CN104638771A - Quantitative analysis method for short-term reliability of process-level network of intelligent substation - Google Patents

Abstract

The invention discloses a quantitative analysis method for the short-term reliability of a process-level network of an intelligent substation. The quantitative analysis method disclosed by the invention is applied to a process-level network of an intelligent substation. According to the quantitative analysis method, a short-term reliability model of a process-level network element is established by using an instantaneous state probability algorithm; the integral instantaneous state probability and the integral instantaneous unavailability as well as the average state probability and the average unavailability of an interval subsystem and the process-level network of the intelligent substation are calculated by combining with a hierarchical equivalence method. According to the quantitative analysis method disclosed by the invention, the instantaneous state probability of each constituent element of the process-level network of the intelligent substation can be analyzed, the calculation scale is greatly reduced, and the reliability parameter convergence procedure of the whole process-level network and each element of the intelligent substation can be described clearly from establishment to initial commissioning to a stable operation process.

Description

The quantitative analysis method of a kind of transformer station process layer network short term reliability

Technical field

The present invention relates to a kind of for intelligent substation reliability engineering field, particularly relate to the computational methods of transformer station process layer network instantaneous state probability and average state probability.

Background technology

Intelligent substation is as the hinge link of electric power system, and be the source and the terminal that gather service data and operation dispatching order, transformer station process layer network then relates to the full data source header at station and the control of switch, plays an important role to the stable operation at full station.Therefore, the safe and reliable operation of transformer station process layer network is significant for guarantee transformer station power supply safety.

Along with the extensive use of practical, the fiber optical network communication technology of IEC61850 establishment of standard, electronic mutual inductor and the universal of intelligent electronic device, the realization for intelligent substation provides good technical foundation.Transformer station process layer network relates to digitlization employing technology, is realized, relate to GOOSE net simultaneously by the cooperation of electronic mutual inductor and merge cells, is realized by the cooperation of intelligent terminal and intelligent switch.The application of these novel electron equipment makes the reliability assessment of transformer station process layer network become more complicated.

Secondary system of intelligent substation builds three layer of two web frame adopted and causes the fusion on 26S Proteasome Structure and Function of relaying protection system, TT&C system and network communicating system, and this brings difficulty to the reliability assessment of transformer station process layer network.

Consider that the existing intelligent substation construction period is shorter, reliability statistics data are imperfect, and the dependability parameter of station equipment may not converge to steady-state value, and traditional Stable reliability appraisal procedure in the case and inapplicable.

The present invention is the weak point overcoming the existence of above-mentioned prior art, the short term reliability quantitative analysis method of transformer station process layer network is provided, analyze the instantaneous state probability of each element of transformer station process layer network, and adopt layering equivalent method to achieve reliability acute assessment that is overall to transformer station process layer network and each introns system, greatly reduce calculating scale, increase computational speed, clearly describe from the initial stage of building up puts into operation again to stable operation process simultaneously, the convergence process of the unavailability ratio of transformer station process layer network entirety and each element.

Summary of the invention

Object of the present invention is exactly to solve the problem, a kind of short term reliability quantitative calculation method for secondary system of intelligent substation is proposed, it have clear logic, algorithm succinct, be easy to the advantage that realizes, provide effective using method for secondary system of intelligent substation short term reliability quantitatively calculates.

To achieve these goals, by the following technical solutions, it comprises in the present invention:

The quantitative analysis method of a kind of transformer station process layer network short term reliability, be applied in transformer station process layer network, transformer station process layer network PLN comprises: public exchange SWC, a n interval switch SWB1-SWBn, n interval merge cells MUB1-MUBn, n Bay Protection Unit PB1-PBn, n interval intelligent terminal ITB1-ITBn, n interval measurement and control unit MCB1-MCBn; Public exchange and n interval switch are Y-connection mode, connect interval merge cells, Bay Protection Unit, interval intelligent terminal, interval measurement and control unit under the switch of each interval;

It is characterized in that: the quantitative analysis method of described transformer station process layer network short term reliability is carried out as follows:

Step 1, the mean time to failure MTTF adding up respective switch and spacer units in described transformer station process layer network and mean time to repair MTTR, calculate failure rate and the repair rate of respective switch and spacer units in described transformer station process layer network;

Step 2, short term reliability modeling is carried out to each element of described transformer station process layer network PLN;

Step 3, interval switch SWB1, interval merge cells MUB1, Bay Protection Unit PB1, interval intelligent terminal ITB1, interval measurement and control unit MCB1 are considered as entirety, be denoted as introns system BSS1, short term reliability quantitative analysis is carried out to introns system BSS1;

Step 4, utilize method described in step 3, by interval switch SWB2-n, interval merge cells MUB2-n, Bay Protection Unit PB2-n, interval intelligent terminal ITB2-n, interval measurement and control unit MCB2-n are considered as entirety, be denoted as introns system BSS2-n respectively, short term reliability quantitative analysis is carried out to introns system BSS2-n;

The value-based algorithms such as step 5, employing layering, calculate and see the equivalent failure rate of introns system BSS1-BSSn and equivalent repair rate;

Step 6, short term reliability quantitative analysis is carried out to the transformer station process layer network PLN be made up of public exchange SWC and n introns system BSS1-n;

Mean time to failure and the mean time to repair of the switch described in step 1 and spacer units comprise:

The mean time to failure MTTF of described center switch SWC _sWCwith MTTR mean time to repair _sWC; The mean time to failure MTTF of described interval switch SWB1-SWBn _sWB1-MTTF _sWBnwith MTTR mean time to repair _sWB1-MTTR _sWBn; The mean time to failure MTTF of described interval merge cells MUB1-MUBn _mUB1-MTTF _mUBnwith MTTR mean time to repair _mUB1-MTTR _mUBn; The mean time to failure MTTF of described Bay Protection Unit PB1-PBn _pB1-MTTF _pBnwith MTTR mean time to repair _pB1-MTTR _pBn; The mean time to failure MTTF of described interval intelligent terminal ITB1-ITBn _iTB1-MTTF _iTBnwith MTTR mean time to repair _iTB1-MTTR _iTBn; The mean time to failure MTTF of described interval measurement and control unit MCB1-MCBn _mCB1-MTTF _mCBnwith MTTR mean time to repair _mCB1-MTTR _mCBn;

Failure rate and the repair rate of the switch described in step 1 and spacer units comprise:

The failure rate λ of described center switch SWC _sWCwith repair rate μ _sWC; The failure rate λ of described interval switch SWB1-SWBn _sWB1-λ _sWBnwith repair rate μ _sWB1-μ _sWBn; The failure rate λ of described interval merge cells MUB1-MUBn _mUB1-λ _mUBnwith repair rate μ _mUB1-μ _mUBn; The failure rate λ of described Bay Protection Unit PB1-PBn _pB1-λ _pBnwith repair rate μ _pB1-μ _pBn; The failure rate λ of described interval intelligent terminal ITB1-ITBn _iTB1-λ _iTBnwith repair rate μ _iTB1-μ _iTBn; The failure rate λ of described interval measurement and control unit MCB1-MCBn _mCB1-λ _mCBnwith repair rate μ _mCB1-μ _mCBn;

Carrying out short term reliability modeling to each element of described transformer station process layer network PLN in step 2 is carry out as follows:

Step 2.1, according to the failure rate λ of described center switch SWC obtained in step 1 _sWCwith repair rate μ _sWC, short term reliability modeling is carried out to center switch SWC;

Adopt state-space method, set up two state models of center switch SWC, the fault subset F of definition center switch SWC _sWC, formed such as formula the state transitions rate matrix Φ shown in (1) _sWC;

${\mathrm{\Φ}}_{\mathrm{SWC}}=\left[\begin{array}{cc}{-\mathrm{\λ}}_{\mathrm{SWC}}& {\mathrm{\λ}}_{\mathrm{SWC}}\\ {\mathrm{\μ}}_{\mathrm{SWC}}& {-\mathrm{\μ}}_{\mathrm{SWC}}\end{array}\right]---\left(1\right)$

Define the initial condition P of described center switch SWC _sWC(t ₀), utilize the instantaneous state probability of formula (2) computer center switch SWC with instantaneous unavailability ratio

$\left\{\begin{array}{c}{P}_{\mathrm{SWC}}^{\mathrm{ins}}\left(t\right)=e^{{\mathrm{\Φ}}_{{\mathrm{SWC}}^t}}{P}_{\mathrm{SWC}}\left(t_0\right)\\ U_{\mathrm{SWC}}^{\mathrm{ins}}=\underset{j\∈F_{\mathrm{BSSn}}}{\mathrm{\Σ}}{P}_{\mathrm{SWC},j}^{\mathrm{ins}}\left(t\right)\end{array}\right.---\left(2\right)$

Step 2.2, according to the failure rate λ of described interval switch SWB1-SWBn obtained in step 1 _sWB1-λ _sWBnwith repair rate μ _sWB1-μ _sWBn, short term reliability modeling is carried out to interval switch SWB1-SWBn;

To arbitrary interval switch SWBi, i=1 ..., n, adopts state-space method, sets up two state models of interval switch SWBi, the fault subset F of definition interval switch SWBi _sWBi, formed such as formula the state transitions rate matrix Φ shown in (3) _sWBi;

${\mathrm{\Φ}}_{\mathrm{SWBi}}=\left[\begin{array}{cc}{-\mathrm{\λ}}_{\mathrm{SWBi}}& {\mathrm{\λ}}_{\mathrm{SWBi}}\\ {\mathrm{\μ}}_{\mathrm{SWBi}}& {-\mathrm{\μ}}_{\mathrm{SWBi}}\end{array}\right]---\left(3\right)$

Define the initial condition P of described center switch SWBi _sWBi(t ₀), utilize the instantaneous state probability of formula (4) computer center switch SWBi with instantaneous unavailability ratio

