CN107370150B - The Power system state estimation Bad data processing method measured based on synchronized phasor - Google Patents

The Power system state estimation Bad data processing method measured based on synchronized phasor Download PDF

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CN107370150B
CN107370150B CN201710795550.0A CN201710795550A CN107370150B CN 107370150 B CN107370150 B CN 107370150B CN 201710795550 A CN201710795550 A CN 201710795550A CN 107370150 B CN107370150 B CN 107370150B
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measurement
bad data
state estimation
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power system
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CN107370150A (en
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林俊杰
周华锋
陆超
姚海成
苏寅生
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Tsinghua University
China Southern Power Grid Co Ltd
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China Southern Power Grid Co Ltd
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00—Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/70—Smart grids as climate change mitigation technology in the energy generation sector
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/22—Flexible AC transmission systems [FACTS] or power factor or reactive power compensating or correcting units

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  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Remote Monitoring And Control Of Power-Distribution Networks (AREA)
  • Other Investigation Or Analysis Of Materials By Electrical Means (AREA)

Abstract

The present invention proposes a kind of Power system state estimation Bad data processing method measured based on synchronized phasor, belongs to Power system state estimation field, for handling the bad data of synchronous phasor measurement unit.The measuring value of the fully synchronized phasor measurement units of discontinuity surface establishes measurement collection when this method obtains one, power grid, obtains the measurement equation for indicating linear relationship between measurement collection and quantity of state；The state estimator of electric system is obtained by electric system linear state estimation；Calculate the estimated value and measurement residual vector of measurement collection；Using measurement residual vector, calculates measurement and concentrate the corresponding bad data index of each measuring value and bad data judgment threshold；When the bad data index of all measuring values is respectively less than its corresponding bad data judgment threshold, show that no bad data, output power system state estimation amount, Bad data processing terminate.The present invention carries out raw data detection using measurement residual error estimation substantial measurement errors, and method is simple and reliable, and accuracy is high.

