Wind-solar complementary energy storage direct current charging method and system based on liquid cooling heat dissipation

Abstract

The invention discloses a wind-solar complementary energy storage direct current charging method and system based on liquid cooling heat dissipation, and relates to the technical field of energy storage charging. Comprising the following steps: S1, collecting wind-solar complementary energy storage data in real time, and carrying out data preprocessing; s2, converting wind-solar power generation into direct current, judging the flow direction of wind-solar power generation energy, and performing corresponding wind-solar power generation energy transmission power supply; s3, judging the limit of the output power of the charging pile, and controlling and adjusting the output of the charging pile in stages; s4, quantifying the liquid cooling flow required by heat dissipation, and performing heat source heat dissipation on the energy storage system and the charging pile; and S5, carrying out coordinated regulation and control, strategy optimization and multi-dimensional visualization on the flow direction of wind and light power generation energy, charging pile output and heat source heat dissipation. The problems that an existing charging station is difficult to deploy in remote and power transmission difficult areas, high-power charging heat dissipation and energy efficiency bottlenecks are prominent, and the efficiency of traditional air cooling and alternating current conversion is low, so that efficient, safe and green energy supplementation is difficult to achieve are solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of energy storage charging, in particular to a wind-solar complementary energy storage direct current charging method and system based on liquid cooling heat dissipation. BACKGROUND

[0002] With the increasing proportion of intermittent power sources such as wind energy and photovoltaic in the power system, and the widespread deployment of high-power direct current charging facilities, the problems of large fluctuation of charge and discharge power and concentration of equipment thermal load are increasingly prominent, which puts higher requirements on the heat dissipation capacity and operation safety of the charging and energy storage system. At the same time, the rapid popularization of electric vehicles has given rise to an urgent demand for high-efficiency, high-power direct current charging facilities. In the face of the thermal safety challenges brought by wind and solar power fluctuations, uneven charging load peaks and valleys, and high-power charging, liquid cooling thermal management technology has gradually become an important supporting technology for high-end charging equipment and energy storage systems. Liquid cooling systems can significantly improve the heat dissipation capacity and safety of key equipment such as high-power charging piles and energy storage batteries, effectively addressing the problems of charging temperature rise, equipment aging and operation reliability.

[0003] For example, the patent for invention with publication number CN119482875A discloses a battery temperature intelligent dynamic optimization method and system for liquid cooling energy storage cabinet, specifically relating to the technical field of battery temperature dynamic optimization, which includes: real-time acquisition of temperature data set in the battery monitoring area; and real-time acquisition of battery operation evaluation coefficient, analysis of the battery operation evaluation coefficient to determine the operation state of the battery; the operation state of the battery includes discharge state and charging state, respectively generating discharge normal instruction or charging normal instruction; the present application can predict future temperature changes by inputting the temperature data set and the battery operation evaluation coefficient into the pre-constructed neural network model, analyze the temperature changes during discharging and charging according to the generated discharging or charging optimization instructions, and obtain targeted temperature optimization strategies, which is beneficial to dynamically adjusting the cooling or current control strategy according to the specific situation during battery discharging or charging, preventing the problems of battery overheating or low efficiency.

[0004] For example, the invention patent with publication number CN118944255A discloses a transformer residual capacity-based liquid cooling energy storage charging and discharging system and method, which includes a transformer module, an energy storage module, a liquid cooling module, and an intelligent control module. When the energy storage module of the energy storage system is charging, the transformer module is used for step-down, thereby realizing charging of the energy storage module. When the energy storage module is discharging, the electric quantity in the energy storage module is directly used. In this way, the problem that the existing energy storage system cannot effectively utilize the residual capacity of the transformer is solved. The energy waste of the transformer under low load is avoided, and the energy conversion efficiency of the entire energy storage system is improved. The hybrid integer programming algorithm is used to evaluate the electric quantity state of the energy storage module and predict the short-term battery cell health state, thereby improving the use efficiency of the energy storage module and the service life of the battery.

[0005] However, the inherent structural defects of traditional charging stations as the main energy supplement place are increasingly prominent, becoming a bottleneck restricting the high-quality development of the industry. Traditional charging stations rely on the State Grid to realize power transmission, but it is difficult to transmit power to remote areas such as grasslands, plateaus, and islands. Moreover, the use of electricity by traditional charging stations will bring a large electric load, increasing the transmission pressure of the power grid. At the same time, to cope with the severe heat dissipation challenge brought by high-power charging, traditional air cooling technology has been unable to meet the needs.

[0006] Therefore, in view of the above problems, there is an urgent need for a wind-solar complementary energy storage direct current charging method and system based on liquid cooling heat dissipation. SUMMARY

[0007] Technical problems solved

[0008] In view of the deficiencies of the prior art, the present application provides a wind-solar complementary energy storage direct current charging method and system based on liquid cooling heat dissipation, which solves the problem that existing charging stations are difficult to deploy in remote and power transmission difficult areas, and the heat dissipation and energy efficiency problems caused by high-power charging are prominent, the traditional air cooling and alternating current conversion efficiency are low, which leads to the difficulty in meeting the efficient, safe, and green energy supplement demand.

[0009] Technical solutions

[0010] In order to achieve the above object, the application is implemented by the following technical solutions: The wind-solar complementary energy storage direct current charging method based on liquid cooling heat dissipation comprises the following steps: S1, real-time acquisition of wind-solar complementary energy storage data, and time synchronization, denoising and smoothing, abnormality detection, missing value completion and normalization processing of the wind-solar complementary energy storage data; S2, conversion of wind-solar power generation into direct current, and judgment of the flow direction of wind-solar power generation energy based on the preprocessed wind-solar complementary energy storage data, corresponding wind-solar power generation energy transmission power supply according to the flow direction of wind-solar power generation energy, and taking priority power supply, energy supplement and safety protection measures; S3, acquisition of wind-solar complementary energy storage data in the wind-solar power generation energy transmission power supply process, judgment of the limit of charging pile output power, adjustment of charging pile output according to the limit of charging pile output power, and stage control and real-time monitoring of state deviation; S4, in the wind-solar power generation energy transmission power supply process, quantification of the liquid cooling flow required for heat dissipation by using the wind-solar complementary energy storage data of the energy storage system and the charging pile, heat source heat dissipation for the energy storage system and the charging pile according to the liquid cooling flow, and evaluation of the heat dissipation effect; S5, monitoring of the wind-solar complementary energy storage data and the whole process, cooperative regulation of the flow direction of wind-solar power generation energy, charging pile output and heat source heat dissipation, strategy optimization and multi-dimensional visualization.

[0011] Further, the specific process of real-time acquisition of wind-solar complementary energy storage data and time synchronization, denoising and smoothing, abnormality detection, missing value completion and normalization processing of the wind-solar complementary energy storage data is as follows: real-time acquisition of wind-solar complementary energy storage data, which includes wind power, photovoltaic power, charging pile load power, charging pile rated maximum power, energy storage battery power, energy storage battery SOC, energy storage battery surface temperature, energy storage liquid cooling inlet temperature, energy storage loop liquid cooling flow, charging pile surface temperature, charging pile liquid cooling inlet temperature, charging pile loop liquid cooling flow, charging gun interface temperature and cooling liquid specific heat capacity; time synchronization and multi-channel alignment of the wind-solar complementary energy storage data, denoising and smoothing processing of the original wind-solar complementary energy storage data by using Kalman filtering and sliding window mean method; identification of abnormal and sudden change data by using standard deviation outlier detection method and quartile interval method, and missing value completion by linear interpolation; standardization and dimensionless normalization processing of the wind-solar complementary energy storage data; establishment of a wind-solar complementary energy storage database, and storage of the wind-solar complementary energy storage data in the wind-solar complementary energy storage database.

[0012] Further, the wind and light power generation is converted into direct current, and based on the pre-processed wind and light complementary energy storage data, the specific process of judging the flow direction of wind and light power generation energy is: in the wind and light power generation energy collection and confluence process, after all wind power generation and photovoltaic power generation units complete energy conversion, the alternating current of wind power generation and photovoltaic power generation is converted into stable output direct current through inversion rectification and MPPT converter; the wind power generation power and the photovoltaic power generation power are obtained in real time, the wind power generation power and the photovoltaic power generation power are added to obtain the total power generation power; the energy storage battery SOC is obtained, based on the sliding time window, the historical energy storage battery SOC is counted and the mean value is calculated to obtain the target energy storage battery SOC value, the absolute difference between the current energy storage battery SOC and the target energy storage battery SOC value is calculated, and the reciprocal is taken as an exponential power to perform natural exponential operation, and the result of the natural exponential operation is subtracted by a constant to obtain an energy storage adjustment factor; the charging pile load power is obtained, and the product of the total power generation power and the energy storage adjustment factor is divided by the sum of the current charging pile load power and a minimum constant value to obtain an energy flow distribution judgment value.

