Battery swap station regulation capacity evaluation method and system considering seasonal excess battery compartment quantity

Abstract

The application discloses a kind of battery swap station regulation capacity evaluation method and system considering seasonal surplus battery compartment quantity, belong to battery swap technical field.Method includes: S1, obtain seasonal typical day vehicle battery swap data;S2, based on the vehicle battery swap data, build the regulation capacity evaluation model of battery swap station considering seasonal characteristics;S3, battery swap station is based on the regulation capacity evaluation model operation, and from the time shift and energy storage two aspects to battery swap station regulation capacity evaluation, obtain evaluation result.The application can significantly improve the regulation capacity and economic benefit of battery swap station, and has popularization value for peak clipping and new energy consumption.The future can be combined with battery health state and multi-station cooperative scheduling, further tap cluster control potential.

Description

Technical Field

[0001] This invention belongs to the field of battery swapping technology, specifically relating to a method and system for assessing the adjustment capacity of battery swapping stations that takes into account the number of seasonal surplus battery compartments. Background Technology

[0002] With the continuous increase in the installed capacity of new energy sources such as photovoltaics and wind power, the peak-valley difference of the power grid load is constantly widening. As a basic unit that combines energy storage and load attributes, battery swapping stations play a potential role in promoting the consumption of new energy and peak shaving of the power system. However, existing battery swapping stations still face problems such as large fluctuations in charging load and insufficient utilization of operational flexibility potential, and there is an urgent need to develop scientific adjustment capacity assessment and optimization strategies.

[0003] In the field of operation optimization and scheduling research, scholars at home and abroad have proposed a variety of management models based on economy and energy efficiency. Although existing research has achieved certain results in the operation optimization of battery swapping stations, the synergy of new energy sources, and market participation, there are still some shortcomings: ① There is a lack of systematic analysis of the differences in operating pressure in different seasons, and the potential adjustment capacity of surplus battery storage in some seasons has not been revealed; ② The flexible adjustment potential has not been systematically characterized from the dual dimensions of energy storage and time-shiftability; ③ The coordinated design of adjustment strategies and battery swapping risk threshold protection mechanisms still needs to be improved. Summary of the Invention

[0004] To address the problems existing in the prior art, this invention proposes a method and system for assessing the regulation capacity of battery swapping stations that considers the seasonality of surplus battery storage capacity. It constructs a regulation capacity model for battery swapping stations that takes into account seasonal characteristics, quantifying the flexibility potential from both time-shiftable and energy storage perspectives. A storage-delayed charging control strategy based on linear programming is designed, introducing a risk threshold protection mechanism. Peak-valley electricity price shifting and risk constraints are achieved by adjusting the charging sequence. This promotes cost reduction and efficiency improvement in battery swapping station operation, laying the foundation for battery swapping stations to respond to the regulation needs of the power system.

[0005] To achieve the above objectives, the present invention provides the following solution: a method for assessing the adjustment capacity of battery swapping stations considering the seasonal surplus of battery storage capacity, comprising the following steps:

[0006] S1. Obtain vehicle battery swapping data for typical seasonal days;

[0007] S2. Construct an evaluation model for the adjustment capability of battery swapping stations that takes into account seasonal characteristics based on the vehicle battery swapping data;

[0008] S3. The battery swapping station operates based on the aforementioned regulation capability assessment model, and the regulation capability of the battery swapping station is assessed from two aspects: time-shiftability and energy storage, and the assessment results are obtained.

[0009] More preferably, the vehicle battery swapping data includes: the number of vehicles arriving, the battery swapping time, the remaining battery power, and the charging power.

[0010] More preferably, the regulation capacity assessment model includes: an on-demand charging operation model during off-peak electricity price periods, a partial grid closure operation model during peak electricity price periods, and a grid closure lifting operation model during periods of high battery swapping risk.

[0011] More preferably, the "on-demand charging during off-peak electricity price periods" operation model involves charging the vehicle immediately after battery swapping, and the operating power and cost include:

[0012] ;

[0013] ;

[0014] In the formula, This indicates the amount of electricity purchased from the grid by the battery swapping station in the Pinggu electricity price period instant charging operation model; Indicates instant charging mode t The number of batteries being charged is constantly being monitored. Indicates the rated power of the battery compartment; This represents the electricity purchase cost of a battery swapping station in the Pinggu electricity price period-based instant charging operation model. Indicates time-of-use electricity pricing; Indicates the number of scheduling periods; This represents the smallest time granularity of the scheduling.

