CN111884219A - Method and device for evaluating reliability of power distribution network accessed by electric automobile - Google Patents

Method and device for evaluating reliability of power distribution network accessed by electric automobile Download PDF

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Publication number
CN111884219A
CN111884219A CN202010759591.6A CN202010759591A CN111884219A CN 111884219 A CN111884219 A CN 111884219A CN 202010759591 A CN202010759591 A CN 202010759591A CN 111884219 A CN111884219 A CN 111884219A
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power
distribution network
load
fault
electric automobile
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Inventor
赵小娟
余佩
谢刚文
张友强
宋伟
朱小军
宫林
王瑞妙
杨爽
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Electric Power Research Institute of State Grid Chongqing Electric Power Co Ltd
State Grid Corp of China SGCC
Beibei Power Supply Co of State Grid Chongqing Electric Power Co Ltd
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Electric Power Research Institute of State Grid Chongqing Electric Power Co Ltd
State Grid Corp of China SGCC
Beibei Power Supply Co of State Grid Chongqing Electric Power Co Ltd
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Priority to CN202010759591.6A priority Critical patent/CN111884219A/en
Publication of CN111884219A publication Critical patent/CN111884219A/en
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    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60L—PROPULSION OF ELECTRICALLY-PROPELLED VEHICLES; SUPPLYING ELECTRIC POWER FOR AUXILIARY EQUIPMENT OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRODYNAMIC BRAKE SYSTEMS FOR VEHICLES IN GENERAL; MAGNETIC SUSPENSION OR LEVITATION FOR VEHICLES; MONITORING OPERATING VARIABLES OF ELECTRICALLY-PROPELLED VEHICLES; ELECTRIC SAFETY DEVICES FOR ELECTRICALLY-PROPELLED VEHICLES
    • B60L53/00—Methods of charging batteries, specially adapted for electric vehicles; Charging stations or on-board charging equipment therefor; Exchange of energy storage elements in electric vehicles
    • B60L53/60—Monitoring or controlling charging stations
    • B60L53/63—Monitoring or controlling charging stations in response to network capacity
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • 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
    • H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/388—Islanding, i.e. disconnection of local power supply from the network
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2113/00—Details relating to the application field
    • G06F2113/04—Power grid distribution networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2119/00—Details relating to the type or aim of the analysis or the optimisation
    • G06F2119/02—Reliability analysis or reliability optimisation; Failure analysis, e.g. worst case scenario performance, failure mode and effects analysis [FMEA]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/70—Energy storage systems for electromobility, e.g. batteries
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00—Road transport of goods or passengers
    • Y02T10/60—Other road transportation technologies with climate change mitigation effect
    • Y02T10/7072—Electromobility specific charging systems or methods for batteries, ultracapacitors, supercapacitors or double-layer capacitors
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02T—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02T90/10—Technologies relating to charging of electric vehicles
    • Y02T90/12—Electric charging stations

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Abstract

The invention discloses a method and a device for evaluating reliability of a power distribution network accessed by an electric automobile, wherein the method comprises the following steps: carrying out simulation analysis according to a pre-established power distribution network model to determine a fault element, determining fault repair time of the fault element, and determining a reliability index of the power distribution network model according to the current state of the electric automobile and the fault repair time. According to the method, the reliability index of the power distribution network model is determined according to the current state of the electric automobile and the fault repair time corresponding to the fault element in the power grid model, and the reliability reference can be provided for the operation of the power grid, so that the operation reliability of the power grid is improved.

Description

Method and device for evaluating reliability of power distribution network accessed by electric automobile
Technical Field
The invention relates to the technical field of power grid analysis, in particular to a method and a device for evaluating reliability of a power distribution network accessed by an electric automobile.
Background
In recent years, with increasing tension in energy and environmental issues, electric vehicles have been actively developed. At present, researches on charging of electric automobiles connected to a power grid mainly focus on the energy-saving and emission-reducing benefits of the electric automobiles, the influence of charging randomness of the electric automobiles on a load curve of the power grid, the planning of a distribution network containing the electric automobiles and the like. These characteristics all contribute to the reliability of the power distribution system, and it is therefore necessary to analyze this influence quantitatively.
Disclosure of Invention
In view of the above-mentioned defects in the prior art, an object of the present invention is to provide a method and an apparatus for evaluating reliability of a power distribution network accessed by an electric vehicle, so as to implement quantitative evaluation of complementary situations between the power distribution network and the electric vehicle and improve reliability of a power grid system.
