司 Single-phase ammeter phase judging method
CN112611997A (en) * 2020-12-01 2021-04-06 国网河南省电力公司电力科学研究院 Online verification method and system for hitching relation of platform area gateway table
CN112611997B (en) * 2020-12-01 2022-05-06 国网河南省电力公司电力科学研究院 Online verification method and system for hitching relation of platform area gateway table

Also Published As

Publication number Publication date
CN109738723B (en) 2021-02-09

Similar Documents

Publication Publication Date Title
CN109725219A (en) A kind of electric energy meter platform area automatic identifying method
CN109738723A (en) A kind of electric energy meter three-phase automatic identification method
CN104794206B (en) A kind of substation data QA system and method
CN111398885A (en) Intelligent electric meter operation error monitoring method combining line loss analysis
Kong et al. Online smart meter measurement error estimation based on EKF and LMRLS method
CN109857975A (en) A kind of electric energy meter platform area and three-phase automatic identification method
CN109840691B (en) Non-invasive polynomial electric quantity estimation method based on deep neural network
CN102818337A (en) Device for monitoring ground source heat pump system based on internet of things
CN107727955B (en) Transformer loss analysis and control method based on power grid line operation error remote calibration
CN103106314B (en) The sequential modelling method of probabilistic of solar photovoltaic power output power
CN109767054A (en) Efficiency cloud appraisal procedure and edge efficiency gateway based on deep neural network algorithm
CN102116857A (en) Method for checking electric quantity at power grid gate
CN108445435A (en) A kind of electric energy meter calibrating apparatus error online evaluation method
CN105959975A (en) Automatic assessment method for energy saving quantity of large-scale base station energy saving project
Caro et al. Impact of transformer correlations in state estimation using the unscented transformation
Liu et al. Distribution system state estimation with high penetration of demand response enabled loads
CN110334952A (en) A kind of distribution network planning Post-assessment Method based on the improved grey model degree of association
CN105868073A (en) Data center energy saving strategy implementation method based on time series analysis
CN111476427A (en) Low-voltage distribution area topology identification method and identification device
Ashok et al. Systematic study of data requirements and AMI capabilities for smart meter analytics
CN102856896A (en) On-line analytical method for direct-current transmission loss
CN108226664A (en) A kind of user side electric energy quality synthesis evaluation system and method
CN111027886A (en) Evaluation method of low-voltage treatment scheme considering unit cost effectiveness
CN109164407A (en) A kind of electric energy metering device field test management system based on mobile job-oriented terminal
Jin et al. An improved combined forecasting method for electric power load based on autoregressive integrated moving average model

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant