An intelligent black box for energy storage power station and its application method

Abstract

The present invention relates to the field of data analysis, and in particular to an intelligent black box of an energy storage power station and an application method thereof, the method comprising: determining a usage similarity state according to the power usage speed of each charging vehicle corresponding to an effective reference period; determining a data analysis target according to the usage similarity state; determining an analysis target according to the route loss rate in the detection of the route loss rate of differentially charged vehicles; determining to adjust an impact value of an impact route or an impact value of task busyness according to a difference in the proportion of impact routes; determining to analyze the number of starts and stops or to adjust an impact value of load weight according to a difference in load weight; calculating an environmental impact coefficient and determining an impact value of the environmental impact coefficient according to the environmental impact coefficient; the present invention obtains different impact values ​​of charging demand through different data processing, thereby improving the prediction efficiency of the user's power demand on the power consumption side of the energy storage power station.

Description

Technical Field

[0001] The present invention relates to the field of data analysis, and in particular to an intelligent black box of an energy storage power station and an application method thereof. Background Art

[0002] AGV is widely used in smart industrial parks, such as material handling, automatic warehousing and outbound transportation of goods, and intelligent distribution. However, due to the different effects of AGV's moving path, task allocation, and environmental impact on the AGV's power consumption rate, the AGV's charging demand is difficult to predict, and the charging efficiency of the energy storage power station cannot be effectively guaranteed. Therefore, how to classify, analyze, or store AGV's power consumption information to provide a prediction strategy for subsequent AGV charging needs is a problem that technicians in this field need to solve urgently.

[0003] Chinese Patent Publication No. CN110350609A discloses a charging management method and system, device and storage medium for AGV, and the charging management method includes the following steps: obtaining the remaining power of each AGV; classifying the multiple AGVs into different sets according to the remaining power and the current state of the AGV; performing different scheduling on the AGVs in the different sets to charge the target AGV. In addition, Chinese Patent Publication No. CN117318053A discloses an energy demand prediction method and system for energy storage power stations, and the method includes: obtaining key energy data in the energy storage power station; wherein the key energy data at least includes voltage data, current data, temperature medium data and energy storage capacity data; constructing a first energy state parameter distribution map of the energy storage power station through the obtained voltage data and current data, and constructing a second energy state parameter distribution map of the energy storage power station according to the temperature medium data and the energy storage capacity data; extracting multiple first key indicators from the first energy state parameter distribution map based on a preset first image analysis function, and extracting multiple second key indicators from the second energy state parameter distribution map based on a preset second image analysis function. It can be seen that although the above technical solutions take into account the different power consumption speeds of AGVs to adjust the charging management method, and process, store and analyze the massive data information generated by the energy storage power station to improve the data processing efficiency, the energy storage power station applied to the smart park, in the power supply for AGV, due to the irregularity of the AGV's power consumption status, it is impossible to predict the charging demand based on the AGV's power consumption data, resulting in poor power supply efficiency of the energy storage power station. Summary of the invention

[0004] To this end, the present invention provides an intelligent black box for an energy storage power station and an application method thereof, so as to overcome the problem in the prior art that the energy storage power station cannot predict the charging demand based on the AGV power consumption data, resulting in poor energy supply efficiency of the energy storage power station.

[0005] To achieve the above object, the present invention provides an intelligent black box for an energy storage power station, comprising:

[0006] A data collection unit, used to collect demand information;

[0007] A data analysis unit connected to the data acquisition unit, configured to determine a cycle category of a target power consumption cycle according to a power consumption reference value, and to determine a similar usage state according to a power consumption speed of each charging vehicle corresponding to a valid reference cycle to determine a data analysis target;

[0008] A retrospective analysis unit connected to the data acquisition unit and the data analysis unit, for determining an analysis target according to the route loss rate of differentially charged vehicles, and determining a corresponding impact value according to a difference in the proportion of impacted routes, a difference in load weight, or a difference in the number of starts and stops;

[0009] A sensing and analyzing unit, connected to the data acquisition unit and the data analyzing unit, for calculating an environmental impact coefficient and determining an impact value of the environmental impact coefficient according to the environmental impact coefficient;

[0010] A storage unit is connected to the data acquisition unit and the data analysis unit, and is used to store demand information corresponding to a target power consumption cycle.

[0011] Further, the data analysis unit detects the power consumption reference value of the target power consumption cycle and determines the cycle category of the target power consumption cycle according to the power consumption reference value, including a valid reference cycle and an invalid reference cycle;

[0012] The data analysis unit performs data analysis on the effective reference cycle.

