New energy automobile charging pile operation management system

Abstract

The invention relates to the technical field of charging pile management, and discloses a new energy vehicle charging pile operation management system comprising a data acquisition module used for acquiring charging pile operation data and vehicle arrival data; the vehicle priority calculation module is used for calculating vehicle priorities based on the vehicle arrival data and a preset congestion coefficient and generating a vehicle queuing sequence; the scheduling pricing module is used for constructing a state matrix, matching a current operation state, extracting an energy storage control label and a pricing additional parameter, and generating an energy storage power control instruction and a service gear price; the execution control module is used for executing charging power issuing according to the service gear price, the preset station-level power demand and the energy storage power control instruction; and the parameter updating module is used for counting the triggering times of the operation state item and the queuing waiting duration of the corresponding period, and performing regularization adjustment on the pricing additional parameter. According to the invention, integrated management of intelligent scheduling and dynamic pricing based on a multi-dimensional operation state is realized.

Description

Technical Field

[0001] This invention belongs to the field of charging pile management technology, specifically relating to a new energy vehicle charging pile operation and management system. Background Technology

[0002] With the rapid popularization of new energy vehicles, the construction of supporting charging infrastructure has become a key factor restricting the industry's development. Traditional charging pile systems mainly rely on static queuing rules and fixed pricing, which are difficult to cope with problems such as resource shortages during peak periods, poor user experience, and low operational efficiency. Especially in scenarios where multiple users and multiple service levels are connected simultaneously, how to dynamically schedule and scientifically price charging based on the urgency of vehicle charging needs, on-site load status, and energy supply capacity has become an important issue for improving the utilization rate and operational efficiency of charging networks. In addition, the operation of charging stations is affected by multiple factors such as fluctuations in photovoltaic output, changes in grid peak and valley electricity prices, and limitations on the state of charge of energy storage, resulting in frequent state changes. If key operating variables cannot be detected in a timely manner and control strategies cannot be dynamically adjusted, it can easily lead to resource scheduling imbalances and efficiency decline. Existing systems generally lack a unified expression mechanism for operating characteristics such as electricity price, power load, and time, and the scheduling and pricing functions are disconnected, making it difficult to optimize them together. Equipment fault detection still relies on manual inspection, which has a response lag and cannot promptly identify potential hazards such as abnormal contact or excessive temperature rise, affecting operational safety. Summary of the Invention

[0003] This invention provides an operation and management system for new energy vehicle charging piles, which solves the technical problems of untimely dispatch response, single pricing strategy and lagging equipment maintenance in related technologies.

[0004] This invention provides a new energy vehicle charging pile operation and management system, comprising:

[0005] The data acquisition module is used to collect and store charging pile operation data and vehicle arrival data;

[0006] The charging pile operation data includes: real-time grid electricity price, photovoltaic output power, energy storage status of charge, gun utilization rate, station-level charging load, and timestamp;

[0007] Vehicle arrival data includes: vehicle charge status upon arrival, user service level, and queue waiting time;

[0008] The vehicle priority calculation module is used to calculate vehicle priority based on vehicle arrival data and the preset congestion coefficient corresponding to the user service level, and generate vehicle queuing order.

[0009] The scheduling and pricing module is used to perform discrete mapping based on charging pile operation data and vehicle arrival data, construct a state matrix containing multiple operation status items, match the current operation status, extract the energy storage control tag and pricing additional parameters corresponding to the current operation status from the state matrix, and generate energy storage power control instructions and service level prices.

[0010] The execution control module is used to execute charging power distribution, transaction metering and settlement, and multi-party revenue sharing operations based on service tier prices, preset station-level power requirements, and energy storage power control commands.

[0011] The parameter update module is used to count the number of times each running status item in the status matrix is ​​triggered and the corresponding queuing waiting time within a set rolling time window, and to make regular adjustments to the pricing additional parameters accordingly.