[0015] More preferably, the peak electricity price period partial battery storage operation model is to delay battery charging, and the adjusted charging period and daily total charging cost are obtained by the battery storage delay charging duration;

[0016] Storage delay charging time:

[0017] ;

[0018] In the formula, This indicates the time intervals in the peak electricity price period partial warehouse closure operation model; For the day's number j Vehicle battery swapping time; Indicates charging time; Indicates the duration of delayed charging after the warehouse is sealed;

[0019] More preferably, the process of adjusting the charging period and operating cost based on the sealed-warehouse delayed charging duration includes:

[0020] Construct ascending and descending auxiliary variables, and calculate the warehouse sealing delay charging time using linear programming.

[0021] Establish constraints that the on-board battery charging period occurs after the battery swapping period:

[0022] ;

[0023] In the formula, In the peak electricity price period partial warehouse closure operation model t Time number is j The charging indicator for the vehicle's onboard battery; Indicates an ascending order auxiliary variable; Represents a descending auxiliary vector; This indicates the maximum allowable delayed charging time limit;

[0024] Construct constraints to keep the charging time constant after adjustment, and constraints to ensure the charging process cannot be interrupted:

[0025] ;

[0026] ;

[0027] In the formula, , These represent the start and end of the charging action, respectively.

[0028] Set a minimum limit for the number of fully charged batteries at different times, and compare their serial numbers. j Determine the battery number based on the difference between the battery swapping time and the charging start time. j Whether the vehicle battery is sealed, and whether a sealing control command is generated;

[0029] Construct a dimension as Auxiliary matrix , Identification number is j The vehicle's batteries are distributed to i Battery compartment charging:

[0030] ;

[0031] ;

[0032] In the formula, Indicates the total number of battery compartments; Indicates the number of vehicles that arrived that day; Indicates battery compartment i exist t The status of the device at any given time: 1 indicates that it is charging, and 0 indicates that it is not charging.

[0033] This leads to the following data in the peak electricity price period partial shutdown operation model: number of batteries charging at the battery swapping station at different times, charging power, and total daily charging cost:

[0034] ;

[0035] ;

[0036] ;

[0037] In the formula, In the peak electricity price period partial warehouse closure operation model t The number of batteries being charged is constantly being monitored. This refers to the power purchased in the partial power closure operation model during peak electricity pricing periods; This represents the electricity purchase cost in the peak electricity price period partial warehouse closure operation model.

[0038] More preferably, the high-risk battery swapping period unsealing operation model unseales existing warehouses based on a risk threshold, including:

[0039] ;

[0040] In the formula, This indicates the safety threshold for the number of backup batteries when fully charged. This indicates the quantity of the warehouse that has been sealed.

[0041] More preferably, the time-shiftability aspect is calculated through battery vacancy rate, and the method includes:

[0042] ;

[0043] In the formula, This indicates the utilization rate of the battery compartments in the battery swapping station's load category; Indicates the number of load-type battery compartments; Indicates the number of scheduling periods; express i Numbered battery compartment t A constant indicator of charging status; This indicates the percentage of the battery compartments at the battery swapping station that can be moved and adjusted backwards.

[0044] Energy storage assessment includes two dimensions: capacity and power.

[0045] ;

[0046] In the formula, , Limits on the adjustable capacity and power of energy storage batteries in battery swapping stations; Indicates the total number of battery compartments; Indicates the rated power of the battery compartment; This indicates the rated capacity of a single battery cell.

[0047] This invention also provides a system for assessing the adjustment capacity of battery swapping stations that takes into account the seasonal surplus battery storage capacity, including:

[0048] The data acquisition module is used to acquire vehicle battery swapping data on typical days of the season.

[0049] The model building module is used to build an evaluation model of the battery swapping station's adjustment capability that takes into account seasonal characteristics based on the vehicle battery swapping data.

[0050] The evaluation module is used to evaluate the regulation capacity of the battery swapping station from both time-shifting and energy storage perspectives when the station is operating based on the regulation capacity evaluation model, and to obtain the evaluation results.

[0051] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0052] 1) Construct a regulation capacity assessment model that takes into account seasonal characteristics, quantify the flexible regulation potential of battery swapping stations from two aspects: time-shiftable and energy storage, and provide support for their participation in grid ancillary services.

[0053] 2) A closed-cell delayed charging control strategy is proposed, which uses linear programming to optimize the charging sequence and introduces risk threshold protection to achieve charging shift during peak and off-peak electricity price periods, thereby reducing operating costs while ensuring timely battery swapping.

