Intelligent load control method and system for charging pile groups based on dynamic power balancing

Abstract

This invention relates to the field of intelligent load control technology for charging pile groups, specifically disclosing a method and system for intelligent load control of charging pile groups based on dynamic power balancing. The method includes: real-time acquisition of transformer oil temperature to calculate the total output power threshold; correction of the actual output power of the charging piles based on line losses and equipment aging; establishment of a multi-dimensional load control decision matrix including user priority, equipment health, and power adjustment sensitivity; and dynamic power allocation strategy through matrix weighting to tilt power allocation towards high-priority users and healthy equipment. This supports emergency power allocation and gradual readjustment when new demand arises, avoiding the impact of sudden power changes on the power grid, ensuring system stability when new loads are connected, and ultimately achieving refined intelligent control of the charging pile group load. This improves transformer safety, charging efficiency, and user experience, ensuring power grid stability and optimal resource allocation.

Description

Technical Field

[0001] This invention belongs to the field of intelligent load control technology for charging pile groups, and relates to a method and system for intelligent load control of charging pile groups based on dynamic power balancing. Background Technology

[0002] With the increasing popularity of electric vehicles, the scale of charging pile networks is constantly expanding, making effective load control increasingly crucial. Currently, traditional methods for managing the load of charging pile networks mainly rely on fixed power allocation schemes or simple power monitoring. This approach often cannot adapt to the dynamic changes in transformer power and the diverse needs of users and equipment in real time. Therefore, to improve user experience and vehicle charging efficiency, intelligent load control of charging pile networks is necessary.

[0003] For example, Chinese patent publication number CN105610218A discloses a coordinated control method for intelligent charging of electric vehicles. The key is to maximize the utilization of transformer redundancy capacity to charge electric vehicles while ensuring safety. One or more outputs of the transformer are individually connected to charging piles, and load monitoring is performed separately for each output and the external load of the charging pile. This better achieves intelligent charging management of electric vehicles using transformer redundancy capacity while meeting normal power consumption. When balancing transformer redundancy capacity and the number of electric vehicles requiring charging, the number of charging piles that can be put into operation each time is determined according to a percentage, and charging is initiated according to the priority level of the charging piles, rather than all redundant capacity being put into charging piles at once.

[0004] For example, Chinese Patent Publication No. CN114498843B discloses a method for adjusting the charging power of a distributed charging equipment group under the user-side power grid. The method involves collecting the power parameters of each smart charging pile in the distributed charging equipment group, establishing a dynamic relationship model between the power parameters and the power grid load in the time dimension based on the power parameters of each smart charging pile and the power grid load, determining the standard value of the power parameters based on the dynamic relationship model, determining the comparison relationship between the real-time power parameters and the standard value of the power parameters, and determining whether the smart charging pile adjusts its charging power according to a preset logic based on the comparison relationship between the real-time power parameters and the standard value of the power parameters.

[0005] The existing technologies mentioned above still have the following problems: 1. Although the redundant capacity of the transformer can be used for charging management and charging piles can be put into operation according to priority, key data such as the top oil temperature of the transformer are not collected in real time to accurately obtain the total output power threshold. The power limit cannot be dynamically adjusted to ensure the safe and stable operation of the transformer. At the same time, when calculating the output power of the charging pile, factors such as cable loss and equipment aging are not considered, and the power calculation is not accurate enough.

[0006] 2. Charging management is based solely on priority levels and the number of units deployed, without constructing a multi-dimensional control decision matrix that includes user fulfillment data, equipment health, power adjustment sensitivity, etc., making it difficult to fully consider user needs and equipment status.

[0007] 3. The charging power is adjusted by simply collecting the power parameters of the smart charging pile and establishing a time-dimensional model with the grid load. However, when new charging demand is added, there is no mechanism to automatically trigger the dynamic reallocation of the power budget, so it cannot flexibly respond to changes in charging demand. Summary of the Invention

[0008] In view of this, in order to solve the problems mentioned in the background technology, a method and system for intelligent load control of charging pile groups based on dynamic power balancing is proposed.

[0009] The objective of this invention can be achieved through the following technical solution: The first aspect of this invention provides a method for intelligent load control of charging pile groups based on dynamic power balancing, including: S1, reading the rated power of the transformer of the target charging station, collecting the top oil temperature of the transformer in real time, and thereby obtaining the total output power threshold of the target charging station.

[0010] S2. Collect the working data of each working charging pile in the target charging station, and generate the corrected actual output power of each working charging pile accordingly.

