CN110245858A - A kind of micro-capacitance sensor reliability estimation method containing electric automobile charging station - Google Patents
A kind of micro-capacitance sensor reliability estimation method containing electric automobile charging station Download PDFInfo
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Abstract
The present invention relates to a kind of micro-capacitance sensor reliability estimation method containing electric automobile charging station, comprising the following steps: 1) according to electric car operation characteristic in microgrid, obtain the state-of-charge of each time point electric automobile power battery；2) according to micro-capacitance sensor internal power interactive tactics, interactive response power calculation model is established；3) Interruption performance is switched according to the position of network switching and different type, region division is carried out to micro-capacitance sensor；4) according to the difference of internal fault point region when micro-capacitance sensor isolated operation, different switch motion modes is taken to carry out Fault Isolation；5) the micro-capacitance sensor operational reliability containing electric automobile charging station is assessed using sequential Monte Carlo simulation.Compared with prior art, the present invention agree at this stage and the development trend of following electric automobile charging station access power grid, consider comprehensively, be widely used.
Description
Technical field
The present invention relates to distribution network planning fields, reliable more particularly, to a kind of micro-capacitance sensor containing electric automobile charging station
Property appraisal procedure.
Background technique
With the fast development of economic society, electric car replaced petroleum as its major impetus energy using electric power in recent years
Source, non-carbon-emitting, it is environmental-friendly the features such as, obtained development energetically.The electric car electric load novel as one kind,
If carrying out unordered charging on a large scale, huge impact must be brought to the security and stability of distribution system, economy.Especially exist
Network load peak period is charged, and by the peak for causing electric load plus peak, increases the power supply burden and operation wind of system
Danger.
Therefore, it is necessary to be accustomed to etc. dividing with vehicle to different types of electric car and different vehicle user
Analysis research.It is analyzed by the charge and discharge behavioral trait of different type electric car, establishes electric automobile charging station and carry out electric car
Centralized planning management is carried out, its load that charges is made to show controllability.Meanwhile between electric car and power grid power interact
The developmental research of technology, electric car access power distribution network as a kind of Mobile energy storage, pass through certain power interactive response plan
Slightly, so that it is can be used as a kind of backup power source in network load peak period and convey electric energy to power grid.
After accessing power grid on a large scale with electric car, electric network composition and the method for operation is made to become more sophisticated.Now also
It is not used to evaluate the appraisal procedure of the micro-capacitance sensor operational reliability comprising electric automobile charging station.
Summary of the invention
It is an object of the present invention to overcome the above-mentioned drawbacks of the prior art and provide one kind to fill containing electric car
The micro-capacitance sensor reliability estimation method in power station.
The purpose of the present invention can be achieved through the following technical solutions:
A kind of micro-capacitance sensor reliability estimation method containing electric automobile charging station, comprising the following steps:
1) according to electric car operation characteristic in microgrid, the state-of-charge of each time point electric automobile power battery is obtained；
2) according to micro-capacitance sensor internal power interactive tactics, interactive response power calculation model is established；
3) Interruption performance is switched according to the position of network switching and different type, region division is carried out to micro-capacitance sensor；
4) according to the difference of internal fault point region when micro-capacitance sensor isolated operation, different switch motion sides is taken
Formula carries out Fault Isolation；
5) electronic to containing using sequential Monte Carlo simulation in the case where considering the interaction of micro-capacitance sensor internal power and Fault Isolation
The micro-capacitance sensor operational reliability of vehicle charging station is assessed.
In the step 1), the state-of-charge of each time point electric automobile power battery meets following constraint:
Wherein, T0、T′0The respectively departure time point of regular bus and private savings electric car morning, and T0< T '0, T1And T2
The time point respectively accessed and left, T3For the time point for being parked in charging station behind regular bus return garden, T '3For the electronic vapour of private savings
The time point that vehicle is got home, SOCmin(T0/T′0)、SOCmin(T1)、SOCmin(T2)、SOCmin(T3/T′3) it is respectively in T0Or T '0、
T1、T2、T3Or T '3The state-of-charge of time point electric vehicle, S1It is regular bus in N1、N3Period travel distance, S2For the electronic vapour of private savings
Vehicle is in n1、n3Period travel distance, N1It is electronic regular bus in morning from garden, returns to garden after fixed station connects employee
Period, N2The period of charging station in garden, N are parked in for electronic regular bus3For regular bus in afternoon send employee to fixed station simultaneously
Return to the period of garden, N4The period of garden charging station, n are parked in for regular bus1For employee early superior private savings electric car from
Family arrives the period of garden, n2The period of charging station in garden, n are parked in for private savings electric car3Multiply the electronic vapour of private savings for employee
The period that vehicle is got home from garden, n4It is parked in employee's family time for private savings electric car, W is every kilometer of consumption of electric car
Electricity, WedFor the specified electric quantity of electric automobile power battery, SOCsd·minFor the certain service life of guarantee power battery
The minimum state-of-charge threshold values of setting.
