CN109613338A - A kind of low-voltage customer circuit resistance estimation method based on linear model - Google Patents

A kind of low-voltage customer circuit resistance estimation method based on linear model Download PDF

Info

Publication number
CN109613338A
CN109613338A CN201811456237.5A CN201811456237A CN109613338A CN 109613338 A CN109613338 A CN 109613338A CN 201811456237 A CN201811456237 A CN 201811456237A CN 109613338 A CN109613338 A CN 109613338A
Authority
CN
China
Prior art keywords
low
user
voltage
loop
circuit resistance
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
CN201811456237.5A
Other languages
Chinese (zh)
Other versions
CN109613338B (en
Inventor
邓士伟
傅萌
苗青
黄莉
冯燕钧
何朝伟
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.)
Jiangsu Zhi Zhen Energy Technology Co Ltd
Original Assignee
Jiangsu Zhi Zhen Energy Technology Co Ltd
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 Jiangsu Zhi Zhen Energy Technology Co Ltd filed Critical Jiangsu Zhi Zhen Energy Technology Co Ltd
Priority to CN201811456237.5A priority Critical patent/CN109613338B/en
Publication of CN109613338A publication Critical patent/CN109613338A/en
Priority to PCT/CN2019/129711 priority patent/WO2020164322A1/en
Application granted granted Critical
Publication of CN109613338B publication Critical patent/CN109613338B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01RMEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R27/00Arrangements for measuring resistance, reactance, impedance, or electric characteristics derived therefrom
    • G01R27/02Measuring real or complex resistance, reactance, impedance, or other two-pole characteristics derived therefrom, e.g. time constant
    • G01R27/08Measuring resistance by measuring both voltage and current

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Measurement Of Resistance Or Impedance (AREA)
  • Measurement And Recording Of Electrical Phenomena And Electrical Characteristics Of The Living Body (AREA)

Abstract

The low-voltage customer circuit resistance estimation method based on linear model that the invention discloses a kind of, belongs to power management techniques field.Time series data of this method based on user's intelligent electric meter collection voltages and electric current, to user loop impedance ZLIt is defined, and utilizes KVL loop-voltage equation, derive the unitary linear model of building low-voltage customer impedance loop.The estimation method of impedance loop, with this area's peak valley, usually section statistics is divided into according to choosing the data acquisition period first, is the current step moment of interval observation user using 5min within the period, and by the voltage and current data-frozen at former and later two moment of step;Then using a day data as sample, linear regression analysis is carried out, user loop impedance Z is estimatedL, the impedance loop numerical value can be used to estimate the healthy degree of aging for sentencing low-voltage distribution network route and user's exception electricity consumption behavior.

