CN110245858A - A kind of micro-capacitance sensor reliability estimation method containing electric automobile charging station - Google Patents

Abstract

The invention relates to a method for evaluating the reliability of a micro-grid with an electric vehicle charging station, comprising the following steps: 1) obtaining the state of charge of the power battery of the electric vehicle at each time point according to the operating characteristics of the electric vehicle in the micro-grid; 2) according to the micro-grid The internal power interaction strategy of the power grid establishes an interactive response power calculation model; 3) According to the position of the network switch and the breaking characteristics of different types of switches, the micro-grid is divided into regions; 4) According to the different areas of the internal fault points during the island operation of the micro-grid , using different switching actions to isolate faults; 5) Sequential Monte Carlo simulation is used to evaluate the operational reliability of the microgrid with electric vehicle charging stations. Compared with the prior art, the present invention conforms to the current and future development trend of connecting electric vehicle charging stations to the power grid, has comprehensive considerations, and is widely used.

Description

A Reliability Assessment Method for Microgrid Containing Electric Vehicle Charging Stations

technical field

The invention relates to the field of distribution network planning, in particular to a method for evaluating the reliability of a micro-grid with electric vehicle charging stations.

Background technique

With the rapid development of the economy and society, in recent years, electric vehicles have replaced petroleum with electricity as their main power source, and have been vigorously developed due to the characteristics of no carbon emissions and environmental friendliness. As a new type of electric load, electric vehicles will definitely have a huge impact on the safety, stability and economy of the power distribution system if they are charged out of order on a large scale. Especially charging during the peak load period of the grid will cause the peak of the power load to increase, which increases the power supply burden and operation risk of the system.

Therefore, it is necessary to conduct analysis and research on different types of electric vehicles and the car habits of different vehicle users. Through the analysis of charging and discharging behavior characteristics of different types of electric vehicles, electric vehicle charging stations are established to carry out centralized planning and management of electric vehicles, so that the charging load is controllable. At the same time, with the development and research of power interaction technology between electric vehicles and the grid, electric vehicles are connected to the distribution network as a mobile energy storage. The backup power supply delivers electrical energy to the grid.

With the large-scale connection of electric vehicles to the power grid, the structure and operation of the power grid have become increasingly complex. There are currently no evaluation methods for evaluating the operational reliability of microgrids that include electric vehicle charging stations.

Contents of the invention

The purpose of the present invention is to provide a method for evaluating the reliability of a micro-grid with an electric vehicle charging station in order to overcome the above-mentioned defects in the prior art.

The purpose of the present invention can be achieved through the following technical solutions:

A method for evaluating the reliability of a microgrid with electric vehicle charging stations, comprising the following steps:

1) Obtain the state of charge of the power battery of the electric vehicle at each time point according to the operating characteristics of the electric vehicle in the microgrid;

2) According to the internal power interaction strategy of the microgrid, an interactive response power calculation model is established;

3) According to the position of the network switch and the breaking characteristics of different types of switches, the microgrid is divided into regions;

4) Depending on the area where the internal fault point is located when the microgrid is operating in an isolated island, different switch action methods are used to isolate the fault;

5) Considering the internal power interaction and fault isolation of the microgrid, the sequential Monte Carlo simulation method is used to evaluate the operational reliability of the microgrid with electric vehicle charging stations.

In the step 1), the state of charge of the electric vehicle power battery at each time point satisfies the following constraints:

Among them, T ₀ and T′ ₀ are the departure time points of the shuttle bus and private electric cars in the morning respectively, and T ₀ <T′ ₀ , T ₁ and T ₂ are the time points of entering and leaving respectively, and T ₃ is the time point of the shuttle bus returning to the park The time point when the private electric car stops at the charging station, T′ ₃ is the time point when the private electric car arrives home, SOC _min (T ₀ /T′ ₀ ), SOC _min (T ₁ ), SOC _min (T ₂ ), SOC _min (T ₃ /T′ ₃ ) are the state of charge of the electric vehicle at T ₀ or T′ ₀ , T ₁ , T ₂ , T ₃ or T′ ₃ respectively, and S ₁ is the travel distance of the shuttle bus at N ₁ and N ₃ , S ₂ is the driving distance of private electric cars in time periods n ₁ and n ₃ , N ₁ is the time period when the electric shuttle bus departs from the park in the morning and returns to the park after picking up employees at a fixed station, N ₂ is the time when the electric shuttle bus parks in the park for charging N3 is the time period for the afternoon shuttle bus to send employees to the fixed station and return to the park, _N4 is the time period for the shuttle bus to stop at the charging station in the park, and _n1 is the _time for employees to take their private electric vehicles from home to the park in the morning , n ₂ is the time period when the private electric car is parked at the charging station in the park, n ₃ is the time period when the employee takes the private electric car from the park to home, n ₄ is the time when the private electric car is parked at the employee’s home, W is the time period of the electric car Power consumption per kilometer, W _ed is the rated power of the electric vehicle power battery, and SOC _sd·min is the minimum state of charge threshold set to ensure a certain service life of the power battery.