One of the purposes of the present invention is realized by such a technical solution, a method for evaluating reliability of a power distribution network accessed by an electric vehicle, comprising:
carrying out simulation analysis according to a pre-established power distribution network model to determine a fault element;
determining a fault repair time for the failed component;
and determining the reliability index of the power distribution network model according to the current state of the electric automobile and the fault repairing time.
Optionally, the performing simulation analysis according to a pre-established distribution network model to determine a faulty element includes:
determining the fault-free working time of each element in the power distribution network model;
and determining the element with the minimum fault-free working time as a fault element.
Optionally, after determining the faulty component according to the pre-established distribution network model, the method further includes:
and accumulating the simulation time according to the fault-free working time of the fault element.
Optionally, the determining the reliability index of the power distribution network model according to the current state of the electric vehicle and the fault repair time includes:
when the electric automobile is in a charging period or a discharging period at present, sampling is carried out based on a distributed power supply output probability model to obtain the output power of a distributed power supply;
carrying out power adjustment on the island power grid according to the output power of the distributed power supply, the charge-discharge power of the electric automobile and the load power so as to balance the power;
and counting the fault information of each load point according to the island power grid after power balance.
Optionally, the performing power adjustment on the islanding power grid according to the output power of the distributed power supply, the charge-discharge power of the electric vehicle, and the load power makes the power balance, including:
when the electric automobile is in a charging period at present, if the output power of the distributed power supply is smaller than the sum of the charging power and the load power of the electric automobile, the load is reduced according to the load priority order until the power is balanced.
Optionally, the performing power adjustment on the islanding power grid according to the output power of the distributed power supply, the charge-discharge power of the electric vehicle, and the load power makes the power balance, including:
when the electric automobile is in a discharging period at present, if the output power of the distributed power supply is smaller than the load power, the electric automobile discharges the island power grid according to the fault repairing time so as to compensate the load.
Optionally, the power adjustment of the island power grid according to the output power of the distributed power supply, the charge-discharge power of the electric vehicle, and the load power makes the power balance, further including:
when the electric automobile is in a discharging period at present, determining the discharging time of the electric automobile;
if the discharge time is longer than the fault repair time and the sum of the output power of the distributed power supply and the discharge power of the electric automobile is smaller than the load power, reducing the load according to the load priority order until the power is balanced;
if the discharging time is less than the fault repairing time, and the sum of the output power of the distributed power supply and the discharging power of the electric automobile is less than the load power, the load is reduced according to the load priority order within the discharging time until the power is balanced, and after the electric automobile exits from the island power grid, the load is reduced for the second time according to the load priority order until the power is balanced.
Optionally, the determining the reliability index of the power distribution network model according to the current state of the electric vehicle and the fault repair time includes: and when the electric automobile is not accessed currently, counting the fault information of each load point in the island power grid.
Optionally, the determining the reliability index of the power distribution network model according to the current state of the electric vehicle and the fault repair time further includes:
repeatedly determining a fault element and accumulating the simulation time until the simulation time reaches a preset time limit value;
and determining the reliability index of the power distribution network model according to all the fault information in the simulation time reaching the preset time limit value.
The second purpose of the invention is realized by the technical scheme, and the device for evaluating the reliability of the power distribution network accessed by the electric automobile comprises:
the fault determining unit is used for carrying out simulation analysis according to a pre-established power distribution network model to determine a fault element;
a time calculation unit for determining a fail-over time of the failed component;
and the data processing unit is used for determining the reliability index of the power distribution network model according to the current state of the electric automobile and the fault repairing time.
Due to the adoption of the technical scheme, the invention has the following advantages: according to the method, the reliability index of the power distribution network model is determined according to the current state of the electric automobile and the fault repair time corresponding to the fault element in the power grid model, and the reliability reference can be provided for the operation of the power grid, so that the operation reliability of the power grid is improved.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention.
Drawings
The drawings of the invention are illustrated as follows:
FIG. 1 is a flow chart of a first embodiment of the present invention;
fig. 2 is a daily load curve in an islanding grid area according to a first embodiment of the present invention;
FIG. 3 is a graph illustrating the effect of an electric vehicle on the load curve of a power distribution network according to a first embodiment of the present invention;
FIG. 4 is a diagram illustrating the effect of the discharging process of the electric vehicle on the load curve of the distribution network according to the first embodiment of the present invention;
FIG. 5 shows the calculation results of the ENSI indicator of the system according to the different embodiments of the present invention;
FIG. 6 is a diagram illustrating system reliability indexes under different scenarios according to the first embodiment of the present invention;
FIG. 7 shows system ENSI indexes of the electric automobile connected to a traditional power distribution network and connected to a power distribution network containing a wind-solar hybrid power supply system according to the first embodiment of the invention.
