CN113890082A - Method for measuring small signal stability of electric vehicle direct current charging network - Google Patents

Method for measuring small signal stability of electric vehicle direct current charging network Download PDF

Info

Publication number
CN113890082A
CN113890082A CN202110799241.7A CN202110799241A CN113890082A CN 113890082 A CN113890082 A CN 113890082A CN 202110799241 A CN202110799241 A CN 202110799241A CN 113890082 A CN113890082 A CN 113890082A
Authority
CN
China
Prior art keywords
network
direct current
electric vehicle
converter
stability
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
CN202110799241.7A
Other languages
Chinese (zh)
Inventor
付强
杜文娟
姚竞宙
王海风
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Sichuan University
Original Assignee
Sichuan University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Sichuan University filed Critical Sichuan University
Priority to CN202110799241.7A priority Critical patent/CN113890082A/en
Publication of CN113890082A publication Critical patent/CN113890082A/en
Withdrawn legal-status Critical Current

Links

Images

Classifications

    • 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
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/16—Matrix or vector computation, e.g. matrix-matrix or matrix-vector multiplication, matrix factorization
    • 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
    • H02J3/12—Circuit arrangements for ac mains or ac distribution networks for adjusting voltage in ac networks by changing a characteristic of the network load
    • 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
    • H02J3/24—Arrangements for preventing or reducing oscillations of power in networks
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • H02J3/322—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means the battery being on-board an electric or hybrid vehicle, e.g. vehicle to grid arrangements [V2G], power aggregation, use of the battery for network load balancing, coordinated or cooperative battery charging

Landscapes

  • Engineering & Computer Science (AREA)
  • Power Engineering (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Data Mining & Analysis (AREA)
  • Computational Mathematics (AREA)
  • Mathematical Analysis (AREA)
  • Mathematical Optimization (AREA)
  • Pure & Applied Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Computing Systems (AREA)
  • Databases & Information Systems (AREA)
  • Software Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • Algebra (AREA)
  • Electric Propulsion And Braking For Vehicles (AREA)

Abstract

The invention discloses a method for measuring small signal stability of a direct current charging network of an electric automobile, which comprises the following steps: the method comprises the following steps: establishing a linear model of a direct current network consisting of M EVCSs (electric vehicle charging stations) and connected to a main alternating current power grid; step two: on the premise of assuming that the dynamic models of M EVCSs are the same, deriving an equivalent model of a direct current network consisting of M subsystems; step three: various factors influencing the stability of the direct current network are researched, and a beneficial conclusion is obtained; the invention provides a modal analysis method with simple calculation and reduced order, which is used for evaluating the small signal stability of a direct current network in EVCS (evolution-virtual Circuit) connection planning.