Described step 2) specifically comprises the following steps:

21) Determine the operating period of the microgrid, including N ₁ , N ₂ , N ₃ and N ₄ periods;

22) Calculate the power balance between the source and the load in the fault-free area, then the power balance between the source and the load is:

P _ph (t)=P _WT (t)+P _PV (t)-P _L (t)

Among them, P _ph (t) is the regional balance power, P _L (t) is the real-time load power in the microgrid; P _WT (t) is the total power generated by the wind turbine at time t, and P _PV (t) is the photovoltaic power generation The total power generated by the unit at time t;

23) When P _ph (t)> ₀ and during N ₁ and N ₃ periods, no electric vehicles are connected, and the microgrid only charges the energy storage device _. When the car is connected, energy storage equipment is needed to maintain the stability of the system. The state of charge of the electric car is at least SOC _ESS·sd , and then the electric car in the electric car charging station is charged;

24) When P _ph (t)≤0 and during N ₁ and N ₃ periods, only the energy storage device is discharged, and during N ₂ and N ₄ periods, when the electric vehicle is discharging, if P _ph (t)+P _EV·dis (t)<0, the energy storage device participates in the discharge operation at the same time, if the joint output of the energy storage device, electric vehicle charging station and renewable energy cannot meet the load demand, that is, P _ph (t)+P _EV·dis When (t)+P _ESS·dis (t)<0, the load reduction will be carried out according to the importance level of the load in the network. If the output power is reduced to zero and the power supply is still insufficient, the load in the island area will be further reduced. Among them, P _{EV dis} (t) is the discharge power of the charging station at time t, and P _{ESS dis} (t) is the discharge power of the energy storage device at time t;

25) Based on the internal power interaction strategy of the microgrid in steps 23) and 24), the calculation formula of the charging and discharging power of the energy storage device in different periods is:

Among them, P _{ESS dis} (t) is the discharge power of the energy storage device, P _{ESS ch} (t) is the charging power of the energy storage device, P _{ESS dis max} is the maximum discharge power of the energy storage device, P _{ESS· ch max} is the maximum charging power of the energy storage, SOC _ESS (t) is the state of charge of the energy storage device, SOC _{ESS sd} is the charge that the energy storage must maintain to maintain the stability of the subsequent system when there is no electric vehicle in the electric vehicle charging station. power state;

26) The number of electric vehicles in the charging station during N ₁ and N ₃ is approximately zero. Considering the interactive power between the electric vehicle charging station and the microgrid during N ₂ and N ₄ , the interactive response power calculation model is:

When P _ph (t)>0, the charging power of the charging station:

When P _ph (t)<0, the charging station discharge power:

P _{EV · dis · max} (t) = N _car (t) · P _{car · dis} + N _bus (t) · P _{bus · dis}

Among them, P _EV·max is the maximum allowable flow power of the main line connecting the charging station to the microgrid, and P _EV·dis·max (t) is the maximum transmittable power of the charging station at time t.

In the step 3), the specific classification of the regional division of the microgrid includes:

First-level area: an area without any type of switching device inside. Once a component failure occurs in this area, the area will be isolated as a whole. overall failure rate;

Second-level area: the area with circuit breaker as the boundary, without circuit breaker in the area, the same branch area composed of multiple first-level areas.

In the step 4), adopting different switch action modes for fault isolation specifically includes:

When a fault occurs in the first-level area with the isolation switch as the boundary, all upstream direction circuit breakers or intelligent switches in this area will act first to cut off the supply current of all power sources, disconnect the isolation switch in the fault area to isolate the fault, and reclose the circuit breaker and Intelligent switch, the fault-free equipment of the micro-grid resumes normal operation;

When there is a failure in the first-level area bounded by the smart switch, only the corresponding smart switch is disconnected;

When the line branch is faulty, it is not necessary to perform the disconnection operation of the isolating switch after the current is blocked, and at the same time, the circuit breaker and the intelligent switch are no longer closed.