Detailed Description
The invention is further illustrated by the following figures and examples.
Example one
The electric automobile can be connected into a power grid for charging, and can form isolated island operation with part of load points when power utilization peak periods and a power distribution network are in fault, so that power is continuously supplied to loads in the isolated island power grid. However, unlike Distributed Generation (DG), the electric vehicle discharge process is time-limited and discharges the load in an islanded grid taking into account the length of its discharge time.
For the charging power model, as the on-duty behavior of residents has strong regularity, according to the charging and discharging control strategy of the electric vehicle, a user needs to drive the vehicle to go out after 7:00, assuming that the initial charging time of the electric vehicle obeys uniform distribution, in order to meet the requirement of the user on the electric quantity for going out, the probability density function at the initial charging time in the embodiment meets the following requirements:
Figure BDA0002612679900000041
in this embodiment, the charging power per hour is calculated in units of 24 hours a day. And obtaining the charging state of each electric vehicle accessed to the power grid in each period according to the probability density function of the initial charging moment. Assuming that a charging and discharging process is carried out once a day, the total charging power of the electric vehicle which starts to be connected into the power grid for charging at the moment t meets the following requirements:
Figure BDA0002612679900000042
in the formula, PchaIn this embodiment, the charging power is a constant value, and M is the total number of the connected electric vehicles.
In the peak load period of the night, the electric vehicles can discharge to the power grid to relieve the power supply pressure, and in the embodiment, it is assumed that all the electric vehicles can completely discharge in the peak load period, so that the state of charge of the electric vehicles is SOC when the electric vehicles start to chargeminThe charging time T required after the electric automobile starts to be connected into the power grid for charging at the moment T can be obtained by combining the total charging power of the electric automobilecha,tAnd satisfies the following conditions:
Figure BDA0002612679900000043
in the formula etachaCharging efficiency for the electric vehicle; ebnThe rated capacity of the battery of the electric automobile is obtained.
For the discharge power model, according to the data statistics result, the electric automobile can leave a residential area for outgoing at 7:00 in the morning, and can perform discharge operation in a load peak period after going home after going out at 19:00 in the evening, so that the power supply pressure of a power distribution network is relieved. The electric automobile generates electric energy loss when travelling in daytime, so the dischargeable capacity after returning home is determined by the residual electric quantity of the electric automobile after finishing driving. Since the driving behavior is a main reason of power consumption of the electric vehicle, if the dischargeable capacity of the electric vehicle connected to the power grid during the discharge period is to be obtained, the daily driving distance of the electric vehicle needs to be analyzed.
Daily mileage and remaining SOC model:
in this embodiment, a lognormal distribution is adopted to fit the daily mileage distribution of the electric vehicle, and the probability density function of the lognormal distribution can represent:
Figure BDA0002612679900000051
in the formula, d is the daily driving mileage of the electric automobile; mu and sigma respectively represent expected values and variances of the daily mileage of the electric automobile, wherein mu is 3.20, and sigma is 0.88.
Meanwhile, the embodiment also provides a charge and discharge control strategy of the electric automobile, which comprises the following steps:
during the charging period of the electric automobile, if the electric automobile is in the state of charge (SOC)t) Not satisfying SOCt＝SOCmaxAnd then the electric automobile is charged until the charging time period is over or the SOC is mett＝SOCmaxAnd then the charging is finished.
During the discharging period of the electric automobile, if the state of charge (SOC) of the electric automobile is at the momentt) Satisfies SOCt＞SOCminThe electric vehicle can be discharged until the discharging period is over or the state of charge of the electric vehicle does not meet the SOCt＞SOCminThe discharge is terminated later, wherein in the formula, SOCminThe lowest state of charge allowed by the battery of the electric automobile can be represented, and the SOC can be presetmin＝0.2。
SOC (state of charge) of battery reaching maximum before electric automobile goes out every daymaxAssuming that the power consumption of the electric vehicle in the unit travel distance is fixed, the charge state of the electric vehicle after the electric vehicle finishes going home every day can be calculated by the following formula:
SOCend＝SOCmax-wd/Ebn
in the formula, SOCendAnd w represents the electric charge state of the electric automobile after going out and going home, and the electric quantity consumed by the electric automobile in unit driving mileage.
