CN109613338B - Low-voltage user loop impedance estimation method based on unitary model - Google Patents

Low-voltage user loop impedance estimation method based on unitary model Download PDF

Info

Publication number
CN109613338B
CN109613338B CN201811456237.5A CN201811456237A CN109613338B CN 109613338 B CN109613338 B CN 109613338B CN 201811456237 A CN201811456237 A CN 201811456237A CN 109613338 B CN109613338 B CN 109613338B
Authority
CN
China
Prior art keywords
voltage
user
low
impedance
loop
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.)
Active
Application number
CN201811456237.5A
Other languages
Chinese (zh)
Other versions
CN109613338A (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 Zhizhen Energy Technology Co ltd
Original Assignee
Jiangsu Zhizhen 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 Zhizhen Energy Technology Co ltd filed Critical Jiangsu Zhizhen 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

Images

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R27/00—Arrangements for measuring resistance, reactance, impedance, or electric characteristics derived therefrom
    • G01R27/02—Measuring real or complex resistance, reactance, impedance, or other two-pole characteristics derived therefrom, e.g. time constant
    • G01R27/08—Measuring 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 invention discloses a unitary model-based low-voltage user loop impedance estimation methodBelonging to the technical field of power management. The method is based on time sequence data of voltage and current collected by a user intelligent ammeter, and the impedance Z of a user loop is measuredLAnd defining, and deducing and constructing a unary linear model of the impedance of the low-voltage user circuit by using a KVL circuit voltage equation. The method for estimating the loop impedance comprises the steps of firstly, statistically dividing the peak-valley level time period of the area into a data acquisition time period according to the selected data, observing the current step time of a user at intervals of 5min in the time period, and freezing voltage and current data at two times before and after the step; then, linear regression analysis is carried out by taking the data of one day as a sample to estimate the impedance Z of the user circuitLThe loop impedance value can be used for estimating the health aging degree of the low-voltage distribution network line and the abnormal electricity utilization behavior of the user.