[0012] Furthermore, based on vehicle arrival data and the preset congestion coefficient corresponding to the user service level, vehicle priority is calculated, and a vehicle queuing order is generated, including:

[0013] S201, obtain the corresponding service level congestion coefficient from the preset congestion coefficient table based on vehicle arrival data;

[0014] S202, calculate the reciprocal of the state of charge upon arrival as the remaining power coefficient, calculate the ratio of the queuing waiting time to the maximum queuing waiting time, and obtain the normalized waiting time;

[0015] S203, based on preset weights, integrates the remaining battery power coefficient, normalized waiting time, and service level congestion coefficient to obtain vehicle priority;

[0016] S204: Sort vehicles according to their priority to generate a vehicle queue order.

[0017] Furthermore, based on a discrete mapping between charging pile operation data and vehicle arrival data, a state matrix containing multiple operation state items is constructed, including:

[0018] S301, based on the real-time electricity price of the power grid, the state of charge of energy storage, the utilization rate of the gun nozzle and the timestamp in the past 24 hours, calculate the distribution interval boundary of each indicator and form a set of interval boundaries;

[0019] S302, based on the interval boundary set, map the real-time electricity price of the power grid, the state of charge of energy storage, the utilization rate of the charging nozzle, and the timestamp into discrete labels, and combine them to obtain the operating status identifier; among which, the discrete labels include: electricity price label, energy storage state of charge label, charging nozzle utilization rate label, and time period label;

[0020] S303 uses the electricity price tag as the row index, the energy storage charge status tag as the column index, and the nozzle utilization rate tag and time period tag as the hierarchical dimensions to construct a state matrix containing multiple operating status items.

[0021] S304 uses each operating status item as a matrix element to store the corresponding energy storage control tag and pricing additional parameters, and records the number of triggers and update time of the operating status item.

[0022] Furthermore, it generates energy storage power control commands and service tier pricing, including:

[0023] S401, locate the operating status item in the status matrix according to the operating status identifier, and extract the corresponding energy storage control tag and pricing additional parameters;

[0024] S402: Set energy storage charging and discharging commands according to the energy storage control tag, and correct the energy storage power by the difference between the station-level charging load and the photovoltaic output power to obtain the energy storage power control command;

[0025] S403: Add the real-time electricity price of the power grid to the preset fixed cost, and divide by the difference between the real-time electricity price and the preset target gross profit margin to obtain the base electricity price. Add the product of the base electricity price, the service level congestion coefficient and the gun utilization rate, and the pricing additional parameters to obtain the corresponding service level price.

[0026] Furthermore, in S402, if the energy storage charge status label of the operating status item is lower than the preset lower limit, the energy storage control label is set to charging; if the energy storage charge status label is higher than the preset upper limit, the energy storage control label is set to discharging; otherwise, the energy storage control label is set to standby.

[0027] Furthermore, based on service tier pricing, preset station-level power requirements, and energy storage power control commands, the system executes charging power distribution, transaction metering and settlement, and multi-party revenue sharing operations, including:

[0028] S501 obtains service tier prices, preset station-level power requirements, energy storage power control commands, maximum power of a single gun and number of active guns, and calculates and issues charging power.

[0029] S502 reads the actual charging amount at the end of each charging session and calculates the transaction fee based on the corresponding service tier price.

[0030] S503 splits revenue among site owners, operators, and the platform according to a preset revenue-sharing ratio.

[0031] Furthermore, in S501, the required grid power is determined based on the difference between the preset station-level power demand and the energy storage power control command. The preset station-level power demand is then evenly distributed to each active charging gun. Finally, limit correction is performed based on the maximum power of a single gun to obtain the target power of a single gun, which is then issued as the charging power.

[0032] Furthermore, the execution control module is also used to collect the temperature rise parameters, contact resistance values ​​and fault event frequencies of the charging gun, and weight them to obtain the equipment health index. When the equipment health index is lower than the preset health threshold, the equipment maintenance operation is triggered.

