CN106355029B - A kind of method that distribution system key measures decoupling Fast Identification - Google Patents
A kind of method that distribution system key measures decoupling Fast Identification Download PDFInfo
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Abstract
The present invention relates to a kind of methods that distribution system key measures decoupling Fast Identification, its technical characterstic is: the following steps are included: step 1, using the distribution system three-phase state algorithm for estimating based on branch current, it selects distribution system branch current magnitudes and phase angle as state variable, sets the state variable initial value；All active power measurement of distribution system is set non-zero constant by step 2；Step 3 forms the part PI Jacobian matrix, gain matrix and measurement calculated value；Step 4, the solution part PI normal equation group obtain state variable changing value；Step 5 calculates the part PI residual sensitivity matrix, and thus calculates active power measurement residuals and standardized residual；Step 6, the standardized residual calculated according to step 5, the measurement that standardized residual value is zero are crucial measurement, and standardized residual is worth equal measurement and forms crucial measurement group.The present invention realizes the crucial decoupled identification measured with crucial measurement group, improves calculating speed.
Description
Technical field
The invention belongs to distribution system measurement technology field, especially a kind of distribution system key measures decoupling Fast Identification
Method.
Background technique
As the permeability of various distributed generation resources in the power system is continuously improved, intermittent and uncertainty makes electricity
The safe and stable operation of Force system especially distribution system is faced with stern challenge, and intelligence electricity is inquired into positive by various countries at present
The development model of distribution system under screen frame frame.It realizes that the fining operational management of distribution system and real-time status perceive and be unable to do without shape
State estimation, and can state estimation operate normally and estimated accuracy with higher is then closely bound up with measurement system situation.
State estimation first has to judge whether can uniquely calculate current system conditions by currently measuring before calculating, i.e., considerable
The property surveyed analysis；When network Observable, however it remains the tender spots of measure configuration, i.e., it is crucial to measure (Critical
) and crucial measurement group (Critical Measurement Set) Measurement.Wherein, critical quantity survey is defined as losing this
Network is unobservable after measurement, and crucial measurement group is defined as losing in the group other all measurements in the group after any one measurement
Become crucial measurement.Key measures and crucial measurement group identification is the important research content of bad data recognition: key measures
For that can not detect when bad data, residual contamination will not be generated；Bad data in crucial measurement group can detecte out but can not
Specific bad measurement is recognized, residual contamination scattered band is limited to the crucial measurement group at place, and therefore, crucial measurement group is also known as
Bad data group (Bad Data Group) or minimum Correlated Case with ARMA Measurement group (Minimal Dependent Set), key is measured and
Crucial measurement group is recognized, and is on the one hand facilitated to assess the robustness of measurement system and is resisted the robustness for measuring and losing, hair
The weak spot of existing measure configuration, and then the measure configuration of distribution system is carried out targetedly perfect；On the other hand can be
The detection and identification of bad data provide effective information, prevent the measurement detected in crucial measurement group from leading to erroneous detection.
Currently, being suitable for high voltage power transmisson system about the research for measuring identification crucial in power grid, using linearisation DC shape
State estimates model, and rarely has research for the crucial measurement identification of three-phase imbalance distribution system and measure configuration.Distribution system
State estimation is different from conventional electric power system state estimation, since radially structure, three-phase imbalance, measurement are deficient for distribution system
The weary, factors such as line parameter circuit value is inaccurate, mostly use branch current as state variable, to realize the three-phase decoupling of algorithm.Although
Three-phase decoupling, but still cannot achieve Jacobian matrix PQ decoupling, it cannot directly be used since transmission system key measures discrimination method
In distribution system, therefore there is an urgent need to the crucial discrimination methods that measures for three-phase imbalance distribution system to be studied.
Summary of the invention
It is an object of the invention to overcome the deficiencies of the prior art and provide a kind of designs reasonable, operation small scale and calculating
The method that fireballing distribution system key measures decoupling Fast Identification.