[0011] S3. Obtain the remaining battery power, full load power, and historical performance data of the vehicles of the users currently charging at each working charging pile, and obtain the equipment operation status data and historical power adjustment data of each working charging pile. Based on this, establish a multi-dimensional load control decision matrix for each working charging pile, including user priority, equipment health, and power adjustment sensitivity.

[0012] S4. Based on the total output power threshold of the target charging station and the corrected actual output power of each working charging pile, a dynamic allocation strategy is generated through the multi-dimensional load control decision matrix.

[0013] S5. When the target charging station detects a new charging demand, it extracts the power demand, allowed charging time and full load power of the newly connected device, collects the working data of the working charging pile corresponding to the newly connected device, and automatically triggers the dynamic reallocation of power budget.

[0014] The second aspect of the present invention provides a charging pile group load intelligent control system based on dynamic power balancing, comprising: a total output power threshold acquisition module, which reads the rated power of the transformer of the target charging station and collects the top oil temperature of the transformer in real time, thereby acquiring the total output power threshold of the target charging station.

[0015] The actual output power generation module collects the working data of each working charging pile in the target charging station and generates the corrected actual output power of each working charging pile accordingly.

[0016] The control decision matrix establishment module obtains the remaining battery power, full load power, and historical performance data of vehicles of users currently charging at each working charging pile, as well as the equipment operation status data and historical power adjustment data of each working charging pile. Based on this, a multi-dimensional load control decision matrix for each working charging pile is established, which includes user priority, equipment health, and power adjustment sensitivity.

[0017] The dynamic allocation strategy generation module generates a dynamic allocation strategy based on the total output power threshold of the target charging station and the corrected actual output power of each working charging pile through the multi-dimensional load control decision matrix.

[0018] The dynamic redistribution trigger module extracts the power demand, allowed charging duration, and full-load power of the newly connected device when the target charging station detects a new charging demand. It also collects the working data of the working charging pile corresponding to the newly connected device and automatically triggers the dynamic redistribution of the power budget.

[0019] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: (1) The present invention calculates the total output power threshold in real time by coupling the rated power of the transformer, the real-time oil temperature, the reference oil temperature and the temperature rise compensation factor, so as to ensure that the transformer operates in the safe power range, avoid overload risk and extend the equipment life.

[0020] (2) This invention improves the accuracy of load statistics by combining line loss and equipment aging to correct the actual output power, reduce energy waste caused by cable loss, and ensure the safe operation of charging piles.

[0021] (3) This invention constructs a multi-dimensional decision matrix that includes user priority (remaining power, performance record), equipment health (number of failures), and power adjustment sensitivity (response time). By calculating a comprehensive score through weighted calculation, the power allocation is tilted towards high-priority users and healthy equipment, taking into account both user experience and equipment reliability.

[0022] (4) When new demand is added, the present invention allocates initial power from the emergency margin based on the demand power and the urgency of electricity use, and avoids the impact of sudden power changes on the power grid through gradual readjustment (exponential decay allocation of adjustment amount), ensuring system stability when new loads are connected, and improving charging efficiency and resource utilization. Attached Figure Description

[0023] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a schematic diagram of the method steps of the present invention.

[0025] Figure 2 This is a schematic diagram of the system structure connection of the present invention.

[0026] Figure 3 This is a schematic diagram of the dynamic redistribution process of the present invention. Detailed Implementation

[0027] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0028] Please see Figure 1 As shown, the first aspect of the present invention provides a method for intelligent load control of charging pile groups based on dynamic power balancing, including: S1, reading the rated power of the transformer of the target charging station and collecting the top oil temperature of the transformer in real time, thereby obtaining the total output power threshold of the target charging station.

[0029] It should be noted that the rated power of the transformer is read in real time through the power monitoring terminal of the target charging station, and the top oil temperature of the transformer is collected by the installed infrared thermometer.

[0030] In a specific embodiment of the present invention, the method for obtaining the total output power threshold of the target charging station is as follows: extract the temperature rise compensation factor and the reference oil temperature of the transformer top layer from the database.

[0031] The total output power threshold of the target charging station is obtained by coupling the rated power of the transformer, the top oil temperature of the transformer, the reference oil temperature of the top oil of the transformer, and the temperature rise compensation factor.

[0032] It should be noted that the specific formula for the total output power threshold of the target charging station is: P 总 =P 额 ×(1-α×(T 顶 -T 基 ), where P 总 and P 额These represent the total output power threshold and the transformer rated power, respectively; α represents the temperature rise compensation factor; and T... 顶 and T 基 These represent the top oil temperature and the reference oil temperature of the top layer of the transformer, respectively.