[0033] Furthermore, within a set rolling time window, the number of triggers for each running state item in the state matrix and the corresponding queuing time are statistically analyzed, and the pricing parameters are adjusted accordingly, including:

[0034] S601, calculate the average waiting time based on the number of triggers and queuing waiting time of each running status item within the set rolling time window, and compare it with the preset target waiting time to generate a waiting deviation;

[0035] S602, if the waiting deviation is positive and the number of triggers exceeds the preset trigger threshold, the pricing additional parameter is increased by the preset step size; if the waiting deviation is negative, the pricing additional parameter is decreased by the same step size.

[0036] S603 writes the updated pricing parameters back to the corresponding running status item and records the update time.

[0037] The beneficial effects of this invention are as follows: It combines multi-dimensional operational status recognition, priority scheduling, dynamic pricing, and charging / discharging control, enabling closed-loop operation management based on multi-source data. By constructing a state matrix containing discrete labels such as electricity price, state of charge, load, and time, it accurately matches operational scenarios, improving the adaptability and response speed of control strategies. Combined with vehicle arrival data and service level settings, it achieves differentiated queuing and power allocation, improving user satisfaction and resource utilization efficiency. This invention employs a rolling time window mechanism to statistically feedback the trigger frequency and waiting performance of operational status items, supporting adaptive adjustment of pricing parameters and enhancing operational flexibility. Furthermore, it integrates charging gun temperature rise, contact resistance, and fault frequency indicators to calculate a health index, triggering maintenance operations in real time and reducing equipment failure risks. Attached Figure Description

[0038] Figure 1 This is a schematic diagram of a module of a new energy vehicle charging pile operation and management system according to the present invention. Detailed Implementation

[0039] The subject matter described herein will now be discussed with reference to exemplary embodiments. It should be understood that these embodiments are discussed only to enable those skilled in the art to better understand and implement the subject matter described herein, and changes may be made to the function and arrangement of the elements discussed without departing from the scope of this specification. Various processes or components may be omitted, substituted, or added as needed in the examples. Furthermore, features described in some examples may be combined in other examples.

[0040] It should be noted that, unless otherwise defined, the technical or scientific terms used in one or more embodiments of the present invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in one or more embodiments of the present invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed after the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0041] like Figure 1 As shown, a new energy vehicle charging pile operation and management system includes:

[0042] Data acquisition module 101 is used to collect and store charging pile operation data and vehicle arrival data;

[0043] The charging pile operation data includes: real-time grid electricity price, photovoltaic output power, energy storage status of charge, gun utilization rate, station-level charging load, and timestamp;

[0044] Vehicle arrival data includes: vehicle charge status upon arrival, user service level, and queue waiting time;

[0045] The vehicle priority calculation module 102 is used to calculate vehicle priority based on vehicle arrival data and preset congestion coefficients corresponding to user service levels, and generate vehicle queuing order.

[0046] The scheduling and pricing module 103 is used to perform discrete mapping based on charging pile operation data and vehicle arrival data, construct a state matrix containing multiple operation status items, match the current operation status, extract the energy storage control tag and pricing additional parameters corresponding to the current operation status from the state matrix, and generate energy storage power control instructions and service level prices.

[0047] The execution control module 104 is used to execute charging power distribution, transaction metering settlement and multi-party revenue sharing operations according to the service level price, preset station-level power demand and energy storage power control instructions;

[0048] The parameter update module 105 is used to count the number of times each running status item in the status matrix is ​​triggered and the corresponding queuing waiting time within a set rolling time window, and to make regular adjustments to the pricing additional parameters accordingly.

[0049] In one embodiment of the present invention, charging pile operation data is acquired at a frequency of 5 seconds per acquisition. This includes obtaining real-time grid electricity prices through an API interface with the grid operator; reading real-time output power from the monitoring port of the photovoltaic inverter; obtaining the energy storage state of charge through the battery management system of the energy storage system; monitoring the insertion / removal status signals of each charging port in real time through the charging pile controller, counting the number of currently occupied charging ports, and dividing by the total number of charging ports at the site to obtain the charging port utilization rate; installing sensors at the main incoming line of the site to collect current and voltage, and calculating the active power as the station-level charging load; all the above data are timestamped using a unified clock module to ensure consistency in the time dimension of the data.

