Charging station monitoring method and system

Abstract

The invention relates to a method and a system for monitoring a charging station. The method comprises the following steps: acquiring station information and historical data information of the charging station; periodically generating a charging and discharging monitoring strategy of the charging station in the next operation period through a preset strategy optimization model according to the station information of the charging station and the historical data information; pre-updating the platform recommendation strategy to a charging service platform according to the charging and discharging monitoring strategy; regularly sending an instruction according to the charging and discharging monitoring strategy to control the energy storage system to carry out charging and discharging operation according to the charging and discharging strategy process, monitoring the state of the energy storage system in real time, and generating a dynamic correction instruction according to a dynamic regulation and control standard to control the energy storage system to carry out additional charging and discharging operation; monitoring data is collected regularly to form a monitoring report to be sent to a manager. On the basis of meeting the charging requirement of the user, the user is guided to consume the clean energy of each charging station, so that the clean energy of each charging station is reasonably utilized, and the green and environment-friendly effects are achieved.

Description

Technical Field

[0001] The present application relates to the field of charging stations, and in particular to a monitoring method and system for charging stations. Background Art

[0002] As electric vehicles (EV) and hybrid electric vehicles (HEV) become more and more popular, the charging stations that support them are also developing rapidly. An electric vehicle charging station is a place that provides electric energy for electric vehicles. It includes a series of charging equipment, power distribution facilities, and related monitoring and management systems. Its main function is to charge the power battery of electric vehicles safely and efficiently, so that electric vehicles can resume driving ability.

[0003] With the deepening of energy conservation, environmental protection and green themes, the share of electric vehicles has increased year by year, the number of electric vehicles has continued to increase, and charging stations have been continuously built. While these charging stations provide convenient charging services for cars, their energy consumption has also continued to increase. For this reason, many power companies often introduce clean power generation equipment to partially power charging stations when building charging stations, such as solar panels, wind turbines, etc. However, the locations of different charging stations are different, and their passenger flow is also different, which will cause the clean energy of some charging stations to be insufficient to charge users' vehicles, and still require a large amount of municipal electricity resources; and some charging stations have insufficient passenger flow due to various factors, resulting in clean energy overflow. In the prior art, guidance is often provided for users to charge through the Internet, indicating where users can charge. For example, Chinese patent CN106240385B discloses a method and device for monitoring charging stations.

[0004] However, how to effectively monitor the data of charging stations to guide users to make rational use of the clean energy of each charging station is an issue to be resolved. Summary of the invention

[0005] In order to solve the above problems, the present application provides a monitoring method and system for a charging station.

[0006] In a first aspect, the present application provides a monitoring method for a charging station, which adopts the following technical solution:

[0007] A monitoring method for a charging station comprises the following steps:

[0008] Obtain site information and historical data information of charging stations;

[0009] The charging and discharging monitoring strategy for the next operation cycle of the charging station is generated regularly through a preset strategy optimization model according to the site information and historical data information of the charging station; the strategy optimization model is a neural network model obtained by iterative training through multiple charging station historical data information; the charging and discharging monitoring strategy includes a platform recommendation strategy, a dynamic control standard, at least one clean charging period, at least one valley charging period, and charging and discharging strategy process information;

[0010] Pre-update the platform recommendation strategy to the charging service platform according to the charging and discharging monitoring strategy;

[0011] According to the charge and discharge monitoring strategy, regular instructions are issued to control the energy storage system to perform charge and discharge operations according to the charge and discharge strategy process, and the state of the energy storage system is monitored in real time. Dynamic correction instructions are generated according to dynamic control standards to control the energy storage system to perform additional charge and discharge operations;

[0012] Monitoring data is collected regularly to form monitoring reports and sent to management personnel.

[0013] Preferably, the site information includes site geographic information, site clean power generation equipment parameter information, site energy storage system parameter information and site charging pile parameter information; the historical data information includes passenger flow-related historical data, charging and discharging-related historical data and other operating data; the passenger flow-related historical data includes charging vehicle records and user information; the charging and discharging-related historical data includes clean power generation equipment power generation data, energy storage system data and charging pile data; the other operating data includes historical weather data and energy cost data.

[0014] Preferably, the site information includes site geographic information, site clean power generation equipment parameter information, site energy storage system parameter information and site charging pile parameter information; the historical data information includes passenger flow-related historical data, charging and discharging-related historical data and other operating data; the passenger flow-related historical data includes charging vehicle records and user information; the charging and discharging-related historical data includes clean power generation equipment power generation data, energy storage system data and charging pile data; the other operating data includes historical weather data and energy cost data.