[0013] Further, according to the flow direction of wind and light power generation energy, corresponding wind and light power generation energy transmission power supply is carried out, and specific processes of taking priority power supply, energy supplement and safety protection measures are: real-time comparison of energy flow distribution judgment value and distribution threshold value, energy flow distribution, when the energy flow distribution judgment value is greater than the distribution threshold value, the wind and light power generation energy flows to the energy storage system; when the energy flow distribution judgment value is less than or equal to the distribution threshold value, the wind and light power generation energy is preferentially dispatched to supply the charging pile, if the wind and light power generation energy is insufficient, the energy storage system is used for energy supplement, if the wind and light power generation energy is excessive, it is transmitted to the energy storage system for storage; real-time monitoring of energy flow distribution result, if the actual energy flow distribution and the direction of energy flow distribution judgment value are detected to be inconsistent, linkage warning is implemented to carry out fault self-checking and direction switching; if the standard deviation of the energy flow distribution judgment value in the sliding time window is greater than the fluctuation threshold value, the safety protection mode is entered, and the load reduction and flow limitation are carried out; all energy flow distribution judgment values and energy flow distribution records are written into the wind and light complementary energy storage database, and based on the historical energy flow distribution judgment value and the actual energy flow distribution effect, the target energy storage battery SOC value is optimized through genetic algorithm.

[0014] Further, the specific process of judging the limit of the output power of the charging pile based on the wind-solar complementary energy storage data in the wind-solar power generation and transmission process is as follows: when the charging pile is powered, the SOC of the energy storage battery is acquired in real time, and the smaller value of the SOC of the energy storage battery and the constant one is selected as the charging progress constraint value; the temperature of the charging gun interface is acquired, the historical charging gun interface temperature is counted based on a sliding time window, and the maximum value is selected to obtain the charging gun temperature limit value; the relative over-temperature ratio is obtained by dividing the difference between the current charging gun interface temperature and the charging gun temperature limit value by the charging gun temperature limit value; the charging safety control value is obtained by multiplying the charging progress constraint value by the product of the relative over-temperature ratio and the temperature weight factor, and then multiplying the sensitivity weight factor; the reciprocal of the charging safety control factor is taken as the exponential power to obtain the comprehensive safety index adjustment value; the comprehensive safety index adjustment value is added to the constant one and the reciprocal is obtained to obtain the charging output suppression coefficient; the rated maximum power of the charging pile is acquired, the rated maximum power of the charging pile is multiplied by the charging output suppression coefficient to obtain the output power limit value of the charging pile.

[0015] Further, the specific process of adjusting the output of the charging pile according to the limit of the output power of the charging pile, controlling in stages and monitoring the state deviation in real time is as follows: the output power limit value of the charging pile is written into the wind-solar complementary energy storage database, and the power upper limit instruction is generated based on the output power limit value of the charging pile and is sent to the charging pile controller in real time to adjust the output power of the charging pile; and the output power limit value of the charging pile is adjusted according to the charging stage during the charging process, that is, the charging stage is divided into the initial stage, the middle stage and the tail stage to realize fast charging in the initial stage, stable charging in the middle stage and trickle charging in the tail stage; the actual output power of the charging pile is collected in real time, and the deviation from the output power limit value of the charging pile is recorded; if the deviation is greater than the deviation threshold, the state self-checking is performed to judge whether the charging pile and the cable are abnormal, and the maintenance and safety warning are linked.

[0016] Further, in the process of wind-solar power generation energy transmission power supply, the specific process of quantifying the required liquid cooling flow is as follows: in the process of wind-solar power generation energy transmission power supply, real-time wind-solar complementary energy storage data of the corresponding heat source, i.e. the energy storage battery and the charging pile, is received; based on a sliding time window, the historical heat source i surface temperature is counted and the maximum value is selected to obtain the maximum allowable temperature of the heat source i, and the historical heat source i loop liquid cooling flow is counted and the minimum value is selected to obtain the heat source i liquid cooling basic flow; the difference between the heat source i surface temperature and the heat source i liquid cooling inlet temperature is multiplied by the heat source i power to obtain the heat source i temperature difference heat load value; the difference between the maximum allowable temperature of the heat source i and the heat source i liquid cooling inlet temperature is multiplied by the specific heat capacity of the cooling liquid to obtain the cooling capacity value of the heat source i; the heat source i heat flow demand ratio is obtained by dividing the heat source i temperature difference heat load value by the heat source i cooling capacity value; the sum of the heat source i heat flow demand ratio and the constant one is subjected to natural logarithm operation, and multiplied by the flow adjustment weight factor to obtain the heat source i adaptive adjustment value; the heat source i adaptive adjustment value is added to the heat source i liquid cooling basic flow to obtain the heat source i liquid cooling flow adjustment value.

[0017] Further, the specific process of cooling the heat source by liquid cooling flow and evaluating the cooling effect is as follows: according to the liquid cooling flow adjustment value, the corresponding flow adjustment instruction is generated and output to the execution element to cool the storage battery pack and the charging pile; according to the liquid cooling flow adjustment value, the circulating guide wheel drives the cooling liquid to flow along the main circulating pipeline, and the cooling liquid enters the single-phase immersion liquid cavity of the storage battery pack through the main loop branch; at the same time, the cooling liquid corresponding to the charging pile enters the single-phase liquid immersion cavity of the charging pile, passes through the current circuit and the external discharge port, and directly cools the charging pile interface; the cooling liquid flowing out of each heat source cavity is unified and flows into the primary liquid storage tank, and is unified and pumped into the ground source heat pump for centralized cooling treatment and flows back to the secondary liquid storage tank; the cooled cooling liquid is driven by the circulating guide wheel and is branched back to each heat source equipment according to the liquid cooling flow adjustment value, and is subjected to closed loop cooling circulation control; the liquid cooling flow adjustment value of the energy storage battery and the charging pile is written into the wind-solar complementary energy storage database, and the cooling process is recorded in real time, and the actual cooling effect is judged and recorded by monitoring the change of the surface temperature of the energy storage battery and the surface temperature of the charging pile.

[0018] Further, the wind-solar complementary energy storage data and the whole process are monitored, the specific process of flow direction of wind-solar power generation, coordinated regulation of charging pile output and heat source heat dissipation, strategy optimization and multi-dimensional visualization is: real-time monitoring of wind-solar complementary energy storage data, tracking energy flow distribution judgment value, charging pile output power limit value, liquid cooling flow regulation value and actual heat dissipation effect trend, using long short-term memory network prediction, reinforcement learning, genetic algorithm and Bayesian optimization algorithm, the strategy of energy flow distribution, charging pile output power regulation and heat dissipation multi-link is optimized, and the distribution threshold is adjusted; a multi-dimensional visualization interface is constructed, the whole process data and state are displayed on a mobile terminal, maintenance suggestions are pushed, remote diagnosis and upgrading are carried out, abnormal early warning and auxiliary decision pushing are realized, combined with automatic repair and operation linkage mechanism, real-time fault handling is realized.

[0019] The second aspect of the application provides a wind-solar complementary energy storage direct current charging system based on liquid cooling heat dissipation, comprising: a wind-solar complementary energy storage data acquisition and processing module, used for real-time acquisition of wind-solar complementary energy storage data, and time synchronization, denoising and smoothing, anomaly detection, missing value completion and normalization processing of the wind-solar complementary energy storage data; a wind-solar energy flow distribution optimization module, used for converting wind-solar power generation into direct current, and judging the flow direction of wind-solar power generation energy based on the preprocessed wind-solar complementary energy storage data, and performing corresponding wind-solar power generation energy transmission power supply according to the flow direction of wind-solar power generation energy, and taking priority power supply, energy supplement and safety protection measures; a direct current intelligent charging control module, used for acquiring wind-solar complementary energy storage data in the wind-solar power generation energy transmission power supply process, judging the limit of charging pile output power, adjusting the charging pile output according to the limit of charging pile output power, and controlling and monitoring the state deviation in stages; a heat dissipation safety regulation module, used for quantifying the liquid cooling flow required for heat dissipation by using the wind-solar complementary energy storage data of the energy storage system and the charging pile during the wind-solar power generation energy transmission power supply process, dissipating heat for the energy storage system and the charging pile according to the liquid cooling flow, and evaluating the heat dissipation effect; an intelligent control visualization module, used for monitoring the wind-solar complementary energy storage data and the whole process, and performing coordinated regulation of the flow direction of wind-solar power generation energy, charging pile output and heat source heat dissipation, strategy optimization and multi-dimensional visualization.

[0020] Advantages

[0021] The application has the following advantages:

[0022] (1) The application realizes the organic integration of wind-solar complementation, energy storage and direct current charging, and realizes real-time acquisition of wind-solar complementary energy storage data, solves the problems of charging station deployment difficulty, unstable power supply in remote and power transmission difficult areas, realizes efficient utilization of green energy on site and independent and reliable power supply, and improves the adaptability of charging facilities.

[0023] (2) This invention, by adopting a full-process multi-source data-driven and energy flow allocation judgment algorithm, can dynamically regulate and optimize the energy allocation of wind and solar power generation, energy storage status and charging load, and adaptively adjust the output power of charging piles, thereby improving the access efficiency of new energy power generation and the intelligent level of charging replenishment.

[0024] (3) This invention significantly improves the high-power heat dissipation capacity and operational safety of energy storage batteries and charging piles by constructing a liquid-cooled safety heat dissipation system and an adaptive liquid-cooled flow rate adjustment method. It effectively overcomes the insufficient heat dissipation capacity of traditional air cooling and the risk of high-temperature operation, and ensures thermal safety and equipment lifespan in high-power fast charging scenarios.

[0025] (4) This invention, through an intelligent control visualization platform and a big data self-learning optimization mechanism, realizes full-process online monitoring, intelligent optimization and visualization decision-making of multiple links such as energy flow distribution, charging output and thermal management, improves operation and maintenance efficiency and system safety and intelligence level, and provides solid technical support for new green energy and smart transportation infrastructure.

[0026] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0027] Figure 1 This is a flowchart of a DC charging method for wind-solar hybrid energy storage based on liquid cooling.