Description

A kind of low-voltage customer circuit resistance estimation method based on linear model
Technical field
The invention belongs to power management techniques field more particularly to a kind of low-voltage customer circuit resistances based on linear model Estimation method.
Background technique
With the increase of route service life and the erosion of external extreme natural environment, route can gradually aging, aging On the one hand there is the possibility of broken string in route, be more decreasing insulating after electric wire aging, is easy to produce electric leakage or short circuit is existing As.But low-voltage network route is many and diverse, and failure influence face is small, the reasons such as input-output ratio is considered, in the operation of low-voltage network In management, distribution trend is seldom calculated, and an important indicator " line loss " of low-voltage distribution network operation also mainly uses power The method of difference calculates, therefore being related to distribution network line impedance computation is always the blind area studied.How research is returned by user The anti-real-time monitoring of roadlock, finds aging circuit phenomenon in time, and carries out short circuit or open circuit fault anticipation, can effectively reduce failure Occur to improve power supply reliability.
This patent is directed to this demand, has studied a kind of low-voltage customer circuit resistance estimation method based on linear model. In addition, the monitoring by low-voltage customer impedance loop is analyzed, the abnormal electricity consumption behavior of user's stealing can be effectively found, help electric power Manager reinforces power consumption management, improves the economic benefit of enterprise, safe and reliable for electricity consumption.
Summary of the invention
In view of the above-mentioned problems, now provide a kind of low-voltage customer circuit resistance estimation method based on linear model, for pair The monitoring of low-voltage customer circuit resistance is analyzed.
Summary of the invention are as follows: a kind of low-voltage customer circuit resistance estimation method based on linear model includes the following steps:
Step 1: determining the acquisition period of two class data of voltage and current;
Step 2: determining current step reduced value ICo
Step 3: the sample data of collection voltages and electric current;
Step 4: building low-voltage customer circuit resistance model calculates low tension loop resistance.
Further, the determination of data acquisition period includes that usually section, resident are flat at large user peak in the step 1 The peak period selects the intersection period of described two users usually section.
Further, current step reduced value I is determined in the step 2CoThe step of include:
Step 2-1: analysis user's history load curve;
Step 2-2: extracting current step sequence i (k), and step quantity is m;
Step 2-3: step magnitude I corresponding to the 0.5m time series is foundCo
Step 2-4: current step reduced value I is determinedCo
Further, the acquisition of sample data includes the following steps: in the step 3
Step 3-1: with 5 minutes for interval, collection voltages and current data;
Step 3-2: judge I (t+5min)-I (t) >=ICoIf then by data-frozen;If it is not, then data are abandoned.
Further, include: the step of building low-voltage customer circuit resistance linear model in the step 5
Step 5-1: Z is definedL1=Zre+ZDA+ZA1; (1)
Step 5-2: according to power network topology, loop-voltage equation is write out
Step 5-3: formula (1) will be rewritten into the form of 1 impedance loop containing user
Step 5-4: two moment of t1 and t2, impedance expression are write out are as follows:
The impedance expression at two moment of step 5-5:t1 and t2, which subtracts each other, takes difference are as follows:
Step 5-6: in formula,
Wherein, δ Z1Influence mainly due to power supply point voltage fluctuation to 1 end voltage of user, δ Z2Mainly due to local Influence of the low-voltage customer load fluctuation to 1 end voltage of user, this two parts is stochastic variable, but meets and be just distributed very much;
Then, further formula (6) is simplified to
Step 5-7: (9) formula is rewritten into U1(t1)-U1(t2)=ZL1(I1(t2)-I1(t1))+δZ' (10)
Step 5-8: with linear regression model (LRM) comparative analysis:
Linear regression model (LRM) are as follows: yi=alpha+beta xii (11)
Wherein, xi yiFor sample size, β is regression coefficient, and α is regression constant item;εiDisturbance, each disturbance quantity it Between it is mutually indepedent, and obey and be just distributed very much;
δ Z' is to meet the stochastic variable being just distributed very much, with the ε in linear regression model (LRM)iMeaning is consistent, by residual error and remains The distribution of remaining mean square deviation MSe detection fitting effect and δ Z';Formula (10) and formula (11) are with uniformity.
Further, the circuit resistance calculating in the step 4 includes the following steps:
Step 6-1: the one day sample data that will acquire carries out simple linear regression analysis;
Step 6-2: residual mean square difference is fitted;
Step 6-3: by the value of regression coefficient β, the loop resistance values Z of the user is estimatedL,
Step 6-4: the detection of model confidence level is carried out with P value.
The utility model has the advantages that a kind of low-voltage customer circuit resistance estimation method based on linear model of the invention, passes through low pressure The monitoring of user loop impedance is analyzed, and can effectively find the abnormal electricity consumption behavior of user's stealing, and electrical management person is helped to reinforce using Fulgurite reason, improves the economic benefit of enterprise, safe and reliable for electricity consumption.
Detailed description of the invention
Fig. 1 is a kind of circuit model figure of low-voltage customer impedance loop of the present invention;
Fig. 2 is a kind of low-voltage customer impedance loop estimation method flow chart of the present invention;
Fig. 3 be in the present invention data acquisition period determine schematic diagram;
Fig. 4 is the sample data list that low-voltage customer of the present invention freezes;
Fig. 5 is low tension loop impedance computation result figure of the present invention.
Specific embodiment
The technical means disclosed in the embodiments of the present invention is not limited to the technical means disclosed in the above technical means, and further includes Technical solution consisting of any combination of the above technical features.With reference to the accompanying drawings and detailed description, it furthers elucidate The present invention.It should be understood that following specific embodiments are merely to illustrate the present invention, rather than limit the scope of the invention.
Modeling process is as follows: low-voltage customer impedance loop ZL, it is exported to what user port was passed through from Circuit Fault on Secondary Transformer The sum of all line impedances and Circuit Fault on Secondary Transformer equivalent impedance, as shown in Figure 1, its impedance loop are as follows:
ZL1=Zre+ZDA+ZA1 (1)