[0015] Preferably, the periodic generation of the charging and discharging monitoring strategy for the next operation cycle of the charging station according to the site information and historical data information of the charging station through a preset strategy optimization model specifically includes the following steps:

[0016] Regularly generate multiple optional strategies for the next operation cycle of the charging station according to the site information and historical data information of the charging station through a preset strategy optimization model; the optional strategies include factor prediction information and platform recommendation strategy, dynamic control standards, at least one clean charging period, at least one valley charging period and charging and discharging strategy process information; the factor prediction information includes passenger flow prediction information and weather prediction information;

[0017] Model the charging station and simulate multiple optional strategies to obtain simulation data;

[0018] Calculate the comprehensive score of each optional strategy according to the simulation data through the preset evaluation calculation formula;

[0019] The various optional strategies are compared and ranked based on the comprehensive scores, and the optional strategy with the highest comprehensive score is selected as the charging and discharging monitoring strategy for the next operation cycle of the charging station.

[0020] Preferably, the step of modeling the charging station and simulating multiple optional strategies to obtain simulation data specifically includes the following steps:

[0021] The strategy optimization model builds a simulation model of the charging station based on the site information;

[0022] The strategy optimization model sets parameters for the simulation model of the charging station according to the site information and historical data information of the charging station;

[0023] The strategy optimization model loads multiple optional strategies into the simulation model of the charging station to perform simulation operation of the next operation cycle to obtain simulation data.

[0024] Preferably, the strategy optimization model loads a plurality of optional strategies into the simulation model of the charging station to perform simulation operation of the next operation cycle of the charging station to obtain simulation data, specifically including the following steps:

[0025] C1. The strategy optimization model selects an unsimulated optional strategy from multiple optional strategies and loads it into the simulation model of the charging station;

[0026] C2. The strategy optimization model uses the simulation model of the charging station to perform a normal simulation operation of the next operation cycle of the charging station based on the factor prediction information to obtain normal simulation data;

[0027] C3. The strategy optimization model again performs simulation operation of the next operation cycle of the charging station through the simulation model of the charging station based on the factor prediction information, and during the operation, randomly generates a rated number of strong emergency events based on the site information and historical data information of the charging station and inserts them into the simulation operation process to obtain emergency simulation data; the strong emergency events include severe weather events, extreme passenger flow events, and other pre-set types of events;

[0028] C4, determine whether there are optional strategies that have not been simulated;

[0029] C5, if it exists, jump to step C1;

[0030] C6. If it does not exist, the normal simulation data and the burst simulation data are packaged to generate simulation data.

[0031] Preferably, the evaluation calculation formula is specifically:

[0032] Y = X1 × Z1 + X2 × Z2;

[0033]

[0034]

[0035] Among them, Y is the comprehensive score of the optional strategy, Z1 is the normal simulation operation score, X1 is the normal simulation weight coefficient, Z2 is the extreme simulation operation score, and X2 is the extreme simulation weight coefficient; and X1 and X2 are set by the management personnel, and the sum of X1 and X2 is 1; e is the effective output energy, which refers to the total energy successfully output to the vehicle through the charging pile during the simulated operation cycle; E is the total input energy, which refers to the sum of the energy generated by the clean power generation equipment and the energy purchased from the power grid; u is the number of users who meet the charging needs during the simulated operation cycle, and U is the total number of visiting vehicles during the simulated operation cycle; d is the actual charging time of the charging pile, and D is the operating time of the charging pile in the charging station; c is the charging net income, C is the total investment in the charging station; r is the duration of energy supply interruption of the energy storage system during the operation cycle, R is the total operation time during the operation cycle; a is the number of vehicles whose emergency charging needs are met, A is the total number of vehicles with emergency charging needs; b is the average waiting time of users with severe emergencies, and B is the preset standard waiting time; W1 is the energy utilization efficiency scoring coefficient, W2 is the user satisfaction scoring coefficient, W3 is the equipment utilization scoring coefficient, W4 is the cost-effectiveness scoring coefficient, W5 is the risk resistance scoring coefficient, W6 is the emergency charging satisfaction scoring coefficient, and W7 is the user satisfaction score under extreme circumstances; and W1, W2, W3, W4, W5, W6, and W7 are all preset by management personnel.

[0036] Preferably, the real-time monitoring of the state of the energy storage system and the generation of dynamic correction instructions according to the dynamic control standard to control the energy storage system to perform additional charging and discharging operations specifically include:

[0037] Monitor the status of the energy storage system in real time. When the energy storage system power is lower than the preset low power threshold in the dynamic control standard, determine whether it is in the clean charging period.

[0038] If not, determine whether it is in the valley charging period;

[0039] If it is, a dynamic correction instruction is generated to enable the valley mains to charge the energy storage system to the preset mains charging threshold in the state control standard or the valley charging period ends;

[0040] If not, verify whether the power generation of the clean power generation equipment meets the minimum charging requirements of the energy storage system;

[0041] If the conditions are met, a dynamic correction instruction is generated to control the clean power generation equipment to charge the energy storage system until the storage capacity reaches the safe power threshold preset in the dynamic control standard;

[0042] If not, the energy storage system charging power supply will be cut off. Based on the real-time load situation of the charging station and the interaction agreement with the power grid, it is determined whether a small amount of electricity is allowed to be purchased from the power grid at a non-peak electricity price for emergency charging of the energy storage system, so as to ensure the basic operating functions of the energy storage system and the emergency power supply capacity of the charging station, and record the emergency charging event at the same time.