Described step 5) specifically comprises the following steps:

51) read the original data, set the initial value T=0 of the analog clock, assume that all elements of the microgrid are initially in normal working condition;

52) According to the fault-free working time TTF and fault repair time TTR of each element in the microgrid, obtain the TTF time series table and the TTR time series table;

53) Enumerate the faults and select the element corresponding to the minimum value TTF _i in the TTF time series table as the fault element;

54) Obtain the operating conditions of the microgrid in different periods of time whether the electric vehicle charging station is connected or not in the simulation time period from T to T+TTF _i , and accumulate the simulation time T=T+TTF _i ;

55) Judging the type and location of the fault and determining the area affected by the fault;

56) Fault isolation of the microgrid after the fault;

57) Before the fault node resumes normal operation, determine whether load reduction is required according to the operating conditions of the isolated fault area, if so, accumulate the power outage time of the reduced load and the reduced load power, and accumulate the simulation time T=T +TTR _i ;

58) Obtain the power outage time of the affected load node;

59) judge whether the time reaches the specified time limit, if not, then return to step 52); if so, continue to the next step;

510) Reliability evaluation is performed according to the reliability evaluation indexes of the microgrid system and load nodes.

In the step 510), the reliability evaluation index includes the conventional reliability evaluation index and the reliability evaluation index of the microgrid containing the electric vehicle charging station.

The conventional reliability evaluation indicators include system annual average power outage frequency SAIFI, system annual average power outage time SAIDI, user annual average power outage duration CAIDI and average power supply availability ASAI.

The micro-grid reliability evaluation indicators including electric vehicle charging stations include the average charge depth ACD, average discharge depth ADD, average load reduction depth ALRD of the charging station, and the electric vehicle charging station's discharge reduction and load reduction strength when the power supply in the non-fault area is insufficient. n.

The formula for calculating the reliability evaluation index of the microgrid including the electric vehicle charging station includes:

in, Respectively, the i-th charge and j-th discharge power of the electric vehicle charging station, CHT, DIST are the total times of charging and discharging of the electric vehicle charging station, PG _i is the electric vehicle charging station i-time charging, the renewable energy The power that can be generated, ALR is the total number of load reductions in the microgrid, and P _z is the load power that is reduced for the zth time.

Compared with the prior art, the present invention has the following advantages:

In the present invention, according to the working nature of electric vehicle users in the park and the driving characteristics of different types of electric vehicles, the power between the energy storage system and the microgrid system in the electric vehicle charging station joint network is proposed when the microgrid in the park is running on an isolated island. The interaction strategy, taking into account a variety of actual operating conditions (charging, failure, reduction, etc.), adopts the sequential Monte Carlo simulation method in combination with the evaluation index proposed by the present invention to evaluate the operation reliability of the microgrid containing the electric vehicle charging station, It can effectively and intuitively reflect the influence of electric vehicles on the operation reliability of the microgrid after participating in the V2G response, and provide reference value for the subsequent operation of the actual microgrid.

Description of drawings

Fig. 1 is the invention flowchart of the present invention.

Figure 2 shows the driving status of two types of electric vehicles at different times of the working day.

Figure 3 shows the internal power interaction operation strategy of the microgrid.

Figure 4 is the simulated feeder system of the park microgrid in the example.

Detailed ways

The present invention will be described in detail below in conjunction with the accompanying drawings and specific embodiments.

Example

As shown in Figure 1, the present invention provides a method for evaluating the operation reliability of a microgrid containing an electric vehicle charging station, comprising the following steps:

S1 calculates the state of charge of the power battery of the electric vehicle at each time point according to the operating characteristics of the electric vehicle in the microgrid;

S2 establishes an interactive response power calculation model according to the internal power interaction strategy of the microgrid;

S3 divides the microgrid according to the position of the network switch and the breaking characteristics of different types of switches;

S4 adopts different switching action strategies to isolate faults according to the different areas where the internal fault points are located when the microgrid is operating in an isolated island;

S5 uses a sequential Monte Carlo simulation algorithm to evaluate the operational reliability of a microgrid with electric vehicle charging stations.