$\left\{\begin{array}{c}{P}_{\mathrm{SWBi}}^{\mathrm{ins}}\left(t\right)=e^{{\mathrm{\Φ}}_{{\mathrm{SWBi}}^t}}{P}_{\mathrm{SWBi}}\left(t_0\right)\\ U_{\mathrm{SWBi}}^{\mathrm{ins}}=\underset{j\∈F_{\mathrm{BSSn}}}{\mathrm{\Σ}}{P}_{\mathrm{SWBi},j}^{\mathrm{ins}}\left(t\right)\end{array}\right.---\left(4\right)$

Step 2.3, according to the failure rate λ of described interval merge cells MUB1-MUBn obtained in step 1 _mUB1-λ _mUBnwith repair rate μ _mUB1-μ _mUBn, short term reliability modeling is carried out to interval merge cells MUB1-MUBn;

To arbitrary interval merge cells MUBi, i=1 ..., n, adopts state-space method, sets up two state models of interval merge cells MUBi, the fault subset F of definition interval merge cells MUBi _mUBi, formed such as formula the state transitions rate matrix Φ shown in (5) _mUBi;

${\mathrm{\Φ}}_{\mathrm{MUBi}}=\left[\begin{array}{cc}{-\mathrm{\λ}}_{\mathrm{MUBi}}& {\mathrm{\λ}}_{\mathrm{MUBi}}\\ {\mathrm{\μ}}_{\mathrm{MUBi}}& {-\mathrm{\μ}}_{\mathrm{MUBi}}\end{array}\right]---\left(5\right)$

Define the initial condition P of described interval merge cells MUBi _mUBi(t ₀), utilize the instantaneous state probability of formula (6) counting period merge cells MUBi with instantaneous unavailability ratio

$\left\{\begin{array}{c}{P}_{\mathrm{MUBi}}^{\mathrm{ins}}\left(t\right)=e^{{\mathrm{\Φ}}_{{\mathrm{MUBi}}^t}}{P}_{\mathrm{MUBi}}\left(t_0\right)\\ U_{\mathrm{MUBi}}^{\mathrm{ins}}=\underset{j\∈F_{\mathrm{BSSn}}}{\mathrm{\Σ}}{P}_{\mathrm{MUBi},j}^{\mathrm{ins}}\left(t\right)\end{array}\right.---\left(6\right)$

Step 2.4, according to the failure rate λ of described Bay Protection Unit PB1-PBn obtained in step 1 _pB1-λ _pBnwith repair rate μ _pB1-μ _pBn, short term reliability modeling is carried out to Bay Protection Unit PB1-PBn;

To arbitrary interval protected location PBi, i=1 ..., n, adopts state-space method, sets up two state models of Bay Protection Unit PBi, the fault subset F of definition Bay Protection Unit PBi _pBi, formed such as formula the state transitions rate matrix Φ shown in (7) _pBi;

${\mathrm{\Φ}}_{\mathrm{PBi}}=\left[\begin{array}{cc}{-\mathrm{\λ}}_{\mathrm{PBi}}& {\mathrm{\λ}}_{\mathrm{PBi}}\\ {\mathrm{\μ}}_{\mathrm{PBi}}& {-\mathrm{\μ}}_{\mathrm{PBi}}\end{array}\right]---\left(7\right)$

Define the initial condition P of described Bay Protection Unit PBi _pBi(t ₀), utilize the instantaneous state probability of formula (8) counting period protected location PBi with instantaneous unavailability ratio

$\left\{\begin{array}{c}{P}_{\mathrm{PBi}}^{\mathrm{ins}}\left(t\right)=e^{{\mathrm{\Φ}}_{{\mathrm{PBi}}^t}}{P}_{\mathrm{PBi}}\left(t_0\right)\\ U_{\mathrm{PBi}}^{\mathrm{ins}}=\underset{j\∈F_{\mathrm{BSSn}}}{\mathrm{\Σ}}{P}_{\mathrm{PBi},j}^{\mathrm{ins}}\left(t\right)\end{array}\right.---\left(8\right)$

Step 2.5, according to the failure rate λ of described interval intelligent terminal ITB1-ITBn obtained in step 1 _iTB1-λ _iTBnwith repair rate μ _iTB1-μ _iTBn, short term reliability modeling is carried out to interval intelligent terminal ITB1-ITBn;

To arbitrary interval intelligent terminal ITBi, i=1 ..., n, adopts state-space method, sets up two state models of interval intelligent terminal ITBi, the fault subset F of definition interval intelligent terminal ITBi _iTBi, formed such as formula the state transitions rate matrix Φ shown in (9) _iTBi;

${\mathrm{\Φ}}_{\mathrm{ITBi}}=\left[\begin{array}{cc}{-\mathrm{\λ}}_{\mathrm{ITBi}}& {\mathrm{\λ}}_{\mathrm{ITBi}}\\ {\mathrm{\μ}}_{\mathrm{ITBi}}& {-\mathrm{\μ}}_{\mathrm{ITBi}}\end{array}\right]---\left(9\right)$

Define the initial condition P of described interval intelligent terminal ITBi _iTBi(t ₀), utilize the instantaneous state probability of formula (10) counting period intelligent terminal ITBi with instantaneous unavailability ratio

$\left\{\begin{array}{c}{P}_{\mathrm{ITBi}}^{\mathrm{ins}}\left(t\right)=e^{{\mathrm{\Φ}}_{{\mathrm{ITBi}}^t}}{P}_{\mathrm{ITBi}}\left(t_0\right)\\ U_{\mathrm{ITBi}}^{\mathrm{ins}}=\underset{j\∈F_{\mathrm{BSSn}}}{\mathrm{\Σ}}{P}_{\mathrm{ITBi},j}^{\mathrm{ins}}\left(t\right)\end{array}\right.---\left(10\right)$

Step 2.6, according to the failure rate λ of described interval measurement and control unit MCB1-MCBn obtained in step 1 _mCB1-λ _mCBnwith repair rate μ _mCB1-μ _mCBn, short term reliability modeling is carried out to interval measurement and control unit MCB1-MCBn;

To arbitrary interval measurement and control unit MCBi, i=1 ..., n, adopts state-space method, sets up two state models of interval measurement and control unit MCBi, the fault subset F of definition interval measurement and control unit MCBi _mCBi, formed such as formula the state transitions rate matrix Φ shown in (11) _mCBi;

${\mathrm{\Φ}}_{\mathrm{MCBi}}=\left[\begin{array}{cc}{-\mathrm{\λ}}_{\mathrm{MCBi}}& {\mathrm{\λ}}_{\mathrm{MCBi}}\\ {\mathrm{\μ}}_{\mathrm{MCBi}}& {-\mathrm{\μ}}_{\mathrm{MCBi}}\end{array}\right]---\left(11\right)$

Define the initial condition P of described interval measurement and control unit MCBi _mCBi(t ₀), utilize the instantaneous state probability of formula (12) counting period measurement and control unit MCBi with instantaneous unavailability ratio

$\left\{\begin{array}{c}{P}_{\mathrm{MCBi}}^{\mathrm{ins}}\left(t\right)=e^{{\mathrm{\Φ}}_{{\mathrm{MCBi}}^t}}{P}_{\mathrm{MCBi}}\left(t_0\right)\\ U_{\mathrm{MCBi}}^{\mathrm{ins}}=\underset{j\∈F_{\mathrm{BSSn}}}{\mathrm{\Σ}}{P}_{\mathrm{MCBi},j}^{\mathrm{ins}}\left(t\right)\end{array}\right.---\left(12\right)$

In step 3, the short term reliability quantitative analysis method of described introns system BSS1 carries out as follows:

Step 3.1, employing state-space method, set up six state models of introns system BSS1, the fault subset F of definition introns system BSS1 _bSS1, formed such as formula the state transitions rate matrix Φ shown in (13) _bSS1;

${\mathrm{\Φ}}_{\mathrm{BSS}1}=\left[\begin{array}{cccccc}-{\mathrm{\λ}}_{B1}& {\mathrm{\λ}}_{\mathrm{SWB}1}& {\mathrm{\λ}}_{\mathrm{MUB}1}& {\mathrm{\λ}}_{\mathrm{PB}1}& {\mathrm{\λ}}_{\mathrm{ITB}1}& {\mathrm{\λ}}_{\mathrm{MCB}1}\\ {\mathrm{\μ}}_{\mathrm{SWB}1}& -{\mathrm{\μ}}_{\mathrm{SWB}1}& & & & \\ {\mathrm{\μ}}_{\mathrm{MUB}1}& & -{\mathrm{\μ}}_{\mathrm{MUB}1}& & & \\ {\mathrm{\μ}}_{\mathrm{PB}1}& & & -{\mathrm{\μ}}_{\mathrm{PB}1}& & \\ {\mathrm{\μ}}_{\mathrm{ITB}1}& & & & -{\mathrm{\μ}}_{\mathrm{ITB}1}& \\ {\mathrm{\μ}}_{\mathrm{MCB}1}& & & & & -{\mathrm{\μ}}_{\mathrm{MCB}1}\end{array}\right]---\left(13\right)$

Wherein, λ _b1=λ _sWB1+ λ _mUB1+ λ _pB1+ λ _iTB1+ λ _mCB1;

Step 3.2, consider state transitions rate matrix Φ _bSS1irreversible, utilize elementary transformation to split it, form equivalent rate of transform Matrix C _bSS1with compensation matrix D _bSS1; By state transitions rate matrix Φ _bSS1launch such as formula (1), deduct the 6th column element with the 1st to the 5th column element successively, get front 5 row, 5 column elements form equivalent rate of transform Matrix C _bSS1such as formula (14); Compensation matrix D is formed by the 1 to 5 row, the 6th column element _bSS1such as formula (15);