Description

Power system state estimation bad data processing method based on synchronous phasor measurement
Technical Field
The invention belongs to the field of power system state estimation, and mainly relates to a power system state estimation bad data processing method based on synchronous phasor measurement.
Background
Synchronous Phasor Measurement Unit (PMU) is a new generation of power grid measuring device, and compared with the traditional measuring device, the PMU has better synchronism, higher refresh frequency and can provide Phasor data of electric quantity. In recent years, with the rapid arrangement of phasor measurement units in a power grid, a large amount of PMU measurement data provides new data for power system analysis and calculation. However, the accuracy of the PMU phase angle measurement data is not sufficient compared to active power measurement, and due to network communication interruption, measurement equipment failure, and the like, measurement data that deviates from the true value seriously, that is, bad data, may exist in the PMU measurement data.
At present, poor data processing technology of the power system mainly aims at traditional measurement data, and a targeted method for PMU data is lacked. Under the full PMU measurement, the measurement equation of the power system state estimation is linear, so a least square solution or a state estimation value can be directly solved, but bad data in measurement data needs to be processed due to the fact that the least square method is lack of robustness. The bad data processing comprises the processing after the pre-processing of state estimation and the processing (after) of state estimation, the main methods before the state estimation comprise a measurement mutation method and the like, and the simple methods after the state estimation comprise a standard residual method, a maximum residual method and the like.
The traditional residual error identification method is to use a weighted residual error or a standard residual error as a characteristic value, determine a threshold value according to a certain confidence level by using hypothesis test of probability theory, and then carry out 'not-that-is-that-other' binary logic judgment on the measured quantity. However, the method has a large residual error, which is not completely equivalent to a large measurement error, so that the method has general reliability, and may have a case of erroneous judgment or missed judgment, and cannot process a case of multi-correlation bad data.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a method for processing bad data of power system state estimation based on synchronous phasor measurement. The method utilizes the synchronous measurement phasor measurement which is widely applied to the power grid at present, utilizes the measurement residual to estimate the actual measurement error to detect the bad data, and has the advantages of reliability, simplicity, high accuracy and higher practical value.
The invention provides a power system state estimation bad data processing method based on synchronous phasor measurement, which is characterized by comprising the following steps of:
1) measuring values of all synchronous vector measuring units of one time section of the power grid are obtained, wherein the measuring values comprise voltage phasor measuring values and current phasor measuring values, and a measuring set Y is established; the measurement set Y is a complex vector, when all measurement values in the measurement set Y are synchronous phasors, according to a physical model of the power grid, a linear relation exists between the measurement set Y and the state quantity X, and a measurement equation is written into a matrix form shown in a formula (1):
Y＝AX+ε(1)
wherein A is a node-branch admittance matrix; assuming that the number of measured values of the synchrophasor measurement unit in the measurement set Y is m and the number of states of the state quantity X is n, rank (a) is n, and epsilon is a measurement error vector;
2) performing linear state estimation on the power system, and solving the state estimation quantity of the power system by adopting a weighted least square method, wherein an expression formula is shown as a formula (2):
Xe＝(AHWCWLSA)-1AHWCWLSY (2)
wherein, WCWLSIs a weight matrix of m x m orders, which is a real diagonal matrix;
3) the state estimator X obtained according to the step 2)eAnd the measurement equation (1) calculates the estimated value Y of the measurement seteAnd measuring a residual vector r;
estimated value Y of measurement seteThe expression is as follows:
Ye＝AXe (3)
measuring residual vector r, the expression is as follows:
r＝Y-Ye (4)
meanwhile, the measurement residual vector r is expressed as:
whereinAs a residual sensitivity matrix, YTThe truth value of a measurement set is represented, and I represents an identity matrix;
according to equation (5), the expression of the measurement error vector is updated as:
wherein deltaYRepresenting an estimated error vector;
4) calculating a bad data index R corresponding to the ith measurement value in the measurement set Yi1,2, … …, m, the expression is as follows:
wherein,<,>represents a point multiplication operation of a vector in a complex vector space.]iThe representation matrix.]Column i, δYi，riEach represents deltaYAnd the ith component of r;
calculating a bad data judgment threshold corresponding to the ith measurement value, wherein the expression is as follows:
wherein k isiRepresents the reliability factor, aiAnd biRespectively representing the maximum measurement error of amplitude and the maximum measurement error of phase angle, Z, of the ith measured valueiRepresenting the amplitude of the ith measurement;
5) and repeating the step 4), calculating bad data indexes of all the measurement values of the synchronous vector measurement units and corresponding bad data judgment threshold values, and judging:
if all the bad data indexes R of the measured values of the synchronous vector measuring unitsiIf the measured values are all smaller than the corresponding bad data judgment threshold values, the situation that no bad data exists in the measurement set Y used for state estimation is shown, the electric power system state estimation quantity calculated in the step 2) is output, and the bad data processing is finished; otherwise all R's will beiMarking the measurement value of the index exceeding the corresponding bad data judgment threshold value as suspicious data, and entering the step 6);