[0013] Furthermore, the data analysis unit performs data analysis on the effective reference cycle, detects the usage similarity status of the charging vehicles in the effective reference cycle, and determines the data analysis target according to the usage similarity status, including the route loss rate or the environmental impact coefficient.

[0014] Furthermore, the data analysis unit determines the similar usage status according to the power usage speed of each charging vehicle corresponding to the effective reference cycle, including that the power usage speed of any charging vehicle is less than the preset power usage speed or there is a charging vehicle whose power usage speed is greater than the preset power usage speed.

[0015] Further, the retrospective analysis unit detects the route loss rate of the differentially charged vehicles and determines the analysis target according to the route loss rate;

[0016] If the route loss rate is within the first preset route loss rate range, the tracing analysis unit determines to analyze the difference in the proportion of the affected routes;

[0017] If the route loss rate is within a second preset route loss rate range, the retrospective analysis unit determines to perform analysis on the movement parameters.

[0018] Furthermore, the tracing analysis unit analyzes the difference in the proportion of the influencing routes to detect the difference in the proportion of the influencing routes;

[0019] If the difference in the proportion of the affected routes is within the first preset difference range, the influence value of the affected routes is increased;

[0020] If the difference of the impact route proportion is within the second preset difference range, the impact value of the task busyness is increased and adjusted.

[0021] Furthermore, the retrospective analysis unit analyzes the movement parameters, detects the load weight difference of the differentially charged vehicles, and determines to analyze the number of starts and stops or to increase the impact value of the load weight according to the load weight difference.

[0022] Furthermore, the retrospective analysis unit analyzes the start and stop times of the differentially charged vehicles, detects the difference in the start and stop times of the differentially charged vehicles, and determines an increase adjustment for the impact value of the start and stop times according to the difference in the start and stop times or sends a quality inspection reminder message for the differentially charged vehicles to the user.

[0023] Further, the sensing and analyzing unit calculates the environmental impact coefficient and determines the impact value of the environmental impact coefficient according to the environmental impact coefficient;

[0024] If the environmental impact coefficient is greater than the preset environmental impact coefficient, the sensor analysis unit determines that the impact value of the environmental impact coefficient and the difference between the environmental impact coefficients are in a positive correlation;

[0025] If the environmental impact coefficient is less than or equal to the preset environmental impact coefficient, the sensing and analyzing unit determines to send a quality inspection reminder message of the differentially charged vehicle to the user.

[0026] The present invention provides an application method for the intelligent black box of the energy storage power station, comprising:

[0027] Detecting a power consumption reference value of a target power consumption cycle and determining a cycle category of the target power consumption cycle according to the power consumption reference value, including a valid reference cycle and an invalid reference cycle;

[0028] Determine the usage similarity state according to the power usage speed of each charging vehicle corresponding to the effective reference period;

[0029] Determine data analysis objectives based on similar usage status, including route loss rate or environmental impact factor;

[0030] In the detection of route loss rate of differentially charged vehicles, the analysis target is determined according to the route loss rate, including the difference degree or movement parameters affecting the route proportion;

[0031] Detect the difference in the proportion of influencing routes;

[0032] According to the difference in the proportion of the influencing routes, the influence value of the influencing routes is adjusted or the influence value of the task busyness is adjusted;

[0033] Analyze the movement parameters and determine the start and stop times or adjust the impact value of the load weight according to the load weight difference;

[0034] In the analysis of the environmental impact coefficient, the environmental impact coefficient is calculated and the impact value of the environmental impact coefficient is determined based on the environmental impact coefficient.

[0035] Compared with the prior art, the beneficial effect of the present invention lies in that, in the technical solution of the present invention, the power consumption reference value is periodically detected, the power consumption reference value is used to reflect the power demand of the charging vehicle, the target power consumption cycle corresponding to the power consumption reference value with abnormal power demand is analyzed, different analysis methods are selected for charging vehicles in different states, the influence of different influencing factors on the demand of the charging vehicle is analyzed, and the user is assisted in predicting the charging strategy according to the determined influence value. The present invention selects different processing methods for different collected demand information, improves data processing efficiency, and improves the effectiveness of the charging strategy of the energy storage power station.