In step S1, according to the operating characteristics of the electric vehicle in the microgrid, the state of charge of the power battery of the electric vehicle at each time point is calculated, and the specific steps are as follows:

Step S11: According to the working time characteristics of electric vehicle users in the park, the driving characteristics of different types of electric vehicles are analyzed. Figure 2 is a schematic diagram of the driving status at different times of the working day. Among them, N ₁ is the time period when the electric shuttle bus departs from the park in the morning and returns to the park after picking up employees at a fixed station; n ₁ is the time period when employees take their private electric cars from home to the park in the morning; N ₂ (n ₂ ) is the electric shuttle bus (private electric vehicles) parked at the charging station in the park; N ₃ is the time period for the afternoon shuttle bus to send employees to the fixed station and return to the park; n ₃ is the time period for employees to take private electric cars from the park to home; N ₄ is The time period when the shuttle bus stops at the charging station in the park, n ₄ is the time when the private electric car is parked at the employee's home;

Step S12: In order to meet the needs of electric vehicle users, the minimum constraints to be met by the state of charge of the power battery at each time point are:

In the formula: T ₀ , T′ ₀ are the departure time points of the shuttle bus and private electric cars in the morning respectively, and T ₀ <T′ ₀ ; T ₁ and T ₂ are the time points of connecting (to work) and leaving (off work) respectively ; T ₃ is the time point when the shuttle bus stops at the charging station after returning to the park; T′ ₃ is the time point when the private EV arrives home; SOC _min (T ₀ /T′ ₀ ), SOC _min (T ₁ ), SOC _min (T ₂ ), SOC _min (T ₃ /T′ ₃ ) is the state of charge of each electric vehicle at T ₀ or T′ ₀ , T ₁ , T ₂ , T ₃ or T′ ₃ time points; S ₁ and S ₂ are respectively Shuttle bus (private electric vehicle) travel distance (kM) during N ₁ (n ₁ ) and N ₃ (n ₃ ); W is the power consumption per kilometer of the electric vehicle, and W _ed is the rated power of the power battery of the electric vehicle; SOC _sd·min is the minimum state of charge threshold set to ensure a certain service life of the power battery.

In step S2, according to the internal power interaction strategy of the microgrid, an interactive response power calculation model is established, and the specific steps are:

Step S21: Determine the operating period of the microgrid, namely N ₁ , N ₂ , N ₃ , N ₄ ;

Step S22: Calculate the power balance between the source and the load in the fault-free area. The power balance formula between the source and the load is as follows:

P _ph (t)=P _WT (t)+P _PV (t)-P _L (t)

In the formula: P _L (t) is the real-time load power in the microgrid; P _WT (t) is the total power generated by the wind turbine at time t, and P _PV (t) is the total power generated by the photovoltaic generator at time t.

Step S23: If P _ph (t)>0. During N ₁ and N ₃ periods, no electric vehicles are connected, and the microgrid will only charge the energy storage battery. In the N ₂ and N ₄ time periods, in order to ensure that the energy storage device is needed to maintain the stability of the system operation when no electric vehicle is connected, its state of charge should maintain a certain limit SOC _ESS·sd . Secondly, charge the electric vehicles in the electric vehicle charging station;

Step S24: If P _ph (t)≤0. During N ₁ and N ₃ periods, only the energy storage battery is discharged. During _N2 and _N4 periods, electric vehicles are first arranged to discharge. If P _ph (t)+P _EV·dis (t)<0, the energy storage battery also participates in the discharge operation at the same time. If the combined output of energy storage batteries, electric vehicle charging stations, and renewable energy cannot meet the load demand, that is, when P _ph (t)+P _EV·dis (t)+P _ESS·dis (t)<0, it is necessary to The importance level of the internal load is used for load reduction. Where P _EV·dis (t) is the discharge power of the charging station at time t, and P _ESS·dis (t) is the discharge power of the energy storage battery at time t. At the same time, changes in the output power of EV charging stations should be considered. When the output power is reduced to zero and the power supply is still insufficient, the load in the island area will be further reduced.

Step S25: Based on the above power interaction strategy, the calculation model of the charging and discharging power of the energy storage device at different time periods is:

In the formula: P _{ESS dis} (t) is the discharge power of the energy storage device, P _{ESS ch} (t) is the charging power of the energy storage device, P _{ESS dis max} is the maximum discharge power of the energy storage device, P _{ESS ch max} is the maximum charging power of the energy storage, SOC _ESS (t) is the state of charge of the energy storage device, and SOC _{ESS sd} is the energy storage to maintain the stability of the subsequent system when there is no electric vehicle at the electric vehicle charging station state of charge.