Description

Method for measuring small signal stability of electric vehicle direct current charging network
Technical Field
The invention relates to the field of electric automobiles, in particular to a method for measuring small signal stability of a direct current charging network of an electric automobile.
Background
Electric Vehicles (EVs) are an important component of future smart grids. In recent years, the rapid development of electric vehicle technology has brought forward high expectations for the careful and reasonable planning of electric vehicle charging facilities in China and society before the realization of large-scale deployment of electric vehicles. Electric vehicle charging station layout planning has been an important research topic and has attracted the widespread interest of many researchers. To date, this study has focused on three major areas. The first aspect is cost reduction, since electric vehicles are a considerable new load burden on the power supply network. The second aspect is the effect of electric vehicle charging on the stability of the supply network. To avoid regret costs and negative impacts, it is essential to explore the problem during the planning phase. A third aspect is the proposal of some advanced control strategies to improve the stability of the dc network.
With the large-scale deployment of electric vehicles in future smart grids, it is very promising to establish a local direct current network specially used for charging electric vehicles. The dc network may consist of hundreds or more of Electric Vehicle Charging Stations (EVCS) and is connected to the main ac grid supply. To date, in studying stability issues related to electric vehicle planning, the electric vehicle charging process is modeled as an aggregated electric vehicle load at the point of common coupling with the ac power grid (PCC). The influence of electric vehicle load on the stability of an alternating current power grid has been studied. For example, researchers have studied the effect of large-scale electric vehicle charging on the transient stability of the north ireland power system. Two typical electric vehicle connection models are compared, indicating that EV loads may pose a potential risk of instability to the ac power system. In addition, a scholars provides an index for evaluating the influence of large-scale connection of the electric automobile on the instantaneous voltage stability of the alternating current power system, and the proposed index is comprehensively evaluated through calculating and simulating example cases.
Technical scheme of prior art I
To simplify the analysis, electric vehicles are generally investigated as constant power loads. Some researchers have studied the influence of transmission lines on the stability of the dc network. Based on the eigenvalue shift graph, it was found that an increase in cable length and output power would reduce the stability of the dc network. Taking the electric vehicle of each charging station as a constant power load connected via a converter, it can also be concluded that the stability of the dc network depends on the number of converters connected in parallel and the grid impedance. Researchers have disclosed mechanisms how the number of dc/dc converters and cable lengths affect the stability of the dc network. In addition, impedance analysis methods have been used to demonstrate that constant power loads have negative incremental resistance, which may reduce the stability margin of the dc network.
Disadvantages of the first prior art
Even if each converter is well designed based on independent operation with sufficient stability, the stability of the entire cascade system may be lost. The impedance analysis method is limited to analyzing a cascade system and cannot be applied to any type of direct current network.
Disclosure of Invention
The invention provides a simple-calculation and reduced-order modal analysis method for evaluating the small-signal stability of a direct current network in EVCS (evolution-virtualization-Circuit) connection planning, and on the basis, important factors influencing the stability of the direct current network, such as the total number of EVCSs, the line length of the direct current network connected with a main alternating current substation, the structure of the direct current network and the like, are analyzed.
The technical scheme adopted by the invention is as follows: a method for measuring small signal stability of an electric vehicle direct current charging network comprises the following steps:
the method comprises the following steps: establishing a linear model of a direct current network consisting of M EVCSs (electric vehicle charging stations) and connected to a main alternating current power grid;
step two: on the premise of assuming that the dynamic models of M EVCSs are the same, deriving an equivalent model of a direct current network consisting of M subsystems;
step three: various factors influencing the stability of the direct current network are researched, and a beneficial conclusion is drawn.
The linear network model of the first step is as follows:
ΔV＝RΔI
wherein R is the resistance matrix of the DC network
ΔV＝[ΔVdc1 ΔVdc2 L ΔVdcm]T，ΔI＝[Δidc1 Δidc2 L Δidcm]T
VdckAnd idckRepresenting the terminal voltage and current injection, respectively, for the kth EVCS.
Preferably, the equivalent model of the dc network formed by the M subsystems in step two is:
PAP-1＝diag[Ac+ρibc Tcc]
the state matrix for each M subsystem is Ac+ρibc Tcc
λk(i) Expressed as a state matrix (a) — ξ (i) ± j ω (i)c+ρibc Tcc)∈R2×2I is the conjugate of 1, 2, … M, λk(i) The resonance frequency of the direct current network oscillation mode is equal to-xi (i) ± j ω (i), and satisfies the condition that
-ξ(i)+jω(i)-ξ(i)-jω(i)＝-2ξ(i)＝Trace(Ac+ρibc Tcc)
＝Trace(Ac)+Trace(ρibc Tcc)＝-2ξc+Trace(ρibc Tcc)
Where Trace (W) refers to the trace of matrix W.
Preferably, the specific steps of step three are:
s31: when in use
Figure RE-GDA0003318846750000041
Time, slave state matrix
Figure RE-GDA0003318846750000042
The oscillation mode of the dc network with the worst damping can be calculated, which means that only calculations are required for evaluating the stability of the dc network
Figure RE-GDA0003318846750000043
Rather than computing all state matrices
Figure RE-GDA0003318846750000044
The modal calculation burden of the direct current network stability evaluation is further reduced;
s32: when in use
Figure RE-GDA0003318846750000045
The oscillation mode ratio lambda of the DC networkk(i) Better damping of ═ ξ (i) ± j ω (i), so the dc network is stable and does not require calculation
Figure RE-GDA0003318846750000046
The characteristic value of (2).
Preferably, the electric vehicle charging station, i.e. EVCS, includes a resistor, an inductor, a capacitor, a dc/dc converter, a diode, a dc load; the resistor comprises a resistor R and a resistor RLSaid capacitor comprises a capacitor CFAnd a capacitor CLThe resistor R is connected with an inductor L, and the inductor L is connected with an inductor L in the direct current/direct current converterFAn inductance L in the DC/DC converterFRespectively connected with capacitors CFAnd a DC/DC converter connected with the diode and the internal inductor L of the DC/DC converter respectivelyLAn internal inductance L of the DC/DC converterLConnecting resistors RL respectively connected with capacitors CLAnd a dc load.
Preferably, the model of EVCS is:
Figure RE-GDA0003318846750000047
Δidc＝ckΔXk
wherein
ΔXk＝[ΔvF Δidc ΔvL ΔiL Δxr ΔxI]T
Figure RE-GDA0003318846750000048
bk＝[0 1/(L+LF) 0 0 0 0]T
ck＝[0 1 0 0 0 0]
Wherein v isdcAnd idcVoltage and current injection at dc node a, respectively: r and L are line resistance and inductance: l isFAnd CFInductance and capacitance of the output filter of the dc/dc converter: vFAnd iFRespectively is through CFVoltage of and from CFSide injection current to dc/dc converter: rLAnd LLResistance and inductance of the line connecting the dc/dc converter and the dc load: cLVoltage regulating capacitance of dc load: vLIs through CLVoltage of (c): i.e. iLAnd pLRespectively load current and active power.
Preferably, a dc network with M electric vehicle charging stations is configured, including electric vehicle charging stations, the M electric vehicle charging stations being arranged in a radial string of the dc network.
The method for measuring the small signal stability of the direct current charging network of the electric automobile has the following beneficial effects:
the invention provides a modal analysis method with simple calculation and reduced order, which is used for evaluating the stability of a direct current charging network of an electric automobile.
Drawings
Fig. 1 is an EVCS model diagram.
Fig. 2 is a diagram of a dc network configured with M EVCSs.
Detailed Description
The following description of the embodiments of the present invention is provided to facilitate the understanding of the present invention by those skilled in the art, but it should be understood that the present invention is not limited to the scope of the embodiments, and it will be apparent to those skilled in the art that various changes may be made without departing from the spirit and scope of the invention as defined and defined in the appended claims, and all matters produced by the invention using the inventive concept are protected.