[0050] For vehicle arrival data, the vehicle's charge status upon arrival is obtained through the communication protocol between the charging gun and the vehicle's BMS. User service levels include: fast charging, standard charging, and delayed charging. Users can choose their own service level. If the user does not actively select a level, the standard charging level will be matched by default. When a vehicle enters the queuing area of ​​the station, the queuing start time is automatically recorded, and the difference between the current time and the queuing start time is used as the queuing waiting time.

[0051] In one embodiment of the present invention, vehicle priority is calculated based on vehicle arrival data and a preset congestion coefficient corresponding to the user service level, and a vehicle queuing order is generated, including:

[0052] S201, obtain the corresponding service level congestion coefficient from the preset congestion coefficient table based on vehicle arrival data; the service level congestion coefficient is calibrated by historical data and is used to reflect the resource occupation priority of different user service levels. Priority is given to 0.4 for the urgent charging level, 0.15 for the standard level, and 0 for the delayed level.

[0053] S202, calculate the reciprocal of the state of charge upon arrival as the remaining power coefficient, calculate the ratio of the queuing waiting time to the maximum queuing waiting time, and obtain the normalized waiting time;

[0054] S203, based on preset weights, integrates the remaining battery power coefficient, normalized waiting time, and service level congestion coefficient to obtain vehicle priority; the calculation formula for vehicle priority is as follows: P represents vehicle priority; the higher the value, the higher the vehicle's priority. w1, w2, and w3 are the first, second, and third preset weights, respectively. SoC in Indicates the state of charge upon arrival at the station, t wait t represents the waiting time in the queue. wait,max This represents the maximum queuing time, set based on historical data, α. k This indicates the congestion coefficient of the service level.

[0055] S204: Sort vehicles according to their priority to generate a vehicle queue order; if the vehicle priority values ​​are the same, prioritize the vehicle with the longer waiting time.

[0056] This embodiment highlights the urgency of recharging low-battery vehicles by using a remaining battery power coefficient, avoids long queues by using normalized waiting time, and reflects payment differences by combining service level congestion coefficients. The priority rule formed by the weighted integration of these three factors not only ensures a rapid response to emergency recharging needs, but also reduces user disputes through transparent sorting.

[0057] In one embodiment of the present invention, a state matrix containing multiple operating state items is constructed by discretely mapping charging pile operation data and vehicle arrival data, including:

[0058] S301, based on the real-time electricity price of the power grid, the state of charge of energy storage, the utilization rate of the gun nozzle and the timestamp in the past 24 hours, calculate the distribution interval boundary of each indicator and form a set of interval boundaries;

[0059] Specifically, for the above four indicators, the quantile method is used to calculate the distribution interval boundaries. Preferably, for the real-time electricity price of the power grid, the 10%, 30%, 70%, and 90% quantile values ​​are used as boundaries to form 5 connected intervals; for the energy storage state of charge, which ranges from 0 to 1, it is divided into 4 intervals according to 0-25%, 25%-50%, 50%-75%, and 75%-100%; for the muzzle utilization rate, which ranges from 0 to 100%, it is divided into 3 intervals according to 0-30%, 30%-70%, and 70%-100%; for the timestamp, 24 hours are divided into 96 time periods at 15-minute intervals to form time interval boundaries. The above distribution interval boundaries together form the interval boundary set, providing a benchmark for the discretization of the indicators.

[0060] S302, based on the interval boundary set, the real-time electricity price of the power grid, the state of charge of energy storage, the utilization rate of the charging nozzle, and the timestamp are mapped to discrete labels, and combined to obtain an operating status identifier; wherein, the discrete labels include: electricity price label, energy storage state of charge label, charging nozzle utilization rate label, and time period label; specifically, when each indicator falls into the corresponding interval, it is labeled, and the above labels are combined in a fixed order to form a unique operating status identifier, which is used to identify the current operating status of the system.