Description

Low-voltage user loop impedance estimation method based on unitary model
Technical Field
The invention belongs to the technical field of power management, and particularly relates to a low-voltage user loop impedance estimation method based on a unitary model.
Background
With the increase of the service life of the line and the corrosion of the external severe natural environment, the line can be aged gradually, on one hand, the aged line has the possibility of wire breakage, and more after the wire is aged, the insulation performance is reduced, and the phenomenon of electric leakage or short circuit is easy to generate. However, the low-voltage distribution network has complicated lines and small fault influence surface, the distribution network load flow is rarely calculated in the operation management of the low-voltage distribution network by considering the input-output ratio and other reasons, and an important index line loss of the operation of the low-voltage distribution network is mainly calculated by adopting a power difference method, so that the calculation related to the impedance of the distribution network lines is a blind area of research all the time. The research on how to find the line aging phenomenon in time through the real-time monitoring of the user loop impedance and carry out the short-circuit or open-circuit fault prejudgment can effectively reduce the occurrence of faults and improve the power supply reliability.
In response to this need, the present patent researches a low-voltage subscriber loop impedance estimation method based on a unitary model. In addition, through the monitoring and analysis of the low-voltage user loop impedance, the abnormal electricity utilization behavior of electricity stealing of the user can be effectively found, an electricity manager is helped to strengthen electricity utilization management, the economic benefit of an enterprise is improved, and safe and reliable electricity supply and utilization are realized.
Disclosure of Invention
In view of the above problems, a unitary model-based method for estimating the impedance of the low-voltage subscriber loop is provided, which is used for monitoring and analyzing the impedance of the low-voltage subscriber loop.
The invention comprises the following steps: a low-voltage user loop impedance estimation method based on a unitary model comprises the following steps:
step 1: determining the acquisition time period of the voltage and current data;
step 2: determining a current step contrast value ICo；
And step 3: collecting sample data of voltage and current;
and 4, step 4: and constructing a low-voltage user loop resistance model and calculating the low-voltage loop resistance.
Furthermore, the determination of the data acquisition time period in step 1 includes a peak-to-average time period of a large user and a peak-to-average time period of a residential user, and an intersection time period of the two user average time periods is selected.
Furthermore, the step 2 determines the contrast value I of the current stepCoComprises the following steps:
step 2-1: analyzing a user historical load curve;
step 2-2: extracting a current step sequence i (k), wherein the step number is m;
step 2-3: find the step value I corresponding to the 0.5m time seriesCo；
Step 2-4: determining a current step contrast value ICo；
Further, the acquiring of the sample data in step 3 includes the following steps:
step 3-1: collecting voltage and current data at intervals of 5 minutes;
step 3-2: judgment I (t +5min) -I (t)>＝ICoIf yes, freezing the data; if not, the data is discarded.
Further, the step of constructing the low-voltage user circuit impedance unary model in step 5 includes:
step 5-1: definition of ZL1＝Zre+ZDA+ZA1； (1)
Step 5-2: according to the power grid topology, a loop voltage equation is written
Figure BDA0001887792670000021
Step 5-3: the formula (1) is rewritten into a form containing the loop impedance of the user 1
Figure BDA0001887792670000022
Step 5-4: writing two times t1 and t2, the impedance expression is:
Figure BDA0001887792670000023
Figure BDA0001887792670000024
step 5-5: subtracting the impedance expressions at the two moments t1 and t2 to obtain the difference:
Figure BDA0001887792670000025
Figure BDA0001887792670000026
in the step 5-6, in the formula,
Figure BDA0001887792670000027
Figure BDA0001887792670000028
wherein, δ Z1Mainly due to the influence of the voltage fluctuation of the power supply point on the voltage of the terminal of the user 1, delta Z2The method is mainly characterized in that the two parts are random variables but are in accordance with positive distribution due to the influence of local low-voltage user load fluctuation on the terminal voltage of a user 1;
thus, the formula (6) is further simplified to
Figure BDA0001887792670000031
And 5-7: rewriting formula (9) to U1(t1)-U1(t2)＝ZL1(I1(t2)-I1(t1))+δZ' (10)
And 5-8: analysis by comparison with a linear regression model:
the linear regression model is: y isi＝α+βxi+εi (11)
Wherein x isi yiTaking the sample amount, beta is a regression coefficient, and alpha is a regression constant term; epsiloniThe disturbance values are random disturbance items, are independent from one another and are subjected to positive distribution;
delta Z' is a random variable conforming to the positive Tai distribution, and epsilon in the linear regression modeliThe meanings are consistent, the fitting effect and the distribution state of the delta Z' are detected through residual errors and residual mean square error MSe; the expressions (10) and (11) have consistency.