According to the probability density function and the SOC, the SOC which is the SOC of the electric automobile after the trip of each day is finished can be obtained through samplingendAnd discharging the power grid by using the energy storage characteristic of the electric automobile in the electric automobile discharging period based on the electric automobile discharging control strategy. Assuming that the network access probabilities of the electric vehicle in each hour of the discharge period are the same, the probability density function of the initial discharge time of the electric vehicle can be obtained:
Figure BDA0002612679900000052
based on this, the state of each electric vehicle can be obtained for each period. The total discharge power of the electric automobile which starts to discharge to the power grid at the moment t meets the following requirements:
Figure BDA0002612679900000053
in the formula, PdisRepresenting the discharge power of the electric vehicle connected to the grid and having Pdis＝Pcha。
The equivalent discharge time T after the electric automobile is connected to the power grid for discharging at the moment T can be obtaineddist,And the calculation formula satisfies:
Figure BDA0002612679900000061
in the formula etadisThe discharge efficiency of the electric automobile is improved.
Since DG and Electric Vehicle (EV) access do not affect the planned off-island load point and the circuit breaker elements are set 100% reliable in this embodiment, only line element faults on the main feeder and element faults within the planned island may result in a power outage at the planned in-island load point. Therefore, in order to simplify the calculation process, in this embodiment, only the reliability of the load point in the planned island is evaluated, and only the fault conditions of the main feeder segment, the line and the transformer in the planned island are considered, so that the electric vehicle is connected to the power distribution network.
Based on the first embodiment of the present invention, a method for evaluating reliability of a power distribution network accessed by an electric vehicle is provided, as shown in fig. 1, including:
s101, performing simulation analysis according to a pre-established power distribution network model to determine a fault element;
specifically, the power grid parameters can be input through the simulation platform, and the data is initialized to complete the establishment of the power distribution network model.
S102, determining the fault repair time of the fault element;
s103, determining the reliability index of the power distribution network model according to the current state of the electric automobile and the fault repairing time.
According to the method, the reliability index of the power distribution network model is determined according to the current state of the electric automobile and the fault repair time corresponding to the fault element in the power grid model, and the reliability reference can be provided for the operation of the power grid, so that the operation reliability of the power grid is improved.
Optionally, the performing simulation analysis according to a pre-established distribution network model to determine a faulty element includes:
determining the fault-free working time of each element in the power distribution network model;
and determining the element with the minimum fault-free working time as a fault element.
Optionally, after determining the faulty component according to the pre-established distribution network model, the method further includes:
and accumulating the simulation time according to the fault-free working time of the fault element.
Specifically, the non-failure operating time TTF of each element can be calculated through simulation, the element with the smallest TTF is found, and assuming that the element number is i, the element is set as a failure element, and the failure operating time TTF is accumulated to the simulation time:
MCTime＝MCTime+TTFmin
calculating the fault repair time TTR of the element i, namely the fault duration D is TTR, and counting the fault power failure times and the power failure time of each load point according to a traditional method if an island cannot be formed due to the fact that the fault element is a branch feeder section or a transformer; and if the fault element is the main feeder section, the next step is carried out, and the state of the electric automobile in the fault time period is judged.
Optionally, the determining the reliability index of the power distribution network model according to the current state of the electric vehicle and the fault repair time includes:
when the electric automobile is currently in a charging period or a discharging period, sampling a DG output probability model to acquire the DG output power;
carrying out power adjustment on the island power grid according to the output power of the DG, the charge-discharge power of the electric automobile and the load power so as to balance the power;
and counting the fault information of each load point according to the island power grid after power balance.
Optionally, the performing power adjustment on the islanding power grid according to the output power of the DG, the charge-discharge power of the electric vehicle, and the load power makes the power balanced includes:
when the electric automobile is in the charging period at present, if the output power of the DG is smaller than the sum of the charging power and the load power of the electric automobile, the load is reduced according to the load priority order until the power is balanced.
Specifically, for the electric automobile in the charging state, according to the DG output probability model, the DG output power P is obtained through samplingDG(equivalent to P when the system does not contain DGsDG0), two cases are distinguished:
when P is presentDG＞PL+PchaWhen is, PLRepresenting the load power, PchaRepresenting the charging power, and continuously supplying power to loads in the island power grid by a DG;
when P is presentDG＜PL+PchaIn time, load reduction is carried out according to an important load priority power supply principle until power balance is met in an island power grid;
and determining fault information of each load point according to the island power grid after power balance, wherein the fault information can be the power failure times and the power failure time in the embodiment.