[0043] Preferably, the real-time monitoring of the energy storage system status also includes: if the energy storage system storage capacity is higher than a preset high capacity threshold in the dynamic control standard, a dynamic correction instruction is generated according to the platform recommendation strategy, and temporary discount information is updated on the charging service platform.

[0044] Preferably, the timed collection of monitoring data to form a monitoring report and send it to the management personnel specifically includes: regularly collecting monitoring data and importing it into a preset monitoring report template, and displaying the historical power generation data, passenger flow data, and clean energy utilization rate change trends of each charging station in the monitoring report with a line chart or a bar chart, with the time span being a unit operating cycle, and sending the monitoring report to the management personnel.

[0045] In a second aspect, the present application provides a monitoring system for a charging station, which adopts the following technical solution:

[0046] A monitoring system for a charging station, comprising:

[0047] An information acquisition module is used to obtain site information and historical data information of the charging station;

[0048] A strategy customization module is used to regularly generate a charging and discharging monitoring strategy for the next operation cycle of a charging station according to the site information and historical data information of the charging station through a preset strategy optimization model; the strategy optimization model is a neural network model obtained by iterative training through historical data information of multiple charging stations; the charging and discharging monitoring strategy includes a platform recommendation strategy, a dynamic control standard, at least one clean charging period, at least one valley charging period, and charging and discharging strategy process information;

[0049] A user guidance module, used to pre-update the platform recommendation strategy to the charging service platform according to the charging and discharging monitoring strategy;

[0050] The monitoring and control module is used to issue instructions regularly according to the charge and discharge monitoring strategy to control the energy storage system to perform charge and discharge operations according to the charge and discharge strategy process, and to monitor the state of the energy storage system in real time and generate dynamic correction instructions according to the dynamic control standard to control the energy storage system to perform additional charge and discharge operations;

[0051] The report summary module is used to collect monitoring data at regular intervals and generate monitoring reports to be sent to management personnel.

[0052] In summary, the present application includes at least one of the following beneficial technical effects:

[0053] 1. By acquiring multi-dimensional site information and rich historical data information, based on the actual situation of the charging station, starting from the equipment, geography, passenger flow, clean energy use, charging and discharging, energy cost and operation of the charging station, taking into full consideration various actual factors in the operation of the charging station, the data relationship is mined through the strategy optimization model, combined with the weather forecast information of the geographical location, the passenger flow and charging and discharging conditions of the charging station in the next cycle are predicted, and then the charging and discharging monitoring strategy for the next operation cycle of the charging station is intelligently and accurately generated, which has strong universality;

[0054] 2. By optimizing the recommended information of charging stations, on the basis of meeting the charging needs of users, we guide users to consume the clean energy of each charging station, so that the clean energy of each charging station can be reasonably used, which is green and environmentally friendly while also effectively improving the profitability and utilization rate of charging stations;

[0055] 3. Intelligent control and monitoring of charging stations can be achieved based on the charging and discharging monitoring strategy, which is conducive to the rational scheduling and use of the energy storage system. In conjunction with the platform recommendation strategy, the utilization rate of green energy can be increased as much as possible, energy overflow loss can be avoided, energy costs can be reduced, and the cost-effectiveness of charging stations can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 is a method flow chart of a monitoring method for a charging station in an embodiment of the present application;

[0057] Figure 2 is a flow chart of a method for generating a charge and discharge monitoring strategy in an embodiment of the present application;

[0058] Figure 3 is a flow chart of a method for simulating an optional strategy in an embodiment of the present application;

[0059] Figure 4 is a flow chart of a method for loading an optional strategy into a simulation model of a charging station to perform simulation of the next operation cycle of the charging station in an embodiment of the present application;

[0060] Figure 5 is a flow chart of a method for generating a dynamic correction instruction to control an energy storage system to perform additional charging and discharging operations in an embodiment of the present application;

[0061] Figure 6 It is a system block diagram of a monitoring system for a charging station in an embodiment of the present application.

[0062] Explanation of the accompanying drawings: 1. Information acquisition module; 2. Policy customization module; 3. User guidance module; 4. Monitoring and control module; 5. Report summary module. DETAILED DESCRIPTION

[0063] The following is combined with Figure 1-6 This application is described in further detail.