[0054] 3) The provided calculation results show that the surplus battery storage accounts for more than 25% in spring, summer and autumn, the average electricity purchase cost is reduced by about 9%, and the optimization rate is 3.91% in winter, which verifies the feasibility and economy of the strategy.

[0055] This invention can significantly improve the regulation capacity and economic benefits of battery swapping stations, and has promotional value for peak shaving and valley filling and renewable energy consumption. In the future, the potential for cluster regulation can be further explored by combining battery health status with multi-station coordinated scheduling. Attached Figure Description

[0056] To more clearly illustrate the technical solution of the present invention, the drawings used in the embodiments are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0057] Figure 1 This is a schematic diagram of the fast battery swapping service process according to an embodiment of the present invention;

[0058] Figure 2 This is a framework diagram of a method for assessing the adjustment capacity of battery swapping stations considering seasonal surplus battery storage capacity, as described in an embodiment of the present invention.

[0059] Figure 3 This is a schematic diagram of the charging period constraint modeling in an embodiment of the present invention;

[0060] Figure 4 This is a schematic diagram of parameters for a typical spring day in an embodiment of the present invention; wherein, Figure 4 (a) is a schematic diagram of the battery swapping frequency at various times; Figure 4 (b) A schematic diagram of the amount of charge to be collected at each time point; Figure 4 (c) is a schematic diagram of a typical battery charging process; Figure 4 (d) is a schematic diagram of peak-valley electricity prices and time period information;

[0061] Figure 5 This is a schematic diagram of the state of charge of each battery compartment at different times in an embodiment of the present invention;

[0062] Figure 6 A schematic diagram illustrating the design of prioritizing charging of lower-numbered battery compartments to calculate the number of spare battery compartments in an embodiment of the present invention;

[0063] Figure 7 This is a schematic diagram of at least part of the battery compartment to reduce charging requirements according to an embodiment of the present invention;

[0064] Figure 8 This is a schematic diagram of the battery charging period for the delayed charging effect in an embodiment of the present invention;

[0065] Figure 9 The battery state of charge of the battery swapping station in the sealed-warehouse delayed charging control mode according to an embodiment of the present invention.

[0066] Figure 10 This is a schematic diagram illustrating the change in the number of fully charged batteries at various times in an embodiment of the present invention;

[0067] Figure 11 This is a schematic diagram of the charging delay in the warehouse sealing & risk threshold protection mode according to an embodiment of the present invention;

[0068] Figure 12 This is a schematic diagram of the load changes of the battery swapping station during peak-valley electricity pricing periods according to an embodiment of the present invention. Detailed Implementation

[0069] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0070] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0071] This invention analyzes the seasonal battery swapping behavior characteristics of taxi battery swapping stations in northern China. The studied taxi battery swapping station model is HB60, with each station equipped with 60 charging bays (rated power 40kW, actual average charging power approximately 28kW in summer and 23kW in winter) and 59 batteries (rated capacity 55kWh). The batteries are owned by FAW Group, while the operating rights belong to State Grid Corporation of China. To extend battery life as much as possible, the engineering constraints allow for delayed but uninterrupted charging, and the batteries are not allowed to discharge externally.

[0072] After an electric taxi enters the battery swapping station, it is automatically registered. The system detects the difference in mileage and charges 0.3 yuan per kilometer. Then, a robotic arm removes the onboard battery and inserts it into a pre-reserved empty compartment in the swapping station. Finally, a fully charged (or maximum charged) battery is retrieved and reinserted into the taxi. The entire process takes only about 2-3 minutes. A diagram illustrating the fast battery swapping service process is shown below. Figure 1 As shown in the figure. The vehicle battery information mainly includes: the battery swapping station number, date and time, the old battery number and charge, the new battery number and charge, etc.; the battery swapping station operating power information includes: the battery swapping station number, date and time, charging power, the number of batteries being charged, etc.

[0073] Winter battery swapping stations are characterized by low driving range, high battery swapping frequency, and low charging rate. This means that the time when the operating pressure and load of battery swapping stations are greatest often occurs in winter. The seasonal load characteristics of a certain electric taxi battery swapping station are shown in Table 1.

[0074] Table 1

[0075]

[0076] The daily power consumption, average power, and maximum power of battery swapping stations all exhibit significant seasonal variations. During the harsh winter, the peak load and daily power consumption of battery swapping stations are approximately 1.23 times and 1.46 times that of spring, respectively. The demand for battery swapping / charging of electric taxis increases dramatically in low-temperature environments, placing higher demands on the power supply capacity of battery swapping stations.