$C_{\mathrm{BSS}1}=\left[\begin{array}{ccccc}-{\mathrm{\λ}}_{B1}-{\mathrm{\λ}}_{\mathrm{MCB}1}& {\mathrm{\λ}}_{\mathrm{SWB}1}-{\mathrm{\λ}}_{\mathrm{MCB}1}& {\mathrm{\λ}}_{\mathrm{MUB}1}-{\mathrm{\λ}}_{\mathrm{MCB}1}& {\mathrm{\λ}}_{\mathrm{PB}1}-{\mathrm{\λ}}_{\mathrm{MCB}1}& {\mathrm{\λ}}_{\mathrm{ITB}1}-{\mathrm{\λ}}_{\mathrm{MCB}1}\\ {\mathrm{\μ}}_{\mathrm{SWB}1}& -{\mathrm{\μ}}_{\mathrm{SWB}1}& & & \\ {\mathrm{\μ}}_{\mathrm{MUB}1}& & -{\mathrm{\μ}}_{\mathrm{MUB}1}& & \\ {\mathrm{\μ}}_{\mathrm{PB}1}& & & -{\mathrm{\μ}}_{\mathrm{PB}1}& \\ {\mathrm{\μ}}_{\mathrm{ITB}1}& & & & -{\mathrm{\μ}}_{\mathrm{ITB}1}\end{array}\right]---\left(14\right)$

D _BSS1＝[λ _MCB10 0 0 0] ^T(15)

Step 3.3, define the initial condition P of described introns system BSS1 _bSS1(t ₀); By initial condition matrix P _bSS1(t ₀), equivalent rate of transform Matrix C _bSS1with compensation matrix D _bSS1, utilize formula (16) to calculate the instantaneous state probability of described introns system BSS1 under different initial condition and instantaneous degree of unavailability

$\left\{\begin{array}{c}{P}_{\mathrm{BSS}1}^{\mathrm{ins}}\left(t\right)=C_{\mathrm{BSS}1}^{-1}[P_{\mathrm{BSS}1}\left(t_0\right)+C_{\mathrm{BSS}1}^{-1}{D}_{\mathrm{BSS}1}]-C_{\mathrm{BSS}1}^{-1}{D}_{\mathrm{BSS}1}\\ U_{\mathrm{BSS}1}^{\mathrm{ins}}=\underset{j\∈F_{\mathrm{BSS}1}}{\mathrm{\Σ}}{P}_{\mathrm{BSS}1,j}^{\mathrm{ins}}\left(t\right)\end{array}\right.---\left(16\right)$

Step 3.4, utilize formula (17) calculate at short term reliability assessment cycle [t ₀, t ₁] in the mean state probability of described introns system BSS1 with average degree of unavailability

$\left\{\begin{array}{c}{P}_{\mathrm{BSS}1}^{\mathrm{ave}}=\frac{C_{\mathrm{BSS}1}^{-1}[P_{\mathrm{BSS}1}^{\mathrm{ins}}\left(t_1\right)-P_{\mathrm{BSS}1}^{\mathrm{ins}}\left(t_0\right)]}{t_1-t_0}-C_{\mathrm{BSS}1}^{-1}{D}_{\mathrm{BSS}1}\\ U_{\mathrm{BSS}1}^{\mathrm{ave}}=\underset{j\∈F_{\mathrm{BSS}1}}{\mathrm{\Σ}}{P}_{\mathrm{BSS}1,j}^{\mathrm{ave}}\end{array}\right.---\left(17\right)$

In step 4, utilize described short term reliability quantitative analysis method, utilize formula (18) and (19) to calculate arbitrary interval subsystem BSSi, i=1 ..., n, instantaneous state probability with instantaneous degree of unavailability and mean state probability with average degree of unavailability

$\left\{\begin{array}{c}{P}_{\mathrm{BSSi}}^{\mathrm{ins}}\left(t\right)=C_{\mathrm{BSSi}}^{-1}[P_{\mathrm{BSSi}}\left(t_0\right)+C_{\mathrm{BSSi}}^{-1}{D}_{\mathrm{BSSi}}]-C_{\mathrm{BSSi}}^{-1}{D}_{\mathrm{BSSi}}\\ U_{\mathrm{BSSi}}^{\mathrm{ins}}=\underset{j\∈F_{\mathrm{BSSi}}}{\mathrm{\Σ}}{P}_{\mathrm{BSSi},j}^{\mathrm{ins}}\left(t\right)\end{array}\right.---\left(18\right)$

$\left\{\begin{array}{c}{P}_{\mathrm{BSSi}}^{\mathrm{ave}}=\frac{C_{\mathrm{BSSi}}^{-1}[P_{\mathrm{BSSi}}^{\mathrm{ins}}\left(t_1\right)-P_{\mathrm{BSSi}}^{\mathrm{ins}}\left(t_0\right)]}{t_1-t_0}-C_{\mathrm{BSSi}}^{-1}{D}_{\mathrm{BSSi}}\\ U_{\mathrm{BSSi}}^{\mathrm{ave}}=\underset{j\∈F_{\mathrm{BSSi}}}{\mathrm{\Σ}}{P}_{\mathrm{BSSi},j}^{\mathrm{ave}}\end{array}\right.---\left(19\right)$

In step 5, adopt layering equivalence method, obtain the equivalent fault rate λ of introns system BSS1-BSSn _bSS1-λ _bSSnwith equivalent repair rate μ _bSS1-μ _bSSn;

The short term reliability appraisal procedure of the layer network of transformer station process described in step 6 PLN is carried out as follows:

Step 6.1, employing state-space method, the n+1 state model of process of establishing layer network PLN, the fault subset F of definition procedure layer network PLN _pLN, formed such as formula the state transitions rate matrix Φ shown in (20) _pLN;

Step 6.2, consider state transitions rate matrix Φ _pLNirreversible, utilize elementary transformation to split it, form equivalent rate of transform Matrix C _pLNwith compensation matrix D _pLN; By state transitions rate matrix Φ _pLNlaunch such as formula (1), deduct the (n+1)th column element with the 1 to the n-th column element successively, get that front n is capable, n column element forms equivalent rate of transform Matrix C _pLNsuch as formula (21); , (n+1)th column element capable by 1 to n forms compensation matrix D _pLNsuch as formula (22);

D _PLN＝[λ _BSSn0 0 0 0] ^T(22)

Step 6.3, define the initial condition P of described process-level network PLN _pLN(t ₀); By initial condition matrix P _pLN(t ₀), equivalent rate of transform Matrix C _pLNwith compensation matrix D _pLN, utilize formula (23) to calculate the instantaneous state probability of described introns system BSS1 under different initial condition and instantaneous degree of unavailability

$\left\{\begin{array}{c}{P}_{\mathrm{PLN}}^{\mathrm{ins}}\left(t\right)=C_{\mathrm{PLN}}^{-1}[P_{\mathrm{PLN}}\left(t_0\right)+C_{\mathrm{PLN}}^{-1}{D}_{\mathrm{PLN}}]-C_{\mathrm{PLN}}^{-1}{D}_{\mathrm{PLN}}\\ U_{\mathrm{PLN}}^{\mathrm{ins}}=\underset{j\∈F_{\mathrm{BSS}1}}{\mathrm{\Σ}}{P}_{\mathrm{PLN},j}^{\mathrm{ins}}\left(t\right)\end{array}\right.---\left(23\right)$

Step 6.4, utilize formula (24) calculate at short term reliability assessment cycle [t ₀, t ₁] in the mean state probability of described introns system BSS1 with average degree of unavailability

$\left\{\begin{array}{c}{P}_{\mathrm{PLN}}^{\mathrm{ave}}=\frac{C_{\mathrm{PLN}}^{-1}[P_{\mathrm{PLN}}^{\mathrm{ins}}\left(t_1\right)-P_{\mathrm{PLN}}^{\mathrm{ins}}\left(t_0\right)]}{t_1-t_0}-C_{\mathrm{PLN}}^{-1}{D}_{\mathrm{PLN}}\\ U_{\mathrm{PLN}}^{\mathrm{ave}}=\underset{j\∈F_{\mathrm{BSS}1}}{\mathrm{\Σ}}{P}_{\mathrm{PLN},j}^{\mathrm{ave}}\end{array}\right.---\left(24\right)$

Compared with prior art, advantage of the present invention is:

1., for transformer station process layer network, introduce the concept of short term reliability, utilize equivalent rate of transform matrix, can quantitative computational process layer network short term reliability parameter;

2. the present invention completes the short term reliability quantitative analysis to transformer station process layer network introns system and element, acquisition short term reliability parameter can be used for the change convergence process describing transformer station process layer network element unavailability ratio;

3. in instantaneous state probability calculation process, consider the complexity of transformer station process layer network structure, the equivalent fault rate of each introns system after adopting equivalence to merge and repair rate replace failure rate and the repair rate of each interval switch and spacer units, avoid dimension disaster, effectively improve arithmetic speed;

4. the present invention adopts mean state probability to carry out the system reliability of quantitative description transformer station process layer network within assessment cycle [t0, t1], avoids the error adopting the instantaneous state probability of state at the whole story to cause;

Accompanying drawing explanation

Fig. 1 is transformer station process layer network structure chart in the present invention;

Fig. 2 is two state models of center switch in the present invention;

Fig. 3 is two state models of interval switch in the present invention;

Fig. 4 is two state models of interval merge cells in the present invention;

Fig. 5 is two state models of Bay Protection Unit in the present invention;

Fig. 6 is two state models of interval intelligent terminal in the present invention;

Fig. 7 is two state models of interval measurement and control unit in the present invention;

Fig. 8 is six state models of interval subsystem in the present invention;

Fig. 9 is equivalence two state model of interval subsystem in the present invention;

Figure 10 is the n+2 state model of process-level network in the present invention;

Specific embodiments

In this example, the quantitative analysis method of a kind of transformer station process layer network short term reliability, be applied in transformer station process layer network, as shown in Figure 1, transformer station process layer network PLN comprises: public exchange SWC, n interval switch SWB1 ?SWBn, n interval merge cells MUB1 ?MUBn, n Bay Protection Unit PB1 ?PBn, n interval intelligent terminal ITB1 ?ITBn, n interval measurement and control unit MCB1 ?MCBn; Public exchange and n interval switch are Y-connection mode, connect interval merge cells, Bay Protection Unit, interval intelligent terminal, interval measurement and control unit under the switch of each interval;