[0033] It should also be noted that the core design idea of ​​this formula is to achieve adaptive adjustment of the transformer power threshold through a dynamic temperature rise compensation mechanism. Its technical essence is to directly couple the temperature variable with the power capacity and use the temperature rise compensation factor to quantify the attenuation effect of temperature on the transformer output capacity.

[0034] This invention calculates the total output power threshold in real time by coupling the transformer's rated power, real-time oil temperature, reference oil temperature, and temperature rise compensation factor, ensuring that the transformer operates within a safe power range, avoiding overload risks, and extending equipment life.

[0035] S2. Collect the working data of each working charging pile in the target charging station, and generate the corrected actual output power of each working charging pile accordingly.

[0036] It should be noted that the working data of each charging pile is collected from the charging pile management backend.

[0037] In a specific embodiment of the present invention, the method for generating the corrected actual output power of each working charging pile is as follows: extract the required output power, grayscale image of the cable connector, current output current, unit length cable resistance and cable length of the circuit from the working data of each working charging pile in the target charging station.

[0038] The line compensation power of each working charging pile is obtained by multiplying the square of the current output current by the resistance per unit length of the cable in the circuit and the cable length.

[0039] The aging degree is assessed based on the grayscale images of the cable connectors of each working charging station, thereby obtaining the safety factor of each working charging station.

[0040] It should be noted that the specific process of obtaining the safety factor of each working charging pile is as follows: extract the gray value of each gray area from the gray image of the cable connector of each working charging pile, and compare it with the gray value range corresponding to the oxidation of the cable connector stored in the database.

[0041] If the gray value of a certain gray area is within the gray value range corresponding to the oxidation of the cable connector, it indicates that the gray area is an oxidation area. The number of oxidation areas of the cable connectors of each working charging pile is counted.

[0042] The difference between the number of oxidized areas on the cable connectors of each working charging station and the set reference value is compared with the set reference value, and the ratio result is used as the degree of oxidation of the cable connectors of each working charging station.

[0043] The oxidation degree of the cable connectors of each working charging pile is compared with the oxidation degree range of the cable connectors corresponding to each safety factor stored in the database. If the oxidation degree of the cable connector of a certain working charging pile is within the oxidation degree range of the cable connectors corresponding to a certain safety factor, then that safety factor is used as the safety factor of the working charging pile. Thus, the safety factor of each working charging pile is obtained.

[0044] Multiply the line compensation power of each working charging station by the safety factor, and sum the result of the multiplication with the required output power to obtain the corrected actual output power of each working charging station.

[0045] This invention improves the accuracy of load statistics, reduces energy waste caused by cable loss, and ensures the safe operation of charging piles by combining line loss and equipment aging to correct the actual output power.

[0046] S3. Obtain the remaining battery power, full load power, and historical performance data of the vehicles of the users currently charging at each working charging pile, and obtain the equipment operation status data and historical power adjustment data of each working charging pile. Based on this, establish a multi-dimensional load control decision matrix for each working charging pile, including user priority, equipment health, and power adjustment sensitivity.

[0047] It should be noted that the remaining battery power and historical performance data of the vehicle are extracted from the charging pile APP settings, the full load battery power is obtained from the vehicle BMS of the user who is charging, and the equipment operation status data and historical power adjustment data of each working charging pile are obtained from the charging pile management backend.

[0048] In a specific embodiment of the present invention, the specific process of establishing a multi-dimensional load control decision matrix for each working charging pile, which includes user priority, equipment health, and power adjustment sensitivity, is as follows: extract the number of reservations and the number of fulfillments from the historical fulfillment data of the users currently charging at each working charging pile, and perform a fusion analysis based on the vehicle's remaining battery power and full load battery power to obtain the user priority of each working charging pile.

[0049] It should be noted that the specific process of obtaining the user priority of each working charging pile is as follows: the fulfillment number and reservation number of the user currently charging at each working charging pile are compared to obtain the fulfillment number of the user currently charging at each working charging pile, and the difference between the fulfillment number and the set reference value is compared with the set reference value to obtain the trustworthiness of the user currently charging at each working charging pile.

[0050] The ratio between the vehicle's remaining battery power and its full load battery power is used as the percentage of the vehicle's remaining battery power for each working charging station corresponding to the user currently charging. The difference between the set reference percentage of the vehicle's remaining battery power and the percentage of the vehicle's remaining battery power for each working charging station corresponding to the user currently charging is compared with the set reference percentage of the vehicle's remaining battery power to obtain the charging urgency for each working charging station corresponding to the user currently charging.

[0051] The user priority of each working charging station is obtained by weighting and summing the trustworthiness and charging urgency of the users currently charging.