[0077] Since existing battery swapping stations can meet the battery swapping demand during the peak winter season, they must have certain seasonal adjustment potential in the spring, summer and autumn seasons. Therefore, this invention focuses on systematic analysis and in-depth exploration of this potential and proposes a method for evaluating the adjustment capacity of battery swapping stations that takes into account the number of seasonal surplus battery compartments.

[0078] Example 1:

[0079] like Figure 2 As shown, this embodiment provides a method for assessing the adjustment capacity of battery swapping stations considering the seasonal surplus battery storage capacity, including the following steps:

[0080] S1. Obtain vehicle battery swapping data for typical seasonal days.

[0081] The vehicle battery swapping data includes: the number of vehicles arriving, the battery swapping time, the remaining battery power, and the charging power.

[0082] S2. Based on the vehicle battery swapping data, construct an evaluation model for the adjustment capability of battery swapping stations that takes into account seasonal characteristics.

[0083] A further implementation in this embodiment is that the regulation capacity assessment model includes: an on-demand charging operation model during off-peak electricity price periods, a partial grid closure operation model during peak electricity price periods, and a grid closure release operation model during periods of high battery swapping risk.

[0084] More preferably, the "on-demand charging during off-peak electricity price periods" operation model involves charging the vehicle immediately after battery swapping, and the operating power and cost include:

[0085] (1)

[0086] (2)

[0087] in, (3)

[0088] (4)

[0089] (5)

[0090] (6)

[0091] In the formula, This indicates the amount of electricity purchased from the grid by the battery swapping station in the Pinggu electricity price period instant charging operation model; This indicates the immediate charging operation model during the Pinggu electricity price period. t The number of batteries being charged is constantly being monitored. Indicates the rated power of the battery compartment; This represents the electricity purchase cost of a battery swapping station in the Pinggu electricity price period-based instant charging operation model. Indicates time-of-use electricity pricing; Indicates the number of scheduling periods; This indicates the smallest time granularity for scheduling, with a value of 15 minutes. Indicates the number of vehicles that arrived that day; This indicates the number in the Pinggu electricity price period instant charging operation model. i vehicle battery t The charging indicator shows the current charging status, with 1 and 0 indicating that the device is charging or not charging, respectively. Indicates the number of days j Vehicle battery swapping time; , These represent the battery level at the moment of battery swapping and the battery level at full capacity, respectively; the battery compartment's rated power is also present. Indicates charging time; This indicates the full charge time in the Pinggu electricity price period's instant charging operation model.

[0092] A further implementation involves the peak electricity price period partial battery storage operation model, which involves delayed battery charging. The adjusted charging period and total daily charging cost are obtained by delaying the battery storage charging time.

[0093] The time for delayed charging after the warehouse is sealed includes:

[0094] (7)

[0095] In the formula, This indicates the time intervals in the peak electricity price period partial warehouse closure operation model; This indicates the duration of the delayed charging after the warehouse is sealed.

[0096] (8)

[0097] (9)

[0098] In the formula, In the peak electricity price period partial warehouse closure operation model t Time number is j The charging indicator for the vehicle's onboard battery; Indicates battery swapping station t The number of batteries constantly being charged; N represents the number of battery compartments in the battery swapping station.

[0099] The core of the closed-warehouse operation lies in calculating the closed-warehouse delayed charging time. This leads to the adjusted charging period, load curve, and operating cost. In this embodiment, linear programming is used to obtain these parameters.

[0100] Construct ascending and descending auxiliary variables to constrain charging time periods as follows: Figure 3 As shown; where, Figure 3 middle , This provides a general description of ascending and descending auxiliary variables.

[0101] Establish a constraint that the on-board battery charging period is after the battery swapping period, using a greater than sign. Then it will appear Therefore, to avoid logical errors, this embodiment uses the less than sign and descending auxiliary vector to model the charging period constraint model as follows:

[0102] (10)

[0103] In the formula, =[1, 2, ..., T] represents an ascending auxiliary variable; =[T, T-1, ..., 1] represents a descending auxiliary vector; This indicates the maximum allowable delay time for charging.

[0104] Construct the following constraints to keep the charging time constant after adjustment, and to ensure that the charging process cannot be interrupted:

[0105] (11)

[0106] (12)

[0107] In the formula, , These represent the start and end of the charging action, respectively.