The present invention solves its technical problem and adopts the following technical solutions to achieve:
A kind of method that distribution system key measures decoupling Fast Identification, comprising the following steps:
Step 1, using the distribution system three-phase state algorithm for estimating based on branch current, select distribution system branch current
Amplitude and phase angle set the state variable initial value as state variable, and all branch currents of distribution system are set as I0∠
0 °, all node voltages are set as U0∠0°；
All active power measurement of distribution system is set non-zero constant by step 2, and weight sets 1；
Step 3 solves the distribution system state estimation based on branch current magnitudes and phase angle using Gauss-Newton method
Model, and it is based on normal equation, solve the part PI Jacobian matrix HPI, gain matrix GPIWith measurement calculated value hPI(x0)；
Step 4, the solution part PI normal equation obtain state variable changing value Δ x0, update state variable x1=x0+Δ
x0；
Step 5 calculates the part PI residual sensitivity matrix WPI, and thus calculate active power measurement residuals rPAnd standardization
Residual error rPN；
Step 6, the standardized residual r calculated according to step 5PN, determine rPNThe measurement that value is zero is crucial measurement, rPNValue
Equal measurement forms crucial measurement group.
Moreover, the distribution system state estimation model based on branch current magnitudes and phase angle of the step 3 is z=h (x)
+v；
In above formula, x is state vector, and z is to measure vector, and v is error in measurement vector, and h (x) is non-linear measurement function.
Moreover, the normal equation of the step 3 are as follows: G (xk)Δxk=HT(xk)R-1[z-h(xk)]；
Wherein, Δ xk=xk+1-xk, R is error in measurement covariance matrix,To measure Jacobean matrix
Battle array, G (xk)=HT(xk)R-1h(xk) it is gain matrix.
Moreover, the step 4 method particularly includes: the part PI normal equation is iterated on the basis of step 3 and is asked
Solution, according to iterative formula Δ xk=G-1(xk)HT(xk)R-1[z-h(xk)], obtain state variable changing value Δ x0, and by xk+1=xk
+ΔxkObtain updated state variable x1=x0+Δx0。
Moreover, the step 5 method particularly includes: according to formula W=[I-H (HTR-1H)-1HTR-1] v calculate the part PI it is residual
Poor sensitivity matrix WPI；Active power measurement residuals r can be calculated by residual computations formula r=WvP, and further basisD=diag [WR] calculates standardized residual rPN；
In above formula, I is unit battle array, and H is to measure Jacobian matrix, R-1For the inverse matrix of error in measurement covariance matrix.
The advantages and positive effects of the present invention are:
1, the present invention use the distribution system three-phase state algorithm for estimating based on branch current, select branch current magnitudes and
Phase angle is as state variable, it can be achieved that the three-phase of Jacobian matrix decouples.It is coupled for distribution system measurement jacobian matrix PQ
The characteristics of, the invention proposes the methods that one kind can realize Jacobian matrix PQ decoupling under given state initial value.Meanwhile the party
Method proposes the state estimation by all reactive powers measurement zero setting of distribution system, when active power sets arbitrary number, under the initial value
It is calculated without being iterated, greatly improves calculating speed.
2, the invention proposes a kind of crucial measurement for three-phase imbalance distribution system and crucial measurement group decoupling are fast
The method of speed identification, the method achieve keys to measure and the decoupling of crucial measurement group and non-iterative crucial measurement and critical quantity
The identification of survey group: on the one hand, the crucial decoupled identification measured with crucial measurement group is realized, identification process only needs to calculate active power
Partial status estimation problem, effectively reduces calculation scale；On the other hand, calculating process is greatly dropped without being iterated calculating
Low calculation scale, improves calculating speed.Before numerical results show quick decoupled identification method speed far faster than decoupling, have
Biggish theory significance and more practical value.
Detailed description of the invention
Fig. 1 is the key that measurement decoupling Fast Identification Method flow chart of the invention.
Specific embodiment
The embodiment of the present invention is described in further detail below in conjunction with attached drawing:
The present invention uses the distribution system three-phase state algorithm for estimating based on branch current, selects branch current magnitudes and phase
Angle is as state variable, it can be achieved that the three-phase of Jacobian matrix decouples.For distribution system measurement jacobian matrix PQ coupling
Feature, the invention proposes the methods that one kind can realize Jacobian matrix PQ decoupling under given state initial value.Meanwhile this method
It proposes all reactive powers measuring zero setting, when active power sets arbitrary number, the state estimation under the initial value is without changing
In generation, calculates.As a result, it is proposed by the present invention measured for three-phase imbalance distribution system key and the decoupling of crucial measurement group it is quick
Discrimination method, as shown in Figure 1, comprising the following specific steps that:
Step 1, using the distribution system three-phase state algorithm for estimating based on branch current, select distribution system branch current
Amplitude and phase angle set the state variable initial value as state variable, and all branch currents of distribution system are set as I0∠
0 °, all node voltages are set as U0∠0°；
All active power measurement of distribution system is set non-zero constant (such as continuous positive integer) by step 2, and weight sets 1；
Step 3 solves the distribution system state estimation based on branch current magnitudes and phase angle using Gauss-Newton method
Model, and it is based on normal equation, solve the part PI Jacobian matrix HPI, gain matrix GPIWith measurement calculated value hPI(x0)；
Wherein, the distribution system state estimation model based on branch current magnitudes and phase angle of the step 3 is z=h (x)
+v；
In above formula, x is state vector, and z is to measure vector, and v is error in measurement vector, and h (x) is non-linear measurement function.