[0064] The present application embodiment discloses a monitoring method for a charging station. Figure 1 , a monitoring method for a charging station comprises the following steps:

[0065] S1. Obtain information: Obtain site information and historical data information of the charging station; the site information includes site geographic information, site clean power generation equipment parameter information, site energy storage system parameter information and site charging pile parameter information; the historical data information includes passenger flow related historical data, charging and discharging related historical data and other operational data; the passenger flow related historical data includes charging vehicle records and user information; the charging and discharging related historical data includes clean power generation equipment power generation data, energy storage system data and charging pile data; the other operational data includes historical weather data and energy cost data;

[0066] S2, generation process: regularly generate the charging and discharging monitoring strategy of the next operation cycle of the charging station according to the site information and historical data information of the charging station through a preset strategy optimization model; the strategy optimization model is a neural network model obtained by iterative training through multiple charging station historical data information; the charging and discharging monitoring strategy includes platform recommendation strategy, dynamic control standard, at least one clean charging period, at least one valley charging period and charging and discharging strategy process information;

[0067] S3, recommendation update: pre-update the platform recommendation strategy to the charging service platform according to the charge and discharge monitoring strategy; the platform recommendation strategy includes preferential strength information, preferential time period information, recommended resource usage requirements (APP open advertisements, advertisement pop-ups, homepage advertisement columns, classified advertisement columns, etc.), temporary preferential information and other recommendation strategy information;

[0068] S4, monitoring and control: according to the charge and discharge monitoring strategy, regular instructions are issued to control the energy storage system to perform charge and discharge operations according to the charge and discharge strategy process, and the state of the energy storage system is monitored in real time, and dynamic correction instructions are generated according to the dynamic control standard to control the energy storage system to perform additional charge and discharge operations;

[0069] S5. Report generation: Regularly collect monitoring data to generate monitoring reports and send them to management personnel. Based on the existing passenger flow prediction model, charging and discharging prediction model, and charging station promotion plan model, a neural network model is used and iterative training is performed through historical data of charging stations to obtain a strategy optimization model. By obtaining multi-dimensional site information and rich historical data information, according to the actual situation of the charging station, starting from the equipment, geography, passenger flow, clean energy use, charging and discharging, energy cost and operation of the charging station, the various actual factors in the operation of the charging station are fully considered. Through the strategy optimization model, the data relationship is mined, and the weather forecast information of the geographical location is combined to predict the passenger flow and charging and discharging conditions of the charging station in the next cycle, and then the charging and discharging monitoring strategy for the next operation cycle of the charging station is intelligently and accurately generated, which has strong universality; and then the recommended information of the charging station is optimized. On the basis of meeting the charging needs of users, the user is guided to consume the clean energy of each charging station, so that the clean energy of each charging station is reasonably used, which is green and environmentally friendly while effectively improving the profitability and utilization rate of the charging station; according to the charging and discharging monitoring strategy, the intelligent control and monitoring of the charging station is realized, which is conducive to the reasonable scheduling and use of the energy storage system, and cooperates with the platform recommendation strategy to maximize the utilization rate of green energy, avoid energy overflow loss, reduce energy costs, and improve the cost-effectiveness of the charging station.

[0070] Reference Figure 2 The periodic generation of the charging and discharging monitoring strategy for the next operation cycle of the charging station according to the site information and historical data information of the charging station through the preset strategy optimization model specifically includes the following steps:

[0071] A1. Generate optional strategies: Regularly generate multiple optional strategies for the next operation cycle of the charging station based on the site information and historical data information of the charging station through a preset strategy optimization model; the optional strategies include factor prediction information and platform recommendation strategies, dynamic control standards, at least one clean charging period, at least one valley charging period, and charging and discharging strategy process information; the factor prediction information includes passenger flow prediction information and weather prediction information;

[0072] A2. Simulation operation: Model the charging station and simulate multiple optional strategies to obtain simulation data;

[0073] A3. Calculate the comprehensive score: Calculate the comprehensive score of each optional strategy according to the simulation data using the preset evaluation calculation formula;

[0074] A4. Select the charging and discharging monitoring strategy: compare and rank the optional strategies based on the comprehensive scores, and select the optional strategy with the highest comprehensive score as the charging and discharging monitoring strategy for the next operation cycle of the charging station. Through the above steps, multiple optional strategies are intelligently decided by the strategy optimization model according to the actual situation of the charging station, and then the charging station is modeled and multiple optional strategies are simulated. The power generation, energy storage, charging and user behavior of the charging station under different strategies are simulated to obtain the execution of different strategies, and the performance of the strategies in the face of risks and uncertainties is understood in advance. Then, multiple optional strategies are evaluated from multiple different dimensions through evaluation calculation formulas, and a more robust optional strategy is selected as the charging and discharging monitoring strategy for the next operation cycle of the charging station, which helps to improve the utilization rate of green energy, avoid energy overflow loss, reduce energy costs, and improve the cost-effectiveness of charging stations.

