Power plant energy efficiency management method and system based on light storage and charging management

Abstract

The application discloses a power station energy efficiency management method and system based on light storage and charging management, belongs to the technical field of power station energy efficiency data processing, and comprises the following steps: obtaining a reference output current of a photovoltaic array of a power station, dynamically adjusting a step length based on a deviation degree, combining light and component efficiency correction to obtain a target output current; calculating photovoltaic real-time power, adjusting equivalent input impedance in combination with inverter efficiency, and locking the maximum power point voltage. Based on the photovoltaic power and the storage energy available power, the total available power of each charging pile is calculated: the piles meeting the demand electric energy are marked as surplus piles, and the surplus power is stored in the storage energy; the piles not meeting the demand are marked as deficiency piles, the output current of the piles is dynamically adjusted, the storage energy calling proportion is dynamically allocated in combination with the deficiency power, the surplus power and historical scheduling parameters, and the surplus storage energy is scheduled to provide load support. The photovoltaic consumption rate of each pile is counted, the proportion of the piles meeting the standard is calculated, if the preset target is not met, the reference output current of the next period is dynamically adjusted, and energy efficiency closed loop optimization is formed.

Description

Technical Field

[0001] This invention relates to the field of power plant energy efficiency data processing technology, and in particular to a power plant energy efficiency management method and system based on photovoltaic, energy storage and charging management. Background Technology

[0002] Photovoltaic-storage-charging management is an intelligent solution that deeply integrates photovoltaics, energy storage, and charging piles through an energy management system. Its core lies in using energy storage systems as a "buffer" to address the dual impacts on the power grid from intermittent photovoltaic power generation and the random charging of electric vehicles. On the one hand, it reduces the demand for transformer expansion and peak-valley electricity pricing through "peak shaving and valley filling"; on the other hand, it prioritizes the consumption of photovoltaic green electricity to improve self-consumption rates. With the popularization of ultra-fast charging and the opening of the electricity market, photovoltaic-storage-charging sites are evolving from single charging service units into virtual power plant nodes with "source-load-storage" collaborative capabilities. This not only achieves efficient closed-loop scheduling of power within the site but also creates added value through participation in grid demand response, making it a key infrastructure for building new microgrids and supporting the full electrification of transportation.

[0003] Existing power plant energy efficiency management primarily relies on digital monitoring platforms and intelligent control strategies. Its core lies in the real-time collection of power data across the entire generation, distribution, and consumption chain through intelligent sensors and IoT terminals deployed on photovoltaic, energy storage, charging piles, and the distribution side. The system utilizes edge computing and artificial intelligence algorithms to accurately predict load and dynamically optimize energy storage charging and discharging strategies (peak shaving and valley filling) and charging pile power allocation to reduce transformer losses and demand charges within the plant. Simultaneously, through integrated generation, grid, load, and storage scheduling, it prioritizes the consumption of photovoltaic green electricity, reducing losses caused by power backflow into the grid, thereby achieving refined closed-loop energy efficiency management from "passive monitoring" to "active optimization."

[0004] For example, the invention patent announcement CN118396479B, which discloses a power plant energy efficiency assessment system and method based on photovoltaic-storage-charging management, includes: a photovoltaic-storage-charging operation data acquisition module for acquiring photovoltaic-storage-charging operation data; a power plant comprehensive energy efficiency assessment model construction module for constructing a power plant comprehensive energy efficiency assessment model that integrates photovoltaic power generation calculation assessment, energy storage efficiency assessment, energy storage discharge efficiency assessment, and load charging efficiency assessment based on preset assessment parameters; and a power plant energy efficiency assessment implementation module for assessing the power plant energy efficiency based on the power plant comprehensive energy efficiency assessment model and the operation data.

[0005] For example, the invention patent with publication number CN121503963A discloses an intelligent operation and maintenance and energy efficiency optimization management system for photovoltaic power plants, including: a data acquisition module for calculating the relative series resistance indication; a window positioning module for setting the dawn window; an amplitude ratio calculation module for calculating the amplitude ratio of the rising and falling phases of the relative series resistance indication; a target parallel branch determination module for screening target branches; a total loss integral calculation module for calculating the total loss integral; a bus voltage adjustment module for adjusting the voltage to reduce losses; and an operation and maintenance work order priority generation module for generating work order priorities based on relevant parameters.