[0036] Furthermore, the data analysis unit in the present invention determines the usage similarity state according to the power usage speed of each charging vehicle corresponding to the effective reference period, and reflects the degree of difference in power usage between the charging vehicles by using the similarity state, thereby selecting different data analysis targets, so that the data analysis targets are more in line with the actual working scenarios, thereby improving the data processing accuracy.

[0037] Furthermore, the retrospective analysis unit in the present invention detects the route loss rate of differentially charged vehicles, and determines the analysis target according to the route loss rate. The route loss rate is used to determine whether the failure to select the preferred route of the charging vehicle has led to an increase in the single-task power consumption of the charging vehicle, thereby making subsequent analysis targets more in line with actual working scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 This is a unit connection diagram of the intelligent black box of the energy storage power station according to an embodiment of the present invention;

[0039] Figure 2 It is a schematic diagram of an application method of an intelligent black box for an energy storage power station according to an embodiment of the present invention. DETAILED DESCRIPTION

[0040] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0041] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0042] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0043] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0044] See also Figure 1 to Figure 2 As shown, the present invention provides an intelligent black box for an energy storage power station, comprising:

[0045] A data collection unit, used to collect demand information;

[0046] A data analysis unit connected to the data acquisition unit, configured to determine a cycle category of a target power consumption cycle according to a power consumption reference value, and to determine a similar usage state according to a power consumption speed of each charging vehicle corresponding to a valid reference cycle to determine a data analysis target;

[0047] A retrospective analysis unit connected to the data acquisition unit and the data analysis unit, for determining an analysis target according to the route loss rate of differentially charged vehicles, and determining a corresponding impact value according to a difference in the proportion of impacted routes, a difference in load weight, or a difference in the number of starts and stops;

[0048] A sensing and analyzing unit, connected to the data acquisition unit and the data analyzing unit, for calculating an environmental impact coefficient and determining an impact value of the environmental impact coefficient according to the environmental impact coefficient;

[0049] A storage unit is connected to the data acquisition unit and the data analysis unit, and is used to store demand information corresponding to a target power consumption cycle.

[0050] The demand information includes the time when each vehicle is put into use and the corresponding power, the charging time of each vehicle, the number of tasks during a single use of each vehicle, the route loss rate during a single use of each vehicle, the number of effective vibrations during a single use of each vehicle, the ambient temperature and the ambient humidity. The time when each vehicle is put into use is the time point corresponding to the start of the first task after a single vehicle leaves the charging area. The charging time point is the time point when the vehicle enters the charging area. The working process corresponding to the time between the time when the vehicle is put into use and the nearest charging time point thereafter is recorded as a single use process.

[0051] The application scenario of the present invention is a smart industrial park, and the vehicle is an AGV carrier vehicle.

[0052] Specifically, the data analysis unit detects the power consumption reference value of the target power consumption cycle and determines the cycle category of the target power consumption cycle according to the power consumption reference value, including a valid reference cycle and an invalid reference cycle;

[0053] The data analysis unit performs data analysis on the effective reference cycle.

[0054] If the power consumption reference value is greater than the preset power consumption reference value, the data analysis unit determines that the target power consumption cycle is a valid reference cycle;

[0055] If the power consumption reference value is less than or equal to the preset power consumption reference value, the data analysis unit determines that the target power consumption cycle is an invalid reference cycle;

[0056] The power reference value is the sum of the power requirements of each charging vehicle, and the preset power reference value is 30% of the sum of the full power of all charging devices in the energy storage power station that can charge the charging vehicles.

[0057] Specifically, the data analysis unit performs data analysis on the effective reference cycle, detects the usage similarity status of the charging vehicles in the effective reference cycle, and determines the data analysis target according to the usage similarity status, including the route loss rate or the environmental impact coefficient.

[0058] Specifically, the data analysis unit determines the usage similarity state based on the power usage speed of each charging vehicle corresponding to the effective reference cycle, including a first usage similarity state in which the power usage speed of any charging vehicle is less than a preset power usage speed, and a second usage similarity state in which the power usage speed of a charging vehicle is greater than the preset power usage speed.

[0059] In the first usage similarity state, the data analysis unit determines that the data analysis target is the route loss rate;

[0060] In the second usage similarity state, the data analysis unit determines that the data analysis target is the environmental impact coefficient.

[0061] Specifically, for a single charging vehicle, the power usage speed of the charging vehicle is the duration between the last time it was put into use and the charging time. The preset power usage speed is set by the user, and a method for determining the value of the preset power usage speed is provided. The average value of the sum of the power usage speeds of all current charging vehicles is recorded as the preset power usage speed.