A method for measuring small signal stability of a direct current charging network of an electric vehicle includes the steps of firstly, establishing a linear model of a direct current network which is composed of M EVCSs and connected to a main alternating current power grid.
Secondly, on the premise of assuming that the dynamic models of the M EVCSs are the same, an equivalent model of a direct current network consisting of M subsystems is deduced.
On the basis of the equivalent model, a direct current network stability modal analysis method which is simple in calculation and reduced in order is provided.
Thirdly, various factors influencing the stability of the direct current network are researched, and a beneficial conclusion is drawn.
Fig. 1 shows a common model of EVCS. In FIG. 1, VdcAnd idcVoltage and current injection at dc node a, respectively: r and L are line resistance and inductance: l isFAnd CFInductance and capacitance of the output filter of the dc/dc converter: vFAnd iFRespectively is through CFVoltage of and from CFSide injection current to dc/dc converter: rLAnd LLResistance and inductance of the line connecting the dc/dc converter and the dc load: cLVoltage regulating capacitance of dc load: vLIs through CLVoltage of (c): i.e. iLAnd PLRespectively load current and active power.
In FIG. 1, the transfer functions of the outer loop voltage and inner loop current PI controllers of the DC/DC converter are
Figure RE-GDA0003318846750000061
And
Figure RE-GDA0003318846750000062
Figure RE-GDA0003318846750000063
is vLControl reference of (a): dL(ii) a Is the transformation ratio of the dc/dc converter.
From FIG. 1, the circuit voltage and current equations can be derived as follows
Figure RE-GDA0003318846750000064
Figure RE-GDA0003318846750000065
Figure RE-GDA0003318846750000066
The control system of the DC/DC converter is described by the following equation
Figure RE-GDA0003318846750000067
Figure RE-GDA0003318846750000068
Figure RE-GDA0003318846750000069
Linearizing (1) and (2) the state space model of the available EVCS
Figure RE-GDA0003318846750000071
Δidc＝ckΔXk (3)
Wherein
Δxk＝[ΔvF Δidc ΔvL ΔiL Δxr ΔxI]T
Figure RE-GDA0003318846750000072
bk＝[0 1/(L+LF) 0 0 0 0]T
ck＝[0 1 0 0 0 0]
The subscript 0 indicates the steady state value of the variable.
The dynamic characteristics of the DC/DC converter are ignored, and a simplified model of the EVCS is obtained.
This is the assumption that the converter control has perfect performance.
The simplified model is a second-order system, and the dominant conjugate complex pole of the system is determined by an output filter. Thus, in the state space representation of the simplified model,
ΔXk＝[ΔvF Δidc]T
Figure RE-GDA0003318846750000073
alternatively, if the dominant conjugate negative point of the EVCS is determined by the converter control system, the dynamics of the rest of the EVCS may be ignored. Thereby obtaining a simplified second-order state space model
Δxk＝[Δvdc ΔxV]T
Figure RE-GDA0003318846750000074
bk＝[1 0]T，ck＝[-KVpdL0 1] (5)
FIG. 2 shows a plan for charging an electric vehicleConfiguration of the streaming network. There are M EVCS arranged in radial strings in the dc network. v. ofdckAnd idckRepresenting the terminal voltage and current injection, respectively, for the kth EVCS. The following linear network voltage equation can be established.
ΔV＝RΔI (6)
Wherein R is the resistance matrix of the DC network
ΔV＝[ΔVdc1 ΔVdc2 L ΔVdcm]T，ΔI＝[Δidc1 Δidc2 L Δidcm]T
Since the EVCS is in radial connection, the resistance matrix R is formed according to the following rule:
(1) of diagonal elements in R is RkkAnd k is 1, 2, L M. . It is the total resistance of the line connecting the kth EVCS to the main DC bus D
(2) R of an off-diagonal element is RkjK, j ═ 1, 2, L M. It is the total resistance of the line common connecting the kth and jth EVCS with the main dc bus D.
Obtaining the state equation of the kth EVCS from (3) and (6)
Figure RE-GDA0003318846750000081
Thus, the state equation of the DC network is obtained
Figure RE-GDA0003318846750000082
Wherein: Δ X ═ Δ X1 T ΔX2 T L ΔXM T]T；A＝[Akj]；[Akj]A block matrix is referred to. The block element matrix A of the k row and j columnkjIs a
Akk＝Ak+Rkkbk Tck，k＝1，2，L M
Akj＝Rkjbk Tcj，j≠k，k，j＝1，2，L M (9)
Equation (8) is referred to as the full-order model of the dc network designed for EVCS.
During the planning phase, typical parameters and operating conditions are typically employed by all EVCSs. It can therefore be assumed that the dynamic model of EVCS is the same, i.e. in (3),