[0061] S303 uses the electricity price tag as the row index, the energy storage charge status tag as the column index, and the nozzle utilization rate tag and time period tag as the hierarchical dimensions to construct a state matrix containing multiple operating status items.

[0062] Specifically, a basic two-dimensional matrix is ​​first constructed using the electricity price tag as the row index and the energy storage charge status tag as the column index. At the same time, the nozzle utilization rate tag and the time period tag are used as the hierarchical dimensions of the matrix. Hierarchical storage is achieved through a multi-dimensional array structure, which further subdivides each cell of the basic two-dimensional matrix into multiple sub-cells. Each sub-cell corresponds to a unique combination of electricity price tag, energy storage charge status tag, nozzle utilization rate tag, and time period tag, i.e., an operating status item. The resulting status matrix completely covers all possible combinations of the four indicators, ensuring that any real-time operating status can find a corresponding mapping item in the matrix.

[0063] S304 uses each operating status item as a matrix element to store the corresponding energy storage control tag and pricing additional parameters, and records the number of triggers and update time of the operating status item.

[0064] Among them, the energy storage control tag is used to specify the energy storage operation in this operating state, such as charging, discharging, and standby; the pricing additional parameter is used to dynamically adjust the service tier price, and the initial value is calibrated based on historical data; the trigger count refers to the cumulative number of times a certain operating state identifier is matched with the same operating state item within a rolling cycle, used to dynamically evaluate the typicality and activity of the operating state item; the update time refers to the timestamp of the most recent match of the operating state item, used to determine whether the state is in a long-term inactive state.

[0065] This embodiment dynamically determines the interval boundary using nearly 24 hours of data, enabling the state division to adapt to the fluctuation patterns of the power grid and user behavior, avoiding matching deviations caused by fixed intervals; by discretizing continuous parameters into finite labels and constructing a multi-dimensional state matrix, a structured expression of the complex system state is realized, enabling the scheduling and pricing module to complete the matching of the current state with the control strategy within milliseconds.

[0066] In one embodiment of the present invention, generating energy storage power control commands and service tier prices includes:

[0067] S401, locate the operating status item in the status matrix according to the operating status identifier, and extract the corresponding energy storage control tag and pricing additional parameters;

[0068] S402: Set energy storage charging and discharging commands according to the energy storage control tag, and correct the energy storage power by the difference between the station-level charging load and the photovoltaic output power to obtain the energy storage power control command;

[0069] Specifically, if the energy storage charge status tag in the operating status item is lower than the preset lower limit, the energy storage control tag is set to charging, and the energy storage charging and discharging command is for the energy storage system to operate at maximum charging power; if the energy storage charge status tag is higher than the preset upper limit, the energy storage control tag is set to discharging, and the energy storage charging and discharging command is for the energy storage system to operate at maximum discharging power; otherwise, the energy storage control tag is set to standby, and the energy storage charging and discharging command is 0 power. The energy storage charging and discharging command is corrected by calculating the difference between the station-level charging load and the photovoltaic output power. When the difference is positive, it indicates insufficient photovoltaic output. If the energy storage control tag is charging, the charging power is reduced or standby is maintained. If the energy storage control tag is discharging, the discharging power is increased to make up for the shortfall. When the difference is negative, it indicates excessive photovoltaic output. If the energy storage control tag is charging, the charging power is increased to absorb the excess power. If the energy storage control tag is discharging, the discharging power is reduced. The corrected power is the final energy storage power control command.

[0070] S403: Add the real-time electricity price of the power grid to the preset fixed cost, and divide by the difference between the real-time electricity price and the preset target gross profit margin to obtain the base electricity price. Add the product of the base electricity price, the service level congestion coefficient and the gun utilization rate, and the pricing additional parameters to obtain the corresponding service level price.

[0071] Specifically, after obtaining the base electricity price, adjustment items are added to obtain the service tier price. The adjustment items include: the service tier congestion coefficient multiplied by the gun barrel utilization rate and additional pricing parameters.