6) all the suspicious data obtained in the step 5) are subjected to R corresponding to the suspicious dataiThe indexes are carried out from large to smallArranged to correspond to RiMarking suspicious data with the maximum index as bad data, and removing the bad data from the measurement set Y;
7) and returning to the step 2) again, and performing power system state estimation again on the new measurement set obtained through the processing in the step 6) until no bad data exists in the measurement set, outputting the power system state estimation quantity, and finishing the bad data processing.
The invention has the characteristics and beneficial effects that:
the invention provides a method for processing bad data of power system state estimation based on synchronous phasor measurement, which provides a novel technology for detecting and identifying bad data after power grid state estimation by analyzing residual errors and errors of state estimation.
The detection method is simple and reliable, the approximate estimation value of the residual error of the measurement set is obtained through the analysis of the relation between the residual error and the error of the measurement set after the power grid state estimation, and the bad data index R for detecting whether the measurement set is the bad data is constructed according to the approximate estimation value, so that the bad data can be effectively identified. And all bad data in the measurement set can be processed by a primary elimination method, including multi-correlation bad data.
Detailed Description
The method for processing bad data of power system state estimation based on synchrophasor measurement according to the present invention is further described in detail with reference to the following embodiments.
The invention provides a power system state estimation bad data processing method based on synchronous phasor measurement, which comprises the following steps:
1) and (3) obtaining measurement values of all PMUs of one time section of the power grid, including voltage phasor and current phasor data, through simulation or actual measurement, and establishing a measurement set Y. The measurement set Y is a complex vector, when all measurement values in the measurement set Y are synchronous phasors, according to a physical model of the power grid, a linear relation exists between the measurement set Y and the state quantity X, and a measurement equation can be written into a matrix form as follows:
Y＝AX+ε(1)
wherein, a is a node-branch admittance matrix, and assuming that the number of PMU measurement values in the measurement set Y is m and the number of states of the state quantity X is n, the rank (a) is n, where elements are all complex numbers, and ∈ is a measurement error vector.
2) Performing linear state estimation on the power system, and solving the state estimation quantity of the power system by adopting a weighted least square method, wherein an expression formula is shown as a formula (2):
Xe＝(AHWCWLSA)-1AHWCWLSY (2)
wherein, WCWLSIs a weight matrix of m × m order, which is a real diagonal matrix.
3) The state estimator X obtained according to the step 2)eAnd measuring equation (1) to calculate the estimated value Y of the PMU measurement seteAnd measuring a residual vector r; estimated value Y of PMU measurement seteThe expression is as follows:
Ye＝AXe (3)
the expression of a PMU measurement set residual vector r is as follows:
r＝Y-Ye (4)
meanwhile, the PMU measurement residual vector r can also be expressed as:
whereinAs a residual sensitivity matrix, YTRepresenting the truth of the measurement set, I representing the unit momentAnd (5) arraying.
According to equation (5), the PMU measurement error vector ∈ may be rearranged as:
wherein deltaYRepresenting an estimated error vector;
the absolute measurement error vector expression obtained by taking the modulus values of the two sides of the formula (6) is shown as follows:
|ε|＝|r|+|δY| (7)
from the above equation, the absolute measurement error vector | epsilon | can be decomposed into two components, i.e., the modulus vector | r | ═ S | epsilon | and the vector | δ |, of the residual errorYWhere | (I-S) | epsilon |, the inner product of the two vectors can be proven to be zero, and the two vectors are mutually orthogonal. The residual vector r is thus only a part of the measurement error vector epsilon, which can be estimated by the residual vector r.
4) According to the above conclusion, the bad data index R corresponding to the i (i ═ 1,2, … …, m) th measured value in the measurement set Y is defined and calculatediThe expression is as follows:
wherein,<,>represents a point multiplication operation of a vector in a complex vector space.]iThe representation matrix.]Column i, δYi，riEach represents deltaYAnd the ith component of r.
Further, a bad data judgment threshold corresponding to the ith measured value is calculated, and the expression is as follows:
wherein k isiThe reliability coefficient is expressed, 1 is generally taken, and k can be increased appropriately when the measurement condition is known to be worseiValue of aiAnd biRespectively representing the maximum measurement error of amplitude and the maximum measurement error of phase angle, Z, of the ith measured valueiRepresenting the magnitude of the ith measurement.
5) And repeating the step 4), calculating bad data indexes of all PMU measurement values and corresponding bad data judgment threshold values, and judging:
if the measured values of all PMUs are not good data index RiIf the measured values are all smaller than the corresponding bad data judgment threshold values, the situation that no bad data exists in the measurement set Y used for state estimation is shown, the electric power system state estimation quantity calculated in the step 2) is output, and the bad data processing is finished; otherwise all R's will beiAnd marking the measurement value of the index exceeding the corresponding bad data judgment threshold value as suspicious data, and entering the step 6).
6) All the suspicious data obtained in the step 5) are subjected to R corresponding to the suspicious dataiThe indexes are arranged from big to small, and the corresponding R is arrangediThe suspicious data with the largest index is marked as bad data, and the bad data is removed from the measurement set Y.
7) And returning to the step 2) again, and performing state estimation again on the new measurement set obtained through the processing in the step 6) until no bad data exists in the measurement set, outputting the state estimation quantity of the power system, and finishing the bad data processing.

