CN110137946A - A kind of Power System Disturbances space-time characteristic extracting method of data-driven - Google Patents
A kind of Power System Disturbances space-time characteristic extracting method of data-driven Download PDFInfo
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- CN110137946A CN110137946A CN201910388536.8A CN201910388536A CN110137946A CN 110137946 A CN110137946 A CN 110137946A CN 201910388536 A CN201910388536 A CN 201910388536A CN 110137946 A CN110137946 A CN 110137946A
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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
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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
- 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]
Abstract
The present invention is a kind of Power System Disturbances space-time characteristic extracting method of data-driven, its main feature is that, it include: the foundation of characteristic quantification index, voltage dynamic space-time distribution character quantificational description and the contents such as dynamic space-time distribution character that voltage is disclosed based on measured data, gradually get rid of the dependence to traditional modeling and simulation, all realize the quick analysis of bulk power grid multidate information and excavate using the space time correlation characteristic of power grid real response information as core.The dynamic process that visual and clear can describe electric system after disturbing, provides foundation for dispatcher, makes safe and stable operation of power system.With scientific and reasonable, the advantages that strong applicability, effect is good.
Description
Technical field
Technical field of the present invention is Electrical Power System Dynamic analysis field, is that a kind of electric system of data-driven is disturbed
Dynamic space-time characteristic extracting method.
Background technique
The continuous expansion of Power System Interconnection range and generation of electricity by new energy scale, increase operation of power networks environment uncertainty and
Complexity, Electrical Power System Dynamic behavior also becomes increasingly complex after disturbance, and a lot of large-area power-cuts things have occurred in recent domestic
Therefore cause huge economic loss and bad social influence.Therefore the dynamic characteristic after research Power System Disturbances is to electric power
System dynamic security analysis, system operation control and perturbation analysis etc. are of great significance.
To the Research on Dynamic Characteristic of power system voltage, most popular method is exactly to use numerical simulation, but numerical simulation
Analytic approach needs to establish all elements of system detailed subordination principle, and is gradually solved by numerical method.This
Sample is difficult to avoid that model parameter and calculation method bring error, with Wide Area Measurement System (Wide-Area
Measurement System, WAMS) gradually popularization, be more and more widely used in the power system, this is split
The work such as Power system dynamic process monitoring, Voltage Stability Analysis, state estimation, the wide-area control based on measured data are opened up to have created
The condition of benefit.
Since each synchronous phasor measuring device (phasor measurement unit, PMU) measurement information has from phase
Closing property and inertia, and Topology connection and its electromagnetic action relationship due to power grid objective reality, phase between multiple PMU measurement informations
There should be direct or indirect relevance.Wide area space-time measurement information has big data due structural and Relating Characteristic,
The multidate information of electric system is directly excavated from data, it is more convenient effective.
Summary of the invention
The technical problems to be solved by the present invention are: overcome the deficiencies in the prior art, proposes a kind of scientific and reasonable, applicability
By force, effect is good, visual and clear can describe the dynamic process of electric system after disturbance, provide foundation for dispatcher, make electric power
The Power System Disturbances space-time characteristic extracting method of the data-driven of system safe and stable operation.