[0108] The number of fully charged batteries decreases by one at the moment of battery swapping and increases by one at the end of charging. This process is repeated to calculate the number of fully charged batteries at each moment, and a minimum limit is set for each value to ensure battery swapping reliability. The model is as follows:

[0109] (13)

[0110] (14)

[0111] In the formula, express t The number of batteries at full capacity at each battery swapping station at any given time; , Representing the number respectively j The vehicle is t Real-time battery swapping indicator and battery fully charged indicator; This represents the minimum number of fully-equipped batteries available for backup to ensure reliable battery swapping.

[0112] By comparing the numbers j The difference between the battery swapping time and the charging start time can be used to determine whether a battery sealing action has occurred and guide the generation of sealing control action commands. The model is as follows:

[0113] (15)

[0114] (16)

[0115] (17)

[0116] In the formula, , Representing the number respectively jThe start time of battery charging and the duration of vehicle warehouse closure control mode; , These are the maximum and minimum limits for the duration of the lock-up period; This is a warehouse closure indicator; This represents the total number of shares locked up for the day, which can be further broken down into the number of shares locked up during the transition between peak and trough periods; superscript T This indicates transpose.

[0117] Modeling the mapping from the vehicle battery charging period matrix to the battery compartment charging period matrix is ​​necessary, as it helps to further map the delayed charging action of the vehicle battery onto the battery compartment hardware.

[0118] Construct a dimension as Auxiliary matrix , Identification number is j The vehicle's batteries are distributed to i Battery compartment charging:

[0119] (18)

[0120] (19)

[0121] In the formula, Indicates the total number of battery compartments; Indicates battery compartment i exist t The status of the device at any given time: 1 indicates that it is charging, and 0 indicates that it is not charging.

[0122] This leads to the following data in the peak electricity price period partial shutdown operation model: number of batteries charging at the battery swapping station at different times, charging power, and total daily charging cost:

[0123] (20)

[0124] ;(twenty one)

[0125] ;(twenty two)

[0126] In the formula, In the peak electricity price period partial warehouse closure operation model The number of batteries being charged is constantly being monitored. This represents the power purchased from the grid by the battery swapping station in the partial grid closure operation model during peak electricity price periods; This represents the electricity purchase cost of the battery swapping station in the peak electricity price period partial shutdown operation model.

[0127] Further implementation involves considering that the sealing of some battery compartments will reduce the number of fully-equipped backup batteries in subsequent times, thereby increasing the risk of untimely battery swapping. By adding a risk threshold, when the number of fully-equipped backup batteries is lower than the threshold, no new sealing will be carried out, and the existing sealing will be partially lifted.

[0128] The high-risk battery swapping period unsealing operation model unseales existing batteries based on risk thresholds, including:

[0129] ;(twenty three)

[0130] In the formula, This indicates the safety threshold for the number of backup batteries when fully charged. This indicates the number of batteries that are not full but are not allowed to be charged.

[0131] S3. The battery swapping station operates based on the aforementioned regulation capability assessment model, and the regulation capability of the battery swapping station is assessed from two aspects: time-shiftability and energy storage, and the assessment results are obtained.

[0132] A further implementation involves that the assessment results of the time-shiftable adjustment capability of battery swapping stations can be used for equivalent calculations using the battery empty capacity rate, including:

[0133] ;(twenty four)

[0134] In the formula, This indicates the utilization rate of the battery compartments in the battery swapping station's load category; Indicates the number of load-type battery compartments; express i Numbered battery compartment t A constant indicator of charging status; This indicates the percentage of the battery compartment in the load class of the battery swapping station that can be moved and adjusted.

[0135] The reliability regulation capability assessment results for energy storage systems at battery swapping stations cover two dimensions: energy capacity and power output.

[0136] (25)

[0137] In the formula, , These represent the adjustable capacity and power limits of energy storage batteries in battery swapping stations, respectively. This indicates the rated capacity of a single battery cell.

[0138] Example 2:

[0139] This embodiment provides a computational example to further illustrate the method proposed in this invention.

[0140] 1. Parameters for typical days in spring.

[0141] This study uses a typical day in spring to characterize the full battery pack cycle swapping analysis, assess the maximum number of surplus battery packs under no-delay swapping constraints, and analyze the delayed charging regulation capacity inherent in the surplus battery packs. It also analyzes the impact of regulation capacity mining on the risk of battery swapping timeliness and the economic benefits of the regulation capacity inherent in the surplus battery packs. Subsequently, it conducts a comparative analysis of the differences in the regulation capacity of swapping stations on typical days in the four seasons to characterize the annual variation trend of the regulation capacity of swapping stations.