[0028] Figure 2 This is a block diagram of a wind-solar hybrid energy storage DC charging system based on liquid cooling.

[0029] Figure 3 Workflow diagram for integrated charging stations combining wind and solar power;

[0030] Figure 4 This is a schematic diagram of the charging controller's working principle.

[0031] Figure 5 Diagram of the working system of a wind-solar hybrid integrated charging station;

[0032] Figure 6 This is a schematic diagram of the working principle of a liquid cooling thermal management system.

[0033] Figure 7 Schematic diagram of the liquid cooling device for a charging pile with a liquid-cooled thermal management system;

[0034] Figure 8 Diagram of the liquid cooling device for the energy storage module of the liquid-cooled thermal management system;

[0035] Figure 9 A three-dimensional relationship diagram for adaptive adjustment of liquid cooling flow rate.

[0036] In the diagram, 1 is the signal control facility; 2 is the current line; 3 is the external discharge port; 4 is the single-phase liquid immersion chamber of the charging pile; 5 is the cold water immersion chamber; 6 is the cold water inlet; 7 is the cold water outlet; 8 is the circulating guide wheel; 9 is the energy storage battery pack; 10 is the single-phase immersion liquid inlet; 11 is the single-phase immersion liquid outlet; and 12 is the single-phase immersion liquid chamber of the energy storage battery pack. Detailed Implementation

[0037] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. As those skilled in the art will understand, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0038] Please see Figures 1-9 This invention provides a technical solution: a DC charging method and system for wind-solar hybrid energy storage based on liquid cooling, such as... Figure 1 As shown, the process includes the following steps: S1, real-time acquisition of wind-solar hybrid energy storage data, and time synchronization, noise reduction and smoothing, anomaly detection, missing value completion, and normalization processing of the wind-solar hybrid energy storage data; S2, conversion of wind and solar power generation into DC power, and based on the pre-processed wind-solar hybrid energy storage data, determination of the energy flow direction of wind and solar power generation, and corresponding wind and solar power energy transmission and power supply according to the energy flow direction, and implementation of priority power supply, energy replenishment, and safety protection measures; S3, acquisition of wind-solar hybrid energy storage data during the wind and solar power energy transmission and power supply process, and determination of… The charging pile output power limit is adjusted according to the charging pile output power limit, and the state deviation is monitored in stages and in real time; S4, during the wind and solar power generation energy transmission and power supply process, the liquid cooling flow required for heat dissipation is quantified by using the wind and solar complementary energy storage data of the energy storage system and the charging pile, and heat dissipation of the energy storage system and the charging pile is carried out according to the liquid cooling flow, and the heat dissipation effect is evaluated; S5, the wind and solar complementary energy storage data and the whole process are monitored, and the flow of wind and solar power generation energy, the coordinated control of charging pile output and heat source heat dissipation, strategy optimization and multi-dimensional visualization are carried out.

[0039] Specifically, the process of real-time acquisition of wind-solar hybrid energy storage data, followed by time synchronization, noise reduction and smoothing, anomaly detection, missing value completion, and normalization, involves: Connecting to both wind and solar power systems, utilizing multiple types of sensors including current sensors, voltage sensors, temperature sensors, flow meters, and the energy storage system's embedded SOC measurement unit to achieve end-to-end data acquisition across multiple stages of power generation, energy storage, and thermal management; simultaneously, engineering input of physical characteristic parameters such as the charging pile's rated maximum power and the coolant's specific heat capacity; real-time acquisition of wind-solar hybrid energy storage data, including: wind power generation, photovoltaic power generation, charging pile load power, charging pile rated maximum power, energy storage battery power, energy storage battery SOC, energy storage battery surface temperature, energy storage liquid cooling inlet temperature, energy storage loop liquid cooling flow rate, charging pile surface temperature, charging pile liquid cooling inlet temperature, charging pile loop liquid cooling flow rate, charging gun interface temperature, and coolant specific heat capacity; and time synchronization and multi-channel alignment of the wind-solar hybrid energy storage data, specifically including the alignment of data from different sensors. The data stream of the device is timestamped and a network time protocol is used to ensure that all channel data are aligned at the same acquisition time, achieving synchronization and consistency of multidimensional data. Kalman filtering and sliding window mean method are used to denoise and smooth the raw wind-solar hybrid energy storage data to improve the real-time performance and accuracy of the data. The standard deviation outlier detection method and the interquartile range method are used to identify abnormal and abrupt data. The standard deviation outlier detection method identifies outliers that deviate significantly from the mean by calculating the standard deviation distance between each data set and its mean. The interquartile range method detects extreme outliers far from the main distribution range by using the quartiles of the statistical data distribution, which is suitable for anomaly detection scenarios of non-normally distributed data. Linear interpolation is used to fill in missing values ​​to ensure the continuity and usability of the data sequence after completion. The wind-solar hybrid energy storage data is standardized and dimensionless normalized. A wind-solar hybrid energy storage database is established to support high-frequency time-series data writing, structured indexing and multidimensional retrieval. The wind-solar hybrid energy storage data is stored in the wind-solar hybrid energy storage database to provide a high-quality data foundation for subsequent stages.

[0040] like Figure 3The diagram shows the workflow of a wind-solar hybrid integrated charging station. The upper layer represents the wind-solar hybrid power generation system, comprising a wind power system, a solar power system, and a wind-solar hybrid power generation controller. This system efficiently converts wind and solar energy into DC power and centrally schedules and optimizes the allocation of wind and solar energy through the wind-solar hybrid controller, ensuring maximum and stable energy input from the renewable energy source. The middle layer is the charging controller, which acts as the energy scheduling hub. Based on external electricity demand, energy storage status, and generation capacity, it determines the flow of wind and solar power in real time: prioritizing power supply to external charging piles or replenishing the energy storage system. It can also dynamically switch the energy supply path between the energy storage system and external loads. The energy storage system serves as an energy transfer and buffer, absorbing excess wind and solar power or releasing energy to supplement power when generation is insufficient, supporting peak electricity demand and emergency needs. The control system achieves intelligent closed-loop regulation of energy flow allocation, charging strategy, energy storage management, and thermal management. Through real-time data acquisition and analysis, it intelligently decides the operating conditions of each subsystem to achieve optimal operation. The thermal management system employs liquid cooling to efficiently dissipate heat from high-heat units in the energy storage and charging stages, such as the battery pack and charging station, significantly improving charging safety and operational efficiency. The external charging system, namely the fast DC charging station for external users, receives energy after energy flow distribution to complete efficient DC fast charging of the vehicle.

[0041] In this implementation plan, high-precision, full-coverage real-time data acquisition is carried out on key links of the entire chain of wind power generation, photovoltaic power generation, energy storage system and liquid cooling heat dissipation. At the same time, time synchronization, noise reduction, anomaly detection, missing value completion, standardization and normalization processing methods are adopted to ensure high consistency and high quality of wind-solar hybrid energy storage data. Finally, high-quality, structured wind-solar hybrid energy storage data is stored in the wind-solar hybrid energy storage database, which improves the data consistency of the whole process and the accuracy and reliability of subsequent links.

[0042] Specifically, the process of converting wind and solar power into direct current (DC) and determining the energy flow direction based on pre-processed wind-solar hybrid energy storage data is as follows: During the energy acquisition and aggregation process, after all wind and solar power units complete their energy conversion, the AC power from wind and solar power is converted into stable DC output via inverter rectification and MPPT converter. This ensures the continuity of output DC voltage and current and maximizes the utilization rate of new energy sources, adapting to the efficient DC power supply needs of subsequent DC combiner boxes, energy storage, and charging. The MPPT converter is a maximum power point tracking converter. Real-time acquisition of wind and solar power output is used to sum the total power output, representing the comprehensive energy flow input from the entire wind and solar power field. This information is then used for subsequent energy distribution and... The system provides a foundation for energy flow direction determination. It acquires the State of Charge (SOC) of the energy storage battery, reflecting the remaining percentage of charge. Based on a sliding time window, it statistically analyzes historical SOC data and calculates the average to obtain the target SOC value, which serves as a scheduling reference. It calculates the absolute difference between the current and target SOC values ​​and uses the inverse as the exponent for natural exponential calculation to achieve nonlinear sensitivity control. Subtracting the natural exponential calculation result from a constant yields the energy storage adjustment factor, quantifying the real-time adjustment capability of the energy storage system in energy flow allocation. It also acquires the charging pile load power, reflecting the actual demand for current charging load. The energy flow allocation judgment value is obtained by dividing the product of the total power generation and the energy storage adjustment factor by the sum of the current charging pile load power and a minimum constant value, where the minimum constant is used to prevent abnormal situations caused by a zero denominator.