[0062] Specifically, the traceability analysis unit detects the route loss rate of the differentially charged vehicles and determines the analysis target according to the route loss rate;

[0063] If the route loss rate is within the first preset route loss rate range, the tracing analysis unit determines to analyze the difference in the proportion of the affected routes;

[0064] If the route loss rate is within a second preset route loss rate range, the retrospective analysis unit determines to perform analysis on the movement parameters.

[0065] A differential charging vehicle is a charging vehicle whose power usage speed is greater than a preset power usage speed, and a stable charging vehicle is a charging vehicle whose power usage speed is less than or equal to a preset power usage speed.

[0066] Specifically, the route loss rate is the number of failed routes corresponding to a differentially charged vehicle during a single use. It can be understood that in actual work, after the AGV obtains the positions of the moving starting point and the moving end point, it can obtain several movable routes through the route generation technology. In the present invention, the distance of each movable route is used as the search order, and the movable routes are searched in order from small to large in route distance. If the number of AGVs on a route is less than the preset AVG number, then the route is the selected route, and the AGV moves through the selected route. If the number of AGVs on a route is greater than or equal to the preset AVG number, then the route is a failed route. The values ​​within the first preset route loss rate range are all greater than the preset route loss rate, and the values ​​within the second preset route loss rate range are all less than or equal to the preset route loss rate. The preset route loss rate is the average of the sum of the number of failed routes corresponding to all current stable charging vehicles.

[0067] Specifically, the traceability analysis unit analyzes the difference in the proportion of the influencing routes and detects the difference in the proportion of the influencing routes;

[0068] If the difference in the proportion of the affected routes is within the first preset difference range, the influence value of the affected routes is increased;

[0069] If the difference of the impact route proportion is within the second preset difference range, the impact value of the task busyness is increased and adjusted.

[0070] Specifically, the difference in the proportion of affected routes = N1 / N2, where N1 is the sum of the number of failed routes corresponding to the most recent use of each charging vehicle, and N2 is the sum of the number of selected routes corresponding to the most recent use of each charging vehicle. The first preset difference range is greater than the preset difference in the proportion of affected routes, and the values ​​within the second preset difference range are less than or equal to the preset difference in the proportion of affected routes. The preset difference in the proportion of affected routes is the average value of the sum of the proportions of affected routes corresponding to each invalid reference period.

[0071] The influence value of the influencing route and the difference degree of the influencing route proportion are positively correlated;

[0072] The impact value of the task busyness is negatively correlated with the difference in the impact route proportion.

[0073] Specifically, the retrospective analysis unit analyzes the movement parameters, detects the load weight difference of the differentially charged vehicles, and determines to analyze the number of starts and stops or to increase the impact value of the load weight according to the load weight difference.

[0074] Movement parameters include load weight and number of starts and stops;

[0075] Load weight difference = M1 / M2, M1 is the average of the average load weights of all differentially charged vehicles, M2 is the average of the average load weights of all stable charged vehicles, and the average load weight of a single charging vehicle is the average of the sum of the load weights of each task corresponding to the most recent use process;

[0076] If the load weight difference is greater than 1, the load weight impact value is adjusted to increase, and the increase in the load weight impact value is positively correlated with the load weight difference;

[0077] If the load weight difference is less than or equal to 1, the number of starts and stops is analyzed.

[0078] Specifically, the retrospective analysis unit analyzes the start and stop times of the differentially charged vehicles, detects the difference in the start and stop times of the differentially charged vehicles, and determines an increase adjustment for the impact value of the start and stop times according to the difference in the start and stop times or sends a quality inspection reminder message for the differentially charged vehicles to the user.

[0079] Specifically, the difference in start-stop times = B1 / B2, where B1 is the average of the sum of the start-stop times of all differentially charged vehicles, and B2 is the average of the sum of the start-stop times of all stably charged vehicles. The start-stop times are the start-stop times corresponding to the most recent use process, and the start-stop times are the number of stops during the movement process.

[0080] If the difference in the number of starts and stops is greater than 1, the influence value of the number of starts and stops is increased and adjusted, and the increase in the number of starts and stops is positively correlated with the difference in the number of starts and stops;

[0081] If the difference in the number of starts and stops is less than or equal to 1, a quality inspection reminder message for differentially charged vehicles is sent to the user.