Claims (1)

1. A method for processing bad data of power system state estimation based on synchronous phasor measurement is characterized by comprising the following steps:
1) measuring values of all synchronous vector measuring units of one time section of the power grid are obtained, wherein the measuring values comprise voltage phasor measuring values and current phasor measuring values, and a measuring set Y is established; the measurement set Y is a complex vector, when all measurement values in the measurement set Y are synchronous phasors, according to a physical model of the power grid, a linear relation exists between the measurement set Y and the state quantity X, and a measurement equation is written into a matrix form shown in a formula (1):
Y＝AX+ε (1)
wherein A is a node-branch admittance matrix; assuming that the number of measured values of the synchrophasor measurement unit in the measurement set Y is m and the number of states of the state quantity X is n, rank (a) is n, and epsilon is a measurement error vector;
2) performing linear state estimation on the power system, and solving the state estimation quantity of the power system by adopting a weighted least square method, wherein an expression formula is shown as a formula (2):
Xe＝(AHWCWLSA)-1AHWCWLSY (2)
wherein, WCWLSIs a weight matrix of m x m orders, which is a real diagonal matrix;
3) the state estimator X obtained according to the step 2)eAnd the measurement equation (1) calculates the estimated value Y of the measurement seteAnd measuring a residual vector r;
estimated value Y of measurement seteThe expression is as follows:
Ye＝AXe (3)
measuring residual vector r, the expression is as follows:
r＝Y-Ye (4)
meanwhile, the measurement residual vector r is expressed as:
whereinAs a residual sensitivity matrix, YTThe truth value of a measurement set is represented, and I represents an identity matrix;
according to equation (5), the expression of the measurement error vector is updated as:
wherein deltaYRepresenting an estimated error vector;
4)calculating a bad data index R corresponding to the ith measurement value in the measurement set Yi1,2, … …, m, the expression is as follows:
wherein,<,>represents a point multiplication operation of a vector in a complex vector space.]iThe representation matrix.]Column i, δYi，riEach represents deltaYAnd the ith component of r;
calculating a bad data judgment threshold corresponding to the ith measurement value, wherein the expression is as follows:
wherein k isiRepresents the reliability factor, aiAnd biRespectively representing the maximum measurement error of amplitude and the maximum measurement error of phase angle, Z, of the ith measured valueiRepresenting the amplitude of the ith measurement;
5) and repeating the step 4), calculating bad data indexes of all the measurement values of the synchronous vector measurement units and corresponding bad data judgment threshold values, and judging:
if all the bad data indexes R of the measured values of the synchronous vector measuring unitsiIf the measured values are all smaller than the corresponding bad data judgment threshold values, the situation that no bad data exists in the measurement set Y used for state estimation is shown, the electric power system state estimation quantity calculated in the step 2) is output, and the bad data processing is finished; otherwise all R's will beiMarking the measurement value of the index exceeding the corresponding bad data judgment threshold value as suspicious data, and entering the step 6);
6) all the suspicious data obtained in the step 5) are subjected to R corresponding to the suspicious dataiThe indexes are arranged from big to small, and the corresponding R is arrangediMarking suspicious data with the maximum index as bad data, and removing the bad data from the measurement set Y;
7) and returning to the step 2) again, and performing power system state estimation again on the new measurement set obtained through the processing in the step 6) until no bad data exists in the measurement set, outputting the power system state estimation quantity, and finishing the bad data processing.
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CN108022046A (en) * 2017-12-05 2018-05-11 国网江西省电力有限公司景德镇供电分公司 A kind of electric power system data method for evaluating quality, storage medium and equipment
CN109193639B (en) * 2018-10-10 2021-05-11 河海大学 Robust estimation method for power system
CN109975594B (en) * 2019-02-28 2021-11-30 北京交通大学 Phasor principal component analysis method for data compression in synchronous measurement system
CN109818349B (en) * 2019-03-13 2022-04-22 东北大学 Power grid robust state prediction method based on multidimensional state matrix sliding matching
CN112230087B (en) * 2020-10-13 2022-08-05 全球能源互联网研究院有限公司 Linear state estimation method and device, electronic equipment and storage medium
CN113191485B (en) * 2021-04-26 2024-05-10 东北大学 Power information network security detection system and method based on NARX neural network
CN116298515B (en) * 2023-05-23 2023-08-01 北京鼎诚鸿安科技发展有限公司 Synchronous waveform measuring terminal and measuring method thereof

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102801162A (en) * 2012-08-23 2012-11-28 清华大学 Two-stage linear weighted least-square power system state estimation method
US8634965B1 (en) * 2010-12-03 2014-01-21 Bei Gou Computer-based method for power system state estimation
CN103745109A (en) * 2014-01-10 2014-04-23 国家电网公司 Bad data detection and identification method based on measurement of PMU (Phasor Measurement Unit) and measurement of SCADA (Supervisory Control and Data Acquisition)
CN104836223A (en) * 2014-11-14 2015-08-12 浙江大学 Power grid parameter error and bad data coordinated identification and estimation method
CN105406471A (en) * 2015-12-23 2016-03-16 云南电力调度控制中心 Bad data identification and estimation method for power grid

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9617018B2 (en) * 2014-03-28 2017-04-11 Rincon Research Corporation Automated detection and characterization of earth-orbiting satellite maneuvers

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8634965B1 (en) * 2010-12-03 2014-01-21 Bei Gou Computer-based method for power system state estimation
CN102801162A (en) * 2012-08-23 2012-11-28 清华大学 Two-stage linear weighted least-square power system state estimation method
CN103745109A (en) * 2014-01-10 2014-04-23 国家电网公司 Bad data detection and identification method based on measurement of PMU (Phasor Measurement Unit) and measurement of SCADA (Supervisory Control and Data Acquisition)
CN104836223A (en) * 2014-11-14 2015-08-12 浙江大学 Power grid parameter error and bad data coordinated identification and estimation method
CN105406471A (en) * 2015-12-23 2016-03-16 云南电力调度控制中心 Bad data identification and estimation method for power grid

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