The step 2) specifically includes the following steps:
21) run the period of micro-capacitance sensor, including N are determined1、N2、N3And N4Period；
22) source, power equilibrium calculation lotus are carried out between fault-free region, then power-balance formula between source, lotus are as follows:
Pph(t)=PWT(t)+PPV(t)-PL(t)
Wherein, PphIt (t) is regional balance power, PLIt (t) is the real-time load power in micro-capacitance sensor；PWTIt (t) is wind turbine
Power generation general power of the group in t moment, PPVIt (t) is the power generation general power of photovoltaic power generation unit t moment；
23) work as Pph(t) > 0 and in N1And N3When the period, no electric car access, micro-capacitance sensor only carries out energy storage device
Charging, in N2And N4When the period, to make the stabilization for needing energy storage device when no electric car accesses to maintain system to run,
The state-of-charge of electric car is at least SOCESS·sd, then charge to the electric car in electric automobile charging station；
24) work as Pph(t)≤0 and in N1And N3When the period, only energy storage device discharges, in N2And N4Period, electronic
When automobile is discharged, if Pph(t)+PEV·dis(t) 0 <, then energy storage device simultaneously participates in discharge operation, if energy storage device, electricity
Electrical automobile charging station and renewable energy joint power output are all unable to satisfy workload demand, i.e. Pph(t)+PEV·dis(t)+
PESS·dis(t) when < 0, then load reduction is carried out according to the severity level of net internal loading, if output power still supplies when being reduced to zero
It is electric insufficient, then further the load in the isolated island region is cut down, wherein PEV·disIt (t) is the electric discharge of t moment charging station
Power, PESS·disIt (t) is discharge power of the energy storage device in t moment；
25) based on step 23) and micro-capacitance sensor internal power interactive tactics 24), energy storage device the filling of different periods,
Discharge power calculating formula are as follows:
Wherein, PESS·disIt (t) is the discharge power of energy storage device, PESS·chIt (t) is the charge power of energy storage device,
PESS·dis·maxFor the maximum discharge power of energy storage device, PESS·ch·maxFor the maximum charge power of energy storage, SOCESSIt (t) is storage
The state-of-charge of energy equipment, SOCESS·sdIt is that energy storage is stablized when electric automobile charging station is without electric car for maintenance follow-up system
The state-of-charge to be kept；
26) in N1、N3Electric car quantity in period charging station is approximately zero, is considered in N2、N4Period electronic vapour
Vehicle charging station and the power situation that interacts between micro-capacitance sensor, i.e. interactive response power calculation model are as follows:
Work as Pph(t) when > 0, charging station charge power:
Work as Pph(t) when < 0, charging station discharge power:
PEV·dis·max(t)=Ncar(t)·Pcar·dis+Nbus(t)·Pbus·dis
Wherein, PEV·maxFor the maximum allowable flowing power of main line that charging station is connect with micro-capacitance sensor, PEV·dis·max(t) it is
Charging station obtains in t moment and maximum sends out power.
In the step 3), the specific classification for carrying out region division to micro-capacitance sensor includes:
Level-1 area: inside does not have the region of any type switching device, once element fault occurs in the region, then
Overall isolation is carried out to the region, and when enumerating failure, using level-1 area as minimum enumeration unit, considers the region
Overall failure rate；
Level-2 area: using breaker as boundary, the region of breaker is not contained in region, is combined by multiple level-1 areas
Made of same bypass region.
In the step 4), takes different switch motion modes to carry out Fault Isolation and specifically includes:
When breaking down in the level-1 area using disconnecting switch as boundary, all updrift side breakers in the region
Or intelligent switch acts first, cuts off the supply current of all power supplys, cut-offs the disconnecting switch isolated fault of fault zone, weight
Breaker and intelligent switch are closed, micro-capacitance sensor fault-free equipment is restored to operate normally；
When using intelligent switch as the level-1 area internal fault on boundary, corresponding intelligent switch is only disconnected；
When circuit branch road failure, it is not necessarily to carry out the operation of cut-offfing of disconnecting switch, while breaker and intelligence after blocking electric current
It can switch and no longer close.