[0072] This embodiment directly matches the energy storage control tag and pricing parameters through a state matrix, ensuring the speed and certainty of decision-making and avoiding delays caused by complex algorithms; it introduces the difference between the station-level charging load and the photovoltaic output power to correct the energy storage power, making the energy storage operation more in line with the real-time energy balance requirements; the calculation of service tier prices integrates cost, profit, service level and real-time status, which not only guarantees the operator's basic revenue, but also guides users to charge during off-peak hours through dynamic adjustments.

[0073] In one embodiment of the present invention, based on the service tier price, preset station-level power demand, and energy storage power control instructions, the following operations are performed: charging power distribution, transaction metering settlement, and multi-party revenue sharing.

[0074] S501: Obtain the service tier price, preset station-level power requirement, energy storage power control command, maximum power of a single charging gun, and number of active charging guns; calculate and issue the charging power. Specifically, the preset station-level power requirement represents the upper limit of the total power requirement of all active charging guns at the current station; obtain the total number of charging ports currently performing charging operations and the maximum power of a single charging gun; calculate the difference between the preset station-level power requirement and the energy storage power control command to obtain the required grid power; and evenly distribute the preset station-level power requirement to each active charging gun to obtain the initial power allocation per charging gun. Since each charging gun has a hardware power limit, i.e., the maximum power of a single charging gun, the initial power allocation per charging gun is compared with the maximum power of a single charging gun. If the initial power allocation per charging gun is less than or equal to the maximum power of a single charging gun, the initial power allocation per charging gun is directly used as the charging power issued; if the initial power allocation per charging gun is greater than the maximum power of a single charging gun, the maximum power of a single charging gun is used as the charging power issued to ensure that it does not exceed the hardware capacity of the equipment.

[0075] S502 reads the actual charging amount at the end of each charging session and calculates the transaction fee based on the corresponding service tier price; the transaction fee is obtained by multiplying the actual charging amount by the service tier price.

[0076] S503 stipulates that revenue is split among site owners, operators, and platforms according to a preset revenue-sharing ratio; the preset revenue-sharing ratio is agreed upon in advance by the operator, site owners, and platform service providers.

[0077] In one embodiment of the present invention, the execution control module is further configured to collect the temperature rise parameters, contact resistance values ​​and fault event frequencies of the charging gun, and weight and superimpose them to obtain the equipment health index. When the equipment health index is lower than a preset health threshold, the equipment maintenance operation is triggered.

[0078] The system collects the current temperature by using temperature sensors distributed at the charging gun head and cable connectors, and calculates the difference between the current temperature and the ambient temperature to obtain the temperature rise parameter; it uses a micro-resistance tester to measure the contact resistance value between the charging gun and the vehicle interface; and it obtains the frequency of charging gun fault events based on records of the past 30 days, including but not limited to: overcurrent protection, communication interruption, and insulation failure.

[0079] The above data is normalized using the maximum-minimum normalization method, mapping it to the range of 0 to 1. The normalized temperature rise parameter, contact resistance value, and fault event frequency are weighted and superimposed to obtain the median value. The equipment health index is obtained by subtracting the median value from 1. The preset health threshold is preferably set to 0.7.

[0080] When the device health index is between 0.5 and 0.7, a yellow alert is triggered, and the system pushes an alert message to the maintenance personnel, indicating that the charging gun has a potential risk and needs to be inspected. When the device health index is between 0.3 and 0.5, the system automatically marks the charging gun as pending maintenance, prohibits users from making appointments, and sends a work order to the maintenance personnel, requiring repair to be completed within 24 hours. When the device health index is between 0 and 0.3, the system immediately cuts off the power to the charging gun, triggers the emergency repair process, and requires maintenance personnel to arrive on site within 4 hours.

[0081] In one embodiment of the present invention, within a set rolling time window, the number of triggers of each running state item in the state matrix and the corresponding queuing waiting time are statistically analyzed, and the pricing additional parameters are adjusted in a regularized manner accordingly, including:

[0082] S601, calculate the average waiting time based on the number of triggers and queuing waiting time of each running status item within the set rolling time window, and compare it with the preset target waiting time to generate a waiting deviation; the rolling time window is preferably set to 2 hours.