Optionally, the performing power adjustment on the islanding power grid according to the output power of the DG, the charge-discharge power of the electric vehicle, and the load power makes the power balanced includes:
and when the electric automobile is in a discharging period at present, if the output power of the DG is smaller than the load power, discharging the island power grid through the electric automobile according to the fault repairing time so as to compensate the load.
For the electric automobile in the discharging state, sampling is carried out according to a DG output probability model to obtain the DG output power PDG(equivalent to P when the system does not contain DGsDG0), too, isTwo cases are distinguished:
when P is presentDG＞PLIn time, the loads in the island can be continuously supplied with power by the DG;
when P is presentDG＜PLWhen the island load is in power balance, the electric automobile which is connected into the power grid for discharging and the DG can supply power to the load in the island together;
and determining fault information of each load point according to the island power grid after power balance, wherein the fault information can be the power failure times and the power failure time in the embodiment.
Optionally, the power adjustment of the islanding grid according to the output power of the DG, the charge-discharge power of the electric vehicle and the load power makes the power balance, further comprising:
when the electric automobile is in a discharging period at present, determining the discharging time of the electric automobile;
if the discharge time is longer than the fault repair time, and the sum of the output power of the DG and the discharge power of the electric automobile is smaller than the load power, reducing the load according to the load priority order until the power is balanced;
if the discharging time is less than the fault repairing time, and the sum of the DG output power and the discharging power of the electric automobile is less than the load power, reducing the load according to the load priority order within the discharging time until the power is balanced, and after the electric automobile exits from the island power grid, reducing the load for the second time according to the load priority order until the power is balanced.
Specifically, in the case that an electric vehicle which is discharged by being connected to a power grid and a DG supply power to a load in an island together, the electric vehicle discharge time T is determined firstlydisThere can be two cases:
I. when T isdisDuration of fault > D, if PDG+Pdis≥PLThe loads in the island can be continuously supplied with power by the DG and the EV, if P isDG+Pdis＜PLThe load needs to be reduced according to the priority order of the load until the power is balanced, and then the fault information of each load point is recorded.
II. When T isdis< D, at TdisAnalysis during the time period same as I, at D-TdisIn a time period, the electric automobile quits the power grid, at the moment, only the distributed power supply supplies power, the load needs to be further reduced according to the load priority order until the power is balanced, and then the fault information of each load point is recorded.
Optionally, the determining the reliability index of the power distribution network model according to the current state of the electric vehicle and the fault repair time includes: and when the electric automobile is not accessed currently, counting the fault information of each load point in the island power grid.
Specifically, if the electric vehicle is not currently in the access state, the fault information of each load point is directly recorded without considering the influence of the electric vehicle.
Optionally, the determining the reliability index of the power distribution network model according to the current state of the electric vehicle and the fault repair time further includes:
repeatedly determining a fault element and accumulating the simulation time until the simulation time reaches a preset time limit value;
and determining the reliability index of the power distribution network model according to all the fault information in the simulation time reaching the preset time limit value.
After the power grid fault information of one fault element is received, whether simulation time MCTIMe reaches a preset simulation time limit value is judged, if yes, the simulation process is ended, and if not, the next fault element is determined repeatedly.
After all fault information within the preset simulation time limit is counted, the reliability index of the island system can be calculated according to the total fault power failure times, the total power failure time and the power shortage amount of each load point of the island power grid within the simulation time.
In summary, the method provided by the invention analyzes the island power grid under the condition of electric vehicle access so as to quantitatively evaluate the reliability of the corresponding power distribution network.
Furthermore, an analysis example is provided in the embodiment, and an example system and parameter setting are as follows:
the wind-solar hybrid power supply system and the electric vehicle are connected to the line 25 on the branch feeder F7. The daily load curve in the island region is shown in fig. 2. Assuming that the electric quantity of each electric automobile is the same in unit mileage and is 0.17kWh/km, the charging parameters of the electric automobile are shown in Table 1. In the calculation process, the electric vehicle load grade is assumed to be low, the electric vehicle charging load is firstly cut off when the load is cut, and the electric vehicles connected to the power grid can interact with the power grid.