The quantitative analysis method of transformer station process layer network short term reliability is carried out as follows:

Step 1, the mean time to failure MTTF adding up respective switch and spacer units in described transformer station process layer network and mean time to repair MTTR, calculate failure rate and the repair rate of respective switch and spacer units in described transformer station process layer network;

Step 2, short term reliability modeling is carried out to each element of described transformer station process layer network PLN;

Step 3, interval switch SWB1, interval merge cells MUB1, Bay Protection Unit PB1, interval intelligent terminal ITB1, interval measurement and control unit MCB1 are considered as entirety, be denoted as introns system BSS1, short term reliability quantitative analysis is carried out to introns system BSS1;

Step 4, utilize method described in step 3, by interval switch SWB2-n, interval merge cells MUB2-n, Bay Protection Unit PB2-n, interval intelligent terminal ITB2-n, interval measurement and control unit MCB2-n are considered as entirety, be denoted as introns system BSS2-n respectively, short term reliability quantitative analysis is carried out to introns system BSS2-n;

The value-based algorithms such as step 5, employing layering, calculate and see the equivalent failure rate of introns system BSS1-BSSn and equivalent repair rate;

Step 6, short term reliability quantitative analysis is carried out to the transformer station process layer network PLN be made up of public exchange SWC and n introns system BSS1-n;

Mean time to failure and the mean time to repair of the switch described in step 1 and spacer units comprise:

The mean time to failure MTTF of described center switch SWC _sWCwith MTTR mean time to repair _sWC; The mean time to failure MTTF of described interval switch SWB1-SWBn _sWB1-MTTF _sWBnwith MTTR mean time to repair _sWB1-MTTR _sWBn; The mean time to failure MTTF of described interval merge cells MUB1-MUBn _mUB1-MTTF _mUBnwith MTTR mean time to repair _mUB1-MTTR _mUBn; The mean time to failure MTTF of described Bay Protection Unit PB1-PBn _pB1-MTTF _pBnwith MTTR mean time to repair _pB1-MTTR _pBn; The mean time to failure MTTF of described interval intelligent terminal ITB1-ITBn _iTB1-MTTF _iTBnwith MTTR mean time to repair _iTB1-MTTR _iTBn; The mean time to failure MTTF of described interval measurement and control unit MCB1-MCBn _mCB1-MTTF _mCBnwith MTTR mean time to repair _mCB1-MTTR _mCBn;

Failure rate and the repair rate of the switch described in step 1 and spacer units comprise:

The failure rate λ of described center switch SWC _sWCwith repair rate μ _sWC; The failure rate λ of described interval switch SWB1-SWBn _sWB1-λ _sWBnwith repair rate μ _sWB1-μ _sWBn; The failure rate λ of described interval merge cells MUB1-MUBn _mUB1-λ _mUBnwith repair rate μ _mUB1-μ _mUBn; The failure rate λ of described Bay Protection Unit PB1-PBn _pB1-λ _pBnwith repair rate μ _pB1-μ _pBn; The failure rate λ of described interval intelligent terminal ITB1-ITBn _iTB1-λ _iTBnwith repair rate μ _iTB1-μ _iTBn; The failure rate λ of described interval measurement and control unit MCB1-MCBn _mCB1-λ _mCBnwith repair rate μ _mCB1-μ _mCBn;

Carrying out short term reliability quantitative analysis to each element of described transformer station process layer network PLN in step 2 is carry out as follows:

Step 2.1, according to the failure rate λ of described center switch SWC obtained in step 1 _sWCwith repair rate μ _sWC, short term reliability modeling is carried out to center switch SWC;

Adopt state-space method, set up two state models of center switch SWC as shown in Figure 2, the fault subset F of definition center switch SWC _sWC, formed such as formula the state transitions rate matrix Φ shown in (1) _sWC;

${\mathrm{\Φ}}_{\mathrm{SWC}}=\left[\begin{array}{cc}{-\mathrm{\λ}}_{\mathrm{SWC}}& {\mathrm{\λ}}_{\mathrm{SWC}}\\ {\mathrm{\μ}}_{\mathrm{SWC}}& {-\mathrm{\μ}}_{\mathrm{SWC}}\end{array}\right]---\left(1\right)$

Define the initial condition P of described center switch SWC _sWC(t ₀), utilize the instantaneous state probability of formula (2) computer center switch SWC with instantaneous unavailability ratio

$\left\{\begin{array}{c}{P}_{\mathrm{SWC}}^{\mathrm{ins}}\left(t\right)=e^{{\mathrm{\Φ}}_{{\mathrm{SWC}}^t}}{P}_{\mathrm{SWC}}\left(t_0\right)\\ U_{\mathrm{SWC}}^{\mathrm{ins}}=\underset{j\∈F_{\mathrm{BSSn}}}{\mathrm{\Σ}}{P}_{\mathrm{SWC},j}^{\mathrm{ins}}\left(t\right)\end{array}\right.---\left(2\right)$

Step 2.2, according to the failure rate λ of described interval switch SWB1-SWBn obtained in step 1 _sWB1-λ _sWBnwith repair rate μ _sWB1-μ _sWBn, short term reliability modeling is carried out to interval switch SWB1-SWBn;

To arbitrary interval switch SWBi, i=1 ..., n, adopts state-space method, sets up two state models of interval switch SWBi as shown in Figure 3, the fault subset F of definition interval switch SWBi _sWBi, formed such as formula the state transitions rate matrix Φ shown in (3) _sWBi;

${\mathrm{\Φ}}_{\mathrm{SWBi}}=\left[\begin{array}{cc}{-\mathrm{\λ}}_{\mathrm{SWBi}}& {\mathrm{\λ}}_{\mathrm{SWBi}}\\ {\mathrm{\μ}}_{\mathrm{SWBi}}& {-\mathrm{\μ}}_{\mathrm{SWBi}}\end{array}\right]---\left(3\right)$

Define the initial condition P of described center switch SWBi _sWBi(t ₀), utilize the instantaneous state probability of formula (4) computer center switch SWBi with instantaneous unavailability ratio

$\left\{\begin{array}{c}{P}_{\mathrm{SWBi}}^{\mathrm{ins}}\left(t\right)=e^{{\mathrm{\Φ}}_{{\mathrm{SWBi}}^t}}{P}_{\mathrm{SWBi}}\left(t_0\right)\\ U_{\mathrm{SWBi}}^{\mathrm{ins}}=\underset{j\∈F_{\mathrm{BSSn}}}{\mathrm{\Σ}}{P}_{\mathrm{SWBi},j}^{\mathrm{ins}}\left(t\right)\end{array}\right.---\left(4\right)$

Step 2.3, according to the failure rate λ of described interval merge cells MUB1-MUBn obtained in step 1 _mUB1-λ _mUBnwith repair rate μ _mUB1-μ _mUBn, short term reliability modeling is carried out to interval merge cells MUB1-MUBn;

To arbitrary interval merge cells MUBi, i=1 ..., n, adopts state-space method, sets up two state models of interval merge cells MUBi as shown in Figure 4, the fault subset F of definition interval merge cells MUBi _mUBi, formed such as formula the state transitions rate matrix Φ shown in (5) _mUBi;

${\mathrm{\Φ}}_{\mathrm{MUBi}}=\left[\begin{array}{cc}{-\mathrm{\λ}}_{\mathrm{MUBi}}& {\mathrm{\λ}}_{\mathrm{MUBi}}\\ {\mathrm{\μ}}_{\mathrm{MUBi}}& {-\mathrm{\μ}}_{\mathrm{MUBi}}\end{array}\right]---\left(5\right)$

Define the initial condition P of described interval merge cells MUBi _mUBi(t ₀), utilize the instantaneous state probability of formula (6) counting period merge cells MUBi with instantaneous unavailability ratio

$\left\{\begin{array}{c}{P}_{\mathrm{MUBi}}^{\mathrm{ins}}\left(t\right)=e^{{\mathrm{\Φ}}_{{\mathrm{MUBi}}^t}}{P}_{\mathrm{MUBi}}\left(t_0\right)\\ U_{\mathrm{MUBi}}^{\mathrm{ins}}=\underset{j\∈F_{\mathrm{BSSn}}}{\mathrm{\Σ}}{P}_{\mathrm{MUBi},j}^{\mathrm{ins}}\left(t\right)\end{array}\right.---\left(6\right)$

Step 2.4, according to the failure rate λ of described Bay Protection Unit PB1-PBn obtained in step 1 _pB1-λ _pBnwith repair rate μ _pB1-μ _pBn, short term reliability modeling is carried out to Bay Protection Unit PB1-PBn;

To arbitrary interval protected location PBi, i=1 ..., n, adopts state-space method, sets up two state models of Bay Protection Unit PBi as shown in Figure 5, the fault subset F of definition Bay Protection Unit PBi _pBi, formed such as formula the state transitions rate matrix Φ shown in (7) _pBi;

${\mathrm{\Φ}}_{\mathrm{PBi}}=\left[\begin{array}{cc}{-\mathrm{\λ}}_{\mathrm{PBi}}& {\mathrm{\λ}}_{\mathrm{PBi}}\\ {\mathrm{\μ}}_{\mathrm{PBi}}& {-\mathrm{\μ}}_{\mathrm{PBi}}\end{array}\right]---\left(7\right)$

Define the initial condition P of described Bay Protection Unit PBi _pBi(t ₀), utilize the instantaneous state probability of formula (8) counting period protected location PBi with instantaneous unavailability ratio