[0075] Reference Figure 3 The step of modeling the charging station and simulating multiple optional strategies to obtain simulation data specifically includes the following steps:

[0076] B1. Model building: The strategy optimization model builds a simulation model of the charging station based on the site information;

[0077] B2. Parameter setting: The strategy optimization model sets parameters for the simulation model of the charging station according to the site information and historical data information of the charging station;

[0078] B3. Simulation: The strategy optimization model loads multiple optional strategies into the simulation model of the charging station to perform simulation operation of the next operation cycle to obtain simulation data.

[0079] Reference Figure 4 The strategy optimization model loads multiple optional strategies into the simulation model of the charging station to perform simulation operation of the next operation cycle of the charging station to obtain simulation data, which specifically includes the following steps:

[0080] C1. Strategy loading: The strategy optimization model selects an unsimulated optional strategy from multiple optional strategies and loads it into the simulation model of the charging station;

[0081] C2. Normal simulation operation: The strategy optimization model uses the simulation model of the charging station to perform normal simulation operation of the next operation cycle of the charging station based on the factor prediction information to obtain normal simulation data;

[0082] C3. Emergency simulation operation: The strategy optimization model again performs a simulation operation of the next operation cycle of the charging station through the simulation model of the charging station based on the factor prediction information, and during the operation, a rated number of strong emergency events are randomly generated based on the site information and historical data information of the charging station and inserted into the simulation operation process to obtain emergency simulation data; the strong emergency events include severe weather events, extreme passenger flow events, and other pre-set types of events;

[0083] C4, determine whether there are optional strategies that have not been simulated;

[0084] C5, if it exists, jump to step C1;

[0085] C6. Package and generate simulation data: If it does not exist, package the normal simulation data and the emergency simulation data to generate simulation data. When performing simulation, the normal simulation and the emergency simulation are run in parallel. The normal simulation can reflect the effects of different strategies of the charging station under the predicted passenger flow and weather conditions, while the emergency simulation can simulate the response capabilities of the strategy under emergency conditions such as bad weather and extreme passenger flow by randomly inserting strong emergencies. This comprehensive simulation method enables the generated simulation data to more realistically reflect the performance of the strategy in various possible situations, providing a more reliable basis for subsequent comprehensive evaluation.

[0086] The above evaluation calculation formula is as follows:

[0087] Y = X1 × Z1 + X2 × Z2;

[0088]

[0089]

[0090] Among them, Y is the comprehensive score of the optional strategy, Z1 is the normal simulation operation score, X1 is the normal simulation weight coefficient, Z2 is the extreme simulation operation score, and X2 is the extreme simulation weight coefficient; and X1 and X2 are set by the management personnel, and the sum of X1 and X2 is 1; e is the effective output energy, which refers to the total energy successfully output to the vehicle through the charging pile during the simulated operation cycle; E is the total input energy, which refers to the sum of the energy generated by the clean power generation equipment and the energy purchased from the power grid; u is the number of users who meet the charging needs during the simulated operation cycle, and U is the total number of visiting vehicles during the simulated operation cycle; d is the actual charging time of the charging pile, and D is the operating time of the charging pile in the charging station; c is the charging net income, C is the total investment of the charging station; r is the duration of energy supply interruption of the energy storage system during the operation cycle, R is the total operation time during the operation cycle; a is the number of vehicles whose emergency charging needs are met, A is the total number of vehicles with emergency charging needs; b is the average waiting time of users with strong emergencies, and B is the preset standard waiting time; W1 is the energy utilization efficiency scoring coefficient, W2 is the user satisfaction scoring coefficient, W3 is the equipment utilization scoring coefficient, W4 is the cost-effectiveness scoring coefficient, W5 is the risk resistance scoring coefficient, W6 is the emergency charging satisfaction scoring coefficient, and W7 is the user satisfaction score under extreme conditions; and W1, W2, W3, W4, W5, W6, and W7 are all preset by the management personnel. By using normal simulation data and emergency simulation data together to calculate the comprehensive score, the evaluation of the optional strategies is more comprehensive and reliable. In actual operation, charging stations will face both conventional operation scenarios and emergencies. Comprehensively considering the performance of strategies in these two situations can avoid the problem of only focusing on normal operations and ignoring risk response capabilities, thereby selecting a more robust charging and discharging monitoring strategy.

[0091] At the same time, in the process of strategy generation and simulation, the uncertainty factors such as passenger flow forecast information and weather forecast information are fully considered, and strong emergencies are inserted into the simulation to test and optimize the risk response capabilities of the strategy. This forward-looking strategy design helps charging stations better respond to various emergencies in actual operation, reduce operational confusion and losses caused by emergencies, and improve the stability and reliability of charging stations.

[0092] Reference Figure 5 The real-time monitoring of the energy storage system status and the generation of dynamic correction instructions according to the dynamic control standard to control the energy storage system to perform additional charging and discharging operations specifically include:

[0093] D1. Monitor the energy storage system to determine whether it is in the clean charging period: Monitor the status of the energy storage system in real time. When the energy storage system power is lower than the preset low power threshold in the dynamic control standard, determine whether it is in the clean charging period.