Ak＝Ac∈RN×N，bk T＝bc T∈RN×1，ck＝cc∈R1×N，
k＝1，2，L M (10)
subsequently, the full-order state matrix of the DC network becomes
Figure RE-GDA0003318846750000091
Wherein: a is an element of RMN×MN，bc Tcc∈RN×NI I is an N identity matrix:
diag[Ac]and diag [ b ]c Tcc]Refers to a diagonal block matrix.
ρiAnd i is 1, 2 and K M is expressed as an R matrix eigenvalue.
There is such a matrix Pc
PcRPc -1＝diag(ρi) (12)
Wherein R ∈ RM×M，Pc∈RM×M，Pc -1∈RM×M，diag(ρi)∈RM×M：diag(ρi) Refers to a diagonal matrix.
In the formula
Figure RE-GDA0003318846750000101
It satisfies
Figure RE-GDA0003318846750000102
Defining a similarity transformation matrix as follows
Figure RE-GDA0003318846750000103
Wherein P ∈ RMN×MN，P-1∈RMN×MNWherein, the step of mixing the raw materials,
PAP-1＝diag[Ac+ρibc Tcc] (16)
equation (16) represents that the dynamics of the dc network is equivalent to the dynamics of the M decomposition subsystems.
The state matrix for each M subsystem is Ac+ρibc Tcc. Therefore, a computationally simple, reduced order modal analysis method may be proposed for assessing the stability of the dc network, as follows.
Using typical parameters and operating conditions of the EVCS, a state space model of a single EVCS (1) is built.
And (5) establishing a resistance matrix R of the direct current network, as shown in (6).
Calculating R ∈ RM×MCharacteristic value ρ ofi，i＝1，2，L M。
The following M matrices (A) are calculatedc+ρibc Tcc)∈RN×NCharacteristic value of 1, 2, L M (17) to evaluate small signal stability of DC network
The dimension of the full-order state matrix A of the medium direct current network is NM.
The matrix latitude involved in the above method is N and M. Therefore, it is a reduced order modal analysis method.
The simplified second-order model of EVCS described in (4) or (5) may be used if the dominant oscillation mode of the EVCS is associated with a filter or converter control system. Thus, it is possible to provide
Ac∈R2×2，bc Tcc∈R2×2 (18)
λc＝-ξc±jωcDenoted as the dominant oscillatory mode of the EVCS.
λc＝-ξc±jωcIs a state matrix ACThe conjugate value of (c).
Clearly, ξ should be stable at all times since the independent EVCS should be stable at all timesc＞0。
λk(i) Expressed as a state matrix (a) — ξ (i) ± j ω (i)c+ρibc Tcc)∈R2×2I is the conjugate of 1, 2, … M. Lambda [ alpha ]k(i) And- ξ (i) ± j ω (i) is a dc network oscillation mode with M EVCSs. It satisfies
-ξ(i)+jω(i)-ξ(i)-jω(i)＝-2ξ(i)＝Trace(Ac+ρibc Tcc)
＝Trace(Ac)+Trace(ρibc Tcc)＝-2ξc+Trace(ρibc Tcc) (19)
Where Trace (W) refers to the trace of matrix W.
The network resistance matrix is R ∈ RM×MA real symmetric matrix.
Thus, ρiAnd i is a positive real number, 1, 2, L M. RhominRepresenting all piI is the largest eigenvalue of 1, 2, L M. As can be seen from (19), it is shown that,
when in use
Figure RE-GDA0003318846750000121
Time, slave state matrix
Figure RE-GDA0003318846750000122
The oscillation mode of the dc network with the worst damping can be calculated, which means that only calculations are required for evaluating the stability of the dc network
Figure RE-GDA0003318846750000123
Rather than computing all state matrices
Figure RE-GDA0003318846750000124
The modal calculation burden of the direct current network stability evaluation is further reduced;
when in use
Figure RE-GDA0003318846750000125
The oscillation mode ratio lambda of the DC networkk(i) Better damping of ═ ξ (i) ± j ω (i), so the dc network is stable and does not require calculation
Figure RE-GDA0003318846750000126
The characteristic value of (2).
RLIs the line resistance connecting the dc grid and the dc main bus D in fig. 1.
In a particular case, the dc network is geographically remote from the main dc bus (AC substation), so that RLMuch more than the resistance of the lines in a dc network. The resistance of the internal lines of the dc network can therefore be neglected. In this particular case, the network resistance matrix is
Figure RE-GDA0003318846750000127
The characteristic value of R is ρi＝0，i＝1，2，L M-1，ρM＝RLM thus, the M order state matrix decomposition of the DC network is the M-1 order first equivalent subsystem AcAnd for the Mth order subsystem (A)c+MRLbc Tcc). When Trace (b)c Tcc) At > 0, the stability limitation of the DC network is
Figure RE-GDA0003318846750000128
It can be seen that the stability of the dc network decreases when the number of EVCSs or/and the line length of the dc network and the dc main bus D increases. In the worst case, when
Figure RE-GDA0003318846750000131
The DC network may lose stability. Meanwhile, when Trace (b)c Tcc) The DC network is always stable when < 0.