$\left\{\begin{array}{c}{P}_{\mathrm{PBi}}^{\mathrm{ins}}\left(t\right)=e^{{\mathrm{\Φ}}_{{\mathrm{PBi}}^t}}{P}_{\mathrm{PBi}}\left(t_0\right)\\ U_{\mathrm{PBi}}^{\mathrm{ins}}=\underset{j\∈F_{\mathrm{BSSn}}}{\mathrm{\Σ}}{P}_{\mathrm{PBi},j}^{\mathrm{ins}}\left(t\right)\end{array}\right.---\left(8\right)$

Step 2.5, according to the failure rate λ of described interval intelligent terminal ITB1-ITBn obtained in step 1 _iTB1-λ _iTBnwith repair rate μ _iTB1-μ _iTBn, short term reliability modeling is carried out to interval intelligent terminal ITB1-ITBn;

To arbitrary interval intelligent terminal ITBi, i=1 ..., n, adopts state-space method, sets up two state models of interval intelligent terminal ITBi as shown in Figure 6, the fault subset F of definition interval intelligent terminal ITBi _iTBi, formed such as formula the state transitions rate matrix Φ shown in (9) _iTBi;

${\mathrm{\Φ}}_{\mathrm{ITBi}}=\left[\begin{array}{cc}{-\mathrm{\λ}}_{\mathrm{ITBi}}& {\mathrm{\λ}}_{\mathrm{ITBi}}\\ {\mathrm{\μ}}_{\mathrm{ITBi}}& {-\mathrm{\μ}}_{\mathrm{ITBi}}\end{array}\right]---\left(9\right)$

Define the initial condition P of described interval intelligent terminal ITBi _iTBi(t ₀), utilize the instantaneous state probability of formula (10) counting period intelligent terminal ITBi with instantaneous unavailability ratio

$\left\{\begin{array}{c}{P}_{\mathrm{ITBi}}^{\mathrm{ins}}\left(t\right)=e^{{\mathrm{\Φ}}_{{\mathrm{ITBi}}^t}}{P}_{\mathrm{ITBi}}\left(t_0\right)\\ U_{\mathrm{ITBi}}^{\mathrm{ins}}=\underset{j\∈F_{\mathrm{BSSn}}}{\mathrm{\Σ}}{P}_{\mathrm{ITBi},j}^{\mathrm{ins}}\left(t\right)\end{array}\right.---\left(10\right)$

Step 2.6, according to the failure rate λ of described interval measurement and control unit MCB1-MCBn obtained in step 1 _mCB1-λ _mCBnwith repair rate μ _mCB1-μ _mCBn, short term reliability modeling is carried out to interval measurement and control unit MCB1-MCBn;

To arbitrary interval measurement and control unit MCBi, i=1 ..., n, adopts state-space method, sets up two state models of interval measurement and control unit MCBi as shown in Figure 7, the fault subset F of definition interval measurement and control unit MCBi _mCBi, formed such as formula the state transitions rate matrix Φ shown in (11) _mCBi;

${\mathrm{\Φ}}_{\mathrm{MCBi}}=\left[\begin{array}{cc}{-\mathrm{\λ}}_{\mathrm{MCBi}}& {\mathrm{\λ}}_{\mathrm{MCBi}}\\ {\mathrm{\μ}}_{\mathrm{MCBi}}& {-\mathrm{\μ}}_{\mathrm{MCBi}}\end{array}\right]---\left(11\right)$

Define the initial condition P of described interval measurement and control unit MCBi _mCBi(t ₀), utilize the instantaneous state probability of formula (12) counting period measurement and control unit MCBi with instantaneous unavailability ratio

$\left\{\begin{array}{c}{P}_{\mathrm{MCBi}}^{\mathrm{ins}}\left(t\right)=e^{{\mathrm{\Φ}}_{{\mathrm{MCBi}}^t}}{P}_{\mathrm{MCBi}}\left(t_0\right)\\ U_{\mathrm{MCBi}}^{\mathrm{ins}}=\underset{j\∈F_{\mathrm{BSSn}}}{\mathrm{\Σ}}{P}_{\mathrm{MCBi},j}^{\mathrm{ins}}\left(t\right)\end{array}\right.---\left(12\right)$

In step 3, the short term reliability quantitative analysis method of described introns system BSS1 carries out as follows:

Step 3.1, employing state-space method, set up six state models of introns system BSS1 as shown in Figure 8, the fault subset F of definition introns system BSS1 _bSS1, formed such as formula the state transitions rate matrix Φ shown in (13) _bSS1;

${\mathrm{\Φ}}_{\mathrm{BSS}1}=\left[\begin{array}{cccccc}-{\mathrm{\λ}}_{B1}& {\mathrm{\λ}}_{\mathrm{SWB}1}& {\mathrm{\λ}}_{\mathrm{MUB}1}& {\mathrm{\λ}}_{\mathrm{PB}1}& {\mathrm{\λ}}_{\mathrm{ITB}1}& {\mathrm{\λ}}_{\mathrm{MCB}1}\\ {\mathrm{\μ}}_{\mathrm{SWB}1}& -{\mathrm{\μ}}_{\mathrm{SWB}1}& & & & \\ {\mathrm{\μ}}_{\mathrm{MUB}1}& & -{\mathrm{\μ}}_{\mathrm{MUB}1}& & & \\ {\mathrm{\μ}}_{\mathrm{PB}1}& & & -{\mathrm{\μ}}_{\mathrm{PB}1}& & \\ {\mathrm{\μ}}_{\mathrm{ITB}1}& & & & -{\mathrm{\μ}}_{\mathrm{ITB}1}& \\ {\mathrm{\μ}}_{\mathrm{MCB}1}& & & & & -{\mathrm{\μ}}_{\mathrm{MCB}1}\end{array}\right]---\left(13\right)$

Wherein, λ _b1=λ _sWB1+ λ _mUB1+ λ _pB1+ λ _iTB1+ λ _mCB1;

Step 3.2, consider state transitions rate matrix Φ _bSS1irreversible, utilize elementary transformation to split it, form equivalent rate of transform Matrix C _bSS1with compensation matrix D _bSS1; By state transitions rate matrix Φ _bSS1launch such as formula (1), deduct the 6th column element with the 1st to the 5th column element successively, get front 5 row, 5 column elements form equivalent rate of transform Matrix C _bSS1such as formula (14); Compensation matrix D is formed by the 1 to 5 row, the 6th column element _bSS1such as formula (15);

$C_{\mathrm{BSS}1}=\left[\begin{array}{ccccc}-{\mathrm{\λ}}_{B1}-{\mathrm{\λ}}_{\mathrm{MCB}1}& {\mathrm{\λ}}_{\mathrm{SWB}1}-{\mathrm{\λ}}_{\mathrm{MCB}1}& {\mathrm{\λ}}_{\mathrm{MUB}1}-{\mathrm{\λ}}_{\mathrm{MCB}1}& {\mathrm{\λ}}_{\mathrm{PB}1}-{\mathrm{\λ}}_{\mathrm{MCB}1}& {\mathrm{\λ}}_{\mathrm{ITB}1}-{\mathrm{\λ}}_{\mathrm{MCB}1}\\ {\mathrm{\μ}}_{\mathrm{SWB}1}& -{\mathrm{\μ}}_{\mathrm{SWB}1}& & & \\ {\mathrm{\μ}}_{\mathrm{MUB}1}& & -{\mathrm{\μ}}_{\mathrm{MUB}1}& & \\ {\mathrm{\μ}}_{\mathrm{PB}1}& & & -{\mathrm{\μ}}_{\mathrm{PB}1}& \\ {\mathrm{\μ}}_{\mathrm{ITB}1}& & & & -{\mathrm{\μ}}_{\mathrm{ITB}1}\end{array}\right]---\left(14\right)$

D _BSS1＝[λ _MCB10 0 0 0] ^T(15)

Step 3.3, define the initial condition P of described introns system BSS1 _bSS1(t ₀); By initial condition matrix P _bSS1(t ₀), equivalent rate of transform Matrix C _bSS1with compensation matrix D _bSS1, utilize formula (16) to calculate the instantaneous state probability of described introns system BSS1 under different initial condition and instantaneous degree of unavailability

$\left\{\begin{array}{c}{P}_{\mathrm{BSS}1}^{\mathrm{ins}}\left(t\right)=C_{\mathrm{BSS}1}^{-1}[P_{\mathrm{BSS}1}\left(t_0\right)+C_{\mathrm{BSS}1}^{-1}{D}_{\mathrm{BSS}1}]-C_{\mathrm{BSS}1}^{-1}{D}_{\mathrm{BSS}1}\\ U_{\mathrm{BSS}1}^{\mathrm{ins}}=\underset{j\∈F_{\mathrm{BSS}1}}{\mathrm{\Σ}}{P}_{\mathrm{BSS}1,j}^{\mathrm{ins}}\left(t\right)\end{array}\right.---\left(16\right)$

Step 3.4, utilize formula (17) calculate at short term reliability assessment cycle [t ₀, t ₁] in the mean state probability of described introns system BSS1 with average degree of unavailability

$\left\{\begin{array}{c}{P}_{\mathrm{BSS}1}^{\mathrm{ave}}=\frac{C_{\mathrm{BSS}1}^{-1}[P_{\mathrm{BSS}1}^{\mathrm{ins}}\left(t_1\right)-P_{\mathrm{BSS}1}^{\mathrm{ins}}\left(t_0\right)]}{t_1-t_0}-C_{\mathrm{BSS}1}^{-1}{D}_{\mathrm{BSS}1}\\ U_{\mathrm{BSS}1}^{\mathrm{ave}}=\underset{j\∈F_{\mathrm{BSS}1}}{\mathrm{\Σ}}{P}_{\mathrm{BSS}1,j}^{\mathrm{ave}}\end{array}\right.---\left(17\right)$

In step 4, utilize described short term reliability quantitative analysis method, utilize formula (18) and (19) to calculate arbitrary interval subsystem BSSi, i=1 ..., n, instantaneous state probability with instantaneous degree of unavailability and mean state probability with average degree of unavailability