Step S26: The number of electric vehicles in the charging station is basically zero during the time periods N ₁ and N ₃ . Therefore, only consider the interactive power between the electric vehicle charging station and the microgrid during N ₂ and N ₄ periods:

When P _ph (t)>0, the charging power of the charging station:

When P _ph (t)<0, the charging station discharge power:

P _{EV · dis · max} (t) = N _car (t) · P _{car · dis} + N _bus (t) · P _{bus · dis}

In the formula: P _{EV max} is the maximum allowable flow power of the main line connecting the charging station to the microgrid, which is limited by the line parameters; P _{EV dis max} (t) is the maximum transmittable power of the charging station at time t, which is limited by the The constraints on the number N _car (t) and N _bus (t) of various types of electric vehicles that can participate in the discharge in the time station and the discharge power P _car·dis and P _bus·dis of a single electric vehicle.

In step S3, according to the position of the network switch and the breaking characteristics of different types of switches, the area of the microgrid is divided, and the specific classification is as follows:

Level 1 area: An area that no longer has any type of switchgear inside. No matter which component fails in this area, the entire area will be isolated. Therefore, when enumerating faults, the first-level area is taken as the smallest enumeration unit, and the overall failure rate of this area is considered.

Secondary area: with the circuit breaker as the boundary, the area no longer contains circuit breakers. Generally, the same branch area is composed of multiple first-level areas.

In step S4, according to the different areas where the internal fault point is located when the microgrid is running in an island, different switching action strategies are adopted to isolate the fault. The specific steps are:

Step S41: When a fault occurs in the first-level area bounded by the isolating switch, all upstream circuit breakers or intelligent switches in this area act first to cut off the supply current of all power sources, disconnect the isolating switch in the fault area to isolate the fault, and reclose and open the circuit Switches and smart switches, the fault-free equipment in the micro-grid resumes normal operation;

Step S42: When there is a failure in the first-level area with the smart switch as the boundary, it is only necessary to disconnect the corresponding smart switch;

Step S43: When there is a fault in the branch of the line, it is not necessary to open the disconnector after the current is blocked, and at the same time the circuit breaker and the intelligent switch cannot be closed again.

In step S5, the sequential Monte Carlo simulation algorithm is used to evaluate the operation reliability of the microgrid with electric vehicle charging stations. The specific steps are:

Step S51: read the original data, set the initial value T=0 of the analog clock, assuming that all components are initially in a normal working state;

Step S52: Calculate the time to failure (TTF) and time to repair (TTR) of each component in the network to obtain a time series table: TTF, TTR;

Step S53: Enumerate faults. Select the component corresponding to the minimum value TTF _i in TTF as the faulty component;

Step S54: Analyze the simulation time T to T+TTF _i time period, the operating status of the system in different time periods whether the electric vehicle charging station is connected or not, and the accumulated simulation time T=T+TTF _i ;

Step S55: determine the type and location of the fault, and determine the area affected by the fault;

Step S56: performing fault isolation on the microgrid after the fault;

Step S57: Before the faulty node resumes normal operation, analyze the operating status of the isolated faulty area. Determine if load shedding is required. If so, the power outage time of the reduced load and the reduced load power are accumulated. And accumulative simulation time T=T+TTR _i ;

Step S58: Calculate the outage time of the affected load nodes;

Step S59: Judging whether the simulation time has reached the prescribed simulation time limit, if not, then return to step S62; if yes, continue to the next step;

Step S510: Calculating reliability evaluation indexes of the system and load nodes.

Reliability evaluation indicators specifically include:

The power supply reliability evaluation index in the island state of the microgrid can adopt the reliability evaluation index of the traditional distribution network (the system's annual average power outage frequency SAIFI, the system's annual average power outage time SAIDI, the user's annual average power outage duration CAIDI and the average power supply availability ASAI ). At the same time, considering the power interaction between the EV charging station and the microgrid system after the access, the present invention proposes the following indicators on the basis of the traditional indicators to analyze the influence of the EV charging station on the operation reliability of the microgrid :

(1) First, by counting the charging and discharging times (CHT, DIST) of the EV charging station in the simulation cycle, as well as the average charging depth (ACD) (kW/time) and the average discharge depth (Averagedischarge depth) of the charging station , ADD) (kW/time) and other parameters to analyze the intimacy between the EV charging station and the microgrid. in:

In the formula: Respectively, the power of the i-th charge and j-th discharge of the EV charging station; PG _i is the power that the renewable energy can generate when the EV station is charged for the i-th time.