[0006] However, in the process of implementing the inventive technical solution in the embodiments of this application, it was found that the above-mentioned technology has at least the following technical problems: In existing technologies, the maximum power point tracking of photovoltaic arrays, the charging and discharging scheduling of energy storage systems, and the load allocation of charging piles usually operate independently, lacking a dynamic adjustment mechanism for coordinated generation, storage, and consumption. This makes it difficult to accurately match photovoltaic power generation and charging load on a time scale, resulting in low green electricity absorption rate, poor energy storage call efficiency, and the inability to close-loop correct the operating benchmark parameters based on the actual absorption level. Consequently, there are problems such as lagging system energy efficiency optimization, untimely power support response, and long-term failure of local charging piles to meet absorption standards. Summary of the Invention

[0007] To address the shortcomings of existing technologies, where photovoltaic array maximum power point tracking, energy storage system charging and discharging scheduling, and charging pile load allocation typically operate independently, lacking a dynamic adjustment mechanism for coordinated generation, storage, and consumption, this invention provides a power plant energy efficiency management method and system based on photovoltaic-storage-charging management. This is because the three components typically operate independently, lacking a dynamic adjustment mechanism for generation, storage, and consumption, resulting in difficulty in accurately matching photovoltaic power generation and charging load on a timescale, leading to low green energy absorption rates, poor energy storage utilization efficiency, and the inability to adjust operating baseline parameters based on actual absorption levels. Furthermore, it addresses issues such as lagging system energy efficiency optimization, untimely power support response, and long-term failure of some charging piles to meet absorption standards. On the one hand, a power station energy efficiency management method based on photovoltaic-storage-charging management is provided. This method includes: S01, obtaining the reference output current of the power station's photovoltaic array; dynamically adjusting the current adjustment step size based on the deviation between the current operating point and the maximum power point; dynamically adjusting the reference output current in conjunction with the irradiance and the photovoltaic module conversion efficiency to obtain the target output current; calculating the real-time photovoltaic power based on the target output current and the real-time operating voltage; dynamically adjusting the inverter's equivalent input impedance in conjunction with the inverter's conversion efficiency to ensure the photovoltaic modules operate at the voltage corresponding to the maximum power point under the current irradiance conditions, thus ensuring the photovoltaic array stably outputs the real-time photovoltaic power under the current operating conditions; S02, calculating the total available power of each charging pile based on the real-time photovoltaic power and the energy storage's dissipable power; and adjusting the total available power to meet the required power demand. Charging piles are marked as surplus charging piles. The surplus power of each surplus charging pile is calculated and stored in its energy storage device. Charging piles whose total available power does not meet the demand are marked as deficit charging piles. The deficit power of each deficit charging pile is calculated, and the output current of the deficit charging piles is dynamically adjusted. Simultaneously, combining the deficit power, the surplus power of each surplus charging pile, and historical dispatch parameters, the energy storage allocation ratio is dynamically adjusted, and surplus energy storage capacity is dispatched to provide temporary load support for deficit charging piles. In step S03, the photovoltaic absorption rate of each charging pile within the current power station energy efficiency management cycle is calculated, and the percentage of charging piles whose photovoltaic absorption rate reaches the preset photovoltaic absorption rate threshold is calculated. It is determined whether the percentage of charging piles reaches the preset percentage target. If so, the current benchmark output current is maintained; otherwise, the benchmark output current for the next power station energy efficiency management cycle is dynamically adjusted.