$\left\{\begin{array}{c}{P}_{\mathrm{BSSi}}^{\mathrm{ins}}\left(t\right)=C_{\mathrm{BSSi}}^{-1}[P_{\mathrm{BSSi}}\left(t_0\right)+C_{\mathrm{BSSi}}^{-1}{D}_{\mathrm{BSSi}}]-C_{\mathrm{BSSi}}^{-1}{D}_{\mathrm{BSSi}}\\ U_{\mathrm{BSSi}}^{\mathrm{ins}}=\underset{j\∈F_{\mathrm{BSSi}}}{\mathrm{\Σ}}{P}_{\mathrm{BSSi},j}^{\mathrm{ins}}\left(t\right)\end{array}\right.---\left(18\right)$

$\left\{\begin{array}{c}{P}_{\mathrm{BSSi}}^{\mathrm{ave}}=\frac{C_{\mathrm{BSSi}}^{-1}[P_{\mathrm{BSSi}}^{\mathrm{ins}}\left(t_1\right)-P_{\mathrm{BSSi}}^{\mathrm{ins}}\left(t_0\right)]}{t_1-t_0}-C_{\mathrm{BSSi}}^{-1}{D}_{\mathrm{BSSi}}\\ U_{\mathrm{BSSi}}^{\mathrm{ave}}=\underset{j\∈F_{\mathrm{BSSi}}}{\mathrm{\Σ}}{P}_{\mathrm{BSSi},j}^{\mathrm{ave}}\end{array}\right.---\left(19\right)$

In step 5, adopt layering equivalence method, set up introns system equivalence two state models as shown in Figure 9, obtain the equivalent fault rate λ of introns system BSS1-BSSn _bSS1-λ _bSSnwith equivalent repair rate μ _bSS1-μ _bSSn;

The short term reliability appraisal procedure of the layer network of transformer station process described in step 6 PLN is carried out as follows:

Step 6.1, employing state-space method, set up the n+1 state model of process-level network PLN as shown in Figure 10, the fault subset F of definition procedure layer network PLN _pLN, formed such as formula the state transitions rate matrix Φ shown in (20) _pLN;

Step 6.2, consider state transitions rate matrix Φ _pLNirreversible, utilize elementary transformation to split it, form equivalent rate of transform Matrix C _pLNwith compensation matrix D _pLN; By state transitions rate matrix Φ _pLNlaunch such as formula (1), deduct the (n+1)th column element with the 1 to the n-th column element successively, get that front n is capable, n column element forms equivalent rate of transform Matrix C _pLNsuch as formula (21); , (n+1)th column element capable by 1 to n forms compensation matrix D _pLNsuch as formula (22);

D _PLN＝[λ _BSSn0 0 0 0] ^T(22)

Step 6.3, define the initial condition P of described process-level network PLN _pLN(t ₀); By initial condition matrix P _pLN(t ₀), equivalent rate of transform Matrix C _pLNwith compensation matrix D _pLN, utilize formula (23) to calculate the instantaneous state probability of described introns system BSS1 under different initial condition and instantaneous degree of unavailability

$\left\{\begin{array}{c}{P}_{\mathrm{PLN}}^{\mathrm{ins}}\left(t\right)=C_{\mathrm{PLN}}^{-1}[P_{\mathrm{PLN}}\left(t_0\right)+C_{\mathrm{PLN}}^{-1}{D}_{\mathrm{PLN}}]-C_{\mathrm{PLN}}^{-1}{D}_{\mathrm{PLN}}\\ U_{\mathrm{PLN}}^{\mathrm{ins}}=\underset{j\∈F_{\mathrm{BSS}1}}{\mathrm{\Σ}}{P}_{\mathrm{PLN},j}^{\mathrm{ins}}\left(t\right)\end{array}\right.---\left(23\right)$

Step 6.4, utilize formula (24) calculate at short term reliability assessment cycle [t ₀, t ₁] in the mean state probability of described introns system BSS1 with average degree of unavailability

$\left\{\begin{array}{c}{P}_{\mathrm{PLN}}^{\mathrm{ave}}=\frac{C_{\mathrm{PLN}}^{-1}[P_{\mathrm{PLN}}^{\mathrm{ins}}\left(t_1\right)-P_{\mathrm{PLN}}^{\mathrm{ins}}\left(t_0\right)]}{t_1-t_0}-C_{\mathrm{PLN}}^{-1}{D}_{\mathrm{PLN}}\\ U_{\mathrm{PLN}}^{\mathrm{ave}}=\underset{j\∈F_{\mathrm{BSS}1}}{\mathrm{\Σ}}{P}_{\mathrm{PLN},j}^{\mathrm{ave}}\end{array}\right.---\left(24\right)$

Claims (7)

1. transformer station process layer network short term reliability quantitative analysis method, be applied in transformer station process layer network, transformer station process layer network PLN comprises: public exchange SWC, a n interval switch SWB1-SWBn, n interval merge cells MUB1-MUBn, n Bay Protection Unit PB1-PBn, n interval intelligent terminal ITB1-ITBn, n interval measurement and control unit MCB1-MCBn; Public exchange and n interval switch are Y-connection mode, connect interval merge cells, Bay Protection Unit, interval intelligent terminal, interval measurement and control unit under the switch of each interval;

It is characterized in that: the quantitative analysis method of described transformer station process layer network short term reliability is carried out as follows:

Step 1, the mean time to failure MTTF adding up respective switch and spacer units in described transformer station process layer network and mean time to repair MTTR, calculate failure rate and the repair rate of respective switch and spacer units in described transformer station process layer network;

Step 2, short term reliability modeling is carried out to each element of described transformer station process layer network PLN;

Step 3, interval switch SWB1, interval merge cells MUB1, Bay Protection Unit PB1, interval intelligent terminal ITB1, interval measurement and control unit MCB1 are considered as entirety, be denoted as introns system BSS1, short term reliability quantitative analysis is carried out to introns system BSS1;

Step 4, utilize method described in step 3, by interval switch SWB2-n, interval merge cells MUB2-n, Bay Protection Unit PB2-n, interval intelligent terminal ITB2-n, interval measurement and control unit MCB2-n are considered as entirety, be denoted as introns system BSS2-n respectively, short term reliability quantitative analysis is carried out to introns system BSS2-n;

The value-based algorithms such as step 5, employing layering, calculate and see the equivalent failure rate of introns system BSS1-BSSn and equivalent repair rate;

Step 6, short term reliability quantitative analysis is carried out to the transformer station process layer network PLN be made up of public exchange SWC and n introns system BSS1-n.

2. transformer station process layer network short term reliability according to claim 1 quantitative analysis method, is characterized in that:

Mean time to failure and the mean time to repair of the switch described in described step 1 and spacer units comprise:

The mean time to failure MTTF of described center switch SWC _sWCwith MTTR mean time to repair _sWC; The mean time to failure MTTF of described interval switch SWB1-SWBn _sWB1-MTTF _sWBnwith MTTR mean time to repair _sWB1-MTTR _sWBn; The mean time to failure MTTF of described interval merge cells MUB1-MUBn _mUB1-MTTF _mUBnwith MTTR mean time to repair _mUB1-MTTR _mUBn; The mean time to failure MTTF of described Bay Protection Unit PB1-PBn _pB1-MTTF _pBnwith MTTR mean time to repair _pB1-MTTR _pBn; The mean time to failure MTTF of described interval intelligent terminal ITB1-ITBn _iTB1-MTTF _iTBnwith MTTR mean time to repair _iTB1-MTTR _iTBn; The mean time to failure MTTF of described interval measurement and control unit MCB1-MCBn _mCB1-MTTF _mCBnwith MTTR mean time to repair _mCB1-MTTR _mCBn;

Failure rate and the repair rate of the switch described in described step 1 and spacer units comprise:

The failure rate λ of described center switch SWC _sWCwith repair rate μ _sWC; The failure rate λ of described interval switch SWB1-SWBn _sWB1-λ _sWBnwith repair rate μ _sWB1-μ _sWBn; The failure rate λ of described interval merge cells MUB1-MUBn _mUB1-λ _mUBnwith repair rate μ _mUB1-μ _mUBn; The failure rate λ of described Bay Protection Unit PB1-PBn _pB1-λ _pBnwith repair rate μ _pB1-μ _pBn; The failure rate λ of described interval intelligent terminal ITB1-ITBn _iTB1-λ _iTBnwith repair rate μ _iTB1-μ _iTBn; The failure rate λ of described interval measurement and control unit MCB1-MCBn _mCB1-λ _mCBnwith repair rate μ _mCB1-μ _mCBn.