[0043] The specific formula for the energy flow allocation judgment value is as follows:

[0044] ;

[0045] In the formula, The energy flow allocation judgment value is used to determine the energy flow allocation decision. That is, by combining the current wind and solar power generation capacity, the SOC state of the energy storage battery and the external load power, it is determined whether the energy should be prioritized to flow to the energy storage or to charge the external load. The larger the energy flow allocation judgment value, the more priority is given to replenishing the energy storage. The smaller the energy flow allocation judgment value, the more priority is given to discharging the external load. Indicates wind power generation capacity; Indicates photovoltaic power generation capacity; It represents the total power generation capacity, which is the total wind and solar power generation capacity that the entire system can dispatch at the current moment. It is a direct reflection of the current energy supply capacity and reflects how much energy is available for distribution. It is the basis for judging the energy flow allocation value. Indicates the state of charge (SOC) of the energy storage battery; Indicates the target SOC value of the energy storage battery; The energy storage adjustment factor reflects the degree of deviation between the current SOC of the energy storage battery and the target SOC. The greater the deviation, the greater the energy storage adjustment factor, indicating that energy storage needs to be replenished urgently. The smaller the deviation, the smaller the energy storage adjustment factor, indicating that energy storage does not need to be replenished. This indicates the load power of the charging pile. When the load is large, the denominator increases and the energy flow allocation judgment value decreases, tending to prioritize meeting the external load. When the load is small, the denominator is small and the energy flow allocation judgment value increases, prioritizing supplementary energy storage. Represents a very small constant value, taking values ​​of This prevents the denominator from being zero and ensures stable calculations.

[0046] like Figure 4 The diagram shows the working principle of the charging controller. The charging controller is essentially a power electronic conversion system. In the diagram, the wind power section uses a rectifier and voltage regulator AC-DC converter to convert unstable alternating current into fluctuating direct current. The solar power section uses an MPPT circuit to dynamically capture maximum solar power and output fluctuating DC. The MPPT controller's intelligent algorithm always ensures that the photovoltaic modules operate at their maximum power point, maximizing solar energy utilization. The two fluctuating DC currents converge at the unstable DC bus, forming a unified DC energy pool. Downstream, a DC-DC converter and a boost / buck voltage regulator accurately convert the fluctuating DC current on the bus into DC current at the target voltage level to suit the energy storage battery and load requirements. The final DC-DC regulator ensures that the DC current supplied to the load and energy storage is absolutely stable, eliminating the impact of voltage and current disturbances on the downstream system and achieving high-quality DC power supply. Among them, the multi-stage DC-DC conversion and voltage regulation ensure that even if the power generation side fluctuates greatly, the downstream load and energy storage side obtain high-quality DC power; the inverter, rectification and voltage regulation process effectively shields the current and voltage fluctuations on the new energy side, greatly improving safety and compatibility.

[0047] In this implementation scheme, an inverter-rectifier and a maximum power point tracking converter achieve efficient DC-DC conversion of AC energy from wind and solar power generation, providing a continuous, stable, and maximized foundation for new energy DC power supply for subsequent energy storage and charging systems. Using the historical average SOC of the energy storage battery based on a sliding window, combined with the current SOC state, a nonlinear exponential calculation is performed to obtain the energy storage adjustment factor, enabling the energy storage system to adaptively regulate energy flow allocation. By real-time aggregation of total wind and solar power generation and charging pile load power, the calculation of the energy flow allocation judgment value effectively correlates the states of each link in the power generation, energy storage, and charging load processes. Furthermore, by utilizing a minimal constant to avoid a zero denominator, the consistency of data, the stability of the algorithm, and the intelligence level of energy allocation during the energy flow process are comprehensively improved.

[0048] Specifically, the process of transmitting and supplying wind and solar power according to the flow of wind and solar energy, and taking priority power supply, energy replenishment, and safety protection measures, is as follows: The energy flow allocation judgment value and allocation threshold are compared in real time to allocate energy flow. When the energy flow allocation judgment value is greater than the allocation threshold, the wind and solar energy flows to the energy storage system. This involves controlling the energy management module to prioritize charging the energy storage battery pack, achieving local energy storage and efficient utilization. When the energy flow allocation judgment value is less than or equal to the allocation threshold, wind and solar energy is prioritized for supplying the charging pile. The energy flow path is switched to the charging pile circuit to prioritize power supply to the external load of the charging pile. If the wind and solar energy is insufficient, the energy storage system replenishes the energy. The energy storage battery pack monitors the SOC status of the energy storage battery in real time and releases electricity as needed to supplement the load demand, ensuring stable charging power. If there is excess wind and solar energy, it is transferred to the energy storage system for storage, achieving energy redundancy. It absorbs and improves the renewable energy consumption rate and system safety redundancy; it monitors energy flow distribution results in real time. If the actual energy flow distribution does not match the direction of the energy flow distribution judgment value, it triggers an early warning, performs fault self-checks, and switches the direction. Specifically, it triggers an energy flow anomaly alarm, automatically diagnoses the status of switches, cables, and power electronic equipment, and switches the energy flow direction through the control system according to the fault to ensure safe and stable operation of the power supply; if the standard deviation of the energy flow distribution judgment value within the sliding time window is found to be greater than the fluctuation threshold, it enters the safety protection mode to reduce load and limit current. That is, when the fluctuation is abnormal, it automatically lowers the load power limit and limits the charging output to prevent overload and system instability, and prioritizes the safety of equipment and personnel; it writes all energy flow distribution judgment values ​​and energy flow distribution records into the wind-solar hybrid energy storage database, and optimizes the SOC value of the target energy storage battery through a genetic algorithm based on the historical energy flow distribution judgment values ​​and the actual energy flow distribution effect.

[0049] like Figure 5The diagram shows the working system of a wind-solar hybrid integrated charging station. Using wind turbines, generators, and solar panels as the front end, it efficiently collects wind and solar energy. The energy is then converted from AC to DC or vice versa by power electronic units of AC-DC and DC-DC converters, respectively, into stable DC power. This DC power is then collected by a DC combiner box to form a DC bus, supplying power to downstream energy storage and charging systems. A wind-solar hybrid controller enables intelligent coordinated scheduling of multiple components, including wind and solar power generation units, energy storage units, and charging units. It automatically optimizes wind and solar priorities and achieves maximum power point tracking and intelligent switching of wind and solar energy flow allocation. The control system, energy storage system, charging system, and thermal management system are deeply integrated. They collect real-time wind-solar hybrid energy storage data and output energy flow allocation, charging power allocation, and heat dissipation flow adjustment commands based on algorithms, forming a data-driven and closed-loop control system across the entire chain. The thermal management system implements liquid cooling active heat dissipation for key energy storage and charging components, ensuring safe equipment operation and thermal stability during the charging process. The entire process supports multi-dimensional parameter monitoring, coordinated optimization of energy flow and heat dissipation, and features anomaly warning, automatic load limiting, and a safety mechanism linked to operation and maintenance. Overall, through a highly integrated and intelligent wind-solar hybrid and DC fast charging fusion architecture, it effectively solves the problem of efficient, safe, and green energy replenishment in remote and high-demand scenarios.

[0050] In this implementation plan, the dynamic allocation and flexible switching of wind and solar power generation between the energy storage system and charging piles are achieved through intelligent comparison of energy flow allocation judgment values ​​and allocation thresholds, ensuring efficient consumption of new energy and priority replenishment of terminal loads. It features multiple safety mechanisms, including real-time monitoring of energy flow anomalies, fault self-diagnosis and direction switching, and abnormal fluctuation load limiting protection. Furthermore, through full-process data recording and genetic algorithm self-learning optimization of the target SOC, the energy flow and operation strategy continuously evolve adaptively, effectively improving data consistency, system energy efficiency, and operational safety.

[0051] Specifically, the process of acquiring wind-solar hybrid energy storage data during the wind-solar power transmission and supply process to determine the limit of the charging pile's output power is as follows: When supplying power to the charging pile, the SOC of the energy storage battery is acquired in real time. This SOC measurement unit embedded in the energy storage system accurately detects the battery's current remaining charge percentage. The SOC is then compared with a constant, and the smaller value is selected as the charging progress constraint value to prevent overcharging and ensure operational safety. The charging gun interface temperature is acquired to comprehensively monitor the thermal safety risks at the connection between the charging gun and the vehicle. Based on a sliding time window, historical charging gun interface temperatures are statistically analyzed, and the maximum value is selected to obtain the charging gun temperature limit, which serves as a dynamic safety threshold to determine whether the charging gun is currently in a high-temperature risk state. The difference between the current charging gun interface temperature and the charging gun temperature limit is divided by the charging gun temperature limit to obtain the charging gun temperature limit. The relative over-temperature ratio reflects the safety margin of the current temperature compared to historical extremes. The charging safety control value is obtained by multiplying the relative over-temperature ratio by the temperature weighting factor and the charging progress constraint value, and then multiplying this by the sensitivity weighting factor. This value serves as the input for the next step of nonlinear safety suppression. The negative of the charging safety control factor is used as the exponent for natural exponential calculation (i.e., an exponential function with base e). By constructing a sigmoid-type nonlinear suppression mechanism, adaptive suppression of charging power when risk increases is achieved, resulting in a comprehensive safety index adjustment value. This comprehensive safety index adjustment value is added to a constant and its reciprocal is taken to obtain the charging output suppression coefficient. The rated maximum power of the charging pile is obtained as the engineering nominal parameter of the charging pile equipment. The rated maximum power of the charging pile is multiplied by the charging output suppression coefficient to obtain the charging pile output power limit value, realizing dynamic and phased safety control of the charging power.