[0142] Taking a battery swapping station for a Hongqi HB60 model as an example, the station has 60 battery compartments containing 59 55kWh batteries, with a rated charging power of 40kW. The charging process includes three stages: trickle charging, constant current charging, and constant voltage charging. The station's operation record information on April 25, 2024 (Thursday) is used as a case study. The parameters mainly cover basic information such as battery swapping frequency at various times, remaining battery power in each vehicle, and typical battery charging processes. See [link / details]. Figure 4 .

[0143] 2. Full battery compartment cyclic battery swapping mode.

[0144] A single battery swapping station contains N cell A series of sequentially numbered battery compartments, each containing N cell - One battery and one empty compartment. When a vehicle wants to swap batteries, the machine will first remove the vehicle's battery and place it into the currently empty battery compartment. i Set its charging period as needed, then remove it. i +1 (when) i When +1>N, let i +1=1) The fully charged battery in the numbered compartment (battery charging follows a first-come, first-served principle, and the removed battery is the oldest remaining battery) is reloaded back under the vehicle, completing the battery swapping task. The new empty compartment location number changes. i +1, Illustration of full battery compartment cyclic battery swapping and charging management, as follows Figure 5 As shown.

[0145] On the same day, the battery compartment was discharged 4.4 times, with an average charging time of 1.3 hours and a charging interval of 2.5 to 9 hours. Although the full battery compartment cyclic battery swapping and charging management can balance the utilization rate of all converters, all battery compartments need to undertake the hard charging task. There is an adjustable ability for delayed charging, but this adjustable ability is affected by the uncertainty of future battery swapping demand, making it difficult to clearly and accurately characterize the adjustment capability of the battery swapping station. Only the battery compartment utilization rate of the battery swapping station at all times of the day (25%) and the idle rate (75%) can be calculated according to formula (24) to qualitatively analyze its inherent adjustment capability.

[0146] 3. Assessment of the maximum number of spare battery compartments under the constraint of no delayed battery swapping.

[0147] By transforming the on-demand charging mode into a priority charging mode for lower-numbered battery compartments, the charging demand is compressed into a few battery compartments. The reliable regulation capability of the battery swapping station's energy storage can be calculated according to formula (25). Among the battery compartments that do not need to undertake hard charging tasks throughout the day, 28 battery compartments, accounting for 47%, have all-weather available regulation capability. Figure 6 As shown.

[0148] Once the number of battery compartments with energy storage / relocatable adjustment capabilities at the battery swapping station is calculated, the battery swapping and charging demands can be redistributed among some of the battery compartments. This simplifies the battery swapping process and balances the lifespan of the inverters. Figure 7 As shown.

[0149] 4. Analysis of the delayed charging regulation capability inherent in the surplus battery compartment.

[0150] A delayed charging control method is adopted to reduce the operating cost of battery swapping stations. During peak hours, fully charged batteries in the surplus battery compartment are prioritized for swapping, and the swapped-out batteries are sealed in the compartment and recharged during off-peak hours. After the surplus batteries are depleted, the cyclic charging mode is resumed. A single peak-valley cycle can adjust the amount of Nn batteries waiting to be charged. The battery charging time period for achieving delayed charging using the surplus battery compartment of the battery swapping station is illustrated in the figure below. Figure 8 As shown.

[0151] For passing Figure 5 , Figure 8 A comparative analysis of charging times before and after the adjustment still cannot intuitively describe the issues of the number and timing of charging bays corresponding to the bay closure delay strategy. Supplementing this analysis with information such as the battery state of charge at the battery swapping station is necessary. Figure 9 As shown. During the peak electricity price period from 09:00 to 11:30, a total of 26 vehicles arrived, which was less than the number of vehicles with spare battery compartments. Therefore, all of them were blocked and their charging was delayed until the off-peak electricity price period after 12:30. During the peak electricity price period from 15:30 to 21:00, a total of 66 vehicles arrived, which was more than the number of vehicles with spare battery compartments (28). Therefore, only 28 vehicle batteries were blocked and their charging was delayed until the off-peak electricity price period after 01:00 the next day.

[0152] 5. Analysis of the impact of regulation capability mining on the timeliness risk of battery swapping.