3. transformer station process layer network short term reliability according to claim 1 quantitative analysis method, is characterized in that:

Carrying out short term reliability modeling to each element of described transformer station process layer network PLN in described step 2 is carry out as follows:

Step 2.1, according to the failure rate λ of described center switch SWC obtained in step 1 _sWCwith repair rate μ _sWC, short term reliability modeling is carried out to center switch SWC;

Adopt state-space method, set up two state models of center switch SWC, the fault subset F of definition center switch SWC _sWC, formed such as formula the state transitions rate matrix Φ shown in (1) _sWC;

${\mathrm{\Φ}}_{\mathrm{SWC}}=\left[\begin{array}{cc}-{\mathrm{\λ}}_{\mathrm{SWC}}& {\mathrm{\λ}}_{\mathrm{SWC}}\\ {\mathrm{\μ}}_{\mathrm{SWC}}& -{\mathrm{\μ}}_{\mathrm{SWC}}\end{array}\right]---\left(1\right)$

Define the initial condition P of described center switch SWC _sWC(t ₀), utilize the instantaneous state probability of formula (2) computer center switch SWC with instantaneous unavailability ratio

$\left\{\begin{array}{c}{P}_{\mathrm{SWC}}^{\mathrm{ins}}\left(t\right)=e^{{\mathrm{\Φ}}_{\mathrm{SWC}}t}{P}_{\mathrm{SWC}}\left(t_0\right)\\ U_{\mathrm{SWC}}^{\mathrm{ins}}=\underset{j\∈F_{\mathrm{BSSn}}}{\mathrm{\Σ}}{P}_{\mathrm{SWC},j}^{\mathrm{ins}}\left(t\right)\end{array}\right.---\left(2\right)$

Step 2.2, according to the failure rate λ of described interval switch SWB1-SWBn obtained in step 1 _sWB1-λ _sWBnwith repair rate μ _sWB1-μ _sWBn, short term reliability modeling is carried out to interval switch SWB1-SWBn;

To arbitrary interval switch SWBi, i=1 ..., n, adopts state-space method, sets up two state models of interval switch SWBi, the fault subset F of definition interval switch SWBi _sWBi, formed such as formula the state transitions rate matrix Φ shown in (3) _sWBi;

${\mathrm{\Φ}}_{\mathrm{SWBi}}=\left[\begin{array}{cc}-{\mathrm{\λ}}_{\mathrm{SWBi}}& {\mathrm{\λ}}_{\mathrm{SWBi}}\\ {\mathrm{\μ}}_{\mathrm{SWBi}}& -{\mathrm{\μ}}_{\mathrm{SWBi}}\end{array}\right]---\left(3\right)$

Define the initial condition P of described center switch SWBi _sWBi(t ₀), utilize the instantaneous state probability of formula (4) computer center switch SWBi with instantaneous unavailability ratio

$\left\{\begin{array}{c}{P}_{\mathrm{SWBi}}^{\mathrm{ins}}\left(t\right)=e^{{\mathrm{\Φ}}_{\mathrm{SWBi}}t}{P}_{\mathrm{SWBi}}\left(t_0\right)\\ U_{\mathrm{SWBi}}^{\mathrm{ins}}=\underset{j\∈F_{\mathrm{BSSn}}}{\mathrm{\Σ}}{P}_{\mathrm{SWBi},j}^{\mathrm{ins}}\left(t\right)\end{array}\right.---\left(4\right)$

Step 2.3, according to the failure rate λ of described interval merge cells MUB1-MUBn obtained in step 1 _mUB1-λ _mUBnwith repair rate μ _mUB1-μ _mUBn, short term reliability modeling is carried out to interval merge cells MUB1-MUBn;

To arbitrary interval merge cells MUBi, i=1 ..., n, adopts state-space method, sets up two state models of interval merge cells MUBi, the fault subset F of definition interval merge cells MUBi _mUBi, formed such as formula the state transitions rate matrix Φ shown in (5) _mUBi;

${\mathrm{\Φ}}_{\mathrm{MUBi}}=\left[\begin{array}{cc}-{\mathrm{\λ}}_{\mathrm{MUBi}}& {\mathrm{\λ}}_{\mathrm{MUBi}}\\ {\mathrm{\μ}}_{\mathrm{MUBi}}& -{\mathrm{\μ}}_{\mathrm{MUBi}}\end{array}\right]---\left(5\right)$

Define the initial condition P of described interval merge cells MUBi _mUBi(t ₀), utilize the instantaneous state probability of formula (6) counting period merge cells MUBi with instantaneous unavailability ratio

$\left\{\begin{array}{c}{P}_{\mathrm{MUBi}}^{\mathrm{ins}}\left(t\right)=e^{{\mathrm{\Φ}}_{\mathrm{MUBi}}t}{P}_{\mathrm{MUBi}}\left(t_0\right)\\ U_{\mathrm{MUBi}}^{\mathrm{ins}}=\underset{j\∈F_{\mathrm{BSSn}}}{\mathrm{\Σ}}{P}_{\mathrm{MUBi},j}^{\mathrm{ins}}\left(t\right)\end{array}\right.---\left(6\right)$

Step 2.4, according to the failure rate λ of described Bay Protection Unit PB1-PBn obtained in step 1 _pB1-λ _pBnwith repair rate μ _pB1-μ _pBn, short term reliability modeling is carried out to Bay Protection Unit PB1-PBn;

To arbitrary interval protected location PBi, i=1 ..., n, adopts state-space method, sets up two state models of Bay Protection Unit PBi, the fault subset F of definition Bay Protection Unit PBi _pBi, formed such as formula the state transitions rate matrix Φ shown in (7) _pBi;

${\mathrm{\Φ}}_{\mathrm{PBi}}=\left[\begin{array}{cc}-{\mathrm{\λ}}_{\mathrm{PBi}}& {\mathrm{\λ}}_{\mathrm{PBi}}\\ {\mathrm{\μ}}_{\mathrm{PBi}}& -{\mathrm{\μ}}_{\mathrm{PBi}}\end{array}\right]---\left(7\right)$

Define the initial condition P of described Bay Protection Unit PBi _pBi(t ₀), utilize the instantaneous state probability of formula (8) counting period protected location PBi with instantaneous unavailability ratio

$\left\{\begin{array}{c}{P}_{\mathrm{PBi}}^{\mathrm{ins}}\left(t\right)=e^{{\mathrm{\Φ}}_{\mathrm{PBi}}t}{P}_{\mathrm{PBi}}\left(t_0\right)\\ U_{\mathrm{PBi}}^{\mathrm{ins}}=\underset{j\∈F_{\mathrm{BSSn}}}{\mathrm{\Σ}}{P}_{\mathrm{PBi},j}^{\mathrm{ins}}\left(t\right)\end{array}\right.---\left(8\right)$

Step 2.5, according to the failure rate λ of described interval intelligent terminal ITB1-ITBn obtained in step 1 _iTB1-λ _iTBnwith repair rate μ _iTB1-μ _iTBn, short term reliability modeling is carried out to interval intelligent terminal ITB1-ITBn;

To arbitrary interval intelligent terminal ITBi, i=1 ..., n, adopts state-space method, sets up two state models of interval intelligent terminal ITBi, the fault subset F of definition interval intelligent terminal ITBi _iTBi, formed such as formula the state transitions rate matrix Φ shown in (9) _iTBi;

${\mathrm{\Φ}}_{\mathrm{ITBi}}=\left[\begin{array}{cc}-{\mathrm{\λ}}_{\mathrm{ITBi}}& {\mathrm{\λ}}_{\mathrm{ITBi}}\\ {\mathrm{\μ}}_{\mathrm{ITBi}}& -{\mathrm{\μ}}_{\mathrm{ITBi}}\end{array}\right]---\left(9\right)$

Define the initial condition P of described interval intelligent terminal ITBi _iTBi(t ₀), utilize the instantaneous state probability of formula (10) counting period intelligent terminal ITBi with instantaneous unavailability ratio

$\left\{\begin{array}{c}{P}_{\mathrm{ITBi}}^{\mathrm{ins}}\left(t\right)=e^{{\mathrm{\Φ}}_{\mathrm{ITBi}}t}{P}_{\mathrm{ITBi}}\left(t_0\right)\\ U_{\mathrm{ITBi}}^{\mathrm{ins}}=\underset{j\∈F_{\mathrm{BSSn}}}{\mathrm{\Σ}}{P}_{\mathrm{ITBi},j}^{\mathrm{ins}}\left(t\right)\end{array}\right.---\left(10\right);$

Step 2.6, according to the failure rate λ of described interval measurement and control unit MCB1-MCBn obtained in step 1 _mCB1-λ _mCBnwith repair rate μ _mCB1-μ _mCBn, short term reliability modeling is carried out to interval measurement and control unit MCB1-MCBn;

To arbitrary interval measurement and control unit MCBi, i=1 ..., n, adopts state-space method, sets up two state models of interval measurement and control unit MCBi, the fault subset F of definition interval measurement and control unit MCBi _mCBi, formed such as formula the state transitions rate matrix Φ shown in (11) _mCBi;

${\mathrm{\Φ}}_{\mathrm{MCBi}}=\left[\begin{array}{cc}-{\mathrm{\λ}}_{\mathrm{MCBi}}& {\mathrm{\λ}}_{\mathrm{MCBi}}\\ {\mathrm{\μ}}_{\mathrm{MCBi}}& -{\mathrm{\μ}}_{\mathrm{MCBi}}\end{array}\right]---\left(11\right)$

Define the initial condition P of described interval measurement and control unit MCBi _mCBi(t ₀), utilize the instantaneous state probability of formula (12) counting period measurement and control unit MCBi with instantaneous unavailability ratio

$\left\{\begin{array}{c}{P}_{\mathrm{MCBi}}^{\mathrm{ins}}\left(t\right)=e^{{\mathrm{\Φ}}_{\mathrm{MCBi}}t}{P}_{\mathrm{MCBi}}\left(t_0\right)\\ U_{\mathrm{MCBi}}^{\mathrm{ins}}=\underset{j\∈F_{\mathrm{BSSn}}}{\mathrm{\Σ}}{P}_{\mathrm{MCBi},j}^{\mathrm{ins}}\left(t\right)\end{array}\right.---\left(12\right).$

4. transformer station process layer network short term reliability according to claim 1 quantitative analysis method, is characterized in that:

In described step 3, the short term reliability quantitative analysis method of described introns system BSS1 carries out as follows:

Step 3.1, employing state-space method, set up six state models of introns system BSS1, the fault subset F of definition introns system BSS1 _bSS1, formed such as formula the state transitions rate matrix Φ shown in (13) _bSS1;