The normal equation of the step 3 are as follows: G (xk)Δxk=HT(xk)R-1[z-h(xk)]；
Wherein, Δ xk=xk+1-xk, R is error in measurement covariance matrix,To measure Jacobean matrix
Battle array, G (xk)=HT(xk)R-1h(xk) it is gain matrix.
Step 4, the solution part PI normal equation group obtain state variable changing value Δ x0, update state variable x1=x0+Δ
x0；
The step 4 method particularly includes: solution, root are iterated to the part PI normal equation on the basis of step 3
According to iterative formula Δ xk=G-1(xk)HT(xk)R-1[z-h(xk)], obtain state variable changing value Δ x0, and by xk+1=xk+Δxk
Obtain updated state variable x1=x0+Δx0。
Step 5 calculates the part PI residual sensitivity matrix WPI, and thus calculate active power measurement residuals rPAnd standardization
Residual error rPN；
The step 5 method particularly includes: according to formula W=[I-H (HTR-1H)-1HTR-1] v calculate the part PI residual error it is sensitive
Spend matrix WPI；Active power measurement residuals r can be calculated by residual computations formula r=WvP, and further basisD=diag [WR] calculates standardized residual rPN；
In above formula, I is unit battle array, and H is to measure Jacobian matrix, R-1For the inverse matrix of error in measurement covariance matrix.
Step 6, the standardized residual r calculated according to step 5PN, determine rPNThe measurement that value is zero is crucial measurement, rPNValue
Equal measurement forms crucial measurement group.
The working principle of the invention is:
Since the measurement jacobian matrix of distribution system is PQ coupling, without the decoupling linear DC shape of similar transmission system
State estimates model, therefore method proposed by the present invention can realize distribution system Jacobian matrix under given state initial value
PQ decoupling, similar to the DC state estimation of transmission system.And if at this time by the idle measurement zero setting of all branches of distribution system,
Arbitrary number is set in active measurement, then the state estimation under the initial value, and without being iterated calculating, to realize distribution system
Key measures and the decoupling Fast Identification of crucial measurement group.
Stringent theoretical proof is given below:
All branch currents are set as I00 ° of ∠, all node voltages are set as U00 ° of ∠, then branch power, which measures, corresponds to
Jacobian matrix H (x)|FlowElement is as follows:
Node injecting power measures corresponding Jacobian matrix H (x)|InjElement is as follows:
In above formula,The respectively p phase of node k injects active and reactive power；The respectively p phase of branch k-m
Branch active and reactive power；The p phase voltage amplitude of respectively node k, phase angle；The p phase electricity of respectively branch k-m
Flow amplitude, phase angle；
It can be seen that measurement jacobian matrix H (x) realizes PQ decoupling, it is made of PI and Q α two parts:
In Gauss-Newton method, each equation of the part PI normal equation group is expressed as follows:
By formula G (xk)=HT(xk)R-1H(xk) it is found that each element of gain matrix G (x), which can be write, measures Jacobi
The weighting inner product of corresponding two column vectors of matrix H (x), it may be assumed that
In above formula, gktFor the element in gain matrix G (x), hjk、hjtIt is the element in measurement jacobian matrix H (x),
rjFor the element in error in measurement covariance matrix R；
Therefore, each element of the part PI normal equation right-hand-side vector can be write:
In above formula, bk=di, zjIt is laterally measured for j-th of amount.
Then normal equation group each equation left and right ends in the part PI are write respectively:
It is obtained by both ends are equal:
If network Observable, normal equation group have unique solution.All reactive powers of distribution system are measured into zero setting, are had
Function power measurement sets arbitrary number.