[0153] Delaying charging by sealing the battery compartment can cause the originally relatively flat distribution of charging demand to become significantly different in peak and valley states. This can lead to huge fluctuations in the number of fully charged batteries available for backup at different times, such as... Figure 10 As shown.

[0154] After adopting the optimized storage quantity mode, the daily fluctuation range of the number of fully-equipped batteries surged from 28 (47%) to 53 (90%). This significantly increased the risk of insufficient fully-equipped battery reserves at the battery swapping station during vehicle swapping times, necessitating the addition of risk threshold protection measures. Specifically, when the number of fully-equipped battery reserves falls below the risk threshold (or before), partial storage should be released, such as... Figure 11 As shown.

[0155] When the number of fully-equipped backup batteries in the station falls below 10, a risk threshold protection measure is triggered. Consequently, the number of batteries locked during the evening peak hours drops sharply from 28 to 19, significantly reducing the consumption of fully-equipped batteries during peak hours. The minimum number of fully-equipped batteries throughout the day increases from 5 to 10. The increased number of fully-equipped batteries enhances the timeliness and reliability of battery swapping.

[0156] 6. Economic benefit analysis of the adjustment capacity inherent in the surplus battery compartment.

[0157] By utilizing spare battery compartments to delay charging of vehicle batteries during peak hours until off-peak electricity pricing periods, the load on battery swapping stations can be flexibly adjusted. Figure 12 As shown, the charging load at battery swapping stations decreased significantly during peak electricity price periods of 09:00~11:30 and 15:30~21:00. After this charging demand shifted to off-peak periods, the charging load increased significantly during off-peak periods of 12:30~14:00 and 01:00~03:00. The daily operating cost of battery swapping stations decreased from 8565 yuan to 7297 yuan, a reduction of 1268 yuan, or 15%.

[0158] 7. Analysis of the evaluation results of the regulation capacity of a typical daily power exchange station in four seasons.

[0159] Table 2 shows a comparative analysis of the operation of the battery swapping station before and after optimization, based on typical days in spring, summer, autumn, and winter.

[0160] Table 2

[0161]

[0162] Significant differences exist in battery swapping frequency, the number of surplus battery compartments, and electricity purchase costs across seasons. In spring, summer, and autumn, the number of surplus battery compartments exceeds 25%, and optimizing their capacity can reduce electricity purchase costs by more than 8%. In winter, higher battery swapping frequency and charging demand result in a surplus battery compartment count below 15%, leading to an electricity purchase cost optimization rate of only 3.91%. This demonstrates that the capacity of the same battery swapping station varies significantly across seasons, with minimal or no capacity in winter, while spring, summer, and autumn offer significant potential for cost reduction and efficiency improvement.

[0163] Example 3:

[0164] This embodiment provides a system for assessing the adjustment capacity of a battery swapping station that considers the number of seasonal surplus battery storage compartments. It implements the assessment method provided in Embodiment 1, and includes: a data acquisition module for acquiring vehicle battery swapping data for typical days of the season; a model building module for constructing an assessment model of the adjustment capacity of the battery swapping station that considers seasonal characteristics based on the vehicle battery swapping data; and an assessment module for assessing the adjustment capacity of the battery swapping station from both time-shifting and energy storage perspectives, while the station is operating based on the assessment model, to obtain the assessment results.