[0052] In one specific embodiment of the present invention, when evaluating the user priority of each working charging station, the weight of trustworthiness and charging urgency are equally important. Therefore, the weight weights of trustworthiness and charging urgency are set to 0.5 and 0.5, respectively.

[0053] Health analysis is performed on the historical number of faults in the equipment operation status data of each working charging pile to obtain the equipment health status of each working charging pile.

[0054] It should be noted that the specific method for obtaining the equipment health status of each working charging pile is as follows: the historical number of faults of each working charging pile is recorded as ε. i , where i represents the number of the working charging station, i = 1, 2, ..., n.

[0055] Calculate the equipment health β of each working charging station. i , Where ε′ represents the number of failures for which a reference is set, and e represents the natural constant.

[0056] It should be further explained that the derivation process of the above equipment health formula is as follows: In the formula, ε′-ε i It reflects the difference between the actual number of failures and the reference number of failures, using an exponential function. It utilizes the property that its value range is (0, +∞) and the function value is 1 when the exponent is 0. The difference is processed through an exponential function to reflect the impact of the difference in the number of failures on equipment health in a non-linear way. The denominator... Make the calculated result β i It is limited to the (0,1) range. Generally, the closer the value is to 1, the higher the health of the equipment; the closer it is to 0, the lower the health, which meets the general requirements for measuring equipment health.

[0057] Sensitivity assessment is performed based on the power adjustment command issuance time and actual response time of each working charging pile in the historical power adjustment data of each working charging pile to obtain the power adjustment sensitivity of each working charging pile.

[0058] It should be noted that the specific process for obtaining the power adjustment sensitivity of each working charging pile is as follows: the interval between the time point of issuing each power adjustment command and the actual response time point is taken as the response time of each power adjustment, and the average of these intervals is calculated to obtain the average response time of each working charging pile, which is denoted as t. i .

[0059] Calculate the power adjustment sensitivity Q of each working charging station. i , Where t represents the response time of the reference setting.

[0060] It should be further explained that the derivation process of the above power adjustment sensitivity formula is as follows: exponential function It has some characteristics, its value ranges from (0, +∞), and the function value is 1 when the exponent is 0. The use of an exponential function here may be to represent the difference in response time in a non-linear way that is easily scaled between 0 and 1. (Denominator) The result can be limited to the (0,1) interval, which meets the measurement requirement of "sensitivity" that is expected to take values ​​within a certain range.

[0061] By combining the user priority, equipment health, and power adjustment sensitivity of each working charging station, a multi-dimensional load control decision matrix for each working charging station is obtained.

[0062] S4. Based on the total output power threshold of the target charging station and the corrected actual output power of each working charging pile, a dynamic allocation strategy is generated through the multi-dimensional load control decision matrix.

[0063] In a specific embodiment of the present invention, the specific process of generating a dynamic allocation strategy through the multidimensional load control decision matrix is ​​as follows: the actual output power of each working charging pile after correction is accumulated to obtain the corrected actual total output power.

[0064] The difference between the total output power threshold of the target charging station and the corrected actual total output power is used to obtain the output power difference of the target charging station.

[0065] The grid load factor of the target charging station is obtained by comparing the corrected actual total output power with the total output power threshold.

[0066] The target charging station's grid load rate is matched with the weighted proportions of user priority, equipment health, and power adjustment sensitivity for each grid load interval stored in the database to obtain the weighted proportions of user priority, equipment health, and power adjustment sensitivity for each target charging station.

[0067] It should be noted that the weights of user priority, equipment health, and power adjustment sensitivity vary for different grid load ranges. The advantage of this design is that this dynamic weight matching design automatically adjusts the weight allocation of user priority, equipment health, and power sensitivity by sensing the grid load rate in real time, thereby achieving intelligent optimization of charging station resources. Through data-driven adaptive strategies, it achieves the optimal balance between the three major objectives of charging efficiency, equipment lifespan, and grid safety. Compared with a fixed weight scheme, it can improve operational efficiency and reduce the failure rate.

[0068] The user priority, equipment health, and power adjustment sensitivity of each working charging station are weighted and summed according to their corresponding percentage weights to obtain the comprehensive evaluation index of each working charging station. The product of this comprehensive evaluation index and the evaluation score corresponding to the unit comprehensive evaluation index stored in the database is used as the comprehensive score of each working charging station.

[0069] When the output power difference is greater than 0, it indicates that the target charging station has remaining power available for allocation, and a positive power allocation adjustment is performed.

[0070] In a specific embodiment of the present invention, the specific process of adjusting the positive power allocation is as follows: sorting each working charging pile in descending order according to its comprehensive score, and using the product of the comprehensive score ratio of each working charging pile after descending order and the difference in output power as the basic power allocation amount of each working charging pile after descending order.