Further, the loop impedance calculation in step 4 includes the following steps:
step 6-1: performing unary linear regression analysis on the acquired sample data of one day;
step 6-2: fitting the residual mean square error;
step 6-3: estimating the loop impedance value Z of the user by the value of the regression coefficient betaL，
Step 6-4: model confidence level detection was performed with P-value.
Has the advantages that: according to the low-voltage user loop impedance estimation method based on the unitary model, disclosed by the invention, through monitoring and analyzing the low-voltage user loop impedance, the abnormal electricity utilization behavior of electricity stealing of a user can be effectively found, an electricity manager is helped to strengthen electricity utilization management, the economic benefit of an enterprise is improved, and safe and reliable electricity supply and utilization are realized.
Drawings
FIG. 1 is a circuit model diagram of a low-voltage subscriber loop impedance of the present invention;
FIG. 2 is a flow chart of a method for estimating the impedance of a low-voltage subscriber loop according to the present invention;
FIG. 3 is a schematic diagram of data acquisition period determination in the present invention;
FIG. 4 is a sample data list of the invention frozen by a low voltage user;
fig. 5 is a diagram of the low-voltage loop impedance calculation result of the present invention.
Detailed Description
The technical means disclosed by the scheme of the invention are not limited to the technical means disclosed by the technical means, and the technical scheme also comprises the technical scheme formed by any combination of the technical characteristics. The invention is further elucidated with reference to the drawings and the detailed description. It should be understood that the following detailed description is illustrative of the invention only and is not intended to limit the scope of the invention.
The modeling process is as follows: low voltage subscriber loop impedance ZLAs shown in fig. 1, the sum of all line impedances passing from the outlet of the secondary side of the transformer to the subscriber port and the equivalent impedance of the secondary side of the transformer has the following loop impedances:
ZL1＝Zre+ZDA+ZA1 (1)
the unitary model of the low-voltage user loop impedance is based on the time sequence data of the voltage and the current collected by the user intelligent ammeter, and the user loop impedance Z is obtainedLIs defined wherein Z isL1Low voltage loop impedance, Z, for User 1reIs the low voltage loop impedance of re in FIG. 1, ZDALow voltage return for DA in fig. 1Road resistance, ZA1The low-pressure loop impedance of A1 in FIG. 1. And deducing and constructing a unary linear model of the low-voltage user loop impedance by using a KVL loop voltage equation,
collected voltage and current time series data, U, of a useri(t)、IiAnd (t) is the effective value of the user voltage and current at each moment, not the instantaneous value.
With loop impedance Z of low-voltage subscriber 1L1For example, the derivation process is as follows:
1) writing a loop voltage equation according to the power grid topology;
Figure BDA0001887792670000041
2) equation 1 is rewritten to a form that contains the user 1 loop impedance:
Figure BDA0001887792670000042
3) at two times t1 and t2, the impedance expression is:
Figure BDA0001887792670000043
Figure BDA0001887792670000044
4) subtracting the impedance expressions at the two moments t1 and t2 to obtain the difference:
Figure BDA0001887792670000051
Figure BDA0001887792670000052
the model of equation 7 is a model for calculating the loop impedance of user 1, where,
Figure BDA0001887792670000053
Figure BDA0001887792670000054
wherein, δ Z1Mainly due to the influence of the voltage fluctuation of the power supply point on the voltage of the terminal of the user 1, delta Z2The two parts are random variables but are in line with positive distribution mainly due to the influence of local low-voltage user load fluctuation on the terminal voltage of the user 1.
5) The model is further simplified to:
Figure BDA0001887792670000055
in the formula, ZL1For low-voltage subscriber loop impedance, Z has stability, usually a constant value, for the line over time. δ Z is δ Z1And δ Z2The composition of (1), namely independent random variables caused by voltage fluctuation of a power supply point and local low-voltage user load fluctuation, conforms to positive distribution.
6) If the voltages of the power supply points are equal at two moments t1 and t2 and the loads of other local low-voltage users are not changed, then:
Figure BDA0001887792670000056
this is a calculable deterministic quantity since the voltage current across the subscriber 1 is a known quantity that can be measured.
As shown in fig. 2, the method for estimating the resistance of the low voltage subscriber loop based on the unitary model includes the following steps:
1) selecting a data acquisition time period, and selecting a peak time period and a flat time period with relatively stable power consumption by combining the division of the peak-valley flat time period of the region and the statistics of the power consumption condition of the users in the season;
2) user current step contrast value ICoTo retrieve the recent history of the userA load curve, extracting the current step sequence I (k) of the user, determining the current step comparison value I (k) of the user by taking the step covering 50% of the user as a standardCo；