[0052] The specific formula for the output power limit of the charging pile is as follows:

[0053] ;

[0054] In the formula, This represents the maximum output power limit of the charging pile. It takes into account two key safety parameters, namely the SOC of the energy storage battery and the temperature of the charging gun, and dynamically calculates the maximum power that the charging pile can output at this moment through a sigmoid suppression function, thereby achieving an automatic balance between efficient charging and thermal safety risks. This indicates the rated maximum power of the charging pile, the maximum output power of the equipment, and the theoretical limit. This indicates the SOC of the energy storage battery, reflecting the current charging progress and how close the battery is to being fully charged. The larger the value, the closer it is to full charge, and the more significant the power suppression. Compared with a constant, it ensures that the battery is not overcharged. This indicates the current temperature of the charging gun interface, reflecting the real-time thermal safety status. This indicates the charging gun temperature limit, which measures the safe temperature threshold of the charging gun. This represents the relative over-temperature ratio, reflecting the proportion of the current charging gun temperature exceeding the safety threshold. If the temperature is too high, the weight will be amplified, leading to increased power suppression. This represents the comprehensive safety index adjustment value, which smoothly reduces the power as needed. When the SOC of the energy storage battery is low and the temperature of the charging gun interface is low, the index approaches 1 and the output power is close to the maximum. When the SOC of the energy storage battery approaches 1 and the temperature of the charging gun interface exceeds the standard, the index increases sharply and the overall power is significantly suppressed. The temperature weighting factor is determined by fitting the historical SOC of the energy storage battery, the temperature of the charging gun interface, the load power of the charging pile, and the actual output power of the charging pile using the least squares regression algorithm. The value ranges from 0.1 to 2. The sensitivity weighting factor is derived from the historical charging gun interface temperature variation and the corresponding actual charging pile output power. It is obtained by fitting the sensitivity weighting factor using a regression analysis algorithm, and its value ranges from 0.5 to 2.

[0055] This implementation scheme achieves high-frequency acquisition and unified time-series alignment of multi-dimensional key data on the SOC of the energy storage battery and the temperature of the charging gun interface. It constructs algorithms for sliding windows, dynamic temperature limit filtering, weight factor sensitivity adjustment, and nonlinear exponential suppression, effectively improving the adaptability and precision of charging safety constraints. It can dynamically correct the output power limit of the charging pile according to the actual operating conditions, preventing overcharging and overheating risks, and improving the safety and reliability of the charging system.

[0056] Specifically, the process of adjusting the charging pile output according to the charging pile's output power limit, and controlling and monitoring the state deviation in stages, is as follows: The charging pile output power limit value is written into the wind-solar hybrid energy storage database. Based on the charging pile output power limit value, a power upper limit command is generated and sent to the charging pile controller in real time to precisely control the output current and voltage of the charging module, thereby adjusting the charging pile output power. Furthermore, during the charging process, the charging pile output power limit value is adjusted according to the charging stage, dividing the charging stage into initial, middle, and final stages to achieve initial fast charging, middle stable charging, and final trickle charging. When the energy storage battery's SOC is less than 30%, it enters the initial fast charging stage. At this time, the battery is in a low charge region and can safely withstand high-current fast charging. Simultaneously, the maximum power output limit is set to improve charging speed and energy injection efficiency. When the energy storage battery's SOC is in the 30%–80% range, it enters the middle stable charging stage. During the charging phase, considering the gradual decrease in battery electrochemical activity and the increase in internal impedance, the output power limit of the charging pile is reduced to achieve steady-state medium-speed charging, balancing safety and charging efficiency. When the SOC of the energy storage battery is higher than 80%, it enters the tail-end trickle charging phase. At this time, to suppress the risk of overcharging, cell temperature rise, and lithium plating at the end, the output power limit of the charging pile is further reduced, and a small current trickle charging is adopted to improve the safety of the end charging and extend battery life. During the charging process, the rate of change of the surface temperature of the energy storage battery and the temperature of the charging gun interface are monitored in real time. If the rate of change is higher than the change threshold, the output power limit of the charging pile is temporarily reduced regardless of the SOC stage of the energy storage battery, and the charging mode is switched to the next level in advance, realizing adaptive charging stage adjustment based on safety redundancy. In each charging stage, the output power limit of the charging pile is dynamically adjusted to adapt to the energy management needs of different stages. The actual output power of the charging pile is collected in real time by a high-precision power meter, and the deviation from the output power limit of the charging pile is recorded. If the deviation is greater than the deviation threshold, a status self-check is performed to determine whether the charging pile has a fault or cable abnormality. If there is an abnormality, maintenance and safety warnings are triggered.

[0057] This implementation plan achieves precise management and safety protection of charging pile output power through phased dynamic power regulation and real-time deviation monitoring throughout the entire process. It not only intelligently switches between fast charging, steady charging, and trickle charging modes based on the charging stage to maximize charging efficiency and battery safety, but also frequently collects actual power data, compares it with limit values ​​in real time, and automatically triggers fault self-checks and safety warnings, ensuring data consistency, operational stability, and timely maintenance. This effectively reduces the risks of overcharging, overheating, and malfunctions, comprehensively improving the safety, intelligence, and traceability of the charging process.

[0058] Specifically, during the power transmission and supply process of wind and solar power generation, the process of quantifying the liquid cooling flow rate required for heat dissipation using wind-solar complementary energy storage data from the energy storage system and charging pile is as follows: During the process of wind and solar power generation supplying power to the energy storage system and charging pile, real-time data from the corresponding heat sources, namely the energy storage battery and the charging pile, is received; based on a sliding time window, historical surface temperatures of heat source i are statistically analyzed, and the maximum value is selected to obtain the maximum allowable temperature of heat source i, which serves as the safety threshold for the thermal management system to prevent overheating; simultaneously, historical liquid cooling flow rates of heat source i are statistically analyzed, and the minimum value is selected to obtain the basic liquid cooling flow rate of heat source i, serving as the minimum flow rate requirement to ensure the bottom line of heat dissipation; the difference between the surface temperature of heat source i and the liquid cooling inlet temperature of heat source i is multiplied by the power of heat source i to obtain the temperature difference heat load value of heat source i, reflecting the actual heat load generated by the heat source per unit time; the maximum allowable temperature of heat source i is multiplied by the liquid cooling inlet temperature of heat source i... The difference is multiplied by the specific heat capacity of the coolant to obtain the cooling capacity value of heat source i. Specific heat capacity is a physical parameter of the coolant, used to characterize the amount of heat required for a unit mass of coolant to absorb a unit temperature increase. The cooling capacity value of heat source i reflects the maximum heat load that the coolant can bear at the current inlet temperature. The heat load value of heat source i is divided by the cooling capacity value of heat source i to obtain the heat flow demand ratio of heat source i. The natural logarithm is performed on the sum of the heat flow demand ratio of heat source i and a constant to enhance the sensitivity to low and high load conditions and prevent lag in heat dissipation regulation under high load. It is then multiplied by the flow regulation weighting factor to obtain the adaptive adjustment value of heat source i, reflecting the flexible control capability of liquid cooling heat dissipation. The adaptive adjustment value of heat source i is added to the liquid cooling base flow rate of heat source i to obtain the liquid cooling flow rate adjustment value of heat source i. As the target flow command, it directly drives the actuator to dynamically allocate the coolant flow rate, realizing heat source classification, on-demand and precise heat dissipation.

[0059] The specific formula for adjusting the liquid cooling flow rate of heat source i is as follows:

[0060] ;

[0061] In the formula, This represents the liquid cooling flow rate adjustment value of heat source i, which realizes the adaptive adjustment of liquid cooling flow rate of energy storage battery and charging pile. It dynamically and in a closed loop balances the actual heat generation demand of heat source and liquid cooling heat carrying capacity, thereby ensuring the safety of heat source temperature, improving cooling efficiency, avoiding pump energy waste, and realizing on-demand cooling and automatic optimization thermal management strategy. This indicates the basic flow rate of the liquid cooling source i, ensuring that there is always a basic circulation flow rate to prevent cooling interruption under extreme low loads. It is the minimum safe flow rate guarantee. This represents the power of the heat source i, reflecting the actual heat generated by the energy storage battery and charging pile at this moment, and is the direct physical basis for cooling requirements; It indicates the surface temperature of heat source i, monitors the thermal status of energy storage batteries and charging piles, and promptly detects overheating risks. The liquid cooling inlet temperature of heat source i represents the actual temperature of the coolant entering the battery pack 9 and the charging pile circuit, and is a key point for evaluating temperature difference and cooling effect. This indicates the maximum allowable temperature of heat source i, ensuring that cooling adjustments do not exceed safe limits; it is an automatic protection threshold. It represents the specific heat capacity of the coolant, which characterizes the heat that a unit volume of coolant can carry away, and is a fundamental physical parameter that affects flow regulation; The flow rate adjustment weight factor is obtained by fitting data on charging pile load power, energy storage battery power, energy storage battery surface temperature, energy storage liquid cooling inlet temperature, energy storage loop liquid cooling flow rate, charging pile surface temperature, charging pile liquid cooling inlet temperature, and charging pile loop liquid cooling flow rate through a multiple linear regression algorithm, with a value range between 0.3 and 3. This represents the heat load value of heat source i due to temperature difference, quantifies the heat that the energy storage battery pack 9 and the charging pile need to be removed at this moment, and directly reflects the size of the heat load. This represents the cooling capacity value of heat source i, and is used to calculate the maximum heat load that the liquid coolant can theoretically withstand at the current inlet temperature, thus calibrating its cooling potential. This represents the ratio of heat source i to heat flow demand, directly comparing actual demand with cooling capacity, reflecting whether the flow rate needs to be increased, or whether the current flow rate is sufficient.