(2) By calculating the number of load reductions (Average load reductions, ALR) (times/year) and the average load reduction depth (Average load reduction depth, ALRD) (kW/times) in the microgrid, the analysis of EV charging stations and The microgrid without EV charging station access, the difference in the reliability of power consumption of loads in the network under two different situations, and further analyze the impact of EV charging station access on the reliability of microgrid power supply. in:

In the formula: P _z is the load power reduced for the zth time.

(3) When the power supply is insufficient in the fault-free area of the network, the EV charging station participates in the discharge, which reduces the lack of power supply in the network, reduces the reduced load power, and thus reduces the number of power outage users. Its effect can be expressed by the following formula:

The network structure diagram of the embodiment is shown in Figure 4, based on the network structure of the RTBS Bus 6 of the IEEE power distribution system reliability evaluation and testing system, the area where the load nodes LP13-LP23 are located is used as a microgrid, and connected to the distribution network through a PCC switch .

Divide the microgrid, as shown in Table 1. There are 11 first-level load areas in total. Photovoltaic and wind turbines are connected to No. ① and No. ③ second-level areas as two power first-level areas respectively. Among them, the photovoltaic installed capacity is 1.5MW, and the wind turbine consists of three 0.8MW wind turbines. Among them, the cut-in wind speed of the fan is 4m/s, the rated wind speed is 12.5m/s, and the cut-out wind speed is 25m/s. The energy storage battery ESS, as a separate first-level area, is connected to No. ③ second-level area, with a capacity of 5000kW·h. And the distribution lines in the microgrid area all use cables. Table 2 is the corresponding reliability parameters.

Table 1 Microgrid partition situation

Table 2 Reliability parameters

For the EV1 and EV2 charging stations in Figure 4, there are 50 private electric vehicle charging piles and 5 electric shuttle charging piles respectively. The private electric vehicles are assumed to be BYD E5 models, and the electric shuttle buses are Yutong E8 models. The two types of electric vehicles The configuration parameters are shown in Table 3. Time nodes T ₀ (T ₀ '), T ₁ , T ₂ , and T ₃ (T ₃ ') are respectively taken as 7:00 (7:30), 9:00, 17:00, 19:00 (18:30 ).

Table 3 Configuration parameters of two types of electric vehicles

In this calculation example, the calculation of the relevant reliability indicators is carried out for the two situations of EV charging station access and no EV charging station, and the results are shown in Table 4 below. Among them, in this calculation example, the importance level of load nodes LP13, LP17, and LP19 is set to be low, and they can be cut first. The subsequent reduction of corresponding loads is determined by the electrical distance between the load point and the power node, and the distance is from farthest to shortest. reduce.

Table 4 Related Reliability Indexes

reliability index EV charging station not included Including EV charging station SAIFI(time/household·year) 2.449 2.212 SAIDI(h/household·year) 14.298 12.103 ASAI 0.99634 0.9986 ACD(kW/time) -- 0.2062 ADD(kW/time) -- 0.1983 ALR (times/year) 1577 676 ALRD(kW/time) 0.3842 0.2763 n -- 0.4178

It can be seen from the calculation results in Table 4 that under the island operation state of the microgrid, considering the power interaction between the electric vehicle charging station and the microgrid, the average power outage time of the microgrid system is reduced by 0.237 (times/household·year). The number of outages decreased by 15.35%, the average load reduction depth (ALRD) decreased by about 28.1%, and the load reduction times (ALR) decreased by 57.1%, effectively reflecting the improvement of the power supply quality of the microgrid to the load under the island operation state. The charging depth index (ACD) of electric vehicles also reflects that fully utilizing the V2G technology of electric vehicle charging stations can not only meet the charging needs of electric vehicles, but also increase the system's ability to absorb distributed energy. When the power generation in the microgrid is abundant, charging electric vehicles can effectively reduce the curtailment rate of wind and light in the system.

Claims (10)