[0071] It should be noted that the ratio of the comprehensive score of each working charging station after descending order to the sum of the comprehensive scores of all working charging stations is used to obtain the comprehensive score percentage of each working charging station after descending order.

[0072] Sensitivity compensation analysis is performed based on the power base allocation and power adjustment sensitivity of each working charging pile after descending order to obtain the actual power allocation of each working charging pile after descending order.

[0073] It should be noted that the specific formula for the actual power allocation of each working charging pile after descending order is as follows: in, and Q represents the actual power allocation and the base power allocation of the j-th working charging pile, respectively, in descending order. j Let A represent the power adjustment sensitivity of the j-th working charging pile after descending order, where A represents the power compensation amplitude factor, and j represents the number of each working charging pile after descending order, j = 1, 2, ..., m.

[0074] In a specific embodiment of the present invention, if the value of the power compensation amplitude factor is too large, it may cause a sudden power change and cause the bus voltage fluctuation to exceed the limit. If it is too small, the sensitivity difference cannot be effectively reflected and the optimization effect is weak. Therefore, the power compensation amplitude factor obtained by optimization through actual charging station operation data can be 0.2.

[0075] It should be further explained that the advantage of the above formula for actual power allocation lies in: through the linear compensation model (1+A×Q) j This design achieves three key objectives: 1) differentiated allocation (high-power adjustment sensitivity devices receive more power, improving overall charging speed), 2) controllable adjustment (limiting the compensation range through a fixed coefficient A to avoid resource imbalance), and 3) computationally efficient (linear formulas simplify real-time calculations). This design respects device performance differences while maintaining overall system balance, improving charging efficiency compared to equal allocation schemes, while keeping grid fluctuations within a safe range.

[0076] When the output power difference is less than 0, it indicates that the total demand exceeds the limit, and the power of some charging piles needs to be reduced and a negative power distribution adjustment needs to be made.

[0077] In a specific embodiment of the present invention, the specific process of adjusting the negative power distribution is as follows: sorting each working charging pile in ascending order according to its comprehensive score, and using the product of the percentage of the comprehensive score of each working charging pile after ascending order and the absolute value of the difference in output power as the power base reduction of each working charging pile after ascending order.

[0078] It should be noted that the overall score of each working charging station after ascending sort is compared with the sum of the overall scores of all working charging stations to obtain the overall score percentage of each working charging station after ascending sort.

[0079] A health protection assessment is conducted based on the power load reduction and equipment health of each working charging pile after ascending order, to obtain the actual power load reduction of each working charging pile after ascending order.

[0080] It should be noted that the formula for expressing the actual power load reduction of each working charging pile after ascending order is as follows: in, and β represents the actual power load reduction and the power base load reduction of the g-th working charging pile after ascending sorting, respectively. g This represents the device health status of the g-th working charging pile after ascending sorting, where g represents the number of each working charging pile after ascending sorting, and g = 1, 2, ..., q.

[0081] It should be further explained that the core idea behind the above formula for actual power load reduction is to dynamically adjust the load reduction range based on equipment health, thereby achieving an intelligent load reduction strategy that prioritizes equipment protection. Its innovation lies in: 1) a reverse compensation mechanism for health (1-β) g 1) Ensure that high-healthy equipment can undertake smaller load reductions, effectively extending the lifespan of critical equipment; 2) The linear calculation model maintains the real-time performance of the algorithm while ensuring the fairness of load reduction; 3) Combined with ascending sorting, it forms a fault-tolerant system of "prioritizing load reduction for low-healthy equipment", which satisfies the power constraints of the power grid and reduces the risk of equipment failure.

[0082] This invention constructs a multi-dimensional decision matrix that includes user priority (remaining battery power, fulfillment records), device health (number of failures), and power adjustment sensitivity (response time). By calculating a comprehensive score through weighted averages, power allocation is tilted towards high-priority users and healthy devices, taking into account both user experience and device reliability.

[0083] S5. When the target charging station detects a new charging demand, it extracts the power demand, allowed charging time and full load power of the newly connected device, collects the working data of the working charging pile corresponding to the newly connected device, and automatically triggers the dynamic reallocation of power budget.

[0084] It should be noted that the power demand and allowed charging time of the newly connected device are extracted from the data manually entered by the user in the charging pile APP, the full load power is obtained directly from the vehicle BMS, and the working data of the working charging pile corresponding to the newly connected device is collected from the charging pile management backend.

[0085] Please see Figure 3 As shown, in a specific embodiment of the present invention, the specific implementation process of the automatic triggering of dynamic redistribution of power budget is as follows: multiply the total output power threshold of the target charging station by the percentage of the total output power corresponding to the emergency margin stored in the database to obtain the emergency margin of the target charging station.