[0083] S602, if the waiting deviation is positive and the number of triggers exceeds the preset trigger threshold, it indicates that the user's waiting time is too long in this state, and it is necessary to guide off-peak through price leverage. At this time, the pricing additional parameter is increased by a preset step size; if the waiting deviation is negative, it indicates that the current price may be too high, and the pricing additional parameter is decreased by the same step size; preferably, the preset trigger threshold is 5 times.

[0084] S603, write the updated pricing additional parameters back to the corresponding running status item and record the update time; if a running status item is not triggered for three consecutive rolling time windows, reset its pricing additional parameters to the initial value to avoid the parameters of long-term inactive status becoming invalid.

[0085] This embodiment achieves dynamic calibration of pricing parameters through a rolling time window, enabling the pricing strategy to respond in real time to changes in user waiting time. Under high load conditions of waiting timeout, price increases are used to guide users to avoid peak hours, while under low load conditions, price reductions are used to attract users, thereby controlling the average waiting time within a preset target range. The setting of preset trigger thresholds avoids blind adjustments under small samples, ensuring the reliability of parameter optimization. Combined with the recording and resetting mechanism of update time, the state matrix always remains adapted to the actual operating state.

[0086] It should be noted that the interval and threshold sizes are set for ease of comparison. The size of the threshold depends on the amount of sample data and the base number set by those skilled in the art for each set of sample data, as long as it does not affect the proportional relationship between the parameter and the quantized value. Furthermore, the above formulas are all dimensionless calculations, and the formulas are derived from software simulations using a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0087] The embodiments of the present invention have been described above, but the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms based on the guidance of the present embodiments, all of which are within the protection scope of the present embodiments.

Claims

1. A new energy vehicle charging pile operation and management system, characterized in that, include: The data acquisition module is used to collect and store charging pile operation data and vehicle arrival data; The charging pile operation data includes: real-time grid electricity price, photovoltaic output power, energy storage status of charge, gun utilization rate, station-level charging load, and timestamp; Vehicle arrival data includes: vehicle charge status upon arrival, user service level, and queue waiting time; The vehicle priority calculation module is used to calculate vehicle priority based on vehicle arrival data and the preset congestion coefficient corresponding to the user service level, and generate vehicle queuing order. The scheduling and pricing module is used to perform discrete mapping based on charging pile operation data and vehicle arrival data, construct a state matrix containing multiple operation status items, match the current operation status, extract the energy storage control tag and pricing additional parameters corresponding to the current operation status from the state matrix, and generate energy storage power control instructions and service level prices. The execution control module is used to execute charging power distribution, transaction metering and settlement, and multi-party revenue sharing operations based on service tier prices, preset station-level power requirements, and energy storage power control commands. The parameter update module is used to count the number of times each running status item in the status matrix is ​​triggered and the corresponding queuing waiting time within a set rolling time window, and to make regular adjustments to the pricing additional parameters accordingly.

2. The new energy vehicle charging pile operation and management system according to claim 1, characterized in that, Based on vehicle arrival data and the preset congestion coefficient corresponding to the user service level, vehicle priority is calculated, and a vehicle queuing order is generated, including: S201, obtain the corresponding service level congestion coefficient from the preset congestion coefficient table based on vehicle arrival data; S202, calculate the reciprocal of the state of charge upon arrival as the remaining power coefficient, calculate the ratio of the queuing waiting time to the maximum queuing waiting time, and obtain the normalized waiting time; S203, based on preset weights, integrates the remaining battery power coefficient, normalized waiting time, and service level congestion coefficient to obtain vehicle priority; S204: Sort vehicles according to their priority to generate a vehicle queue order.