Low-voltage customer impedance loop linear model, the time series number based on user's intelligent electric meter collection voltages and electric current According to user loop impedance ZLIt is defined, wherein ZL1For the low tension loop resistance of user 1, ZreIt is returned for the low pressure of re in Fig. 1 Road resistance, ZDAFor the low tension loop resistance of DA in Fig. 1, ZA1For the low tension loop resistance of A1 in Fig. 1.And utilize KVL loop voltage Equation derives the unitary linear model of building low-voltage customer impedance loop,
The voltage and current time series data of the user of acquisition, Ui(t)、IiIt (t) is each moment user voltage, electric current Virtual value, rather than instantaneous value.
With the impedance loop Z of low-voltage customer 1L1For, derivation process is as follows:
1) according to power network topology, loop-voltage equation is write out;
2) formula 1 is rewritten into the form of 1 impedance loop containing user:
3) two moment of t1 and t2, impedance expression are as follows:
4) impedance expression at two moment of t1 and t2, which subtracts each other, takes difference are as follows:
The model of formula 7 is the impedance loop computation model of user 1, in formula,
Wherein, δ Z1Influence mainly due to power supply point voltage fluctuation to 1 end voltage of user, δ Z2Mainly due to local Influence of the low-voltage customer load fluctuation to 1 end voltage of user, this two parts is stochastic variable, but meets and be just distributed very much.
5) further by model simplification at:
In formula, ZL1For low-voltage customer impedance loop, for route, Z has stability in a period of time, usually fixed Value.δ Z is δ Z1With δ Z2Synthesis, i.e. independent random caused by power supply point voltage fluctuation and local low-voltage customer load fluctuation becomes Amount, but meet and be just distributed very much.
If 6) two moment of t1 and t2, other equal and local low-voltage customer loads of power supply point voltage are constant, then:Since the voltage and current at 1 both ends of user is the known quantity that can be measured, so this part It is computable determining amount.
As shown in Fig. 2, the low-voltage customer circuit resistance estimation method based on linear model comprising the steps of:
1) data are chosen and acquires the period, united in conjunction with the usually division of section of this area's peak valley and this season user power utilization situation Meter chooses the electricity consumption metastable peak period peaceful period;
2) user's current step reduced value ICoDetermination, transfer user's recent history load curve, extract the user's Current step sequence I (k) determines the current step reduced value I of the user using the step for covering the user 50% as standardCo
3) user's current step moment is chosen, acquires user port electricity by interval of 5min within the period that step 1 determines Pressure, current data, and by current difference I (the t+5min)-I (t) and I at two moment of front and backCoIt compares, if I (t+5min)-I (t) >= ICo, then the voltage and current data at former and later two moment of step are freezed;
4) data for freezing one day select one-variable linear regression method to carry out impedance analysis as sample.
5) the loop resistance values Z that regression coefficient estimates the user is chosenL, and the inspection of model confidence level is carried out with P value It surveys, detects fitting effect using residual mean square difference MSe.
Further, the determination of data acquisition period, in this area on the basis of the peak valley usually division of section, choosing should The peak of regional electricity consumption, usually section avoid sharp period and paddy period, and main cause is peak, usually the power load distributing of section is concentrated, and is in The maximum probability concentrated area of power load distributing;And the user power utilization randomness of paddy, sharp period is strong, is in small probability distributed area.
Further, the determination at current step moment sets user's electricity based on user's recent history load curve Flow step reduced value ICo, the electric appliance of mainly user is different, if setting reduced value according to universal experience, is easy to cause part User's sample size is insufficient;In addition, being even more that can not detect for undercurrent stealing user.
Low-voltage customer impedance loop estimation method uses one-variable linear regression method,
1) linear regression model (LRM) are as follows:
yi=alpha+beta xii (9)
Wherein, xi yiFor sample size, β is regression coefficient, and α is regression constant item;εiDisturbance, each disturbance quantity it Between it is mutually indepedent, and obey and be just distributed very much.
2) formula 8 is rewritten into following form,
U1(t1)-U1(t2)=ZL1(I1(t2)-I1(t1))+δZ' (10)
3) contrast 8 with formula 9, two models are with uniformity, and δ Z' is to meet the stochastic variable being just distributed very much, and linear ε in regression modeliMeaning is consistent, detects fitting effect and the distribution of δ Z' by residual error and residual mean square difference MSe.
4) value for passing through regression coefficient β, estimates the loop resistance values Z of the userL, and model confidence water is carried out with P value Flat detection.
Embodiment 1:
Step 1: the determination of data acquisition period: data are chosen and acquire the period, in conjunction with the division of this area's peak valley usually section It is counted with this season user power utilization situation, chooses the electricity consumption metastable peak period peaceful period;As shown in figure 3, for Anhui Area is the flat Time segments division of peak valley implementing time-of-use tariffs and carrying out, which is based on historical statistical data, reflects Social power load distributing situation takes peak, usual friendship collection from the Time segments division and resident's Time segments division of large user, and as target data acquires Period.
Step 2: current step reduced value I is determinedCo:User's current step reduced value ICoDetermination, it is recent to transfer the user Historical load curve extracts the current step sequence I (k) of the user, and using the step for covering the user 50% as standard, determining should The current step reduced value I of userCo;In example, powerful device is more in target analysis user, determines current step amount ICo For 8A.
Step 3: the sample data of collection voltages and electric current: choosing user's current step moment, when step 1 determines It using 5min is interval acquisition user port voltage, current data in section, and by current difference I (the t+5min)-I at two moment of front and back (t) and ICoIt compares, if I (t+5min)-I (t) >=ICo, then the voltage and current data at former and later two moment of step are frozen Knot;
Step 4: building low-voltage customer circuit resistance model, calculate low tension loop resistance: the data that one day is freezed as Sample selects one-variable linear regression method to carry out impedance analysis.To target analysis user, freeze sample data, wherein usually section 12 groups of data, 18 groups of data of peak period, are shown in attached drawing 4.Choose the loop resistance values Z that regression coefficient estimates the userL, and with P Value carries out the detection of model confidence level, detects fitting effect using residual mean square difference MSe.In example, user loop impedometer Calculation result is 0.065 Europe, and the data and actual circuit impedance coincide, and residual mean square difference MSe is 0.44, and fitting effect is ideal.It sets Believe that the confidence interval that level is 99% is (0.049,0.082).