[0086] The required power of the newly connected device is obtained by comparing its power demand with its allowed charging time.

[0087] The power urgency of the newly connected device is obtained by comprehensively processing its power demand and full load power.

[0088] It should be noted that the specific method for obtaining the power urgency of the newly connected device is as follows: the power demand of the newly connected device is compared with the full load power to obtain the power demand ratio of the newly connected device, and the difference between the power demand ratio and the set reference power demand ratio is compared with the set reference power demand ratio to obtain the power urgency of the newly connected device.

[0089] Based on the urgency and power demand of the newly connected devices, initial power is allocated from the emergency reserve to the newly connected devices, and the power of the target charging station is gradually readjusted.

[0090] It should be noted that the initial power is specifically: P 初始 =min(P 需 ,P 裕量 ×δ 新 ), where P 初始 P represents the initial power allocated to newly connected devices. 需 and P 裕量 δ represents the emergency margin of the target charging station for the power demand of newly connected devices. 新 This indicates the urgency of power consumption for newly connected devices.

[0091] In a specific embodiment of the present invention, the specific process of triggering the progressive readjustment of the power of the target charging station is as follows: based on the working data of the working charging pile corresponding to the newly connected device, the corrected actual output power of the working charging pile corresponding to the newly connected device is generated in the same way as the generation method of the corrected actual output power of each working charging pile.

[0092] The corrected actual total output power is added to the corrected actual output power of the working charging pile corresponding to the newly connected device to obtain the corrected actual output power of all working charging piles, and this is used as the current total load of the target charging station.

[0093] The difference between the total output power threshold of the target charging station and the initial power of the newly connected device is used as the updated total power threshold.

[0094] The difference between the updated total power threshold and the current total load is used as the updated output power difference.

[0095] The number of permitted adjustment stages is calculated by rounding up the updated output power difference and the maximum allowable adjustment amount for a single adjustment stage stored in the database.

[0096] It should be noted that the specific number of license adjustment stages is as follows: Where N represents the number of license adjustment stages, ΔP max ΔP represents the maximum allowable adjustment amount for a single adjustment phase stored in the database. 新 This represents the updated output power difference.

[0097] It should also be noted that the maximum allowable adjustment amount in a single adjustment phase is extracted from the charging safety rules of the target charging station. In a specific embodiment of the present invention, the maximum allowable adjustment amount in a single adjustment phase can be 50kW.

[0098] Based on the permitted adjustment stage number and the updated output power difference, the power adjustment amount for each adjustment stage is allocated according to the exponential decay curve method, thereby obtaining the power adjustment amount for each adjustment stage.

[0099] It should be noted that the specific method for obtaining the power adjustment amount at each adjustment stage is as follows: in, Let λ represent the power adjustment amount in the r-th adjustment stage, λ be the system inertia coefficient, and r represent the adjustment stage number, r = 1, 2, ..., N.

[0100] It should also be noted that the system inertia coefficient was obtained by fitting the actual decay curve through a step response experiment. Specifically, this involves: first, applying a step power disturbance to the target charging station's power grid system, simultaneously acquiring the time-domain response curve of the bus voltage, and then using the exponential decay model P(t)=P0×e -λt Fit the measured data, where t represents the adjustment stage number, optimize the solution of λ value using the least squares method, combine it with the physical consistency of λ verified by the rated parameters of the equipment, and finally correct the λ value through iterative testing to ensure that the voltage fluctuation is always within the set range under typical operating conditions.

[0101] It should be further explained that the core idea of ​​the power adjustment formula is to achieve gradual dynamic adjustment of power through an exponential decay model. Its core value lies in: 1) scientific matching of physical laws: the exponential characteristics naturally fit the inertia of the power grid, with rapid response in the early stage and fine convergence in the later stage; 2) triple stability guarantee: the dynamic response capability of the system is quantified by the inertia coefficient, and the voltage fluctuation is suppressed within the set range by combining the decay stage and amplitude control.

[0102] In this embodiment of the invention, when new demand arises, initial power is allocated from the emergency margin based on the demand power and the urgency of electricity use, and the power is gradually readjusted (exponential decay of the adjustment amount) to avoid the impact of sudden power changes on the power grid, thereby ensuring system stability when new loads are connected, and improving charging efficiency and resource utilization.

[0103] Reference Figure 2 As shown, the second aspect of the present invention provides a charging pile group load intelligent control system based on dynamic power balancing, including: a total output power threshold acquisition module, an actual output power generation module, a control decision matrix establishment module, a dynamic allocation strategy generation module, and a dynamic redistribution triggering module.