Have for branch power measurement:
Have for the measurement of node injecting power:
In second iteration, had according to formula (9), (10):
In above formula,Respectively branch power measures the corresponding branch current magnitudes of j and phase angle state variable
Correction amount；
The corresponding node downstream leg number of j is measured for injecting power；
The corresponding branch current magnitudes of upstream branch and phase of node respectively where injecting power measurement j
Horn shape state variable correction amount；
The corresponding branch current of i-th downstream leg of node respectively where injecting power measurement j
Amplitude and phase angle state variable correction amount；
The branch current magnitudes state of branch becomes where branch power measures j when the respectively the 1st, 2 iteration
Magnitude；
The corresponding branch of upstream branch of node where injecting power measures j when the respectively the 1st, 2 iteration
Current amplitude state variable value；
I-th article of downstream leg of node is corresponding where injecting power measures j when the respectively the 1st, 2 iteration
Branch current magnitudes state variable value；
hPFlow(1)(x1)hPInj(1)(x1) branch active power and active power measurement is injected when being respectively the 2nd iteration
Estimated value；
It can be seen that normal equation right-hand-side vector (b=z-h (x when second of iteration1)) one it is set to null vector, it solves
State variable correction amount vector is null vector, meets the condition of convergence.
In summary, for the distribution system state estimation model based on branch current magnitudes and phase angle, in given shape
Under state initial value, all reactive powers are measured into zero setting, state estimation at this time is PQ decoupling, and without being iterated calculating,
Greatly improve measurement speed.
It is emphasized that embodiment of the present invention be it is illustrative, without being restrictive, therefore packet of the present invention
Include and be not limited to embodiment described in specific embodiment, it is all by those skilled in the art according to the technique and scheme of the present invention
The other embodiments obtained, also belong to the scope of protection of the invention.
Claims (5)
1. a kind of method that distribution system key measures decoupling Fast Identification, it is characterised in that: the following steps are included:
Step 1, using the distribution system three-phase state algorithm for estimating based on branch current, select distribution system branch current magnitudes
With phase angle as state variable, the state variable initial value is set, and all branch currents of distribution system are set as I00 ° of ∠, institute
There is node voltage to be set as U0∠0°；
All active power measurement of distribution system is set non-zero constant by step 2, and weight sets 1；
Step 3 solves the distribution system state estimation model based on branch current magnitudes and phase angle using Gauss-Newton method,
And it is based on normal equation, solve the part PI Jacobian matrix HPI, gain matrix GPIWith measurement calculated value hPI(x0)；
Step 4, the solution part PI normal equation obtain state variable changing value Δ x0, update state variable x1=x0+Δx0；
Step 5 calculates the part PI residual sensitivity matrix WPI, and thus calculate active power measurement residuals rPAnd standardized residual
rPN；
Step 6, the standardized residual r calculated according to step 5PN, determine rPNThe measurement that value is zero is crucial measurement, rPNIt is worth equal
Measurement form crucial measurement group.
2. the method that a kind of distribution system key according to claim 1 measures decoupling Fast Identification, it is characterised in that: institute
The distribution system state estimation model based on branch current magnitudes and phase angle for stating step 3 is z=h (x)+v；
In above formula, x is state vector, and z is to measure vector, and v is error in measurement vector, and h (x) is non-linear measurement function.
3. the method that a kind of distribution system key according to claim 2 measures decoupling Fast Identification, it is characterised in that: institute
State the normal equation of step 3 are as follows: G (xk)Δxk=HT(xk)R-1[z-h(xk)]；
Wherein, Δ xk=xk+1-xk, R is error in measurement covariance matrix,For measurement jacobian matrix, G
(xk)=HT(xk)R-1h(xk) it is gain matrix.
4. the method that a kind of distribution system key according to claim 1 measures decoupling Fast Identification, it is characterised in that: institute
State step 4 method particularly includes: solution is iterated to the part PI normal equation on the basis of step 3, according to iterative formula
Δxk=G-1(xk)HT(xk)R-1[z-h(xk)], obtain state variable changing value Δ x0, and by xk+1=xk+ΔxkAfter obtaining update
State variable x1=x0+Δx0。
5. the method that a kind of distribution system key according to claim 1 measures decoupling Fast Identification, it is characterised in that: institute
State step 5 method particularly includes: according to formula W=[I-H (HTR-1H)-1HTR-1] the v calculating part PI residual sensitivity matrix WPI；
Active power measurement residuals r can be calculated by residual computations formula r=WvP, and further basisD=diag
[WR] calculates standardized residual rPN；
In above formula, I is unit battle array, and H is to measure Jacobian matrix, R-1For the inverse matrix of error in measurement covariance matrix.
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| CN105701568A (en) * | 2016-01-11 | 2016-06-22 | 华北电力大学 | Heuristic power distribution network state estimation measurement position rapid optimization method |
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