Claims (6)

1. a kind of low-voltage customer circuit resistance estimation method based on linear model, it is characterised in that:
Include the following steps:
Step 1: determining the acquisition period of two class data of voltage and current;
Step 2: determining current step reduced value ICo
Step 3: the sample data of collection voltages and electric current;
Step 4: building low-voltage customer circuit resistance model calculates low tension loop resistance.
2. the low-voltage customer circuit resistance estimation method according to claim 1 based on linear model, it is characterised in that: the step The determination of data acquisition period includes large user peak usually section, resident's flat peak period in rapid 1, selects described two users flat The intersection period of period.
3. the low-voltage customer circuit resistance estimation method according to claim 1 based on linear model, it is characterised in that: the step Current step reduced value I is determined in rapid 2CoThe step of include:
Step 2-1: analysis user's history load curve;
Step 2-2: extracting current step sequence i (k), and step quantity is m;
Step 2-3: step magnitude I corresponding to the 0.5m time series is foundCo
Step 2-4: current step reduced value I is determinedCo
4. the low-voltage customer circuit resistance estimation method according to claim 3 based on linear model, it is characterised in that:
The acquisition of sample data includes the following steps: in the step 3
Step 3-1: with 5 minutes for interval, collection voltages and current data;
Step 3-2: judge I (t+5min)-I (t) >=ICoIf then by data-frozen;If it is not, then data are abandoned.
5. the low-voltage customer circuit resistance estimation method according to claim 1 based on linear model: it is characterized by: institute Stating the step of low-voltage customer circuit resistance linear model is constructed in step 5 includes:
Step 5-1: Z is definedL1=Zre+ZDA+ZA1; (1)
Step 5-2: according to power network topology, loop-voltage equation is write out
Step 5-3: formula (1) will be rewritten into the form of 1 impedance loop containing user
Step 5-4: two moment of t1 and t2, impedance expression are write out are as follows:
The impedance expression at two moment of step 5-5:t1 and t2, which subtracts each other, takes difference are as follows:
Step 5-6: in formula,
Wherein, δ Z1Influence mainly due to power supply point voltage fluctuation to 1 end voltage of user, δ Z2Mainly due to local low pressure Customer charge fluctuates the influence to 1 end voltage of user, this two parts is stochastic variable, but meets and be just distributed very much;
Then, further formula (6) is simplified to
Step 5-7: (9) formula is rewritten into U1(t1)-U1(t2)=ZL1(I1(t2)-I1(t1))+δZ' (10)
Step 5-8: with linear regression model (LRM) comparative analysis:
Linear regression model (LRM) are as follows: yi=alpha+beta xii (11)
Wherein, xi yiFor sample size, β is regression coefficient, and α is regression constant item;εiIt is Disturbance, phase between each disturbance quantity It is mutually independent, and obey and be just distributed very much;
δ Z' is to meet the stochastic variable being just distributed very much, with the ε in linear regression model (LRM)iMeaning is consistent, equal by residual error and residue Variance MSe detects fitting effect and the distribution of δ Z';Formula (10) and formula (11) are with uniformity.
6. the low-voltage customer circuit resistance estimation method according to claim 5 based on linear model, it is characterised in that: Circuit resistance calculating in the step 4 includes the following steps:
Step 6-1: the one day sample data that will acquire carries out simple linear regression analysis;
Step 6-2: residual mean square difference is fitted;
Step 6-3: by the value of regression coefficient β, the loop resistance values Z of the user is estimatedL,
Step 6-4: the detection of model confidence level is carried out with P value.
CN201811456237.5A 2019-02-12 2019-02-12 Low-voltage user loop impedance estimation method based on unitary model Active CN109613338B (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN201811456237.5A CN109613338B (en) 2019-02-12 2019-02-12 Low-voltage user loop impedance estimation method based on unitary model
PCT/CN2019/129711 WO2020164322A1 (en) 2019-02-12 2019-12-30 Unigram model-based low-voltage user loop impedance estimation method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201811456237.5A CN109613338B (en) 2019-02-12 2019-02-12 Low-voltage user loop impedance estimation method based on unitary model