[0104] It should be noted that the present invention also includes a database for storing temperature rise compensation factors and transformer top-level reference oil temperature, grayscale value ranges corresponding to cable joint oxidation, cable joint oxidation ranges corresponding to each safety factor, the percentage weights corresponding to user priority, equipment health and power adjustment sensitivity of each power grid load range, the maximum allowable adjustment amount in a single adjustment phase, the percentage of total output power corresponding to emergency margin, and the evaluation score corresponding to the unit comprehensive evaluation index.

[0105] The total output power threshold acquisition module, the actual output power generation module, and the control decision matrix establishment module are all connected to the dynamic allocation strategy generation module. The total output power threshold acquisition module, the actual output power generation module, and the dynamic allocation strategy generation module are all connected to the dynamic redistribution trigger module. The total output power threshold acquisition module, the actual output power generation module, the dynamic allocation strategy generation module, and the dynamic redistribution trigger module are all connected to the database.

[0106] The total output power threshold acquisition module reads the rated power of the transformer of the target charging station and collects the top oil temperature of the transformer in real time, thereby obtaining the total output power threshold of the target charging station.

[0107] The actual output power generation module collects the working data of each working charging pile in the target charging station and generates the corrected actual output power of each working charging pile accordingly.

[0108] The control decision matrix establishment module obtains the remaining battery power, full load power, and historical performance data of the vehicles of the users currently charging at each working charging pile, and obtains the equipment operation status data and historical power adjustment data of each working charging pile. Based on this, it establishes a multi-dimensional load control decision matrix for each working charging pile, which includes user priority, equipment health, and power adjustment sensitivity.

[0109] The dynamic allocation strategy generation module generates a dynamic allocation strategy based on the total output power threshold of the target charging station and the corrected actual output power of each working charging pile, through the multi-dimensional load control decision matrix.

[0110] When the target charging station detects a new charging demand, the dynamic redistribution trigger module extracts the power demand, allowed charging time, and full-load power of the newly connected device, collects the working data of the working charging pile corresponding to the newly connected device, and automatically triggers the dynamic redistribution of the power budget.

[0111] The above content is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described, or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, and all such modifications and additions should fall within the protection scope of the present invention.

Claims

1. A method for intelligent load control of charging pile groups based on dynamic power balancing, characterized in that, include: S1. Read the rated power of the transformer of the target charging station and collect the top oil temperature of the transformer in real time to obtain the total output power threshold of the target charging station. S2. Collect the working data of each working charging pile in the target charging station, and generate the corrected actual output power of each working charging pile accordingly. The specific method is as follows: Extract the required output power, grayscale image of the cable connector, current output current, unit length cable resistance and cable length from the working data of each working charging pile in the target charging station; Multiply the square of the current output current by the resistance per unit length of the cable in the circuit and the cable length to obtain the line compensation power of each working charging pile. The aging degree is assessed based on the cable connector images of each working charging station, thereby obtaining the safety factor of each working charging station. Multiply the line compensation power of each working charging pile by the safety factor, and sum the result of the multiplication with the required output power to obtain the corrected actual output power of each working charging pile. S3. Obtain the remaining battery power, full load power, and historical performance data of vehicles of users currently charging at each working charging pile. Also obtain the equipment operation status data and historical power adjustment data of each working charging pile. Based on this, establish a multi-dimensional load control decision matrix for each working charging pile, including user priority, equipment health, and power adjustment sensitivity. The specific method is as follows: The number of reservations and the number of reservations are extracted from the historical data of users who are charging at each working charging station. Based on the remaining battery power and full battery power of the vehicle, a fusion analysis is performed to obtain the user priority of each working charging station. Health analysis is performed on the historical number of faults in the equipment operation status data of each working charging pile to obtain the equipment health status of each working charging pile. Sensitivity assessment is performed based on the power adjustment command issuance time and actual response time in the historical power adjustment data of each working charging pile to obtain the power adjustment sensitivity of each working charging pile. By combining the user priority, equipment health, and power adjustment sensitivity of each working charging station, a multi-dimensional load control decision matrix for each working charging station is obtained. S4. Based on the total output power threshold of the target charging station and the corrected actual output power of each working charging pile, a dynamic allocation strategy is generated through the multi-dimensional load control decision matrix. S5. When the target charging station detects a new charging demand, it extracts the power demand, allowed charging time and full load power of the newly connected device, collects the working data of the working charging pile corresponding to the newly connected device, and automatically triggers the dynamic reallocation of power budget.