The scheme for solving the use of its technical problem is a kind of Power System Disturbances space-time characteristic extraction side of data-driven
Method, characterized in that it includes the following contents:
1) foundation of characteristic quantification index
1. average voltage change rate
kv=(U0-Umin)/(t0-tmin) (1)
In formula: U0,UminRespectively Initial Voltage Value and minimum point value, t0,tminTo be respectively Initial Voltage Value and minimum point
It is worth corresponding time, kvRepresent average voltage change rate；
2. voltage maximum relative variation
ΔUmax=[Δ umax1,Δumax2,...,Δumaxn] (2)
In formula: Δ umaxi(i=1,2 ..., n) be observation point i voltage maximum relative variation, U0iFor the initial of voltage
Value, UminiFor minimum point voltage value；
3. disturbing contribution index (DCI)
For voltage data collection, covariance matrix is calculated with wherein N number of data sample, expression formula are as follows:
C in formulasysCovariance is represented, G is the voltage data of acquisition；
The matrix Z for being n × m for a dimension, energy are indicated by Frobenius norm are as follows:
E (Z) represents norm, z in formulaijIndicate the matrix of n × m；
CsysNorm be system generate gross energy, n is the quantity of measuring point, and m is the number of data time series, together
The covariance matrix for i-th of observation point of sample indicates are as follows:
By the Frobenius norm of formula (5) formula, the gross energy of middle data set in disturbing every time is sought, therefore, by i-th
The energy content of a measurement point and the ratio of whole system energy content disturb tribute to whole system as i-th of observation point of measurement
Offer the index of degree, referred to as the disturbance contribution index (DCI) of i observation point, expression formula are as follows:
DCI is expressed as disturbance contribution index, E (Ci) represent the gross energy disturbed every time, E (Csys) indicate the total energy disturbed
Amount；
4. response delay
The response time of each observation point is indicated with one group of time series:
Tr=[tr1,tr2,...,trn] (8)
T in formulari(i=1,2 ..., n) indicates the response time at observation point i；
If the response time determines, the time t of generation is disturbed0Also it determines, it will be able to determine each observation point to disturbance
Delay time:
ΔTr=[tr1-t0,tr2-t0,...,trn-t0] (9)
5. frequency maximum offset
The maximum value of the absolute value of each nodal frequency offset is indicated are as follows:
Δ F=[Δ fmax1,Δfmax2,...,Δfmaxn] (10)
Wherein Δ fmaxi(i=1,2 ..., n) is the maximum frequency deviation amount at observation point i；
2) Electrical Power System Dynamic spatial and temporal distributions characteristic quantificational description
For n observation point constitute observation data set, by average voltage change rate, voltage maximum relative variation,
Contribution index, response delay, frequency maximum offset characteristic quantity are disturbed, the space-time characterisation index Description Matrix of n × 5 is constituted:
Wherein: kiFor the average rate of change of the voltage at observation point i；ΔtriFor the voltage responsive delay at observation point i；Δ
umaxiFor the voltage maximum relative variation at observation point i；ΔfmaxiChange for frequency maximum at observation point i；DCIiFor observation point
Disturbance contribution index at i；
By the way that in index matrix D, each observation point is electrical after the situation of change of each index value effectively reflects disturbance
The variation tendency of amount can analyze the dynamic space-time characteristic distributions of electric system from the angular quantification of multidimensional.
3) the dynamic space-time distribution character of voltage is disclosed based on measured data
(1) electric network data for choosing certain region analyzes the time series and spatial character of voltage.It is derived as disturbing
The voltage's distribiuting situation of each observation point in the process.By comparing the voltage change characteristic of each node, analyze after failure, totally
Voltage level how to change, electrical distance and the relationship of influence degree disturbed.
(2) the dynamic space-time distribution character based on overall target quantitative analysis electric system
Establish observation data set, observation data set should the entire power grid of covering as far as possible, while being accounted for the superfluous of data
Remaining；The electrical distance for defining observation point and fault point is observed range, calculates obtained voltage Link dynamics to each
Item index is analyzed.
The Power System Disturbances space-time characteristic extracting method of data-driven of the invention, can be after visual and clear description disturbance
The dynamic process of electric system provides foundation for dispatcher, makes safe and stable operation of power system.With scientific and reasonable, fit
It is strong with property, the advantages that effect is good.
Detailed description of the invention
Fig. 1 spatial and temporal distributions characteristic figure；
The relational graph of Fig. 2 average voltage change rate and electrical distance；
The relational graph of Fig. 3 voltage maximum relative variation and electrical distance；
The relational graph of Fig. 4 response delay and electrical distance；
The relational graph of Fig. 5 disturbance contribution index and electrical distance；
Fig. 6 maximum is with respect to voltage variety variation diagram.
Specific embodiment
Below with drawings and examples, the present invention is described in detail.