Publications (2)

Publication Number Publication Date
CN109613338A true CN109613338A (en) 2019-04-12
CN109613338B CN109613338B (en) 2021-03-16

Family

ID=66006688

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201811456237.5A Active CN109613338B (en) 2019-02-12 2019-02-12 Low-voltage user loop impedance estimation method based on unitary model

Country Status (2)

Country Link
CN (1) CN109613338B (en)
WO (1) WO2020164322A1 (en)

Cited By (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111060750A (en) * 2019-12-20 2020-04-24 天津大学 Method for estimating impedance of power system equivalent system
CN111062176A (en) * 2019-12-09 2020-04-24 国网山西省电力公司长治供电公司 Low-voltage user loop impedance binary linear model construction and solving method
CN111208351A (en) * 2020-01-17 2020-05-29 北京市腾河电子技术有限公司 Method for calculating power supply line impedance based on load jump and storage medium
WO2020164322A1 (en) * 2019-02-12 2020-08-20 江苏智臻能源科技有限公司 Unigram model-based low-voltage user loop impedance estimation method
CN111610371A (en) * 2020-05-14 2020-09-01 国网河北省电力有限公司电力科学研究院 Real-time calculation method for distribution room impedance
CN111984925A (en) * 2020-07-29 2020-11-24 江苏方天电力技术有限公司 Circuit abnormity positioning method based on loop impedance, storage medium and computing equipment
CN112560239A (en) * 2020-12-03 2021-03-26 广东电网有限责任公司云浮供电局 Method and system for calculating line impedance of transformer area and computer readable storage medium

Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104052053A (en) * 2014-06-20 2014-09-17 国家电网公司 Power distribution network double-end line segment impedance analysis method based on unary linear regression model
CN106066451A (en) * 2016-08-01 2016-11-02 西安工程大学 A kind of T-type line based on longitudinal impedance protection computational methods
CN106154040A (en) * 2015-03-24 2016-11-23 国家电网公司 One is used for calculating electrical network single-point equivalent time Equivalent Harmonic impedance methodologies
CN109164319A (en) * 2018-08-31 2019-01-08 深圳供电局有限公司 Method for judging abnormal electricity utilization of building user
CN109190242A (en) * 2018-08-31 2019-01-11 深圳供电局有限公司 Impedance estimation method for line of service segment
CN109325622A (en) * 2018-09-26 2019-02-12 巢湖学院 A kind of method of Load Prediction In Power Systems

Family Cites Families (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR102309483B1 (en) * 2015-04-01 2021-10-08 주식회사 히타치엘지 데이터 스토리지 코리아 Apparatus for detecting whether power is supplied abnormally
KR101751310B1 (en) * 2015-12-23 2017-06-28 만도헬라일렉트로닉스(주) Circuit Fault Detection System And Method Thereof
CN107167662A (en) * 2017-06-01 2017-09-15 宁波迦南智能电气股份有限公司 A kind of method that user loop impedance is measured by intelligent electric meter
CN207964994U (en) * 2018-03-28 2018-10-12 国网上海市电力公司 Grounding net of transformer substation health status detection device
CN109613338B (en) * 2019-02-12 2021-03-16 江苏智臻能源科技有限公司 Low-voltage user loop impedance estimation method based on unitary model