[0082] Specifically, the sensing and analyzing unit calculates the environmental impact coefficient and determines the impact value of the environmental impact coefficient according to the environmental impact coefficient;

[0083] If the environmental impact coefficient is greater than the preset environmental impact coefficient, the sensor analysis unit determines that the impact value of the environmental impact coefficient and the difference between the environmental impact coefficients are in a positive correlation;

[0084] If the environmental impact coefficient is less than or equal to the preset environmental impact coefficient, the sensing and analyzing unit determines to send a quality inspection reminder message of the differentially charged vehicle to the user.

[0085] Specifically, the environmental impact coefficient = (ambient temperature / standard temperature) × α1 + (ambient humidity / standard humidity) × α2, where α1 is the first weight coefficient, α2 is the second weight coefficient, and a value of a weight coefficient is provided, α1 = 0.7, α2 = 0.3, the standard temperature and standard humidity are set by the user, the standard temperature is the optimal operating temperature of the AGV, and the standard humidity is the optimal operating humidity of the AGV.

[0086] The default environmental impact factor is 1.5.

[0087] The storage unit also stores the impact value of the route, the impact value of the load weight, the impact value of the task busyness and the impact value of the environmental impact coefficient.

[0088] The greater the impact value of the route, the greater the impact of the number of AGVs on the route on the charging demand;

[0089] The greater the impact value of the load weight, the greater the impact of the AGV's load weight on the charging demand;

[0090] The greater the impact value of task busyness, the greater the impact of the number of tasks in a single use process of the AGV on the charging demand;

[0091] The greater the impact value of the environmental impact coefficient, the greater the impact of ambient temperature and ambient humidity on charging requirements.

[0092] The present invention also provides an application method for the energy storage power station intelligent black box, comprising:

[0093] Detecting a power consumption reference value of a target power consumption cycle and determining a cycle category of the target power consumption cycle according to the power consumption reference value, including a valid reference cycle and an invalid reference cycle;

[0094] Determine the usage similarity state according to the power usage speed of each charging vehicle corresponding to the effective reference period;

[0095] Determine data analysis objectives based on similar usage status, including route loss rate or environmental impact factor;

[0096] In the detection of route loss rate of differentially charged vehicles, the analysis target is determined according to the route loss rate, including the influencing route proportion or movement parameters;

[0097] Analyze the proportion of affected routes and detect the difference in the proportion of affected routes;

[0098] According to the difference in the proportion of the influencing routes, the influence value of the influencing routes is adjusted or the influence value of the task busyness is adjusted;

[0099] Analyze the movement parameters and determine the start and stop times or adjust the impact value of the load weight according to the load weight difference;

[0100] In the analysis of the environmental impact coefficient, the environmental impact coefficient is calculated and the impact value of the environmental impact coefficient is determined based on the environmental impact coefficient.

[0101] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0102] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An intelligent black box for energy storage power station, It is characterized in that include: A data collection unit, used to collect demand information; A data analysis unit connected to the data acquisition unit, configured to determine a cycle category of a target power consumption cycle according to a power consumption reference value, and to determine a similar usage state according to a power consumption speed of each charging vehicle corresponding to a valid reference cycle to determine a data analysis target; A retrospective analysis unit connected to the data acquisition unit and the data analysis unit, for determining an analysis target according to the route loss rate of differentially charged vehicles, and determining a corresponding impact value according to a difference in the proportion of impacted routes, a difference in load weight, or a difference in the number of starts and stops; A sensing and analyzing unit, connected to the data acquisition unit and the data analyzing unit, for calculating an environmental impact coefficient and determining an impact value of the environmental impact coefficient according to the environmental impact coefficient; A storage unit connected to the data acquisition unit and the data analysis unit, and used to store demand information corresponding to a target power consumption cycle; The data analysis unit performs data analysis on the effective reference cycle, detects the usage similarity status of the charging vehicles in the effective reference cycle, and determines the data analysis target according to the usage similarity status, including the route loss rate or the environmental impact coefficient; The data analysis unit determines the similar usage status according to the power usage speed of each charging vehicle corresponding to the effective reference period, including that the power usage speed of any charging vehicle is less than the preset power usage speed or there is a charging vehicle whose power usage speed is greater than the preset power usage speed; The traceability analysis unit detects the route loss rate of differentially charged vehicles and determines the analysis target according to the route loss rate; If the route loss rate is within the first preset route loss rate range, the tracing analysis unit determines to analyze the difference in the proportion of the affected routes; If the route loss rate is within a second preset route loss rate range, the retrospective analysis unit determines to analyze the movement parameters; The reference value for electricity consumption is the sum of the electricity demand corresponding to each charging vehicle; The difference in the proportion of affected routes = N1 / N2, where N1 is the sum of the number of failed routes corresponding to the most recent use of each charging vehicle, and N2 is the sum of the number of selected routes corresponding to the most recent use of each charging vehicle; Load weight difference = M1 / M2, M1 is the average of the sum of the average load weights of all differentially charged vehicles, M2 is the average of the sum of the average load weights of all stable charged vehicles, and the average load weight of a single charging vehicle is the average of the sum of the load weights in each task corresponding to the most recent use process; Start-stop number difference = B1 / B2, B1 is the average of the sum of the start-stop numbers of all differentially charged vehicles, B2 is the average of the sum of the start-stop numbers of all stable charged vehicles, and the start-stop number is the number of stops during the movement process corresponding to the most recent use process; Environmental impact coefficient = (ambient temperature / standard temperature) × α1 + (ambient humidity / standard humidity) × α2, where α1 is the first weight coefficient and α2 is the second weight coefficient; The route loss rate is the number of failed routes corresponding to a differential charging vehicle during a single use; Movement parameters include load weight and number of starts and stops; A differential charging vehicle is a charging vehicle whose power usage speed is greater than a preset power usage speed.