The step 5) specifically includes the following steps:
51) initial data, the initial value T=0 of setting simulation clock, it is assumed that all elements of micro-capacitance sensor are initially positive are read
Normal working condition；
52) according to the time between failures TTF and fault correction time TTR of element each in micro-capacitance sensor, when obtaining TTF
Between sequence table and TTR time series table；
53) it enumerates failure and chooses minimum value TTF in TTF time series tableiCorresponding element is fault element；
54) it obtains from T to T+TTFiSimulation time section in, micro-capacitance sensor electric automobile charging station access whether not
With the operation conditions in the period, and cumulative simulation time T=T+TTFi；
55) judge fault type and position and determine failure influence area；
56) Fault Isolation is carried out to micro-capacitance sensor after failure；
57) before malfunctioning node restores to operate normally, need are determined whether according to the operation conditions in the region after isolated fault
Load reduction is carried out, if so, the accumulative load power for being cut in the power off time of load and being cut in, and cumulative emulation
Time T=T+TTRi；
58) power off time of impacted load bus is obtained；
59) judge whether the time reaches the regulation time limit, if it is not, then return step 52)；If so, continuing in next step；
510) reliability assessment is carried out according to the reliability assessment index of micro-grid system and load bus.
In the step 510), reliability assessment index includes conventional reliability evaluation index and fills containing electric car
The micro-capacitance sensor reliability assessment index in power station.
When the conventional reliability evaluation index includes system annual power failure frequency SAIFI, system annual power failure
Between SAIDI, user annual interruption duration CAIDI and averagely power availability ASAI.
The micro-capacitance sensor reliability assessment index containing electric automobile charging station includes the average charge depth of charging station
Electric automobile charging station when ACD, averaged discharge depth ADD, average load cut down depth ALRD, fault-free block supply deficiency
Electric discharge reduces reduction plans dynamics η.
The calculating formula of the micro-capacitance sensor reliability assessment index containing electric automobile charging station includes:
Wherein,The respectively power of the charging of electric automobile charging station i-th and jth time electric discharge, CHT, DIST
The respectively total degree of electric automobile charging station charging and discharging, PGiIt is renewable when charging for electric automobile charging station i-th
The capable of emitting power of the energy, ALR are the total degree that load reduction is carried out in micro-capacitance sensor, PzThe load power cut down for the z times.
Compared with prior art, the invention has the following advantages that
According to the job specification of automobile user in garden in the present invention, according to the row of different types of electric car
It sails characteristic and proposes garden micro-capacitance sensor in isolated operation, the energy-storage system and micro-capacitance sensor in electric automobile charging station joint net
Power interactive tactics between system, it is contemplated that a variety of actual operation conditions (charging, failure, reduction etc.), using sequential illiteracy
Special Carlow simulation combines evaluation index proposed by the present invention to carry out the micro-capacitance sensor operational reliability containing electric automobile charging station
Assessment effectively intuitively reflects the influence after electric car participation V2G is responded to micro-capacitance sensor operational reliability, is subsequent
The operation of real micro-capacitance sensor provides reference value.
Detailed description of the invention
Fig. 1 is invention flow chart of the invention.
Fig. 2 is the driving status of the different periods of two types electric car on weekdays.
Fig. 3 is that micro-capacitance sensor internal power interacts operation reserve.
Fig. 4 is that garden micro-capacitance sensor emulates feeder system in example.
Specific embodiment
The present invention is described in detail with specific embodiment below in conjunction with the accompanying drawings.
Embodiment
As shown in Figure 1, the present invention provides a kind of assessment side of micro-capacitance sensor operational reliability containing electric automobile charging station
Method, comprising the following steps:
S1 calculates the state-of-charge of each time point electric automobile power battery according to electric car operation characteristic in microgrid；
S2 establishes interactive response power calculation model according to micro-capacitance sensor internal power interactive tactics；
S3 switchs Interruption performance according to the position of network switching and different type, carries out region division to micro-capacitance sensor；
S4 takes different switch motion plans according to the difference of internal fault point region when micro-capacitance sensor isolated operation
Slightly carry out Fault Isolation；
S5 comments the micro-capacitance sensor operational reliability containing electric automobile charging station using sequential Monte Carlo simulation algorithm
Estimate.