2. The intelligent load control method for charging pile groups based on dynamic power balancing according to claim 1, characterized in that: The specific method for obtaining the total output power threshold of the target charging station is as follows: Extract the temperature rise compensation factor and the transformer top-level reference oil temperature from the database; The total output power threshold of the target charging station is obtained by coupling the rated power of the transformer, the top oil temperature of the transformer, the reference oil temperature of the top oil of the transformer, and the temperature rise compensation factor.

3. The intelligent load control method for charging pile groups based on dynamic power balancing according to claim 1, characterized in that: The specific process of generating a dynamic allocation strategy through the multidimensional load control decision matrix is ​​as follows: The corrected actual total output power of each working charging station is summed to obtain the corrected actual total output power. The difference between the total output power threshold of the target charging station and the corrected actual total output power is used to obtain the output power difference of the target charging station. The grid load factor of the target charging station is obtained by comparing the corrected actual total output power with the total output power threshold. The target charging station's grid load rate is matched with the user priority, equipment health, and power adjustment sensitivity corresponding to each grid load interval stored in the database to obtain the corresponding percentage weights of the target charging station's user priority, equipment health, and power adjustment sensitivity. The user priority, equipment health, and power adjustment sensitivity of each working charging pile are weighted and summed according to their corresponding percentage weights to obtain the comprehensive evaluation index of each working charging pile. The product of this index and the evaluation score corresponding to the unit comprehensive evaluation index stored in the database is used as the comprehensive score of each working charging pile. When the output power difference is greater than 0, it indicates that the target charging station has remaining power available for allocation, and a positive power allocation adjustment is performed. When the output power difference is less than 0, it indicates that the total demand exceeds the limit, and the power of some charging piles needs to be reduced and a negative power distribution adjustment needs to be made.

4. The intelligent load control method for charging pile groups based on dynamic power balancing according to claim 3, characterized in that: The specific process for adjusting the positive power distribution is as follows: The charging piles are sorted in descending order based on their comprehensive scores. The product of the comprehensive score percentage of each charging pile after descending order and the difference in output power is used as the basic power allocation for each charging pile after descending order. Sensitivity compensation analysis is performed based on the power base allocation and power adjustment sensitivity of each working charging pile after descending order to obtain the actual power allocation of each working charging pile after descending order.

5. The intelligent load control method for charging pile groups based on dynamic power balancing according to claim 3, characterized in that: The specific process for adjusting the negative power distribution is as follows: The charging piles are sorted in ascending order based on their comprehensive scores. The product of the percentage of the comprehensive score of each charging pile after the ascending order and the absolute value of the difference in output power is used as the power base reduction of each charging pile after the ascending order. A health protection assessment is conducted based on the power load reduction and equipment health of each working charging pile after ascending order, to obtain the actual power load reduction of each working charging pile after ascending order.

6. The intelligent load control method for charging pile groups based on dynamic power balancing according to claim 3, characterized in that: The specific implementation process of the automatic triggering of dynamic reallocation of power budget is as follows: The emergency margin of the target charging station is obtained by multiplying the total output power threshold of the target charging station by the percentage of the total output power corresponding to the emergency margin stored in the database. The power demand of the newly connected device is obtained by comparing the power demand of the newly connected device with the allowed charging time. The power urgency of the newly connected device is obtained by comprehensively processing the power demand and full load power of the newly connected device. Based on the urgency and power demand of the newly connected devices, initial power is allocated from the emergency reserve to the newly connected devices, and the power of the target charging station is gradually readjusted.

7. The intelligent load control method for charging pile groups based on dynamic power balancing according to claim 6, characterized in that: The specific process of triggering the gradual power readjustment of the target charging station is as follows: Based on the working data of the working charging piles corresponding to the newly connected device, the corrected actual output power of the working charging piles corresponding to the newly connected device is generated in the same way as the method of generating the corrected actual output power of each working charging pile. The corrected actual total output power is added to the corrected actual output power of the working charging pile corresponding to the newly connected device to obtain the corrected actual output power of all working charging piles, and this is used as the current total load of the target charging station. The difference between the total output power threshold of the target charging station and the initial power of the newly connected device is used as the updated total power threshold; The difference between the updated total power threshold and the current total load is used as the updated output power difference; The number of permitted adjustment stages is calculated by rounding up the updated output power difference and the maximum allowable adjustment amount for a single adjustment stage stored in the database. Based on the permitted adjustment stage number and the updated output power difference, the power adjustment amount for each adjustment stage is allocated according to the exponential decay curve method, thereby obtaining the power adjustment amount for each adjustment stage.

8. A charging pile group load intelligent control system based on dynamic power balancing, which is used to execute the charging pile group load intelligent control method based on dynamic power balancing as described in any one of claims 1-7.

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