3) Selecting a user current step moment, collecting voltage and current data of a user port at intervals of 5min within a time period determined in the step 1, and comparing current differences I (t +5min) -I (t) and I (t) of the two momentsCoComparison, if I (t +5min) -I (t)>＝ICoFreezing the voltage and current data at two moments before and after the step;
4) and taking the frozen data in one day as a sample, and selecting a unary linear regression method for impedance analysis.
5) Selecting regression coefficient to estimate loop impedance value Z of the userLAnd performing model confidence level detection by using the P value, and detecting the fitting effect by using the residual mean square error MSe.
Furthermore, the data acquisition time period is determined, on the basis of the division of the peak-valley-average time period of the area, the peak and ordinary time periods of the electricity consumption of the area are selected, and the peak time period and the ordinary time period are avoided, wherein the main reason is that the load distribution of the peak time period and the ordinary time period is concentrated and is in a large probability concentrated area of the load distribution; and the electricity utilization randomness of the users in the valley and peak periods is strong, and the users are in a small probability distribution interval.
Further, the current step time is determined, and a user current step comparison value I is set based on the recent historical load curve of the userCoMainly, the electrical appliances of users are different, and if a contrast value is set according to general experience, the sample size of part of users is easy to be insufficient; in addition, it is not detectable for users with power theft.
The low-voltage user loop impedance estimation method adopts a unary linear regression method,
1) the linear regression model is:
yi＝α+βxi+εi (9)
wherein x isi yiTaking the sample amount, beta is a regression coefficient, and alpha is a regression constant term; epsiloniAre random disturbance terms, the disturbance quantities are independent of each other and obey positive distribution.
2) The formula 8 is rewritten into the following form,
U1(t1)-U1(t2)＝ZL1(I1(t2)-I1(t1))+δZ' (10)
3) comparing equation 8 with equation 9, the two models have consistency, δ Z' is a random variable conforming to the positive-Tai distribution, and ε in the linear regression modeliThe meaning is consistent, the fitting effect is detected by the residual error and the residual mean square error MSe, and the distribution state of the delta Z' is detected.
4) Estimating the loop impedance value Z of the user by the value of the regression coefficient betaLAnd performing model confidence level detection by using the P value.
Example 1:
the method comprises the following steps: determination of data acquisition period: selecting a data acquisition time period, and selecting a peak time period and a flat time period with relatively stable power consumption by combining the division of the peak-valley flat time period of the region and the statistics of the power consumption condition of the users in the season; as shown in fig. 3, peak-valley-level time interval division is performed for implementing peak-valley electricity prices in the Anhui region, the time interval division is based on historical statistical data, the social load distribution condition is reflected, and a peak-level intersection set is taken from the time interval division and the resident time interval division of a large user, namely, a target data acquisition time interval.
Step two: determining a current step contrast value ICo：User current step contrast value ICoDetermining, namely calling a recent historical load curve of the user, extracting a current step sequence I (k) of the user, and determining a current step comparison value I of the user by taking a step covering 50% of the user as a standardCo(ii) a In the calculation example, the target analysis user has more high-power equipment, and the current step quantity I is determinedCoIs 8A.
Step three: collecting sample data of voltage and current: selecting a user current step moment, collecting voltage and current data of a user port at intervals of 5min within a time period determined in the step 1, and comparing current differences I (t +5min) -I (t) and I (t) of the two momentsCoComparison, if I (t +5min) -I (t)>＝ICoFreezing the voltage and current data at two moments before and after the step;
step four:constructing a low-voltage user loop resistance model, and calculating the low-voltage loop resistance: and taking the frozen data in one day as a sample, and selecting a unary linear regression method for impedance analysis. For the target analysis user, sample data is frozen, with 12 sets of data for flat periods and 18 sets of data for peak periods, see fig. 4. Selecting regression coefficient to estimate loop impedance value Z of the userLAnd performing model confidence level detection by using the P value, and detecting the fitting effect by using the residual mean square error MSe. In the example, the calculation result of the user loop impedance is 0.065 ohms, the data is consistent with the actual circuit impedance, the residual mean square error MSe is 0.44, and the fitting effect is ideal. The confidence interval with a confidence level of 99% was (0.049, 0.082).