Claims (7)

1. A method for measuring small signal stability of an electric vehicle direct current charging network is characterized by comprising the following steps:
the method comprises the following steps: establishing a linear model of a direct current network consisting of M EVCSs (electric vehicle charging stations) and connected to a main alternating current power grid;
step two: on the premise of assuming that the dynamic models of M EVCSs are the same, deriving an equivalent model of a direct current network consisting of M subsystems;
step three: various factors influencing the stability of the direct current network are researched, and a beneficial conclusion is drawn.
2. The method for measuring the small signal stability of the direct current charging network of the electric vehicle according to claim 1, wherein the linear network model of the first step is as follows:
ΔV＝RΔI
wherein R is the resistance matrix of the DC network
ΔV＝[ΔVdc1 ΔVdc2 L ΔVdcm]T，ΔI＝[Δidc1 Δidc2 L Δidcm]T
VdckAnd idckRepresenting the terminal voltage and current injection, respectively, for the kth EVCS.
3. The method for measuring the small-signal stability of the direct-current charging network of the electric vehicle according to claim 1, wherein the equivalent model of the direct-current network formed by the M subsystems in the second step is as follows:
PAP-1＝diag[Ac+ρibc Tcc]
moment of state for each M subsystemArray is Ac+ρibc Tcc
λk(i) Expressed as a state matrix (a) — ξ (i) ± j ω (i)c+ρibc Tcc)∈R2×2I is the conjugate of 1, 2, … M, λk(i) The resonance frequency of the direct current network oscillation mode is equal to-xi (i) ± j ω (i), and satisfies the condition that
-ξ(i)+jω(i)-ξ(i)-jω(i)＝-2ξ(i)＝Trace(Ac+ρibc Tcc)
＝Trace(Ac)+Trace(ρibc Tcc)＝-2ξc+Trace(ρibc Tcc)
Where Trace (W) refers to the trace of matrix W.
4. The method for measuring the small signal stability of the direct current charging network of the electric automobile according to claim 1, wherein the third step comprises the following specific steps:
s31: when in use
Figure RE-FDA0003318846740000021
Time, slave state matrix
Figure RE-FDA0003318846740000022
The oscillation mode of the dc network with the worst damping can be calculated, which means that only calculations are required for evaluating the stability of the dc network
Figure RE-FDA0003318846740000023
Rather than computing all state matrices
Figure RE-FDA0003318846740000024
The modal calculation burden of the direct current network stability evaluation is further reduced;
s32: when in use
Figure RE-FDA0003318846740000027
The oscillation mode ratio lambda of the DC networkk(i) Better damping of ═ ξ (i) ± j ω (i), so the dc network is stable and does not require calculation
Figure RE-FDA0003318846740000025
The characteristic value of (2).
5. The method for measuring the small-signal stability of the electric vehicle direct current charging network according to claim 1, wherein the Electric Vehicle Charging Station (EVCS) comprises a resistor, an inductor, a capacitor, a direct current/direct current converter, a diode, a direct current load; the resistor comprises a resistor R and a resistor RLSaid capacitor comprises a capacitor CFAnd a capacitor CLThe resistor R is connected with an inductor L, and the inductor L is connected with an inductor L in the direct current/direct current converterFAn inductance L in the DC/DC converterFRespectively connected with capacitors CFAnd a DC/DC converter connected with the diode and the internal inductor L of the DC/DC converter respectivelyLThe internal inductor LL of the DC/DC converter is connected with a resistor RL, and the resistor RL is respectively connected with a capacitor CLAnd a dc load.
6. The method for measuring the small-signal stability of the direct-current charging network of the electric vehicle according to claim 1, wherein the model of the EVCS is as follows:
Figure RE-FDA0003318846740000026
Δidc＝ckΔxk
wherein
Δxk＝[ΔvF Δidc ΔvL ΔiL ΔxV ΔxI]T
Figure RE-FDA0003318846740000031
bk＝[0 1/(L+LF) 0 0 0 0]T
ck＝[0 1 0 0 0 0]
Wherein v isdcAnd idcVoltage and current injection at dc node a, respectively: r and L are line resistance and inductance: l isFAnd CFInductance and capacitance of the output filter of the dc/dc converter: vFAnd iFRespectively is through CFVoltage of and from CFSide injection current to dc/dc converter: rLAnd LLResistance and inductance of the line connecting the dc/dc converter and the dc load: cLVoltage regulating capacitance of dc load: vLIs through CLVoltage of (c): i.e. iLAnd pLRespectively load current and active power.
7. The method of measuring small signal stability of an electric vehicle dc charging network of claim 1, wherein the dc network is configured with M electric vehicle charging stations, including electric vehicle charging stations, the M electric vehicle charging stations arranged in a radial string of the dc network.
CN202110799241.7A 2021-07-13 2021-07-13 Method for measuring small signal stability of electric vehicle direct current charging network Withdrawn CN113890082A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202110799241.7A CN113890082A (en) 2021-07-13 2021-07-13 Method for measuring small signal stability of electric vehicle direct current charging network