[0094] D2. If not, determine whether it is in the valley charging period;

[0095] D3. Charge the energy storage system: If it is in the state, a dynamic correction instruction is generated to enable the valley mains to charge the energy storage system until the mains charging threshold preset in the state control standard is reached or the valley charging period ends;

[0096] D4. If not, verify whether the power generation of the clean power generation equipment meets the minimum charging requirement of the energy storage system;

[0097] D5. Control the clean power generation equipment to charge the energy storage system: If the conditions are met, a dynamic correction instruction is generated to control the clean power generation equipment to charge the energy storage system until the storage capacity reaches the safety power threshold preset in the dynamic control standard;

[0098] D6. Emergency charging of the energy storage system from the power grid: If not met, the energy storage system charging supply is cut off. According to the real-time load of the charging station and the interaction agreement with the power grid, it is determined whether to allow a small amount of electricity to be purchased from the power grid at a non-valley price for emergency charging of the energy storage system to ensure the basic operating functions of the energy storage system and the emergency power supply capacity of the charging station, and record the emergency charging event at the same time. By real-time monitoring of the energy storage system status, changes in the amount of stored electricity can be discovered in a timely manner, so that a rapid response can be made according to the dynamic control standards, and charging can be arranged according to the characteristics of different time periods (clean charging period, valley charging period), so as to maximize the use of clean energy and valley electricity price resources. It not only reduces the dependence on traditional city electricity, but also improves the utilization rate of clean energy. It can flexibly adjust the charging and discharging operations of the energy storage system so that the operation of the energy storage system can better adapt to changes in the actual operating environment.

[0099] In addition, real-time monitoring of the energy storage system status also includes: if the energy storage system's storage capacity is higher than the preset high power threshold in the dynamic control standard, a dynamic correction instruction is generated according to the platform's recommended strategy to update temporary discount information on the charging service platform. When the energy storage system has a high storage capacity, in order to avoid affecting the subsequent collection of clean energy, a dynamic correction instruction is generated according to the platform's recommended strategy to update temporary discount information, attract users to charge and consume, avoid idle waste of clean energy, and realize flexible adjustment of pricing strategies according to the real-time energy storage system status. On the basis of improving the utilization rate of clean energy, it is mutually beneficial with users and improves user stickiness and satisfaction.

[0100] The regular collection of monitoring data to form a monitoring report and send it to the management personnel specifically includes: regularly collecting monitoring data and importing it into a preset monitoring report template, and displaying the historical power generation data, passenger flow data, and clean energy utilization rate change trends of each charging station in the monitoring report with a line chart or a bar chart, with the time span being a unit operating cycle, and sending the monitoring report to the management personnel. By obtaining multi-dimensional site information and rich historical data information, according to the actual situation of the charging station, starting from the equipment, geography, passenger flow, clean energy use, charging and discharging, energy cost and operation of the charging station, the various actual factors in the operation of the charging station are fully considered. Through the strategy optimization model, the data relationship is mined, and the weather forecast information of the geographical location is combined to predict the passenger flow and charging and discharging conditions of the charging station in the next cycle, and then the charging and discharging monitoring strategy for the next operation cycle of the charging station is intelligently and accurately generated, which has strong universality; and then the recommended information of the charging station is optimized. On the basis of meeting the charging needs of users, the user is guided to consume the clean energy of each charging station, so that the clean energy of each charging station is reasonably used, which is green and environmentally friendly while effectively improving the profitability and utilization rate of the charging station; according to the charging and discharging monitoring strategy, the intelligent control and monitoring of the charging station is realized, which is conducive to the reasonable scheduling and use of the energy storage system, and cooperates with the platform recommendation strategy to maximize the utilization rate of green energy, avoid energy overflow loss, reduce energy costs, and improve the cost-effectiveness of the charging station.

[0101] The present application also discloses a monitoring system for a charging station. Figure 6 , a monitoring system for a charging station, comprising:

[0102] Information acquisition module 1, used to obtain site information and historical data information of the charging station;

[0103] Strategy customization module 2, used to regularly generate a charging and discharging monitoring strategy for the next operation cycle of the charging station according to the site information and historical data information of the charging station through a preset strategy optimization model; the strategy optimization model is a neural network model obtained by iterative training through historical data information of multiple charging stations; the charging and discharging monitoring strategy includes a platform recommendation strategy, a dynamic control standard, at least one clean charging period, at least one valley charging period, and charging and discharging strategy process information;

[0104] The user guidance module 3 is used to pre-update the platform recommendation strategy to the charging service platform according to the charging and discharging monitoring strategy;

[0105] Monitoring and control module 4, used to issue instructions regularly according to the charge and discharge monitoring strategy to control the energy storage system to perform charge and discharge operations according to the charge and discharge strategy process, and to monitor the state of the energy storage system in real time and generate dynamic correction instructions according to the dynamic control standard to control the energy storage system to perform additional charge and discharge operations;

[0106] The report summary module 5 is used to collect monitoring data at regular intervals to form monitoring reports and send them to management personnel.