[0165] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made to the technical solutions of the present invention by those skilled in the art without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. A method for assessing the adjustment capacity of battery swapping stations considering the seasonal surplus of battery storage capacity, characterized in that, Includes the following steps: S1. Obtain vehicle battery swapping data for typical seasonal days; S2. Construct an evaluation model for the adjustment capability of battery swapping stations that takes into account seasonal characteristics based on the vehicle battery swapping data; The regulation capacity assessment model includes: the on-demand charging operation model during the off-peak electricity price period, the partial battery storage operation model during the peak electricity price period, and the battery storage release operation model during periods of high battery swapping risk. The peak electricity price period partial storage operation model is to delay battery charging. The adjusted charging period and the total daily charging cost are obtained by the storage delay charging duration. The process of adjusting the charging period and operating cost based on the aforementioned warehouse delay charging time includes: Construct ascending and descending auxiliary variables, and calculate the warehouse sealing delay charging time using linear programming. Establish constraints that the on-board battery charging period occurs after the battery swapping period: ； In the formula, In the peak electricity price period partial warehouse closure operation model t Time number is j The charging indicator for the vehicle's onboard battery; Indicates an ascending order auxiliary variable; Represents a descending auxiliary vector; This indicates the maximum allowable delayed charging time limit; For the day's number j Vehicle battery swapping time; Indicates charging time; Indicates the number of scheduling periods; Construct a constraint that the charging time remains constant after adjustment, and a constraint that the charging process cannot be interrupted: ； ； In the formula, , These represent the start and end of the charging action, respectively. Set a minimum limit for the number of fully charged batteries at different times, and compare their serial numbers. j Determine the battery number based on the difference between the battery swapping time and the charging start time. j Whether the vehicle battery is sealed, and whether a sealing control command is generated; Construct a dimension as Auxiliary matrix , Identification number is j The vehicle's batteries are distributed to i Battery compartment charging: ； ； In the formula, Indicates the total number of battery compartments; This indicates the number of vehicles that arrived that day; Indicates battery compartment i exist t The status of the device at any given time: 1 indicates that it is charging, and 0 indicates that it is not charging. This leads to the following data in the peak electricity price period partial shutdown operation model: number of batteries charging at the battery swapping station at different times, charging power, and total daily charging cost: ； ； ； In the formula, In the peak electricity price period partial warehouse closure operation model t The number of batteries being charged is constantly being monitored. This refers to the power purchased in the partial power closure operation model during peak electricity pricing periods; This refers to the electricity purchase cost in the peak electricity price period partial warehouse closure operation model; This represents the smallest time granularity of the scheduling. Indicates the rated power of the battery compartment; Indicates time-of-use electricity pricing; S3. The battery swapping station operates based on the aforementioned regulation capability assessment model, and the regulation capability of the battery swapping station is assessed from two aspects: time-shiftability and energy storage, and the assessment results are obtained.

2. The method for assessing the adjustment capacity of battery swapping stations considering the number of seasonal surplus battery storage units as described in claim 1, characterized in that, The vehicle battery swapping data includes: number of vehicles arriving, battery swapping time, remaining battery power, and charging power.

3. The method for assessing the adjustment capacity of battery swapping stations considering the number of seasonal surplus battery storage units as described in claim 1, characterized in that, The Pinggu electricity price period instant charging operation model involves charging vehicles immediately after battery swapping. The operating power and cost include: ； ； In the formula, This indicates the amount of electricity purchased from the grid by the battery swapping station in the Pinggu electricity price period instant charging operation model; Indicates instant charging mode t The number of batteries being charged is constantly being monitored. This represents the electricity purchase cost of a battery swapping station in the Pinggu electricity price period's immediate charging operation model.

4. The method for assessing the adjustment capacity of battery swapping stations considering the number of seasonal surplus battery storage units as described in claim 3, characterized in that, Storage delay charging time: ； In the formula, This indicates the time intervals in the peak electricity price period partial warehouse closure operation model; This indicates the duration of the delayed charging after the warehouse is sealed.

5. The method for assessing the adjustment capacity of battery swapping stations considering the number of seasonal surplus battery storage units as described in claim 1, characterized in that, The high-risk battery swapping period unsealing operation model unseales existing batteries based on risk thresholds, including: ； In the formula, This indicates the safety threshold for the number of backup batteries when fully charged. This indicates the quantity of the warehouse that has been sealed.

6. The method for assessing the adjustment capacity of battery swapping stations considering the number of seasonal surplus battery storage units as described in claim 1, characterized in that, The time-shiftability aspect is calculated through battery vacancy rate, and the methods include: ； In the formula, This indicates the utilization rate of the battery compartments in the battery swapping station's load category; Indicates the number of load-type battery compartments; express i Numbered battery compartment t A constant indicator of charging status; This indicates the percentage of the battery compartments at the battery swapping station that can be moved and adjusted backwards. Energy storage assessment includes two dimensions: capacity and power. ； In the formula, , Limits on the adjustable capacity and power of energy storage batteries in battery swapping stations; This indicates the rated capacity of a single battery cell.

7. A system for assessing the adjustment capacity of battery swapping stations considering the number of seasonally surplus battery storage units, said system being used to implement the assessment method as described in any one of claims 1-6, characterized in that, include: The data acquisition module is used to acquire vehicle battery swapping data on typical days of the season. The model building module is used to build an evaluation model of the battery swapping station's adjustment capability that takes into account seasonal characteristics based on the vehicle battery swapping data. The evaluation module is used to evaluate the regulation capacity of the battery swapping station from both time-shifting and energy storage perspectives when the station is operating based on the regulation capacity evaluation model, and to obtain the evaluation results.

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