[0062] In this embodiment, Table 1 is a data table of liquid cooling flow rate adjustment values. The liquid cooling base flow rate is set to 12, the maximum allowable temperature is set to 55, the flow rate adjustment weight factor is 3, and the coolant specific heat capacity is 4.18. The table details the heat source power, heat source surface temperature, heat source liquid cooling inlet temperature, and heat source liquid cooling flow rate adjustment values ​​corresponding to five different heat source operating conditions. Among them, the heat source power corresponding to heat source operating condition 1 is 42, the heat source surface temperature is 48.5, the heat source liquid cooling inlet temperature is 32, and the heat source liquid cooling flow rate adjustment value is 18.32; the heat source power corresponding to heat source operating condition 2 is 38, the heat source surface temperature is 46.0, and the heat source liquid cooling inlet temperature is 3... 0.5, the heat source liquid cooling flow rate adjustment value is 17.73; the heat source power corresponding to heat source condition 3 is 52, the heat source surface temperature is 53.0, the heat source liquid cooling inlet temperature is 36.0, and the heat source liquid cooling flow rate adjustment value is 19.49; the heat source power corresponding to heat source condition 4 is 30, the heat source surface temperature is 44.0, the heat source liquid cooling inlet temperature is 28.0, and the heat source liquid cooling flow rate adjustment value is 16.98; the heat source power corresponding to heat source condition 5 is 56, the heat source surface temperature is 54.5, the heat source liquid cooling inlet temperature is 40.0, and the heat source liquid cooling flow rate adjustment value is 19.91.

[0063] Table 1. Liquid Cooling Flow Rate Adjustment Data

[0064]

[0065] like Figure 9The figure shows a three-dimensional relationship diagram of adaptive liquid cooling flow rate adjustment. It illustrates the influence of heat source power, heat source surface temperature, and liquid cooling inlet temperature on the liquid cooling flow rate adjustment value under different heat source operating conditions. Each point in the figure represents a set of actual operating condition data, with coordinates representing heat source power, heat source surface temperature, and the corresponding liquid cooling flow rate adjustment value, respectively. The color of the point indicates the level of the liquid cooling inlet temperature. (Based on Table 1 and...) Figure 9 It can be seen that as the heat source power and surface temperature increase, the liquid cooling flow rate adjustment value generally shows an upward trend, meaning that under high heat load and high temperature conditions, the liquid cooling flow rate will be actively increased to enhance the heat dissipation effect. Meanwhile, the higher the liquid cooling inlet temperature (i.e., the more purplish the color), the slightly higher the corresponding flow rate adjustment value, indicating that the inlet temperature has a certain influence on the heat dissipation flow rate setting. Furthermore, the adaptive flow rate adjustment results under different operating conditions can better match the actual cooling requirements of the heat source, achieving precise and flexible thermal management control.

[0066] This implementation scheme dynamically quantifies the actual heat dissipation requirements of each heat source under different operating conditions. Combining temperature difference heat load values, cooling capacity values, and flow rate adjustment weighting factor parameters, a nonlinear adjustment algorithm is used to generate liquid cooling flow rate adjustment values, achieving graded, on-demand, and precise liquid cooling heat dissipation control. This effectively prevents thermal runaway and localized overheating, improves equipment operational safety and heat dissipation efficiency, and provides a solid guarantee for the efficient and safe operation of charging and energy storage processes.

[0067] Specifically, the process of heat dissipation for the energy storage system and charging pile based on liquid cooling flow rate and evaluating the heat dissipation effect is as follows: A corresponding flow regulation command is generated based on the liquid cooling flow rate adjustment value and output to the actuators, including the pump and electronic regulating valve flow control device, to dissipate heat from the energy storage battery pack 9 and the charging pile. Based on the liquid cooling flow rate adjustment value, the circulating guide wheel 8 pushes the coolant along the main circulation pipeline, forming an efficient cooling circuit. The coolant is then diverted through the main circuit into the single-phase immersion liquid chamber 12 of the energy storage battery pack, achieving full-surface liquid cooling of the energy storage module and improving heat dissipation efficiency and temperature uniformity. Simultaneously, the coolant corresponding to the charging pile enters the single-phase liquid immersion chamber 4 of the charging pile and passes through the current circuit. 2 and external discharge port 3 provide direct liquid cooling for the charging pile interface, minimizing the risk of localized high temperatures and thermal runaway during charging. The single-phase immersion liquid chamber employs a high-strength sealing structure, with the chamber shell made of high-polymer composite materials. The interface area uses multi-layer sealing rings and precision flange connections to reliably protect against high temperatures, coolant leakage, and humid environments. Simultaneously, the internal flow guidance design of the single-phase immersion liquid chamber ensures that the coolant fully covers the surface of the heating element on the main charging current line and the external discharge port, preventing heat accumulation in dead zones. The sealed chamber design also ensures easy maintenance and replacement, and compatibility with mainstream coolant types to prevent material aging and chemical corrosion, thus improving overall reliability and lifespan. The coolant flowing out of each heat source cavity is uniformly collected and enters the primary storage tank for temporary buffering and mixing of high-temperature coolant. It is then pumped into the ground source heat pump, i.e., the underground cold source heat exchange system, for centralized cooling and flows back to the secondary storage tank. The secondary storage tank is used for low-temperature coolant storage. The cooled coolant is driven by the circulation guide wheel 8 and distributed back to each heat source device according to the liquid cooling flow rate adjustment value, performing closed-loop heat dissipation cycle control. The liquid cooling flow rate adjustment values ​​of the energy storage battery and charging pile are written into the wind-solar hybrid energy storage database, and the heat dissipation process is recorded in real time. The actual heat dissipation effect is judged and recorded by monitoring the changes in the surface temperature of the energy storage battery and the surface temperature of the charging pile. If the temperature is detected to be below the safe range or there is an abnormal temperature rise, the flow rate is increased and the heat dissipation strategy is adjusted to ensure the continuous stability of the thermal safety and cooling performance.

[0068] like Figure 6The diagram shows the working principle of the liquid-cooled thermal management system. It illustrates the complete circulation process and core components of the system, demonstrating the intelligent circulating heat dissipation mechanism of compartmentalization, mixing, heat exchange, and re-distribution. Both the energy storage module and the charging pile adopt a single-phase immersion liquid cooling structure, meaning the heat-generating components are directly immersed in a high-heat-capacity coolant, achieving efficient and uniform heat dissipation. As the energy storage module and charging pile generate heat during operation, the coolant absorbs this heat, increasing its temperature to a high-temperature immersion liquid. This high-temperature reflux liquid then flows into a primary high-temperature reflux tank for temporary collection and buffering. After being uniformly mixed within the tank, the primary high-temperature reflux liquid is transported via pipeline to the ground source heat pump heat exchange unit. Through heat exchange with the underground cold source, the liquid temperature is rapidly reduced, forming a low-temperature reflux liquid. Driven by a pump, the low-temperature reflux liquid re-enters the circulation pipeline, supplying the single-phase immersion liquid chambers of the energy storage module and charging pile respectively, achieving continuous and efficient closed-loop heat dissipation. Throughout the entire cycle, the liquid cooling flow rate can be adjusted based on real-time liquid cooling flow rate settings, ensuring that the equipment temperature rise does not exceed limits while also improving energy efficiency and thermal safety. This highlights the high-efficiency heat exchange capability, energy recovery, and intelligent control of the liquid cooling system, providing advanced temperature control protection for high-power charging and energy storage scenarios.

[0069] like Figure 7 The diagram shows the liquid cooling device of the charging pile's liquid-cooled thermal management system. It illustrates the core structure and fluid path of the system. Signal control facility 1 and current line 2 jointly handle power transmission and status feedback for the charging pile, enabling real-time monitoring and coordinated control. Signal control facility 1 is the signal acquisition unit for sensors, as well as the linkage controller for electronic valves and pumps. The external discharge port 3 demonstrates the direct liquid cooling arrangement of the charging pile interface. Coolant from the main circulation flows around the external discharge port 3 through pipelines, directly cooling heat-generating points such as the charging gun, thereby greatly reducing the risk of thermal runaway and improving safety margins. The single-phase liquid-cooled immersion chamber of the charging pile is a high-power-density area, where coolant fully covers the module surface, improving heat dissipation efficiency and temperature uniformity. The cold water immersion chamber 5, cold water inlet 6, and cold water outlet 7 indicate the inflow and outflow of the liquid cooling fluid and the location of the chamber. Coolant enters through the cold water inlet 6, passes through the modular single-phase liquid-cooled chamber, and carries heat to the outlet, forming a complete heat dissipation loop. This structure supports efficient liquid cooling, can dynamically adjust the flow rate, and works in conjunction with the front-end thermal management system to respond in real time to changes in charging heat load, ensuring the temperature safety of the charging pile under high-power fast charging and long-term stable output conditions.

[0070] like Figure 8The diagram shows the liquid cooling device for the energy storage module in the liquid-cooled thermal management system. It illustrates the principle and structure of the liquid cooling thermal management device on the battery pack side of the energy storage system. The circulating guide wheel 8 is the main circulation drive device of the liquid cooling system, responsible for driving the coolant to circulate between each energy storage battery pack and an external cold source such as a ground source heat pump, achieving efficient closed-loop heat exchange. The energy storage battery pack 9 has an embedded single-phase liquid-cooled immersion chamber. Each module has an independent single-phase immersion liquid inlet 10 and a single-phase immersion liquid outlet 11, achieving full-coverage immersion liquid cooling. After flowing through the inlet, the coolant fully covers the surface of the battery module, efficiently carrying away working heat, and flows back to the system after exiting through the outlet. The overall structural design supports parallel liquid cooling of multiple energy storage battery packs, achieving zoned temperature control and heat distribution, which helps to solve the risk of thermal runaway during high-rate charging and discharging and continuous operation of energy storage. Combined with an external ground source heat pump and temperature regulation strategy, the flow distribution can be dynamically adjusted according to the real-time operating conditions of the energy storage system, ensuring safe, uniform, and stable heat dissipation of the energy storage modules.