1. A microgrid reliability evaluation method containing electric vehicle charging station, is characterized in that, comprises the following steps: 1) Obtain the state of charge of the power battery of the electric vehicle at each time point according to the operating characteristics of the electric vehicle in the microgrid; 2) According to the internal power interaction strategy of the microgrid, an interactive response power calculation model is established; 3) According to the position of the network switch and the breaking characteristics of different types of switches, the microgrid is divided into regions; 4) Depending on the area where the internal fault point is located when the microgrid is operating in an isolated island, different switch action methods are used to isolate the fault; 5) Considering the internal power interaction and fault isolation of the microgrid, the sequential Monte Carlo simulation method is used to evaluate the operational reliability of the microgrid with electric vehicle charging stations. 2. A method for evaluating the reliability of a microgrid containing electric vehicle charging stations according to claim 1, wherein in the step 1), the state of charge of the electric vehicle power battery at each time point satisfies the following constraints : Among them, T ₀ and T′ ₀ are the departure time points of the shuttle bus and private electric cars in the morning respectively, and T ₀ <T′ ₀ , T ₁ and T ₂ are the time points of entering and leaving respectively, and T ₃ is the time point of returning the shuttle bus to the park The time point when the private electric car stops at the charging station, T′ ₃ is the time point when the private electric car arrives home, SOC _min (T ₀ /T′ ₀ ), SOC _min (T ₁ ), SOC _min (T ₂ ), SOC _min (T ₃ /T′ ₃ ) are the state of charge of the electric vehicle at T ₀ or T′ ₀ , T ₁ , T ₂ , T ₃ or T′ ₃ respectively, and S ₁ is the travel distance of the shuttle bus at N ₁ and N ₃ , S ₂ is the driving distance of private electric cars in time periods n ₁ and n ₃ , N ₁ is the time period when the electric shuttle bus departs from the park in the morning and returns to the park after picking up employees at a fixed station, N ₂ is the time when the electric shuttle bus parks in the park for charging N3 is the time period for the afternoon shuttle bus to send employees to the fixed station and return to the park, _N4 is the time period for the shuttle bus to stop at the charging station in the park, and _n1 is the _time for employees to take their private electric vehicles from home to the park in the morning , n ₂ is the time period when the private electric car is parked at the charging station in the park, n ₃ is the time period when the employee takes the private electric car from the park to home, n ₄ is the time when the private electric car is parked at the employee’s home, W is the time period of the electric car Power consumption per kilometer, W _ed is the rated power of the electric vehicle power battery, and SOC _sd·min is the minimum state of charge threshold set to ensure a certain service life of the power battery. 3. a kind of micro-grid reliability evaluation method containing electric vehicle charging station according to claim 2, is characterized in that, described step 2) specifically comprises the following steps: 21) Determine the operating period of the microgrid, including N ₁ , N ₂ , N ₃ and N ₄ periods; 22) Calculate the power balance between the source and the load in the fault-free area, then the power balance between the source and the load is: P _ph (t)=P _WT (t)+P _PV (t)-P _L (t) Among them, P _ph (t) is the regional balance power, P _L (t) is the real-time load power in the microgrid; P _WT (t) is the total power generated by the wind turbine at time t, and P _PV (t) is the photovoltaic power generation The total power generated by the unit at time t; 23) When P _ph (t)> ₀ and during N ₁ and N ₃ periods, no electric vehicles are connected, and the microgrid only charges the energy storage device _. When the car is connected, energy storage equipment is needed to maintain the stability of the system. The state of charge of the electric car is at least SOC _ESS·sd , and then the electric car in the electric car charging station is charged; 24) When P _ph (t)≤0 and during N ₁ and N ₃ periods, only the energy storage device is discharged, and during N ₂ and N ₄ periods, when electric vehicles are discharging, if P _ph (t)+P _EV·dis (t)<0, the energy storage device participates in the discharge operation at the same time, if the joint output of the energy storage device, electric vehicle charging station and renewable energy cannot meet the load demand, that is, P _ph (t)+P _EV·dis When (t)+P _ESS·dis (t)<0, the load reduction will be carried out according to the importance level of the load in the network. If the output power is reduced to zero and the power supply is still insufficient, the load in the island area will be further reduced. Among them, P _{EV dis} (t) is the discharge power of the charging station at time t, and P _{ESS dis} (t) is the discharge power of the energy storage device at time t; 25) Based on the internal power interaction strategy of the microgrid in steps 23) and 24), the calculation formula of the charging and discharging power of the energy storage device in different periods is: Among them, P _{ESS dis} (t) is the discharge power of the energy storage device, P _{ESS ch} (t) is the charging power of the energy storage device, P _{ESS dis max} is the maximum discharge power of the energy storage device, P _{ESS· ch max} is the maximum charging power of the energy storage, SOC _ESS (t) is the state of charge of the energy storage device, SOC _{ESS sd} is the charge that the energy storage must maintain to maintain the stability of the subsequent system when there is no electric vehicle in the electric vehicle charging station. power state; 26) The number of electric vehicles in the charging station during