TABLE 1 electric vehicle Battery charging parameters
Figure BDA0002612679900000091
Analysis of influence of electric vehicle charging and discharging processes on power distribution network load
1. Influence of electric vehicle charging process on load of power distribution network
The following three comparison schemes are set in the system of the present embodiment to study the influence of the charging process of the electric vehicle on the load of the power distribution network in different charging modes:
the first scheme is as follows: the electric automobile is not connected;
scheme II: 500 electric vehicles are connected, and a slow charging mode is adopted, so that the power grid is not discharged;
the third scheme is as follows: 500 electric vehicles are connected, and a quick charging mode is adopted, so that the electric power grid is not discharged.
Fig. 3 shows the effect of the electric vehicle on the load curve of the distribution network in slow and fast charging modes. As can be seen from fig. 3, when the electric vehicle is connected to the power distribution network as a load to perform a charging operation, the load of the power distribution network is increased in the charging period of 00:00-7:00, and the discharging process of the electric vehicle to the power distribution network is not considered, so that the load of the power distribution network is not affected in other periods. In the slow charging mode, the charging power of a single electric vehicle is low, but the required charging time is long, so that a peak value is formed in the low-valley period of the system load when a large number of electric vehicles are connected to carry out slow charging at different moments; in the fast charging mode, the charging power of the electric automobile is larger, but the required charging time is shorter, so the charging power accessed to the power grid at each moment in the charging period is more consistent, and the equivalent load of the system in the period is larger.
2. Influence of electric vehicle discharge process on power distribution network load
The following three comparison schemes are set in the system of the present embodiment to analyze the influence of the electric vehicle discharging process on the load of the distribution network in different charging modes:
the first scheme is as follows: the electric automobile is not connected;
and the scheme is as follows: 500 electric vehicles are connected, a slow charging mode is adopted, and the discharging process of the electric vehicles is calculated;
and a fifth scheme: 500 electric vehicles are connected, and a rapid charging mode is adopted to take account of the discharging process of the electric vehicles.
Fig. 4 shows the effect of the discharging process of the electric vehicle on the load curve of the distribution network in the slow charging mode and the fast charging mode. As can be seen from the figure, when the electric automobile with the V2G technology is connected to a power distribution network, the load of the power distribution network is increased in a charging period, and the power supply pressure of the power distribution network is reduced by returning electric energy to the power distribution network in a discharging period, so that the peak clipping and valley filling functions can be achieved.
Analysis of influence of electric vehicle access on reliability of power distribution network
1. Influence of electric vehicle as charging load on grid reliability
The following three comparison schemes are set in the system of the present embodiment to analyze the influence of the electric vehicle as a charging load on the reliability of the power distribution network in different charging modes:
the first scheme is as follows: the electric automobile is not connected;
scheme II: 500 electric vehicles are connected, and a slow charging mode is adopted, so that the power grid is not discharged;
the third scheme is as follows: 500 electric vehicles are connected, and a quick charging mode is adopted, so that the electric power grid is not discharged.
Based on a Matlab programming program, the reliability of the operator system is evaluated by using a sequential Monte Carlo simulation method, and the reliability indexes of the operator system under different schemes are obtained and are shown in Table 2 and FIG. 5.
TABLE 2 System reliability index under different schemes
Figure BDA0002612679900000101
The calculation results in table 2 show that the access of the charging load of the electric vehicle has no influence on other reliability indexes of the power grid, and only influences on the ENSI index. FIG. 5 shows the calculation results of the ENSI indexes of the systems under different schemes when the electric vehicle is connected to the power distribution network only as a load.
When the electric vehicle is connected to the power distribution network only as a charging load, the following conclusions can be drawn from fig. 5:
1. because the electric automobile is connected into the power grid for charging operation, the total load level of the system in the charging period is increased, and therefore after the charging load of the electric automobile is connected into the power distribution network, the expected power shortage amount of the power distribution network is increased, and the reliability level of the system is reduced;
2. compared with the slow charging mode, when the electric automobile is charged in the fast charging mode, the charging power of the electric automobile is higher, so that the total charging load connected to a power grid is higher, and therefore the expected power shortage index ENSI of the system is higher than that of the slow charging mode in the fast charging mode;
influence of dual attributes of load and power supply of electric automobile on reliability of power grid
The following three comparison schemes are set in the system of the calculation example, and the influence of the dual attributes of the electric automobile on the reliability of the power distribution network is researched:
the first scheme is as follows: the electric automobile is not connected;
scheme II: 500 electric vehicles are connected, and a slow charging mode is adopted, so that the power grid is not discharged;
and the scheme is as follows: 500 electric vehicles are connected, and a slow charging mode is adopted to take account of the discharging process of the electric vehicles.