[0071] In this implementation scheme, automated closed-loop flow control based on liquid cooling flow rate adjustment values ​​enables tiered, on-demand, and precise heat dissipation for key heat source equipment such as the energy storage battery pack 9 and charging piles, significantly improving the response speed and heat dissipation efficiency of the thermal management system. Flow rate adjustment, coolant circulation, and temperature monitoring data throughout the entire process are synchronously written into the wind-solar hybrid energy storage database, ensuring data consistency and traceability during the heat dissipation process. By dynamically evaluating and promptly adjusting the heat dissipation effect, and automatically responding to abnormal temperature rises, the risk of overheating runaway and equipment damage is significantly reduced, effectively ensuring the safe, stable, and efficient operation of the charging and energy storage processes.

[0072] Specifically, the process of monitoring wind-solar hybrid energy storage data and the entire process, and coordinating the flow of wind and solar power generation, charging pile output, and heat source heat dissipation, involves strategy optimization and multi-dimensional visualization. This includes real-time monitoring of wind-solar hybrid energy storage data, tracking energy flow allocation judgment values, charging pile output power limits, liquid cooling flow adjustment values, and actual heat dissipation trends. Second-level updates and historical data review are achieved through the wind-solar hybrid energy storage database and edge computing platform, providing a high-precision data foundation for intelligent control and anomaly detection. Long Short-Term Memory (LSTM) network prediction, reinforcement learning, genetic algorithms, and Bayesian optimization algorithms are used to optimize strategies for energy flow allocation, charging pile output power adjustment, and heat dissipation, while adjusting allocation thresholds. The LSTM network temporal deep learning algorithm predicts fluctuations in wind and solar power generation, changes in charging pile load power, and the SOC trend of energy storage batteries, providing forward-looking decision-making for energy flow and scheduling. A multi-dimensional visualization interface is constructed, displaying full-process data and status on mobile terminals through curves, trend charts, heatmaps, and operation process animations. This facilitates remote monitoring of the entire system operation by maintenance personnel and users, and pushes maintenance suggestions such as regular health checks, anomaly diagnosis, and parameter calibration. It also enables remote diagnosis and upgrades, allowing for remote policy distribution and firmware upgrades to ensure continuous intelligent evolution. When operational anomalies are detected and potential risks are predicted, anomaly warnings and push notifications to assist decision-making are implemented. Combined with automated repair reporting and operation and maintenance linkage mechanisms, fault handling processes are triggered immediately, including push alarms, remote diagnosis, linked maintenance commands, and automatic load limiting, enabling real-time fault handling.

[0073] This implementation plan achieves coordinated adaptive control and global strategy optimization across various stages, including energy flow allocation, charging output, and liquid cooling, by real-time monitoring of multi-dimensional, high-frequency data throughout the entire wind-solar hybrid energy storage charging process and integrating deep learning prediction and intelligent optimization algorithms. It supports multi-terminal visualization and remote intelligent operation and maintenance, significantly improving the consistency, traceability, and scientific nature of operational data, while also enhancing operational efficiency and anomaly response capabilities. This comprehensively ensures efficient, safe, and intelligent operation of charging and discharging, thermal management, and energy flow scheduling.

[0074] Reference Figure 2As shown, the second aspect of the present invention provides a DC charging system for wind-solar hybrid energy storage based on liquid cooling, applied to the aforementioned DC charging method for wind-solar hybrid energy storage based on liquid cooling, comprising: a wind-solar hybrid energy storage data acquisition and processing module, used to acquire wind-solar hybrid energy storage data in real time, and perform time synchronization, noise reduction and smoothing, anomaly detection, missing value completion, and normalization processing on the wind-solar hybrid energy storage data; a wind-solar energy flow allocation optimization module, used to convert wind and solar power generation into DC power, and based on the pre-processed wind-solar hybrid energy storage data, determine the direction of wind and solar power energy flow, and perform corresponding wind and solar power energy transmission and power supply according to the direction of wind and solar power energy flow, and take priority power supply, energy replenishment, and safety protection measures; and DC intelligent charging. The control module acquires wind-solar hybrid energy storage data during the wind-solar power transmission process, determines the output power limit of the charging pile, adjusts the charging pile output according to the limit, and controls and monitors the state deviation in stages. The heat dissipation and safety regulation module quantifies the liquid cooling flow required for heat dissipation using the wind-solar hybrid energy storage data of the energy storage system and charging pile during the wind-solar power transmission process, dissipates heat from the energy storage system and charging pile according to the liquid cooling flow, and evaluates the heat dissipation effect. The intelligent control visualization module monitors the wind-solar hybrid energy storage data and the entire process, performs coordinated regulation of wind-solar power generation energy flow, charging pile output and heat source heat dissipation, strategy optimization and multi-dimensional visualization.

[0075] This implementation plan, through modular design, achieves real-time data acquisition and preprocessing, energy flow allocation optimization, DC intelligent charging control, liquid cooling heat dissipation safety regulation, and multi-dimensional intelligent visualization monitoring throughout the entire wind-solar hybrid energy storage charging scheduling process. The collaborative operation of each module effectively ensures efficient integration of wind and solar power generation and energy storage, dynamically optimizes charging and discharging and energy flow allocation, intelligently adjusts liquid cooling heat dissipation, and improves system safety and energy efficiency. Simultaneously, all process data is uniformly stored in a database, supporting real-time status monitoring and strategy optimization, significantly improving the consistency of data across the entire chain, the intelligence of operation, and the scientific nature of maintenance, providing a solid technical foundation for efficient and safe green energy replenishment.

[0076] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0077] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. As those skilled in the art will understand, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A wind-solar complementary energy storage direct current charging method based on liquid cooling heat dissipation, characterized in that, The method comprises the following steps: S1, real-time acquisition of wind-solar complementary energy storage data, and time synchronization, denoising and smoothing, anomaly detection, missing value completion and normalization processing of the wind-solar complementary energy storage data; S2, converting wind-solar power generation into direct current, and based on the preprocessed wind-solar complementary energy storage data, judging the flow direction of wind-solar power generation energy, corresponding wind-solar power generation energy transmission power supply according to the flow direction of wind-solar power generation energy, and taking priority power supply, energy supplement and safety protection measures; S3, obtaining wind-solar complementary energy storage data in the wind-solar power generation energy transmission power supply process, judging the limit of the output power of the charging pile, adjusting the output of the charging pile according to the limit of the output power of the charging pile, and controlling and monitoring the state deviation in stages in real time; S4, in the wind-solar power generation energy transmission power supply process, using the wind-solar complementary energy storage data of the energy storage system and the charging pile to quantify the liquid cooling flow required for heat dissipation, dissipating heat for the energy storage system and the charging pile according to the liquid cooling flow, and evaluating the heat dissipation effect; S5, monitoring the wind-solar complementary energy storage data and the whole process, and cooperatively controlling, optimizing and multi-dimensionally visualizing the flow direction of wind-solar power generation energy, the output of the charging pile and the heat dissipation of the heat source.

2. The liquid cooling-based heat dissipation wind-solar complementary energy storage DC charging method according to claim 1, characterized in that, The specific process of real-time acquisition of wind-solar complementary energy storage data, and time synchronization, denoising and smoothing, anomaly detection, missing value completion and normalization processing of the wind-solar complementary energy storage data is as follows: Real-time acquisition of wind-solar complementary energy storage data, including wind power, photovoltaic power, charging pile load power, charging pile rated maximum power, energy storage battery power, energy storage battery SOC, energy storage battery surface temperature, energy storage liquid cooling inlet temperature, energy storage loop liquid cooling flow, charging pile surface temperature, charging pile liquid cooling inlet temperature, charging pile loop liquid cooling flow, charging gun interface temperature and cooling liquid specific heat capacity; Time synchronization and multi-channel alignment of wind-solar complementary energy storage data, denoising and smoothing processing of original wind-solar complementary energy storage data by Kalman filtering and sliding window mean method, identification of abnormal and mutant data by standard deviation outlier detection method and quartile interval method, missing value completion by linear interpolation, standardization and dimensionless normalization processing of wind-solar complementary energy storage data, and storage of wind-solar complementary energy storage data in a wind-solar complementary energy storage database.

3. The liquid cooling-based heat dissipation wind-solar complementary energy storage DC charging method according to claim 1, characterized in that, The specific process of converting wind-solar power generation into direct current, and judging the flow direction of wind-solar power generation energy based on the preprocessed wind-solar complementary energy storage data is as follows: In the wind-solar power generation energy acquisition and convergence process, after all wind power generation and photovoltaic power generation units complete energy conversion, the alternating current of wind power generation and photovoltaic power generation is converted into stable output direct current by inversion rectification and MPPT converter. Real-time acquisition of wind power and photovoltaic power, addition of wind power and photovoltaic power to obtain total power generation; obtain the SOC of the energy storage battery, based on a sliding time window, statistically analyze the historical SOC of the energy storage battery and calculate the mean value to obtain the target SOC value of the energy storage battery, calculate the absolute difference between the current SOC of the energy storage battery and the target SOC value of the energy storage battery, and take the opposite number as the exponential power to perform natural exponential operation, and subtract the natural exponential operation result by a constant to obtain an energy storage adjustment factor; Obtain the charging pile load power, and divide the product of the total power generation and the energy storage adjustment factor by the sum of the current charging pile load power and a minimum constant value to obtain an energy flow distribution judgment value.