Claims (3)

1. A low-voltage user loop impedance estimation method based on a unitary model is characterized by comprising the following steps: the method comprises the following steps:
step 1: determining the acquisition time period of the voltage and current data;
step 2: determining a current step magnitude ICo；
Step 2-1: analyzing a user historical load curve;
step 2-2: extracting a current step sequence i (k), wherein the step number is m;
step 2-3: find the step value I corresponding to the 0.5m time seriesCo；
Step 2-4: determining a step magnitude I corresponding to the current stepCo；
And step 3: collecting sample data of voltage and current;
step 3-1: collecting voltage and current data at intervals of 5 minutes;
step 3-2: judgment I (t +5min) -I (t)>＝ICoIf yes, freezing the data; if not, discarding the data;
and 4, step 4: constructing a low-voltage user loop resistance model, and calculating the low-voltage loop resistance;
the method for constructing the low-voltage user circuit impedance unary model comprises the following steps:
step 5-1: definition of ZL1＝Zre+ZDA+ZA1； (1)
Figure FDA0002840275650000011
In the formula, ZL1Low voltage loop impedance, Z, for subscriber 1reLow-voltage loop resistance, Z, of re at the output of the low-voltage transformerDALow voltage loop impedance from point D to A, ZA1The resistance of a low-voltage loop from the point A to the point 1 is realized; u shapei(t)、Ii(t) is the effective value of the user voltage and current at each moment;
step 5-2: writing a loop voltage equation according to the power grid topology;
step 5-3: the formula (1) is rewritten into a form containing the loop impedance of the subscriber 1,
Figure FDA0002840275650000012
step 5-4: writing two times t1 and t2, the impedance expression is:
Figure FDA0002840275650000013
Figure FDA0002840275650000014
step 5-5: subtracting the impedance expressions at the two moments t1 and t2 to obtain the difference:
Figure FDA0002840275650000015
Figure FDA0002840275650000021
and 5-6: in the formula
Figure FDA0002840275650000022
Figure FDA0002840275650000023
Wherein, δ Z1Is the influence of the voltage fluctuation of the power supply point on the voltage of the subscriber 1 terminal, deltaZ2The influence of the load fluctuation of a local low-voltage user on the terminal voltage of the user 1 is represented by random variables, but the random variables are in accordance with positive distribution;
thus, the formula (6) is further simplified to
Figure FDA0002840275650000024
And 5-7: rewriting formula (9) to U1(t1)-U1(t2)＝ZL1(I1(t2)-I1(t1))+δZ'(10)
And 5-8: analysis by comparison with a linear regression model: the linear regression model is: y isi＝α+βxi+εi(11)
Wherein x isi，yiTaking the sample amount, beta is a regression coefficient, and alpha is a regression constant term; epsiloniThe disturbance values are random disturbance items, are independent from one another and are subjected to positive distribution;
delta Z' is a random variable conforming to the positive Tai distribution, and epsilon in the linear regression modeliThe meanings are consistent, the fitting effect and the distribution state of the delta Z' are detected through residual errors and residual mean square error MSe; the expressions (10) and (11) have consistency.
2. A method for estimating the impedance of a low voltage subscriber loop based on a univariate model according to claim 1, characterized in that: the determination of the data acquisition time period in the step 1 comprises a large user peak-average time period and a resident user peak-average time period, and an intersection time period of the two user peak-average time periods is selected.
3. A method for estimating the resistance of a low voltage subscriber loop based on a unitary model as claimed in claim 1, characterized by:
the loop impedance calculation in the step 4 comprises the following steps:
step 6-1: performing unary linear regression analysis on the acquired sample data of one day;
step 6-2: fitting the residual mean square error;
step 6-3: estimating the loop impedance value Z of the user by the value of the regression coefficient betaL，
Step 6-4: model confidence level detection was performed 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 CN109613338A (en) 2019-04-12
CN109613338B true 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)

Families Citing this family (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
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
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
CN111208351B (en) * 2020-01-17 2022-05-17 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
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
CN112560239B (en) * 2020-12-03 2022-01-21 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

Also Published As

Publication number Publication date
WO2020164322A1 (en) 2020-08-20
CN109613338A (en) 2019-04-12

Similar Documents

Publication Publication Date Title
CN109613338B (en) Low-voltage user loop impedance estimation method based on unitary model
CN111062176B (en) Low-voltage user loop impedance binary linear model construction and solving method
Ni et al. Online risk-based security assessment
CN110516912B (en) Method for identifying household transformer relation of distribution station
CN113641723B (en) Power theft prediction method based on line impedance parameter estimation
EP2339517A1 (en) Method and system for demand response management in a network
CN107221927A (en) A kind of analysis method of opposing electricity-stealing based on quantitative appraisement model stealing suspicion parser
CN109164319B (en) Method for judging abnormal electricity utilization of building user
CN112560239B (en) Method and system for calculating line impedance of transformer area and computer readable storage medium
CN109190242B (en) Method for estimating line impedance of household section
CN109374995A (en) Low-voltage distribution system, aging circuit and oppose electricity-stealing monitoring method and correspondence system
CN107563641B (en) Disaster-resistant multi-scene differentiation planning method for power distribution network considering disaster preference
CN110231503B (en) High-loss platform area electricity stealing user identification and positioning method based on Glandum causal test
Zhong et al. Optimal Sizing and placement method for dynamic voltage restorers with mitigation expectation index
CN107767060B (en) Theoretical line loss calculation system and method for distribution network line
CN115712811A (en) Impedance calculation model based on low-voltage topological power distribution network
CN108512214A (en) A kind of line loss calculation method of the power circuit based on load coefficient
CN111796143B (en) Energy-saving metering method for energy-saving equipment of power distribution and utilization system
Baran et al. State estimation for real time monitoring of distribution feeders
CN108802567B (en) Island monitoring method for new energy power supply
Fang et al. Calculation method of outage probability of distribution network based on real-time failure rate of equipment
Yang et al. Evaluating the effectiveness of conservation voltage reduction with multilevel robust regression
CN109886832A (en) Distribution network reliability evaluation method and application based on average and scattered sampling method
CN107546742B (en) Day-ahead planned power flow active power and voltage calculation error analysis method
Zhang et al. Distribution network reliability considering weather and distribution generation

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