A kind of Power System Disturbances space-time characteristic extracting method of data-driven of the invention, including the following contents:
1) foundation of characteristic quantification index
1. average voltage change rate
kv=(U0-Umin)/(t0-tmin) (1)
In formula: U0,UminRespectively Initial Voltage Value and minimum point value, t0,tminTo be respectively Initial Voltage Value and minimum point
It is worth corresponding time, kvRepresent average voltage change rate；
2. voltage maximum relative variation
ΔUmax=[Δ umax1,Δumax2,...,Δumaxn] (2)
In formula: Δ umaxi(i=1,2 ..., n) be observation point i voltage maximum relative variation, U0iFor the initial of voltage
Value, UminiFor minimum point voltage value；
3. disturbing contribution index (DCI)
For voltage data collection, covariance matrix is calculated with wherein N number of data sample, expression formula are as follows:
C in formulasysCovariance is represented, G is the voltage data of acquisition；
The matrix Z for being n × m for a dimension, energy are indicated by Frobenius norm are as follows:
E (Z) represents norm, z in formulaijIndicate the matrix of n × m；
CsysNorm be system generate gross energy, n is the quantity of measuring point, and m is the number of data time series, together
The covariance matrix for i-th of observation point of sample indicates are as follows:
By the Frobenius norm of formula (5) formula, the gross energy of middle data set in disturbing every time is sought, therefore, by i-th
The energy content of a measurement point and the ratio of whole system energy content disturb tribute to whole system as i-th of observation point of measurement
Offer the index of degree, referred to as the disturbance contribution index (DCI) of i observation point, expression formula are as follows:
DCI is expressed as disturbance contribution index, E (Ci) represent the gross energy disturbed every time, E (Csys) indicate the total energy disturbed
Amount；
4. response delay
The response time of each observation point is indicated with one group of time series:
Tr=[tr1,tr2,...,trn] (8)
T in formulari(i=1,2 ..., n) indicates the response time at observation point i；
If the response time determines, the time t of generation is disturbed0Also it determines, it will be able to determine each observation point to disturbance
Delay time:
ΔTr=[tr1-t0,tr2-t0,...,trn-t0] (9)
5. frequency maximum offset
The maximum value of the absolute value of each nodal frequency offset is indicated are as follows:
Δ F=[Δ fmax1,Δfmax2,...,Δfmaxn] (10)
Wherein Δ fmaxi(i=1,2 ..., n) is the maximum frequency deviation amount at observation point i；
2) Electrical Power System Dynamic spatial and temporal distributions characteristic quantificational description
For n observation point constitute observation data set, by average voltage change rate, voltage maximum relative variation,
Contribution index, response delay, frequency maximum offset characteristic quantity are disturbed, the space-time characterisation index Description Matrix of n × 5 is constituted:
Wherein: kiFor the average rate of change of the voltage at observation point i；ΔtriFor the voltage responsive delay at observation point i；Δ
umaxiFor the voltage maximum relative variation at observation point i；ΔfmaxiChange for frequency maximum at observation point i；DCIiFor observation point
Disturbance contribution index at i；
By the way that in index matrix D, each observation point is electrical after the situation of change of each index value effectively reflects disturbance
The variation tendency of amount can analyze the dynamic space-time characteristic distributions of electric system from the angular quantification of multidimensional.
3) Electrical Power System Dynamic spatial and temporal distributions characteristic is disclosed based on measured data
(1) electric network data for choosing certain region analyzes the time series and spatial character of voltage.It is derived as disturbing
The voltage's distribiuting situation of each observation point in the process.Fig. 1 is the voltage's distribiuting situation of each observation point in perturbation process, passes through different sections
Known to the measured data analysis of point: when the decline of the voltage of fault point, the global voltage of power grid also all declines, with apart from disturbance point
Distance increase, the amplitude of the decline of voltage becomes smaller.
(2) the dynamic space-time distribution character based on overall target quantitative analysis electric system
Establish observation data set, observation data set should the entire power grid of covering as far as possible, while being accounted for the superfluous of data
Remaining.The electrical distance for defining observation point and fault point is observed range, calculates obtained Link dynamics Description Matrix
As shown in table 1.
The calculated result of 1 observation point specifying information of table and feature figureofmerit
From the result of upper table it is found that there is significantly the average rate of change that each observation point drops under voltage after disturbance generation
Difference: maximum about to differ 3 times with minimum.It is very big for the disturbance contribution index near fault point, it is 0.393, the phase of voltage
4 times or so are differed with minimum to variable quantity maximum.It is surveyed it can be seen that as the electrical distance of distance fault point is remoter Fig. 2~3
The overall trend of average voltage change rate is increasing, and the delay time of decline is totally in increase trend, and maximum voltage is opposite to be deviated
Amount is gradually reduced.As electrical distance increases, the degree disturbed is gradually weaker, but the duration is essentially identical.It is obtained by Fig. 5
It is 0 to disturbance contribution index other than certain distance, disturbance contribution is concentrated mainly in certain region.Pass through point of characteristic index
Analysis description, the dynamic characteristic of voltage can be showed significantly.