According to electric car operation characteristic in microgrid in step S1, the lotus of each time point electric automobile power battery is calculated
Electricity condition, the specific steps are that:
Step S11: according to the operating time behavior of automobile user in garden, to the row of different type electric vehicle
It sails characteristic to be analyzed, Fig. 2 is the driving status schematic diagram of its different periods on weekdays.Wherein N1For electronic regular bus in morning
From garden, the period of garden is returned after fixed station connects employee；n1For employee early superior private savings electric car from
Family arrives the period of garden；N2(n2) it is that electronic regular bus (private savings electric car) is parked in the period of charging station in garden；N3For
Regular bus sent employee to fixed station and returned to the period of garden, n afternoon3Multiply private savings electric car for employee to get home from garden
Period；N4The period of garden charging station, n are parked in for regular bus4Employee's family time is parked in for private savings electric car；
Step S12: for the use vehicle demand for meeting automobile user, the state-of-charge of each time point power battery need to expire
The minimum constraint of foot are as follows:
In formula: T0、T′0The respectively departure time point of regular bus and private savings electric car morning, and T0< T '0； T1And T2
It respectively accesses (working) and leaves the time point of (next)；T3For the time point for being parked in charging station behind regular bus return garden；T′3
The time point got home for private savings EV；SOCmin(T0/T′0)、SOCmin(T1)、 SOCmin(T2)、SOCmin(T3/T′3) it is in T0Or T
′0、T1、T2、T3Or T '3The state-of-charge of time point each electric vehicle；S1、S2Respectively regular bus (private savings electric car) is in N1
(n1)、N3(n3) period travel distance (kM)；W is every kilometer of power consumption of electric car, WedFor electric automobile power battery
Specified electric quantity； SOCsd·minThe minimum state-of-charge threshold values set to guarantee the certain service life of power battery.
According to micro-capacitance sensor internal power interactive tactics in step S2, interactive response power calculation model, specific steps are established
Are as follows:
Step S21: determine micro-capacitance sensor run the period, i.e. N1,N2,N3,N4；
Step S22: power equilibrium calculation carrying out source, lotus to fault-free region, power-balance formula is as follows between source, lotus:
Pph(t)=PWT(t)+PPV(t)-PL(t)
In formula: PLIt (t) is the real-time load power in micro-capacitance sensor；PWTIt (t) is power generation total work of the Wind turbines in t moment
Rate, PPVIt (t) is the power generation general power of photovoltaic power generation unit t moment.
Step S23: if Pph(t) 0 >.In N1And N3When the period, no electric car access, micro-capacitance sensor will be only to energy storage electricity
It charges in pond.In N2And N4Period, to make when no electric car accesses, it is steady to maintain system to run to need energy storage device
Fixed, state-of-charge should possess certain restrictions SOCESS·sd.And then the electric car in electric automobile charging station is filled
Electricity；
Step S24: if Pph(t)≤0.In N1And N3When the period, only energy-storage battery discharges.In N2And N4Period, first
Electric car is arranged to discharge.If Pph(t)+PEV·dis(t) 0 <, then energy-storage battery also simultaneously participates in discharge operation.If storage
Energy battery, electric automobile charging station and renewable energy joint power output are all unable to satisfy workload demand, i.e. Pph(t)+PEV·dis
(t)+PESS·dis(t) when < 0, load reduction need to be carried out according to the severity level of net internal loading.When wherein, PEV·disIt (t) is t
The discharge power of moment charging station, PESS·disIt (t) is discharge power of the energy-storage battery in t moment.Meanwhile being considered as electronic vapour
The variation of the output power of vehicle charging station.It can not also power when output power is reduced to zero still insufficient, then it will be further to this
Load in isolated island region is cut down.
Step S25: above-mentioned power interactive tactics, charge and discharge power calculation model of the energy storage device in different periods are based on
Are as follows:
In formula: PESS·disIt (t) is the discharge power of energy storage device, PESS·chIt (t) is the charge power of energy storage device,
PESS·dis·maxFor the maximum discharge power of energy storage device, PESS·ch·maxFor the maximum charge power of energy storage, SOCESSIt (t) is storage
The state-of-charge of energy equipment, SOCESS·sdIt is that energy storage is stablized when electric automobile charging station is without electric car for maintenance follow-up system
The state-of-charge to be kept.
Step S26: in N1、N3Electric car quantity in period charging station is substantially zeroed.Therefore, only consider in N2、
N4Period electric automobile charging station interacts power situation between micro-capacitance sensor:
Work as Pph(t) when > 0, charging station charge power:
Work as Pph(t) when < 0, charging station discharge power:
PEV·dis·max(t)=Ncar(t)·Pcar·dis+Nbus(t)·Pbus·dis
In formula: PEV·maxFor the maximum allowable flowing power of main line that charging station is connect with micro-capacitance sensor, about by line parameter circuit value
Beam；PEV·dis·max(t) for charging station t moment obtain it is maximum send out power, may participate in all kinds of electricity of electric discharge by moment station
Electrical automobile quantity Ncar(t)、Nbus(t) and single electric car discharge power Pcar·dis、Pbus·disConstraint.