N ₁ and N ₃ is approximately zero. Considering the interactive power between the electric vehicle charging station and the microgrid during N ₂ and N ₄ , the interactive response power calculation model is: When P _ph (t)>0, the charging power of the charging station: When P _ph (t)<0, the charging station discharge power: P _{EV · dis · max} (t) = N _car (t) · P _{car · dis} + N _bus (t) · P _{bus · dis} Among them, P _EV·max is the maximum allowable flow power of the main line connecting the charging station to the microgrid, and P _EV·dis·max (t) is the maximum transmittable power of the charging station at time t. 4. a kind of microgrid reliability assessment method that contains electric vehicle charging station according to claim 1, is characterized in that, in described step 3), the concrete classification that carries out regional division to microgrid comprises: First-level area: An area without any type of switching device inside. Once a component failure occurs in this area, the area will be isolated as a whole, and when enumerating faults, the first-level area will be used as the smallest enumeration unit. overall failure rate; Second-level area: The area with circuit breakers as the boundary, without circuit breakers in the area, and the same branch area composed of multiple first-level areas. 5. A method for evaluating the reliability of a microgrid containing an electric vehicle charging station according to claim 1, wherein, in the step 4), adopting different switch action modes for fault isolation specifically includes: When a fault occurs in the first-level area with the isolation switch as the boundary, all upstream direction circuit breakers or intelligent switches in this area will act first to cut off the supply current of all power sources, disconnect the isolation switch in the fault area to isolate the fault, and reclose the circuit breaker and Intelligent switch, the fault-free equipment of the micro-grid resumes normal operation; When there is a failure in the first-level area bounded by the smart switch, only the corresponding smart switch is disconnected; When the line branch fails, it is not necessary to perform the disconnection operation of the isolating switch after the current is blocked, and at the same time, the circuit breaker and the intelligent switch are no longer closed. 6. A method for evaluating the reliability of a microgrid containing an electric vehicle charging station according to claim 1, wherein said step 5) specifically includes the following steps: 51) read the original data, set the initial value T=0 of the analog clock, assume that all elements of the microgrid are initially in a normal working state; 52) Obtain the TTF time series table and the TTR time series table according to the fault-free working time TTF and fault repair time TTR of each component in the microgrid; 53) Enumerate the faults and select the element corresponding to the minimum value TTF _i in the TTF time series table as the fault element; 54) Obtain the operating conditions of the microgrid in different periods of time whether the electric vehicle charging station is connected or not in the simulation time period from T to T+TTF _i , and accumulate the simulation time T=T+TTF _i ; 55) Judging the type and location of the fault and determining the area affected by the fault; 56) Fault isolation of microgrid after fault; 57) Before the fault node resumes normal operation, determine whether load reduction is required according to the operating conditions of the isolated fault area, if so, accumulate the power outage time of the reduced load and the reduced load power, and accumulate the simulation time T=T +TTR _i ; 58) Obtain the power outage time of the affected load node; 59) determine whether the time reaches the specified time limit, if not, then return to step 52); if so, continue to the next step; 510) Reliability evaluation is performed according to the reliability evaluation indexes of the microgrid system and load nodes. 7. A method for evaluating the reliability of a microgrid containing an electric vehicle charging station according to claim 6, characterized in that, in the step 510), the reliability evaluation indicators include conventional reliability evaluation indicators and electric vehicle charging stations Microgrid Reliability Evaluation Indicators for Charging Stations. 8. A method for evaluating the reliability of a microgrid with electric vehicle charging stations according to claim 7, wherein the conventional reliability evaluation indicators include the system annual average power outage frequency SAIFI, the system annual average power outage time SAIDI , the user's annual average power outage duration CAIDI and the average power supply availability ASAI. 9. A method for evaluating the reliability of a micro-grid containing an electric vehicle charging station according to claim 7, wherein the reliability evaluation index of the micro-grid containing an electric vehicle charging station includes the average charging depth of the charging station ACD, average discharge depth ADD, average load reduction depth ALRD, electric vehicle charging station discharge reduction and load reduction strength η when the power supply in the non-fault area is insufficient. 10. A method for evaluating the reliability of a micro-grid containing an electric vehicle charging station according to claim 9, wherein the calculation formula for evaluating the reliability of the micro-grid containing an electric vehicle charging station includes: in, Respectively, the i-th charge and j-th discharge power of the electric vehicle charging station, CHT, DIST are the total number of charging and discharging times of the electric vehicle charging station, PG _i is the renewable energy when the electric vehicle charging station is charged for the i-th time The power that can be generated, ALR is the total number of load reductions in the microgrid, and P _z is the load power that is reduced for the zth time.