By establishing reliable index, to reflect the Electrical Power System Dynamic variation after disturbance, and these indexs have one
Order tonality.The communication process of disturbance and the influence degree of different zones disturbance can be clearly embodied by Fig. 6, be convenient for
The safety analysis of electric system.The spatial and temporal distributions characteristic of electric system can be presented in these indexs from different dimensions, from reality
Information is extracted in measured data, reflects the true dynamic behaviour of electric system.
Claims (1)
1. a kind of Power System Disturbances space-time characteristic extracting method of data-driven, its main feature is that, it includes the following contents:
1) foundation of characteristic quantification index
1. average voltage change rate
kv=(U0-Umin)/(t0-tmin) (1)
In formula: U0,UminRespectively Initial Voltage Value and minimum point value, t0,tminTo be respectively Initial Voltage Value and minimum point value pair
The time answered, kvRepresent average voltage change rate；
2. voltage maximum relative variation
ΔUmax=[Δ umax1,Δumax2,...,Δumaxn] (2)
In formula: Δ umaxi(i=1,2 ..., n) be observation point i voltage maximum relative variation, U0iFor the initial value of voltage,
UminiFor minimum point voltage value；
3. disturbing contribution index (DCI)
For voltage data collection, covariance matrix is calculated with wherein N number of data sample, expression formula are as follows:
C in formulasysCovariance is represented, G is the voltage data of acquisition；
The matrix Z for being n × m for a dimension, energy are indicated by Frobenius norm are as follows:
E (Z) represents norm, z in formulaijIndicate the matrix of n × m；
CsysNorm be system generate gross energy, n is the quantity of measuring point, and m is the number of data time series, similarly
The covariance matrix of i-th of observation point is indicated are as follows:
By the Frobenius norm of formula (5) formula, therefore the gross energy for seeking middle data set in disturbing every time is surveyed i-th
The ratio of the energy content and whole system energy content of measuring point disturbs contribution journey to whole system as i-th of observation point of measurement
The index of degree, referred to as the disturbance contribution index (DCI) of i observation point, expression formula are as follows:
DCI is expressed as disturbance contribution index, E (Ci) represent the gross energy disturbed every time, E (Csys) indicate the gross energy disturbed；
4. response delay
The response time of each observation point is indicated with one group of time series:
Tr=[tr1,tr2,...,trn] (8)
T in formulari(i=1,2 ..., n) indicates the response time at observation point i；
If the response time determines, the time t of generation is disturbed0Also it determines, it will be able to when determining delay of each observation point to disturbance
Between:
ΔTr=[tr1-t0,tr2-t0,...,trn-t0] (9)
5. frequency maximum offset
The maximum value of the absolute value of each nodal frequency offset is indicated are as follows:
Δ F=[Δ fmax1,Δfmax2,...,Δfmaxn] (10)
Wherein Δ fmaxi(i=1,2 ..., n) is the maximum frequency deviation amount at observation point i
2) Electrical Power System Dynamic spatial and temporal distributions characteristic quantificational description
For the observation data set that n observation point is constituted, pass through average voltage change rate, voltage maximum relative variation, disturbance
Contribution index, response delay, frequency maximum offset characteristic quantity, constitute the space-time characterisation index Description Matrix of n × 5:
Wherein: kiFor the average rate of change of the voltage at observation point i；ΔtriFor the voltage responsive delay at observation point i；Δumaxi
For the voltage maximum relative variation at observation point i；ΔtciFor the duration at observation point i；DCIiFor disturbing at observation point i
Dynamic contribution index；
By the way that in index matrix D, the situation of change of index value effectively reflects the variation of each observation point electrical quantity after disturbance
Trend can analyze the dynamic space-time characteristic distributions of electric system from the angular quantification of multidimensional；
3) Electrical Power System Dynamic spatial and temporal distributions characteristic is disclosed based on measured data
(1) electric network data for choosing certain region analyzes the time series and spatial character of voltage, is derived as perturbation process
In each observation point voltage's distribiuting situation；By comparing the voltage change characteristic of each node, overall electricity after failure is analyzed
How voltage levels change, the relationship of electrical distance and the influence degree disturbed；
(2) the dynamic space-time distribution character based on overall target quantitative analysis electric system
Establish observation data set, observation data set should the entire power grid of covering as far as possible, while being accounted for the redundancy of data；
The electrical distance for defining observation point and fault point is observed range, calculates obtained voltage Link dynamics to indices
It is analyzed.
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