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202110799241.7A CN113890082A (en) 2021-07-13 2021-07-13 Method for measuring small signal stability of electric vehicle direct current charging network

Publications (1)

Publication Number Publication Date
CN113890082A true CN113890082A (en) 2022-01-04

Family

ID=79010654

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202110799241.7A Withdrawn CN113890082A (en) 2021-07-13 2021-07-13 Method for measuring small signal stability of electric vehicle direct current charging network

Country Status (1)

Country Link
CN (1) CN113890082A (en)

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20130076332A1 (en) * 2011-09-09 2013-03-28 Virginia Tech Intellectual Properties, Inc. Method of Evaluating and Ensuring Stability of AC/DC Power Systems
CN108321798A (en) * 2018-02-05 2018-07-24 华北电力大学 A kind of open loop mode analysis method suitable for multi-input multi-output system
CN109617079A (en) * 2018-12-18 2019-04-12 华南理工大学 A kind of existence and method for analyzing stability of direct-flow distribution system flow solution
CN109787234A (en) * 2019-01-25 2019-05-21 国网上海市电力公司 The distributed generation resource ultra harmonics stable mode acquisition methods of the interface containing VSC
CN110021952A (en) * 2019-04-18 2019-07-16 天津大学 The sagging control coefrficient optimization method of multiterminal flexible direct current system based on small-signal modeling
CN110957714A (en) * 2019-11-07 2020-04-03 中国电建集团江西省电力设计院有限公司 Virtual direct current motor control method for stabilizing voltage fluctuation of direct current microgrid of charging station
WO2020245752A1 (en) * 2019-06-05 2020-12-10 Universita' Degli Studi Di Genova Method and system for assessing the island mode micronetwork stability