Based on a Matlab programming program, the reliability of the operator system is evaluated by using a sequential Monte Carlo simulation method, and the reliability indexes of the operator system under different schemes are obtained and are shown in Table 3 and FIG. 6.
TABLE 3 System reliability index under different schemes
Figure BDA0002612679900000111
As can be seen from the calculation results in table 3, when the electric vehicle is used as a load and a storage battery, after the electric vehicle is connected to the power grid, the SAIDI index of the system is not changed, and the SAIDI index is decreased, because when the power distribution network fails in the discharge period of the electric vehicle, the electric vehicle can form an isolated island operation with a partial load, and the remaining electric quantity is sent back to the power grid, thereby reducing the power failure time at the partial load point. FIG. 6 shows the calculation results of the ENSI indexes of the systems under different schemes when the dual attributes of the load and the power supply of the electric automobile are considered.
As can be seen from fig. 6, compared with the situation that the electric vehicle is not added, when the dual attributes of the load and the power supply of the electric vehicle are considered, after the electric vehicle is connected to the power distribution network, the ENS index of the system is increased by 2.0574MWh, because although the electric vehicle can continue to supply power to a partial load point by discharging to the power distribution network when the power distribution network fails in the discharging period, the charging load of the electric vehicle increases the total load level of the system in the charging period, and the electric power that the electric vehicle can feed back to the power distribution network in the discharging period is limited, so the reliability level of the system still decreases;
compared with the second scheme, the discharging process of the electric automobile to the power grid is calculated, the power shortage index ENSI of the system is reduced by 1.7002MWh, and therefore after the electric automobile is connected to the power distribution network, the residual electric quantity of the electric automobile is transmitted back to the power grid by using the corresponding technology in the power utilization peak period, and negative effects of the connection of the electric automobile on the reliability of the power distribution network can be improved to a certain extent.
Influence of simultaneous access of electric automobile-wind-solar hybrid power supply system on reliability of power distribution network
In order to research the influence of the simultaneous access of the electric automobile and the distributed power supply to the power distribution network on the reliability of the system, the following three comparison schemes are arranged in the system of the embodiment:
the first scheme is as follows: the system does not contain an electric automobile and a distributed power supply;
and the scheme is as follows: 500 electric vehicles are connected, a slow charging mode is adopted, and the discharging process of the electric vehicles is calculated;
and a fifth scheme: and simultaneously, 500 electric vehicles and a wind-solar hybrid power supply system are accessed, and a slow charging mode is adopted to take account of the discharging process of the electric vehicles.
Based on a Matlab programming program, the reliability of the operator system is evaluated by using a sequential Monte Carlo simulation method, and the reliability indexes of the operator system under different schemes are obtained and are shown in Table 4 and FIG. 7.
TABLE 4 System reliability index under different schemes
Figure BDA0002612679900000121
The calculation results in table 4 show that when the electric vehicle is used as a load and a power supply with dual attributes, the SAIDI index of the system is not changed and the SAIDI index is reduced after the electric vehicle is connected to a power distribution network including a wind-solar hybrid power supply system. FIG. 7 shows the calculation results of the ENSI indexes of the systems under different schemes when the dual attributes of the electric vehicle are considered.
As can be seen from fig. 7, when the electric vehicle is connected to the conventional power distribution network and the power distribution network including the wind-solar hybrid power supply system, both the system ENSI indexes are increased, because the electric vehicle increases the load of the power distribution network during the charging period. Compared with the fourth scheme, the ENSI index of the system in the sixth scheme is reduced, which shows that the distributed power supply can weaken the negative influence of the network access of the electric automobile on the reliability of the system to a certain extent.
Example two
A second embodiment of the present invention provides an apparatus for evaluating reliability of a power distribution network accessed by an electric vehicle, including:
the fault determining unit is used for carrying out simulation analysis according to a pre-established power distribution network model to determine a fault element;
a time calculation unit for determining a fail-over time of the failed component;
and the data processing unit is used for determining the reliability index of the power distribution network model according to the current state of the electric automobile and the fault repairing time.
According to the method, the reliability index of the power distribution network model is determined according to the current state of the electric automobile and the fault repair time corresponding to the fault element in the power grid model, and the reliability reference can be provided for the operation of the power grid, so that the operation reliability of the power grid is improved.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting the same, and although the present invention is described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications and equivalents may be made to the embodiments of the invention without departing from the spirit and scope of the invention, which is to be covered thereby.