2. The energy storage power station intelligent black box according to claim 1, It is characterized in that The data analysis unit detects the power consumption reference value of the target power consumption cycle and determines the cycle category of the target power consumption cycle according to the power consumption reference value, including a valid reference cycle and an invalid reference cycle; The data analysis unit performs data analysis on the effective reference cycle.

3. The energy storage power station intelligent black box according to claim 2, It is characterized in that The traceability analysis unit analyzes the difference in the proportion of the influencing routes and detects the difference in the proportion of the influencing routes; If the difference in the proportion of the affected routes is within the first preset difference range, the influence value of the affected routes is increased; If the difference of the impact route proportion is within the second preset difference range, the impact value of the task busyness is increased and adjusted.

4. The energy storage power station intelligent black box according to claim 3, It is characterized in that The retrospective analysis unit analyzes the movement parameters, detects the load weight difference of the differentially charged vehicles, and determines to analyze the start-stop times or increase the impact value of the load weight according to the load weight difference.

5. The energy storage power station intelligent black box according to claim 4, It is characterized in that The retrospective analysis unit analyzes the start and stop times of the differentially charged vehicles, detects the difference in the start and stop times of the differentially charged vehicles, and determines an increase adjustment for the impact value of the start and stop times according to the difference in the start and stop times or sends a quality inspection reminder message for the differentially charged vehicles to the user.

6. The energy storage power station intelligent black box according to claim 5, It is characterized in that The sensing and analyzing unit calculates the environmental impact coefficient and determines the impact value of the environmental impact coefficient according to the environmental impact coefficient; If the environmental impact coefficient is greater than the preset environmental impact coefficient, the sensor analysis unit determines that the impact value of the environmental impact coefficient and the difference between the environmental impact coefficients are in a positive correlation; If the environmental impact coefficient is less than or equal to the preset environmental impact coefficient, the sensing and analyzing unit determines to send a quality inspection reminder message of the differentially charged vehicle to the user.

7. A method for using the intelligent black box of an energy storage power station according to any one of claims 1 to 6, It is characterized in that include: Detecting a power consumption reference value of a target power consumption cycle and determining a cycle category of the target power consumption cycle according to the power consumption reference value, including a valid reference cycle and an invalid reference cycle; Determine the usage similarity state according to the power usage speed of each charging vehicle corresponding to the effective reference period; Determine data analysis objectives based on similar usage status, including route loss rate or environmental impact factor; In the detection of route loss rate of differentially charged vehicles, the analysis target is determined according to the route loss rate, including the difference degree or movement parameters affecting the route proportion; Detect the difference in the proportion of influencing routes; According to the difference in the proportion of the influencing routes, the influence value of the influencing routes is adjusted or the influence value of the task busyness is adjusted; Analyze the movement parameters and determine the start and stop times or adjust the impact value of the load weight according to the load weight difference; In the analysis of the environmental impact coefficient, the environmental impact coefficient is calculated and the impact value of the environmental impact coefficient is determined based on the environmental impact coefficient.

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