Interruption performance is switched according to the position of network switching and different type in step S3, region is carried out to micro-capacitance sensor
It divides, it is specific to classify are as follows:
Level-1 area: internal there is no the regions of any type switching device.Whichever element fault in the region,
Overall isolation will be carried out to the region.Therefore, when enumerating failure, using level-1 area as minimum enumeration unit, consider the area
The overall failure rate in domain.
Level-2 area: using breaker as boundary, no longer containing the region of breaker in region.Generally by multiple level-one areas
The same bypass region that domain is composed.
According to the difference of internal fault point region when micro-capacitance sensor isolated operation in step S4, different switches is taken
Action policy carries out Fault Isolation, specific steps are as follows:
Step S41: when using disconnecting switch to break down in the level-1 area on boundary, all updrift sides in the region
Breaker or intelligent switch act first, cut off the supply current of all power supplys, cut-off the disconnecting switch isolation event of fault zone
Barrier, is overlapped breaker and intelligent switch, and micro-capacitance sensor fault-free equipment is restored to operate normally；
Step S42: when using intelligent switch as the level-1 area internal fault on boundary, corresponding intelligent switch need to only be disconnected i.e.
It can；
Step S43: when with circuit branch road failure, blocking and cut-off operation without carry out disconnecting switch after electric current, disconnected simultaneously
Road device and intelligent switch cannot close again.
Using sequential Monte Carlo simulation algorithm to the micro-capacitance sensor operational reliability containing electric automobile charging station in step S5
It is assessed, specific steps are as follows:
Step S51: initial data, the initial value T=0 of setting simulation clock, it is assumed that all elements are initially normally are read
Working condition；
Step S52: the time between failures (time to failure, TTF) and failure of each element in network are calculated
Repair time (time to repair, TTR), obtain time series table: TTF, TTR；
Step S53: failure is enumerated.Choose minimum value TTF in TTFiCorresponding element is fault element；
Step S54: analysis simulation time T to T+TTFiPeriod, system electric automobile charging station access whether not
With the operation conditions in the period, add up simulation time T=T+TTFi；
Step S55: judging fault type and position, determines failure influence area；
Step S56: Fault Isolation is carried out to micro-capacitance sensor after failure；
Step S57: before malfunctioning node restores to operate normally, the operation conditions in the region after isolated fault is divided
Analysis.Determine whether that load reduction need to be carried out.If so, the accumulative power off time for being cut in load, and the load function being cut in
Rate.And accumulative simulation time T=T+TTRi；
Step S58: the power off time of impacted load bus is calculated；
Step S59: judging whether simulation time reaches the regulation emulation time limit, if it is not, then return step S62；If so,
Continue in next step；
Step S510: the reliability assessment index of computing system and load bus.
Reliability assessment index specifically includes:
Reliability Evaluation index under micro-capacitance sensor island state can take the reliability assessment of conventional electrical distribution net to refer to
Mark (system annual power failure frequency SAIFI, system annual power off time SAIDI, user's annual interruption duration
The CAIDI and availability ASAI that averagely powers).Meanwhile the power after the access of consideration EV charging station between micro-grid system interacts
Situation, the present invention propose following index on the basis of traditional index transported after analyzing the access of EV charging station to micro-capacitance sensor
The influence of row reliability:
(1) the charge and discharge number (CHT, DIST) first by statistics EV charging station in emulation cycle, and charging
The average charge depth (Average charging depth, ACD) (kW/ times) stood, averaged discharge depth (Average
Discharge depth, ADD) parameters such as (kW/ times), to analyze the cohesion between EV charging station and micro-capacitance sensor.Wherein:
In formula:The respectively power of the charging of EV charging station i-th and jth time electric discharge；PGiFor the power station EV i-th
When secondary charging, the capable of emitting power of renewable energy.
(2) number (Average load reductions, ALR) of load reduction is carried out in micro-capacitance sensor by calculating
(times/year) and average load cut down depth (Average load reduction depth, ALRD) (kW/ times), and analysis contains
The micro-capacitance sensor that EV charging station is accessed with no EV charging station, in the difference of the electricity consumption reliability of two kinds of off line internal loadings of different situations,
The further influence after the access of analysis EV charging station to micro-capacitance sensor power supply reliability.Wherein:
In formula: PzThe load power cut down for the z times.