[0107] The embodiment of the present application also discloses a computer-readable storage medium, which stores a computer program that can be loaded by a processor and executed as in the above method. The computer-readable storage medium includes, for example: a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

[0108] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the scope of protection of the invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on these embodiments, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in this field can still combine, add, delete or make other adjustments to the features in the various embodiments of the present invention according to the circumstances without conflict, without making creative work, so as to obtain different other technical solutions that do not deviate from the concept of the present invention in essence, and these technical solutions also belong to the scope of protection of the present invention.

Claims

1. A monitoring method for a charging station, characterized in that: The following steps are involved: Obtain site information and historical data information of charging stations; The charging and discharging monitoring strategy for the next operation cycle of the charging station is generated regularly through a preset strategy optimization model according to the site information and historical data information of the charging station; the strategy optimization model is a neural network model obtained by iterative training through historical data information of multiple charging stations; The charge and discharge monitoring strategy includes a platform recommendation strategy, a dynamic control standard, at least one clean charging period, at least one valley charging period, and charge and discharge strategy process information; Pre-update the platform recommendation strategy to the charging service platform according to the charging and discharging monitoring strategy; According to the charge and discharge monitoring strategy, regular instructions are issued to control the energy storage system to perform charge and discharge operations according to the charge and discharge strategy process, and the state of the energy storage system is monitored in real time. Dynamic correction instructions are generated according to dynamic control standards to control the energy storage system to perform additional charge and discharge operations; Monitoring data is collected regularly to form monitoring reports and sent to management personnel.

2. A monitoring method for a charging station according to claim 1, characterized in that: The site information includes site geographic information, site clean power generation equipment parameter information, site energy storage system parameter information and site charging pile parameter information; the historical data information includes passenger flow-related historical data, charging and discharging-related historical data and other operating data; the passenger flow-related historical data includes charging vehicle records and user information; the charging and discharging-related historical data includes clean power generation equipment power generation data, energy storage system data and charging pile data; the other operating data includes historical weather data and energy cost data.

3. A monitoring method for a charging station according to claim 2, characterized in that: The method of periodically generating a charging and discharging monitoring strategy for the next operation cycle of the charging station according to the site information and historical data information of the charging station through a preset strategy optimization model specifically includes the following steps: Regularly generate multiple optional strategies for the next operation cycle of the charging station according to the site information and historical data information of the charging station through a preset strategy optimization model; the optional strategies include factor prediction information and platform recommendation strategy, dynamic control standards, at least one clean charging period, at least one valley charging period and charging and discharging strategy process information; the factor prediction information includes passenger flow prediction information and weather prediction information; Model the charging station and simulate multiple optional strategies to obtain simulation data; Calculate the comprehensive score of each optional strategy according to the simulation data through the preset evaluation calculation formula; The various optional strategies are compared and ranked based on the comprehensive scores, and the optional strategy with the highest comprehensive score is selected as the charging and discharging monitoring strategy for the next operation cycle of the charging station.

4. A monitoring method for a charging station according to claim 3, characterized in that: The modeling of the charging station and the simulation of multiple optional strategies to obtain simulation data specifically include the following steps: The strategy optimization model builds a simulation model of the charging station based on the site information; The strategy optimization model sets parameters for the simulation model of the charging station according to the site information and historical data information of the charging station; The strategy optimization model loads multiple optional strategies into the simulation model of the charging station to perform simulation operation of the next operation cycle to obtain simulation data.

5. A monitoring method for a charging station according to claim 4, characterized in that: The strategy optimization model loads multiple optional strategies into the simulation model of the charging station to perform simulation operation of the next operation cycle of the charging station to obtain simulation data, which specifically includes the following steps: C1. The strategy optimization model selects an unsimulated optional strategy from multiple optional strategies and loads it into the simulation model of the charging station; C2. The strategy optimization model uses the simulation model of the charging station to perform a normal simulation operation of the next operation cycle of the charging station based on the factor prediction information to obtain normal simulation data; C3. The strategy optimization model again performs simulation operation of the next operation cycle of the charging station through the simulation model of the charging station based on the factor prediction information, and during the operation, randomly generates a rated number of strong emergency events based on the site information and historical data information of the charging station and inserts them into the simulation operation process to obtain emergency simulation data; the strong emergency events include severe weather events, extreme passenger flow events, and other pre-set types of events; C4, determine whether there are optional strategies that have not been simulated; C5, if it exists, jump to step C1; C6. If it does not exist, the normal simulation data and the burst simulation data are packaged to generate simulation data.