3. The new energy vehicle charging pile operation and management system according to claim 1, characterized in that, Based on a discrete mapping between charging pile operation data and vehicle arrival data, a state matrix containing multiple operation status items is constructed, including: S301, based on the real-time electricity price of the power grid, the state of charge of energy storage, the utilization rate of the gun nozzle and the timestamp in the past 24 hours, calculate the distribution interval boundary of each indicator and form a set of interval boundaries; S302, based on the interval boundary set, map the real-time electricity price of the power grid, the state of charge of energy storage, the utilization rate of the charging nozzle, and the timestamp into discrete labels, and combine them to obtain the operating status identifier; among which, the discrete labels include: electricity price label, energy storage state of charge label, charging nozzle utilization rate label, and time period label; S303 uses the electricity price tag as the row index, the energy storage charge status tag as the column index, and the nozzle utilization rate tag and time period tag as the hierarchical dimensions to construct a state matrix containing multiple operating status items. S304 uses each operating status item as a matrix element to store the corresponding energy storage control tag and pricing additional parameters, and records the number of triggers and update time of the operating status item.

4. The new energy vehicle charging pile operation and management system according to claim 3, characterized in that, Generate energy storage power control commands and service tier pricing, including: S401, locate the operating status item in the status matrix according to the operating status identifier, and extract the corresponding energy storage control tag and pricing additional parameters; S402: Set energy storage charging and discharging commands according to the energy storage control tag, and correct the energy storage power by the difference between the station-level charging load and the photovoltaic output power to obtain the energy storage power control command; S403: Add the real-time electricity price of the power grid to the preset fixed cost, and divide by the difference between the real-time electricity price and the preset target gross profit margin to obtain the base electricity price. Add the product of the base electricity price, the service level congestion coefficient and the gun utilization rate, and the pricing additional parameters to obtain the corresponding service level price.

5. The new energy vehicle charging pile operation and management system according to claim 4, characterized in that, In S402, if the energy storage charge status label of the operating status item is lower than the preset lower limit, the energy storage control label is set to charging; if the energy storage charge status label is higher than the preset upper limit, the energy storage control label is set to discharging; if the energy storage charge status label is within the range of the preset lower limit and the preset upper limit, the energy storage control label is set to standby.

6. The new energy vehicle charging pile operation and management system according to claim 4, characterized in that, Based on service tier pricing, preset station-level power requirements, and energy storage power control commands, the system executes charging power distribution, transaction metering and settlement, and multi-party revenue sharing operations, including: S501 obtains service tier prices, preset station-level power requirements, energy storage power control commands, maximum power of a single gun and number of active guns, and calculates and issues charging power. S502 reads the actual charging amount at the end of each charging session and calculates the transaction fee based on the corresponding service tier price. S503 splits revenue among site owners, operators, and the platform according to a preset revenue-sharing ratio.

7. The new energy vehicle charging pile operation and management system according to claim 6, characterized in that, In S501, the required grid power is determined based on the difference between the preset station-level power demand and the energy storage power control command. The preset station-level power demand is then evenly distributed to each active charging gun. The maximum power of a single gun is then combined with limit correction to obtain the target power of a single gun, which is then issued as the charging power.

8. The new energy vehicle charging pile operation and management system according to claim 1, characterized in that, The execution control module is also used to collect the temperature rise parameters, contact resistance values ​​and fault event frequency of the charging gun, and weight and superimpose them to obtain the equipment health index. When the equipment health index is lower than the preset health threshold, the equipment maintenance operation is triggered.

9. The new energy vehicle charging pile operation and management system according to claim 1, characterized in that, Within a set rolling time window, the number of triggers for each running state item in the state matrix and the corresponding queuing time are statistically analyzed, and the pricing parameters are adjusted accordingly, including: S601, calculate the average waiting time based on the number of triggers and queuing waiting time of each running status item within the set rolling time window, and compare it with the preset target waiting time to generate a waiting deviation; S602, if the waiting deviation is positive and the number of triggers exceeds the preset trigger threshold, the pricing additional parameter is increased by the preset step size; if the waiting deviation is negative, the pricing additional parameter is decreased by the same step size. S603 writes the updated pricing parameters back to the corresponding running status item and records the update time.

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