${\mathrm{\Φ}}_{\mathrm{BSS}1}=\left[\begin{array}{cccccc}-{\mathrm{\λ}}_{B1}& {\mathrm{\λ}}_{\mathrm{SWB}1}& {\mathrm{\λ}}_{\mathrm{MUB}1}& {\mathrm{\λ}}_{\mathrm{PB}1}& {\mathrm{\λ}}_{\mathrm{ITB}1}& {\mathrm{\λ}}_{\mathrm{MCB}1}\\ {\mathrm{\μ}}_{\mathrm{SWB}1}& -{\mathrm{\μ}}_{\mathrm{SWB}1}& & & & \\ {\mathrm{\μ}}_{\mathrm{MUB}1}& & -{\mathrm{\μ}}_{\mathrm{MUB}1}& & & \\ {\mathrm{\μ}}_{\mathrm{PB}1}& & & -{\mathrm{\μ}}_{\mathrm{PB}1}& & \\ {\mathrm{\μ}}_{\mathrm{ITB}1}& & & & -{\mathrm{\μ}}_{\mathrm{ITB}1}& \\ {\mathrm{\μ}}_{\mathrm{MCB}1}& & & & & -{\mathrm{\μ}}_{\mathrm{MCB}1}\end{array}\right]---\left(13\right)$

Wherein, λ _b1=λ _sWB1+ λ _mUB1+ λ _pB1+ λ _iTB1+ λ _mCB1;

Step 3.2, consider state transitions rate matrix Φ _bSS1irreversible, utilize elementary transformation to split it, form equivalent rate of transform Matrix C _bSS1with compensation matrix D _bSS1; By state transitions rate matrix Φ _bSS1launch such as formula (1), deduct the 6th column element with the 1st to the 5th column element successively, get front 5 row, 5 column elements form equivalent rate of transform Matrix C _bSS1such as formula (14); Compensation matrix D is formed by the 1 to 5 row, the 6th column element _bSS1such as formula (15);

$C_{\mathrm{BSS}1}=\left[\begin{array}{ccccc}-{\mathrm{\λ}}_{B1}-{\mathrm{\λ}}_{\mathrm{MCB}1}& {\mathrm{\λ}}_{\mathrm{SWB}1}\text{-}{\mathrm{\λ}}_{\mathrm{MCB}1}& {\mathrm{\λ}}_{\mathrm{MUB}1}\text{-}{\mathrm{\λ}}_{\mathrm{MCB}1}& {\mathrm{\λ}}_{\mathrm{PB}1}\text{-}{\mathrm{\λ}}_{\mathrm{MCB}1}& {\mathrm{\λ}}_{\mathrm{ITB}1}\text{-}{\mathrm{\λ}}_{\mathrm{MCB}1}\\ {\mathrm{\μ}}_{\mathrm{SWB}1}& -{\mathrm{\μ}}_{\mathrm{SWB}1}& & & \\ {\mathrm{\μ}}_{\mathrm{MUB}1}& & -{\mathrm{\μ}}_{\mathrm{MUB}1}& & \\ {\mathrm{\μ}}_{\mathrm{PB}1}& & & -{\mathrm{\μ}}_{\mathrm{PB}1}& \\ {\mathrm{\μ}}_{\mathrm{ITB}1}& & & & -{\mathrm{\μ}}_{\mathrm{ITB}1}\end{array}\right]---\left(14\right)$

D _BSS1＝[λ _MCB10 0 0 0] ^T(15)

Step 3.3, define the initial condition P of described introns system BSS1 _bSS1(t ₀); By initial condition matrix P _bSS1(t ₀), equivalent rate of transform Matrix C _bSS1with compensation matrix D _bSS1, utilize formula (16) to calculate the instantaneous state probability of described introns system BSS1 under different initial condition and instantaneous degree of unavailability

$\left\{\begin{array}{c}{P}_{\mathrm{BSS}1}^{\mathrm{ins}}\left(t\right)=C_{\mathrm{BSS}1}^{-1}[P_{\mathrm{BSS}1}\left(t_0\right)+C_{\mathrm{BSS}1}^{-1}{D}_{\mathrm{BSS}1}]-C_{\mathrm{BSS}1}^{-1}{D}_{\mathrm{BSS}1}\\ U_{\mathrm{BSS}1}^{\mathrm{ins}}=\underset{j\∈F_{\mathrm{BSS}1}}{\mathrm{\Σ}}{P}_{\mathrm{BSS}1,j}^{\mathrm{ins}}\left(t\right)\end{array}\right.---\left(16\right)$

Step 3.4, utilize formula (17) calculate at short term reliability assessment cycle [t ₀, t ₁] in the mean state probability of described introns system BSS1 with average degree of unavailability

$\left\{\begin{array}{c}{P}_{\mathrm{BSS}1}^{\mathrm{ave}}=\frac{C_{\mathrm{BSS}1}^{-1}[P_{\mathrm{BSS}1}^{\mathrm{ins}}\left(t_1\right)-P_{\mathrm{BSS}1}^{\mathrm{ins}}\left(t_0\right)]}{t_1-t_0}-C_{\mathrm{BSS}1}^{-1}{D}_{\mathrm{BSS}1}\\ U_{\mathrm{BSS}1}^{\mathrm{ave}}=\underset{j\∈F_{\mathrm{BSS}1}}{\mathrm{\Σ}}{P}_{\mathrm{BSS}1,j}^{\mathrm{ave}}\end{array}\right.---\left(17\right).$

5. transformer station process layer network short term reliability according to claim 1 quantitative analysis method, is characterized in that:

In described step 4, utilize described short term reliability quantitative analysis method, utilize formula (18) and (19) to calculate arbitrary interval subsystem BSSi, i=1 ..., n, instantaneous state probability with instantaneous degree of unavailability and mean state probability with average degree of unavailability

$\left\{\begin{array}{c}{P}_{\mathrm{BSSi}}^{\mathrm{ins}}\left(t\right)=C_{\mathrm{BSSi}}^{-1}[P_{\mathrm{BSSi}}\left(t_0\right)+C_{\mathrm{BSSi}}^{-1}{D}_{\mathrm{BSSi}}]-C_{\mathrm{BSSi}}^{-1}{D}_{\mathrm{BSSi}}\\ U_{\mathrm{BSSi}}^{\mathrm{ins}}=\underset{j\∈F_{\mathrm{BSSi}}}{\mathrm{\Σ}}{P}_{\mathrm{BSSi},j}^{\mathrm{ins}}\left(t\right)\end{array}\right.---\left(18\right)$

$\left\{\begin{array}{c}{P}_{\mathrm{BSSi}}^{\mathrm{ave}}=\frac{C_{\mathrm{BSSi}}^{-1}[P_{\mathrm{BSSi}}^{\mathrm{ins}}\left(t_1\right)-P_{\mathrm{BSSi}}^{\mathrm{ins}}\left(t_0\right)]}{t_1-t_0}-C_{\mathrm{BSSi}}^{-1}{D}_{\mathrm{BSSi}}\\ U_{\mathrm{BSSi}}^{\mathrm{ave}}=\underset{j\∈F_{\mathrm{BSSi}}}{\mathrm{\Σ}}{P}_{\mathrm{BSSi},j}^{\mathrm{ave}}\end{array}\right.---\left(19\right).$

6. transformer station process layer network short term reliability according to claim 1 quantitative analysis method, is characterized in that, in described step 5, adopts layering equivalence method, obtains the equivalent fault rate λ of introns system BSS1-BSSn _bSS1-λ _bSSnwith equivalent repair rate μ _bSS1-μ _bSSn.

7. transformer station process layer network short term reliability according to claim 1 quantitative analysis method, is characterized in that:

The short term reliability appraisal procedure of the PLN of transformer station process layer network described in described step 6 is carried out as follows:

Step 6.1, employing state-space method, the n+2 state model of process of establishing layer network PLN, the fault subset F of definition procedure layer network PLN _pLN, formed such as formula the state transitions rate matrix Φ shown in (20) _pLN;

Step 6.2, consider state transitions rate matrix Φ _pLNirreversible, utilize elementary transformation to split it, form equivalent rate of transform Matrix C _pLNwith compensation matrix D _pLN; By state transitions rate matrix Φ _pLNlaunch such as formula (1), deduct the n-th+2 column element with the 1 to the (n+1)th column element successively, get that front n+1 is capable, n+1 column element forms equivalent rate of transform Matrix C _pLNsuch as formula (21); , n-th+2 column element capable by 1 to n+1 forms compensation matrix D _pLNsuch as formula (22);

D _PLN＝[λ _SWC0 0 0 … 0] ^T(22)

Step 6.3, define the initial condition P of described process-level network PLN _pLN(t ₀); By initial condition matrix P _pLN(t ₀), equivalent rate of transform Matrix C _pLNwith compensation matrix D _pLN, utilize formula (23) to calculate the instantaneous state probability of described introns system BSS1 under different initial condition and instantaneous degree of unavailability

$\left\{\begin{array}{c}{P}_{\mathrm{PLN}}^{\mathrm{ins}}\left(t\right)=C_{\mathrm{PLN}}^{-1}[P_{\mathrm{PLN}}\left(t_0\right)+C_{\mathrm{PLN}}^{-1}{D}_{\mathrm{PLN}}]-C_{\mathrm{PLN}}^{-1}{D}_{\mathrm{PLN}}\\ U_{\mathrm{PLN}}^{\mathrm{ins}}=\underset{j\∈F_{\mathrm{BSS}1}}{\mathrm{\Σ}}{P}_{\mathrm{PLN},j}^{\mathrm{ins}}\left(t\right)\end{array}\right.---\left(23\right)$

Step 6.4, utilize formula (24) calculate at short term reliability assessment cycle [t ₀, t ₁] in the mean state probability of described introns system BSS1 with average degree of unavailability

$\left\{\begin{array}{c}{P}_{\mathrm{PLN}}^{\mathrm{ave}}=\frac{C_{\mathrm{PLN}}^{-1}[P_{\mathrm{PLN}}^{\mathrm{ins}}\left(t_1\right)-P_{\mathrm{PLN}}^{\mathrm{ins}}\left(t_0\right)]}{t_1-t_0}-C_{\mathrm{PLN}}^{-1}{D}_{\mathrm{PLN}}\\ U_{\mathrm{PLN}}^{\mathrm{ave}}=\underset{j\∈F_{\mathrm{BSS}1}}{\mathrm{\Σ}}{P}_{\mathrm{PLN},j}^{\mathrm{ave}}\end{array}\right.---\left(24\right).$