Claims (10)

1. A method for evaluating reliability of a power distribution network accessed by an electric automobile is characterized by comprising the following steps:
carrying out simulation analysis according to a pre-established power distribution network model to determine a fault element;
determining a fault repair time for the failed component;
and determining the reliability index of the power distribution network model according to the current state of the electric automobile and the fault repairing time.
2. The method for evaluating the reliability of the power distribution network accessed by the electric vehicle as claimed in claim 1, wherein the step of performing simulation analysis to determine the fault element according to the pre-established power distribution network model comprises the following steps:
determining the fault-free working time of each element in the power distribution network model;
and determining the element with the minimum fault-free working time as a fault element.
3. The method for evaluating the reliability of the power distribution network accessed by the electric vehicle according to claim 2, wherein after the determining the fault element according to the pre-established power distribution network model, the method further comprises the following steps:
and accumulating the simulation time according to the fault-free working time of the fault element.
4. The method for evaluating the reliability of the power distribution network accessed by the electric vehicle according to claim 3, wherein the determining the reliability index of the power distribution network model according to the current state of the electric vehicle and the fault repairing time comprises:
when the electric automobile is in a charging period or a discharging period at present, sampling is carried out based on a distributed power supply output probability model to obtain the output power of a distributed power supply;
carrying out power adjustment on the island power grid according to the output power of the distributed power supply, the charge-discharge power of the electric automobile and the load power so as to balance the power;
and counting the fault information of each load point according to the island power grid after power balance.
5. The method for evaluating reliability of the power distribution network accessed by the electric vehicle according to claim 4, wherein the power adjustment of the island power network according to the output power of the distributed power supply, the charge and discharge power of the electric vehicle and the load power to balance the power comprises:
when the electric automobile is in the charging period at present, if the output power of the distributed power supply is smaller than the sum of the charging power and the load power of the electric automobile, the load is reduced according to the load priority order until the power is balanced.
6. The method for evaluating reliability of the power distribution network accessed by the electric vehicle according to claim 4, wherein the power adjustment of the island power network according to the output power of the distributed power supply, the charge and discharge power of the electric vehicle and the load power to balance the power comprises:
when the electric automobile is in a discharging period at present, if the output power of the distributed power supply is smaller than the load power, the electric automobile discharges the island power grid according to the fault repairing time so as to compensate the load.
7. The method for evaluating reliability of the power distribution network accessed by the electric vehicle according to claim 6, wherein the power adjustment of the island power network according to the output power of the distributed power supply, the charge and discharge power of the electric vehicle and the load power is performed to balance the power, further comprising:
when the electric automobile is in a discharging period at present, determining the discharging time of the electric automobile;
if the discharge time is longer than the fault repair time and the sum of the output power of the distributed power supply and the discharge power of the electric automobile is smaller than the load power, reducing the load according to the load priority order until the power is balanced;
if the discharging time is less than the fault repairing time, and the sum of the output power of the distributed power supply and the discharging power of the electric automobile is less than the load power, the load is reduced according to the load priority order within the discharging time until the power is balanced, and after the electric automobile exits from the island power grid, the load is reduced for the second time according to the load priority order until the power is balanced.
8. The method for evaluating the reliability of the power distribution network accessed by the electric vehicle according to claim 4, wherein the determining the reliability index of the power distribution network model according to the current state of the electric vehicle and the fault repairing time comprises: and when the electric automobile is not accessed currently, counting the fault information of each load point in the island power grid.
9. The method for evaluating the reliability of the power distribution network accessed by the electric vehicle according to claim 8, wherein the determining the reliability index of the power distribution network model according to the current state of the electric vehicle and the fault repairing time further comprises:
repeatedly determining a fault element and accumulating the simulation time until the simulation time reaches a preset time limit value;
and determining the reliability index of the power distribution network model according to all the fault information in the simulation time reaching the preset time limit value.
10. The utility model provides a distribution network reliability evaluation device of electric automobile access which characterized in that includes:
the fault determining unit is used for carrying out simulation analysis according to a pre-established power distribution network model to determine a fault element;
a time calculation unit for determining a fail-over time of the failed component;
and the data processing unit is used for determining the reliability index of the power distribution network model according to the current state of the electric automobile and the fault repairing time.
CN202010759591.6A 2020-07-31 2020-07-31 Method and device for evaluating reliability of power distribution network accessed by electric automobile Pending CN111884219A (en)

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