6. A monitoring method for a charging station according to claim 5, characterized in that: The evaluation calculation formula is specifically: Y = X1 × Z1 + X2 × Z2; Among them, Y is the comprehensive score of the optional strategy, Z1 is the normal simulation operation score, X1 is the normal simulation weight coefficient, Z2 is the extreme simulation operation score, and X2 is the extreme simulation weight coefficient; and X1 and X2 are set by the management personnel, and the sum of X1 and X2 is 1; e is the effective output energy, which refers to the total energy successfully output to the vehicle through the charging pile during the simulated operation cycle; E is the total input energy, which refers to the sum of the energy generated by the clean power generation equipment and the energy purchased from the power grid; u is the number of users who meet the charging needs during the simulated operation cycle, and U is the total number of visiting vehicles during the simulated operation cycle; d is the actual charging time of the charging pile, and D is the operating time of the charging pile in the charging station; c is the charging net income, C is the total investment in the charging station; r is the duration of energy supply interruption of the energy storage system during the operation cycle, R is the total operation time during the operation cycle; a is the number of vehicles whose emergency charging needs are met, A is the total number of vehicles with emergency charging needs; b is the average waiting time of users with severe emergencies, and B is the preset standard waiting time; W1 is the energy utilization efficiency scoring coefficient, W2 is the user satisfaction scoring coefficient, W3 is the equipment utilization scoring coefficient, W4 is the cost-effectiveness scoring coefficient, W5 is the risk resistance scoring coefficient, W6 is the emergency charging satisfaction scoring coefficient, and W7 is the user satisfaction score under extreme circumstances; and W1, W2, W3, W4, W5, W6, and W7 are all preset by management personnel.

7. A monitoring method for a charging station according to claim 2, characterized in that: The real-time monitoring of the state of the energy storage system and the generation of dynamic correction instructions according to the dynamic control standard to control the energy storage system to perform additional charging and discharging operations specifically include: Monitor the status of the energy storage system in real time. When the energy storage system power is lower than the preset low power threshold in the dynamic control standard, determine whether it is in the clean charging period. If not, determine whether it is in the valley charging period; If it is, a dynamic correction instruction is generated to enable the valley mains to charge the energy storage system to the preset mains charging threshold in the state control standard or the valley charging period ends; If not, verify whether the power generation of the clean power generation equipment meets the minimum charging requirements of the energy storage system; If the conditions are met, a dynamic correction instruction is generated to control the clean power generation equipment to charge the energy storage system until the storage capacity reaches the safe power threshold preset in the dynamic control standard; If not, the energy storage system charging power supply will be cut off. Based on the real-time load situation of the charging station and the interaction agreement with the power grid, it is determined whether a small amount of electricity is allowed to be purchased from the power grid at a non-peak electricity price for emergency charging of the energy storage system, so as to ensure the basic operating functions of the energy storage system and the emergency power supply capacity of the charging station, and record the emergency charging event at the same time.

8. A monitoring method for a charging station according to claim 7, characterized in that: The real-time monitoring of the energy storage system status also includes: if the energy storage system storage capacity is higher than the preset high capacity threshold in the dynamic control standard, a dynamic correction instruction is generated according to the platform recommendation strategy, and temporary discount information is updated on the charging service platform.

9. A monitoring method for a charging station according to claim 2, characterized in that: The timed collection of monitoring data to form a monitoring report and send it to the management personnel specifically includes: regularly collecting monitoring data and importing it into a preset monitoring report template, and displaying the historical power generation data, passenger flow data, and clean energy utilization rate change trends of each charging station in the monitoring report with a line chart or a bar chart, with the time span being a unit operating cycle, and sending the monitoring report to the management personnel.

10. A monitoring system for a charging station, characterized in that: include: An information acquisition module (1) is used to acquire site information and historical data information of a charging station; A strategy customization module (2) is used to regularly generate a charging and discharging monitoring strategy for the next operation cycle of the charging station based on the site information and historical data information of the charging station through a preset strategy optimization model; the strategy optimization model is a neural network model obtained by iterative training through historical data information of multiple charging stations; The charge and discharge monitoring strategy includes a platform recommendation strategy, a dynamic control standard, at least one clean charging period, at least one valley charging period, and charge and discharge strategy process information; A user guidance module (3), used for pre-updating the platform recommendation strategy to the charging service platform according to the charging and discharging monitoring strategy; A monitoring control module (4) is used to periodically issue instructions according to the charge and discharge monitoring strategy to control the energy storage system to perform charge and discharge operations according to the charge and discharge strategy process, and to monitor the state of the energy storage system in real time and generate dynamic correction instructions according to the dynamic control standard to control the energy storage system to perform additional charge and discharge operations; The report summary module (5) is used to collect monitoring data at regular intervals and generate monitoring reports to be sent to management personnel.

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