(3) in netting when fault-free block supply deficiency, EV charging station participates in electric discharge, reduces scarce power supply volume in net, subtracts
The load power cut down is lacked, to reduce the number of users of power failure.Its effect can be expressed from the next:
Embodiment network structure is as shown in figure 4, with IEEE reliability evaluation test macro RTBS Bus 6
Network structure based on, using the region load bus LP13-LP23 as micro-capacitance sensor, pass through PCC switch access distribution
Net.
Subregion is carried out to micro-capacitance sensor, partitioning scenario is as shown in table 1, totally 11 load level-1 areas, photovoltaic and wind-power electricity generation
1. number and 3. unit is respectively connected in number level-2 area region as two power supply level-1 areas.Wherein, photovoltaic installed capacity is
1.5MW, Wind turbines are made of the blower of 3 0.8MW.Wherein, the incision wind speed of blower is 4m/s, and rated wind speed is
12.5m/s, cut-out wind speed 25m/s.Energy-storage battery ESS is accessed in 3. number level-2 area as an individual level-1 area,
Capacity is 5000kWh.And distribution line is all made of cable in micro-capacitance sensor region.Table 2 is its corresponding reliability ginseng
Number.
1 micro-capacitance sensor partitioning scenario of table
2 dependability parameter of table
For EV1, EV2 charging station in Fig. 4, it is respectively equipped with 50 private savings electric automobile charging piles and 5 electronic regular buses fills
Electric stake, private savings electric car hypothesis are unified for BYD E5 vehicle, and electronic regular bus is that space leads to E8 vehicle, two types electric vehicle
Configuration parameter it is as shown in table 3.Timing node T0(T0‘)、T1、T2、T3(T3') it is taken as 7:00 (7:30), 9:00,17 respectively:
00、19:00(18:30)。
The configuration parameter of 3 two types electric vehicle of table
This example has carried out related reliability respectively and has referred to meter and the access of EV charging station and without two kinds of situations of EV charging station
Target calculates, as a result as shown in table 4 below.Wherein, the severity level of this example assumed load node LP13, LP17, LP19 compared with
It is low, it can preferentially be cut down, the reduction of subsequent corresponding load is then determined by the electrical distance between load point and power supply node, away from
From by successively cutting down as far as close.
4 related reliability index of table
| Reliability index | Without EV charging station | Charging station containing EV |
| SAIFI (secondary/family year) | 2.449 | 2.212 |
| SAIDI (family h/ year) | 14.298 | 12.103 |
| ASAI | 0.99634 | 0.9986 |
| ACD (kW/ times) | -- | 0.2062 |
| ADD (kW/ times) | -- | 0.1983 |
| ALR (times/year) | 1577 | 676 |
| ALRD (kW/ times) | 0.3842 | 0.2763 |
| η | -- | 0.4178 |
From in 4 calculated result of table as can be seen that micro-capacitance sensor island operation state under, consider electric automobile charging station with it is micro-
Power between power grid interacts situation, and the average power off time of micro-grid system reduces 0.237 (secondary/family year), average power failure
Number reduces 15.35%, and load, which averagely cuts down depth (ALRD), reduces about 28.1%, and load is cut down number (ALR) and then dropped
Low 57.1%, effectively reflect raising of the micro-capacitance sensor under island operation state to the power supply quality of load.Electric car
Depth of charge index (ACD) also reflects, makes full use of the V2G technology of electric automobile charging station, is meeting electric car charging
While demand, system is also increased to the digestion capability of distributed energy.In micro-capacitance sensor when generated output affluence, to electricity
Electrical automobile charging can effectively reduce the abandonment in system, abandon light rate.
Claims (10)
1. a kind of micro-capacitance sensor reliability estimation method containing electric automobile charging station, which comprises the following steps:
1) according to electric car operation characteristic in microgrid, the state-of-charge of each time point electric automobile power battery is obtained；
2) according to micro-capacitance sensor internal power interactive tactics, interactive response power calculation model is established；
3) Interruption performance is switched according to the position of network switching and different type, region division is carried out to micro-capacitance sensor；
4) according to the difference of internal fault point region when micro-capacitance sensor isolated operation, take different switch motion modes come into
Row Fault Isolation；
5) use sequential Monte Carlo simulation to containing electric car in the case where considering the interaction of micro-capacitance sensor internal power and Fault Isolation
The micro-capacitance sensor operational reliability of charging station is assessed.