4. The liquid cooling-based heat dissipation wind-solar complementary energy storage DC charging method according to claim 1, characterized in that, The specific process of the wind-solar power energy flow direction corresponding to the wind-solar power energy transmission power supply and the adoption of priority power supply, energy supplement and safety protection measures is as follows: Real-time comparison of energy flow distribution judgment value and distribution threshold, energy flow distribution, when the energy flow distribution judgment value is greater than the distribution threshold, the wind-solar power energy flows to the energy storage system; when the energy flow distribution judgment value is less than or equal to the distribution threshold, the wind-solar power energy is preferentially dispatched to supply the charging pile, if the wind-solar power energy is insufficient, the energy storage system is used for energy supplement, and if the wind-solar power energy is excessive, it is transmitted to the energy storage system for storage; Real-time monitoring of energy flow distribution results, if the actual energy flow distribution direction is detected to be inconsistent with the energy flow distribution judgment value, the fault self-checking and direction switching are implemented through linkage warning; If the standard deviation of the energy flow distribution judgment value in the sliding time window is greater than the fluctuation threshold, enter the safety protection mode, and perform load reduction and flow limitation; All energy flow distribution judgment values and energy flow distribution records are written into the wind-solar complementary energy storage database, and based on the historical energy flow distribution judgment value and the actual energy flow distribution effect, the target SOC value of the energy storage battery is optimized through a genetic algorithm.

5. The liquid cooling-based heat dissipation wind-solar complementary energy storage DC charging method according to claim 1, characterized in that, The specific process of obtaining wind-solar complementary energy storage data in the wind-solar power energy transmission power supply process and judging the limit of the charging pile output power is as follows: When supplying power to the charging pile, the SOC of the energy storage battery is obtained in real time, and the smaller value of the SOC of the energy storage battery and a constant is selected as the charging progress constraint value; Obtain the charging gun interface temperature, based on a sliding time window, statistically analyze the historical charging gun interface temperature and select the maximum value to obtain a charging gun temperature limit value, and divide the difference between the current charging gun interface temperature and the charging gun temperature limit value by the charging gun temperature limit value to obtain a relative over-temperature ratio; The charging safety control value is obtained by multiplying the charging progress constraint value by the product of the relative over-temperature ratio and the temperature weight factor, and multiplying by the sensitivity weight factor, and the opposite number of the charging safety control factor is taken as the exponential power to perform natural exponential operation to obtain a comprehensive safety index adjustment value, and the charging output suppression coefficient is obtained by adding the comprehensive safety index adjustment value to a constant and taking the reciprocal; Obtain the rated maximum power of the charging pile, multiply the rated maximum power of the charging pile by the charging output suppression coefficient to obtain the charging pile output power limit value.

6. The liquid cooling-based heat dissipation wind-solar complementary energy storage DC charging method according to claim 1, characterized in that, The specific process of adjusting the charging pile output according to the limit of the charging pile output power, controlling in stages and monitoring the state deviation in real time is as follows: The charging pile output power limit value is written into the wind-solar complementary energy storage database, and a power upper limit instruction is generated according to the charging pile output power limit value and is sent to the charging pile controller in real time to adjust the charging pile output power; and the charging pile output power limit value is adjusted according to the charging stage during the charging process, that is, the charging stage is divided into initial stage, middle stage and tail stage, to realize fast charging in the initial stage, stable charging in the middle stage and trickle charging in the tail stage; The actual charging pile output power is collected in real time, and the deviation from the charging pile output power limit value is recorded. If the deviation is greater than the deviation threshold, the state self-checking is performed to determine whether the charging pile and the cable are abnormal, and the maintenance and safety warning are linked.

7. The liquid cooling-based heat dissipation wind-solar complementary energy storage DC charging method according to claim 1, characterized in that, The specific process of quantifying the liquid cooling flow required for heat dissipation in the wind-solar complementary energy storage data of the energy storage system and the charging pile during the wind-solar power generation energy transmission and power supply process is as follows: During the process of supplying power to the energy storage system and the charging pile by wind-solar power generation energy, the wind-solar complementary energy storage data of the corresponding heat source, i.e., the energy storage battery and the charging pile, are received in real time; based on a sliding time window, the historical surface temperature of the heat source i is counted and the maximum value is selected to obtain the highest allowable temperature of the heat source i, and the historical heat source i loop liquid cooling flow is counted to obtain the minimum value, i.e., the heat source i liquid cooling basic flow; The difference between the surface temperature of the heat source i and the liquid cooling inlet temperature of the heat source i is multiplied by the power of the heat source i to obtain the heat source i temperature difference heat load value; The difference between the highest allowable temperature of the heat source i and the liquid cooling inlet temperature of the heat source i is multiplied by the specific heat capacity of the cooling liquid to obtain the cooling capacity value of the heat source i; The heat source i heat flow demand ratio is obtained by dividing the heat source i temperature difference heat load value by the heat source i cooling capacity value; the sum of the heat source i heat flow demand ratio and a constant one is subjected to natural logarithm operation, and then multiplied by the flow adjustment weight factor to obtain the heat source i adaptive adjustment value; The heat source i adaptive adjustment value is added to the heat source i liquid cooling basic flow to obtain the heat source i liquid cooling flow adjustment value. 8.The liquid cooling heat dissipation based wind-solar complementary energy storage DC charging method according to claim 1, characterized in that, The specific process of dissipating heat from the energy storage system and the charging pile according to the liquid cooling flow and evaluating the heat dissipation effect is as follows: According to the liquid cooling flow adjustment value, the corresponding flow adjustment instruction is generated and output to the execution element to dissipate heat from the energy storage battery pack (9) and the charging pile: according to the liquid cooling flow adjustment value, the circulating guide wheel (8) drives the cooling liquid to flow along the main circulating pipeline, and the cooling liquid enters the single-phase immersion liquid cavity (12) of the energy storage battery pack through the main loop branch; at the same time, the cooling liquid corresponding to the charging pile enters the single-phase liquid immersion cavity (4) of the charging pile, passes through the current circuit (2) and the external discharge port (3), and directly cools the charging pile interface; the cooling liquid flowing out of each heat source cavity is unified and flows into the primary liquid storage tank, and is uniformly pumped into the ground source heat pump for centralized cooling treatment and flows back to the secondary liquid storage tank. The cooled cooling liquid is driven by the circulating guide wheel (8) and is branched back to each heat source equipment according to the liquid cooling flow adjustment value, and is subjected to closed-loop heat dissipation and circulation control; The liquid cooling flow adjustment values of the energy storage battery and the charging pile are written into the wind-solar complementary energy storage database, and the heat dissipation process is recorded in real time. The actual heat dissipation effect is judged and recorded by monitoring the changes of the surface temperatures of the energy storage battery and the charging pile. 9.The liquid cooling heat dissipation based wind-solar complementary energy storage DC charging method according to claim 1, characterized in that, The wind-solar complementary energy storage data and the whole process are monitored, and the specific process of the flow direction of wind-solar power generation, the collaborative regulation of charging pile output and heat source heat dissipation, strategy optimization and multi-dimensional visualization is as follows: Real-time monitoring of wind-solar complementary energy storage data, tracking energy flow distribution judgment value, charging pile output power limit value, liquid cooling flow regulation value and actual heat dissipation effect trend, using long short-term memory network prediction, reinforcement learning, genetic algorithm and Bayesian optimization algorithm, optimizing the strategy of energy flow distribution, charging pile output power regulation and heat dissipation multi-link, and adjusting the distribution threshold value; A multi-dimensional visualization interface is constructed to display the whole process data and state on a mobile terminal, push maintenance suggestions, and perform remote diagnosis and upgrade, realize abnormal early warning and push auxiliary decision-making, combine automatic repair and operation linkage mechanism, and perform fault handling in real time.

10. The wind-solar complementary energy storage direct current charging system based on liquid cooling heat dissipation, characterized in that, It includes: A wind-solar complementary energy storage data acquisition and processing module is used to acquire wind-solar complementary energy storage data in real time, and to perform time synchronization, denoising and smoothing, anomaly detection, missing value completion and normalization processing on the wind-solar complementary energy storage data; A wind-solar energy flow distribution optimization module is used to convert wind-solar power generation into direct current, and based on the preprocessed wind-solar complementary energy storage data, to judge the flow direction of wind-solar power generation energy, to perform corresponding wind-solar power generation energy transmission power supply according to the flow direction of wind-solar power generation energy, and to take priority power supply, energy supplement and safety protection measures; A direct current intelligent charging control module is used to acquire wind-solar complementary energy storage data in the wind-solar power generation energy transmission power supply process, to judge the limit of charging pile output power, to adjust the charging pile output according to the limit of charging pile output power, to control and monitor the state deviation in stages; A heat dissipation safety regulation module is used to utilize the wind-solar complementary energy storage data of the energy storage system and the charging pile in the wind-solar power generation energy transmission power supply process, to quantify the liquid cooling flow required for heat dissipation, to perform heat source heat dissipation for the energy storage system and the charging pile according to the liquid cooling flow, and to evaluate the heat dissipation effect; An intelligent control visualization module is used to monitor the wind-solar complementary energy storage data and the whole process, to perform collaborative regulation of the flow direction of wind-solar power generation energy, charging pile output and heat source heat dissipation, strategy optimization and multi-dimensional visualization.

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