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN104052053A (en) * 2014-06-20 2014-09-17 国家电网公司 Power distribution network double-end line segment impedance analysis method based on unary linear regression model
CN106154040A (en) * 2015-03-24 2016-11-23 国家电网公司 One is used for calculating electrical network single-point equivalent time Equivalent Harmonic impedance methodologies
CN106066451A (en) * 2016-08-01 2016-11-02 西安工程大学 A kind of T-type line based on longitudinal impedance protection computational methods
CN109164319A (en) * 2018-08-31 2019-01-08 深圳供电局有限公司 Method for judging abnormal electricity utilization of building user
CN109190242A (en) * 2018-08-31 2019-01-11 深圳供电局有限公司 Impedance estimation method for line of service segment
CN109325622A (en) * 2018-09-26 2019-02-12 巢湖学院 A kind of method of Load Prediction In Power Systems

Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2020164322A1 (en) * 2019-02-12 2020-08-20 江苏智臻能源科技有限公司 Unigram model-based low-voltage user loop impedance estimation method
CN111062176A (en) * 2019-12-09 2020-04-24 国网山西省电力公司长治供电公司 Low-voltage user loop impedance binary linear model construction and solving method
CN111062176B (en) * 2019-12-09 2023-09-22 国网山西省电力公司长治供电公司 Low-voltage user loop impedance binary linear model construction and solving method
CN111060750A (en) * 2019-12-20 2020-04-24 天津大学 Method for estimating impedance of power system equivalent system
CN111208351A (en) * 2020-01-17 2020-05-29 北京市腾河电子技术有限公司 Method for calculating power supply line impedance based on load jump and storage medium
CN111610371A (en) * 2020-05-14 2020-09-01 国网河北省电力有限公司电力科学研究院 Real-time calculation method for distribution room impedance
CN111984925A (en) * 2020-07-29 2020-11-24 江苏方天电力技术有限公司 Circuit abnormity positioning method based on loop impedance, storage medium and computing equipment
CN111984925B (en) * 2020-07-29 2024-03-12 江苏方天电力技术有限公司 Circuit abnormality positioning method based on loop impedance, storage medium and computing device
CN112560239A (en) * 2020-12-03 2021-03-26 广东电网有限责任公司云浮供电局 Method and system for calculating line impedance of transformer area and computer readable storage medium

Also Published As

Publication number Publication date
WO2020164322A1 (en) 2020-08-20
CN109613338B (en) 2021-03-16

Similar Documents

Publication Publication Date Title
CN109613338A (en) A kind of low-voltage customer circuit resistance estimation method based on linear model
CN111062176B (en) Low-voltage user loop impedance binary linear model construction and solving method
WO2022110558A1 (en) Smart electricity meter malfunction early warning method and device
US9945889B2 (en) Method for detecting power theft in a power distribution system
CN103390254B (en) A kind of low-voltage platform area line loss Integrated Assessment On The Level method
Della Giustina et al. Electrical distribution system state estimation: measurement issues and challenges
Nikovski et al. Smart meter data analysis for power theft detection
CN109377008A (en) The integrated energy system methods of risk assessment of electro thermal coupling
JP5727949B2 (en) Current waveform identification device
CN105975745B (en) A kind of pre- judgment method of low-voltage dynamic based on extendible capacity ability
Ballanti et al. Initial assessment of voltage-led demand response from UK residential loads
CN106127047A (en) A kind of power system malicious data detection method based on Jensen Shannon distance
CN113641723A (en) Electricity stealing prediction method based on line impedance parameter estimation
CN107069718A (en) The low-voltage distribution network line loss calculation method influenceed based on three-phase imbalance on line loss
CN109164319A (en) Method for judging abnormal electricity utilization of building user
CN107257130A (en) The low-voltage network loss computing method of decoupling is measured based on region
Liu et al. A methodology to analyze conservation voltage reduction performance using field test data
Baran Branch current based state estimation for distribution system monitoring
Leinakse et al. Estimation of exponential and zip load model of aggregated load with distributed generation
Duong et al. A method for real time voltage stability monitoring in sub-transmission networks
Soliman et al. Power system voltage stability margin identification using local measurements
CN111796143B (en) Energy-saving metering method for energy-saving equipment of power distribution and utilization system
Tariq et al. Real time electricity theft detection in microgrids through wireless sensor networks
Jie et al. Non-Intrusive Load Decomposition Based on Graph Convolutional Network
US9817419B2 (en) Method for determining an individual power consumption

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