2. a kind of micro-capacitance sensor reliability estimation method containing electric automobile charging station according to claim 1, feature exist
In in the step 1), the state-of-charge of each time point electric automobile power battery meets following constraint:
Wherein, T0、T′0The respectively departure time point of regular bus and private savings electric car morning, and T0< T '0, T1And T2Respectively
For the time point accessed and left, T3For the time point for being parked in charging station behind regular bus return garden, T '3It is arrived for private savings electric car
The time point of family, SOCmin(T0/T′0)、SOCmin(T1)、SOCmin(T2)、SOCmin(T3/T′3) it is respectively in T0Or T '0、T1、T2、
T3Or T '3The state-of-charge of time point electric vehicle, S1It is regular bus in N1、N3Period travel distance, S2Exist for private savings electric car
n1、n3Period travel distance, N1It is electronic regular bus in morning from garden, when returning to garden after fixed station connects employee
Between section, N2The period of charging station in garden, N are parked in for electronic regular bus3Employee is sent to fixed station for regular bus in afternoon and returns to garden
The period in area, N4The period of garden charging station, n are parked in for regular bus1For employee early superior private savings electric car from the home to garden
Period, n2The period of charging station in garden, n are parked in for private savings electric car3Multiply private savings electric car from garden for employee
The period got home, n4It is parked in employee's family time for private savings electric car, W is every kilometer of power consumption of electric car, WedFor
The specified electric quantity of electric automobile power battery, SOCsd·minThe minimum lotus set to guarantee the certain service life of power battery
Electricity condition threshold values.
3. a kind of micro-capacitance sensor reliability estimation method containing electric automobile charging station according to claim 2, feature exist
In, the step 2) specifically includes the following steps:
21) run the period of micro-capacitance sensor, including N are determined1、N2、N3And N4Period；
22) source, power equilibrium calculation lotus are carried out between fault-free region, then power-balance formula between source, lotus are as follows:
Pph(t)=PWT(t)+PPV(t)-PL(t)
Wherein, PphIt (t) is regional balance power, PLIt (t) is the real-time load power in micro-capacitance sensor；PWTIt (t) is Wind turbines in t
The power generation general power at moment, PPVIt (t) is the power generation general power of photovoltaic power generation unit t moment；
23) work as Pph(t) > 0 and in N1And N3When the period, no electric car access, micro-capacitance sensor only charges to energy storage device,
N2And N4When the period, to make the stabilization for needing energy storage device when no electric car accesses to maintain system to run, electric car
State-of-charge be at least SOCESS·sd, then charge to the electric car in electric automobile charging station；
24) work as Pph(t)≤0 and in N1And N3When the period, only energy storage device discharges, in N2And N4Period, electric car into
When row electric discharge, if Pph(t)+PEV·dis(t) 0 <, then energy storage device simultaneously participates in discharge operation, if energy storage device, electric car
Charging station and renewable energy joint power output are all unable to satisfy workload demand, i.e. Pph(t)+PEV·dis(t)+PESS·dis(t) 0 <
When, then load reduction is carried out according to the severity level of net internal loading, if still electricity shortage when output power is reduced to zero, into one
Step cuts down the load in the isolated island region, wherein PEV·disIt (t) is the discharge power of t moment charging station, PESS·dis(t)
For energy storage device t moment discharge power；
25) the micro-capacitance sensor internal power interactive tactics based on step 23) and 24), charge and discharge function of the energy storage device in different periods
Rate calculating formula are as follows:
Wherein, PESS·disIt (t) is the discharge power of energy storage device, PESS·chIt (t) is the charge power of energy storage device, PESS·dis·max
For the maximum discharge power of energy storage device, PESS·ch·maxFor the maximum charge power of energy storage, SOCESSIt (t) is the lotus of energy storage device
Electricity condition, SOCESS·sdIt is that energy storage maintains follow-up system stabilization to be kept when electric automobile charging station is without electric car
State-of-charge；
26) in N1、N3Electric car quantity in period charging station is approximately zero, is considered in N2、N4The charging of period electric car
The power situation that interacts stood between micro-capacitance sensor, i.e. interactive response power calculation model are as follows:
Work as Pph(t) when > 0, charging station charge power:
Work as Pph(t) when < 0, charging station discharge power:
PEV·dis·max(t)=Ncar(t)·Pcar·dis+Nbus(t)·Pbus·dis
Wherein, PEV·maxFor the maximum allowable flowing power of main line that charging station is connect with micro-capacitance sensor, PEV·dis·maxIt (t) is charging
It stands to obtain in t moment and maximum sends out power.