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20130076332A1 (en) * 2011-09-09 2013-03-28 Virginia Tech Intellectual Properties, Inc. Method of Evaluating and Ensuring Stability of AC/DC Power Systems
CN108321798A (en) * 2018-02-05 2018-07-24 华北电力大学 A kind of open loop mode analysis method suitable for multi-input multi-output system
CN109617079A (en) * 2018-12-18 2019-04-12 华南理工大学 A kind of existence and method for analyzing stability of direct-flow distribution system flow solution
CN109787234A (en) * 2019-01-25 2019-05-21 国网上海市电力公司 The distributed generation resource ultra harmonics stable mode acquisition methods of the interface containing VSC
CN110021952A (en) * 2019-04-18 2019-07-16 天津大学 The sagging control coefrficient optimization method of multiterminal flexible direct current system based on small-signal modeling
WO2020245752A1 (en) * 2019-06-05 2020-12-10 Universita' Degli Studi Di Genova Method and system for assessing the island mode micronetwork stability
CN110957714A (en) * 2019-11-07 2020-04-03 中国电建集团江西省电力设计院有限公司 Virtual direct current motor control method for stabilizing voltage fluctuation of direct current microgrid of charging station

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
WENJUAN DU 等: ""Small-signal Stability of a DC Network Planned for Electric Vehicle Charging"" *
杜威 等: ""光伏微电网孤岛运行时多种振荡模式的小信号建模分析"" *
饶雪;刘开培;杨洁;秦亮;: "基于小信号模型的柔性直流输电网络运行稳定性研究" *

Similar Documents

Publication Publication Date Title
CN102545207B (en) Voltage source commutation-high voltage direct current (VSC-HVDC) alternating-direct current optimal power flow method based on predictor-corrector inner point method
CN110808605B (en) Dynamic stability analysis method for current mode droop control multi-terminal direct current system
Kwon et al. Frequency-domain modeling and simulation of dc power electronic systems using harmonic state space method
CN110676841B (en) Transient stability analysis method for power electronic power system based on direct method
CN112636324B (en) Stability judging method and system for feeding multiple power electronic devices into complex weak power grid
Rui et al. Line inductance stability operation domain assessment for weak grids with multiple constant power loads
CN114722714A (en) Electric power-traffic coupling network expansion planning method considering traffic balance
Chang et al. Modeling and low-frequency oscillation analysis of an asymmetrical traction power system connected to power grid
CN107230982B (en) Micro-grid linear load flow calculation method
CN111553080B (en) Closed-loop identification method for load dynamic equivalent non-mechanism model parameters of distribution substation
CN113890082A (en) Method for measuring small signal stability of electric vehicle direct current charging network
CN106374452A (en) Feedback passive control method for direct current microgrid converters
Li et al. A new low-frequency oscillation suppression method based on EMU on-board energy storage device
Wang et al. Fast charging control method for electric vehicle-to-vehicle energy interaction devices
Han et al. Real-time online optimal control of current-fed dual active bridges based on machine learning
CN105305392A (en) Symmetrical component method for short circuit calculation of voltage-controlled type IIDG included power distribution network
CN115495892A (en) Stability analysis modeling method and device for low-voltage transformer area flexible interconnection system
CN113836678A (en) Method for analyzing stability of direct-current power distribution system containing electric automobile load
CN107144749A (en) Electric automobile electric charging station electricity quality evaluation method
Samia et al. Frequency splitting approach using wavelet for energy management strategies in fuel cell ultra-capacitor hybrid system
Sagert et al. Current and Voltage Harmonics in the Powertrain of Electric Vehicles
CN112564154A (en) Method for estimating state of undetectable signal of nonlinear constant-power load of direct-current micro-grid
Stanchev et al. Harmonic Resonance Analysis of Buck-Boost DC-DC Converter
Schwendemann et al. Comparison of different Interface Algorithms for a highly dynamic grid Emulator based on a Series Hybrid Converter
CN111541296B (en) Three-phase PWM rectifier direct current bus capacitor current reconstruction and capacity identification method

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
WW01 Invention patent application withdrawn after publication
WW01 Invention patent application withdrawn after publication

Application publication date: 20220104