4. a kind of micro-capacitance sensor reliability estimation method containing electric automobile charging station according to claim 1, feature exist
In in the step 3), the specific classification for carrying out region division to micro-capacitance sensor includes:
Level-1 area: inside does not have the region of any type switching device, once occurs element fault, the area Ze Duigai in the region
Domain carries out overall isolation, and when enumerating failure, using level-1 area as minimum enumeration unit, considers the whole event in the region
Barrier rate；
Level-2 area: using breaker as boundary, the region of breaker is not contained in region, is composed of multiple level-1 areas
Same bypass region.
5. a kind of micro-capacitance sensor reliability estimation method containing electric automobile charging station according to claim 1, feature exist
In taking different switch motion modes to carry out Fault Isolation and specifically include in the step 4):
When breaking down in the level-1 area using disconnecting switch as boundary, all updrift side breakers or intelligence in the region
Switch acts first, cuts off the supply current of all power supplys, cut-offs the disconnecting switch isolated fault of fault zone, is overlapped breaker
And intelligent switch, micro-capacitance sensor fault-free equipment are restored to operate normally；
When using intelligent switch as the level-1 area internal fault on boundary, corresponding intelligent switch is only disconnected；
When circuit branch road failure, it is not necessarily to carry out the operation of cut-offfing of disconnecting switch after blocking electric current, while breaker and intelligence are opened
It no longer closes pass.
6. a kind of micro-capacitance sensor reliability estimation method containing electric automobile charging station according to claim 1, feature exist
In, the step 5) specifically includes the following steps:
51) initial data, the initial value T=0 of setting simulation clock, it is assumed that all elements of micro-capacitance sensor are initially normal work are read
State；
52) according to the time between failures TTF and fault correction time TTR of element each in micro-capacitance sensor, TTF time series is obtained
Table and TTR time series table；
53) it enumerates failure and chooses minimum value TTF in TTF time series tableiCorresponding element is fault element；
54) it obtains from T to T+TTFiSimulation time section in, micro-capacitance sensor electric automobile charging station access whether different periods
Interior operation conditions, and cumulative simulation time T=T+TTFi；
55) judge fault type and position and determine failure influence area；
56) Fault Isolation is carried out to micro-capacitance sensor after failure；
57) before malfunctioning node restores to operate normally, determine whether to need to carry out according to the operation conditions in the region after isolated fault
Load is cut down, if so, the accumulative load power for being cut in the power off time of load and being cut in, and cumulative simulation time T
=T+TTRi；
58) power off time of impacted load bus is obtained；
59) judge whether the time reaches the regulation time limit, if it is not, then return step 52)；If so, continuing in next step；
510) reliability assessment is carried out according to the reliability assessment index of micro-grid system and load bus.
7. a kind of micro-capacitance sensor reliability estimation method containing electric automobile charging station according to claim 6, feature exist
In in the step 510), reliability assessment index includes conventional reliability evaluation index and containing electric automobile charging station
Micro-capacitance sensor reliability assessment index.
8. a kind of micro-capacitance sensor reliability estimation method containing electric automobile charging station according to claim 7, feature exist
In the conventional reliability evaluation index includes system annual power failure frequency SAIFI, system annual power off time
SAIDI, user annual interruption duration CAIDI and the availability ASAI that averagely powers.
9. a kind of micro-capacitance sensor reliability estimation method containing electric automobile charging station according to claim 7, feature exist
In the micro-capacitance sensor reliability assessment index containing electric automobile charging station includes the average charge depth ACD of charging station, puts down
Electric automobile charging station electric discharge is reduced when equal depth of discharge ADD, average load cut down depth ALRD, fault-free block supply deficiency
Reduction plans dynamics η.
10. a kind of micro-capacitance sensor reliability estimation method containing electric automobile charging station according to claim 9, feature exist
In the calculating formula of the micro-capacitance sensor reliability assessment index containing electric automobile charging station includes:
Wherein,The respectively power of the charging of electric automobile charging station i-th and jth time electric discharge, CHT, DIST difference
For the total degree that electric automobile charging station is charged and discharged, PGiWhen charging for electric automobile charging station i-th, renewable energy
Capable of emitting power, ALR are the total degree that load reduction is carried out in micro-capacitance sensor, PzThe load power cut down for the z times.
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| CN111985777A (en) * | 2020-07-20 | 2020-11-24 | 中国农业大学 | Method and system for establishing electric vehicle load aggregate regulation and control capability assessment model |
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