[0008] On the other hand, a power plant energy efficiency management system based on photovoltaic-storage-charging management is provided, including a photovoltaic array maximum power point tracking (MPPT) adjustment module, a photovoltaic-storage-charging collaborative power allocation and scheduling module, and a photovoltaic grid absorption rate closed-loop feedback adjustment module. The photovoltaic array MPPT adjustment module is used to obtain the reference output current of the power plant's photovoltaic array, dynamically adjust the current adjustment step size based on the deviation between the current operating point and the maximum power point, and dynamically adjust the reference output current in conjunction with the irradiance and photovoltaic module conversion efficiency to obtain the target output current. Based on the target output current and the real-time operating voltage, the real-time photovoltaic power is calculated, and the inverter's equivalent input impedance is dynamically adjusted in conjunction with the inverter conversion efficiency to ensure that the photovoltaic modules operate at the voltage corresponding to the maximum power point under the current irradiance conditions. The photovoltaic-storage-charging collaborative power allocation and scheduling module is used to calculate the total available power of each charging pile based on the real-time photovoltaic power and the energy storage discharge capacity of each charging pile. The system marks charging piles whose total available power reaches the required electricity as surplus charging piles, calculates the surplus power of each surplus charging pile, and stores it in the energy storage device of that surplus charging pile. Charging piles whose total available power does not reach the required electricity are marked as deficit charging piles. The system calculates the deficit power of each deficit charging pile and dynamically adjusts the output current of the deficit charging pile. At the same time, it combines the deficit power, the surplus power of each surplus charging pile, and historical scheduling parameters to dynamically adjust the energy storage call allocation ratio and schedule surplus energy storage capacity to provide temporary load support for deficit charging piles. The photovoltaic absorption rate closed-loop feedback adjustment module is used to calculate the photovoltaic absorption rate of each charging pile in the current power station energy efficiency management cycle, calculate the proportion of charging piles whose photovoltaic absorption rate reaches the preset photovoltaic absorption rate threshold, and determine whether the proportion of charging piles reaches the preset proportion target. If so, the current benchmark output current is maintained; otherwise, the benchmark output current for the next power station energy efficiency management cycle is dynamically adjusted.

[0009] On the other hand, a power plant energy efficiency management device based on photovoltaic, energy storage and charging management is provided, comprising: one or more processors; and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the power plant energy efficiency management method based on photovoltaic, energy storage and charging management as described in any one of claims 1 to 8.

[0010] Beneficial effects The beneficial effects of the technical solutions provided in the embodiments of the present invention include at least the following: 1. By dynamically adjusting the target output current of the photovoltaic array and the equivalent input impedance of the inverter, the power allocation of the charging pile and the energy storage call ratio are optimized. Combined with the photovoltaic absorption rate feedback to dynamically correct the reference output current and related adaptive mechanisms, the photovoltaic array can stably output the maximum power under the current operating conditions, achieve a balance between power supply and demand of the charging pile, improve the local photovoltaic absorption level, and reduce the dependence on the energy storage system and the power grid. This leads to the improvement of the energy efficiency management level, green electricity self-consumption rate and project economics of the photovoltaic-storage-charging integrated power station, and ensures the overall stable and efficient operation of the power station.

[0011] 2. By collecting real-time photovoltaic array operating point parameters, irradiance, and photovoltaic module conversion efficiency, and combining them with preset power point mapping rules, the voltage and power deviation is calculated and weighted to obtain a comprehensive deviation. Based on this, the effective current adjustment step size is matched and limited. At the same time, the reference current correction amount is calculated according to the corresponding current correction ratio matched with the irradiance and module conversion efficiency, and then the reference output current is dynamically corrected to obtain the target output current. This allows the current adjustment step size of the photovoltaic array to adapt to the degree of deviation from the operating conditions and to be within a reasonable range. In addition, the output current is accurately corrected by combining real-time environment and module performance, thereby achieving the speed and accuracy of maximum power point tracking of the photovoltaic array, and improving the energy conversion efficiency and output stability of photovoltaic power generation.

[0012] 3. By comparing the total available power of the charging pile with the minimum sustaining power threshold and adjusting the output current in stages, and matching the reference output current with the total available power, and dynamically correcting the reference output current according to the power deficit and power consumption rate, the charging pile can maintain basic operation when the power is insufficient. At the same time, the output current is accurately adapted to the available power, the degree of deficit and the power consumption rate, thereby realizing the stable and reliable power supply of the charging pile and the fine-grained power adjustment, improving the power utilization efficiency and operational safety of the charging pile.

[0013] 4. By statistically analyzing the average and minimum absorption rate deviations of low-absorption charging piles, a reference current correction coefficient and a limit current correction coefficient are matched and weighted to correct the reference output current for the next cycle. Simultaneously, based on the absorption rate deviation time series fitting of the comprehensive convergence speed index, the reference current correction coefficient is adaptively adjusted or an abnormal alarm is triggered to lock the reference output current to a safe threshold. This balances the global optimization adjustment of photovoltaic absorption rate with the worst-case individual boundary forced correction. It flexibly controls according to the convergence speed and ensures system safety when control fails. In this way, the photovoltaic absorption rate is quickly converged to the preset threshold, improving the local photovoltaic absorption level and energy efficiency management adaptive, safe and stable control capabilities of the photovoltaic-storage-charging integrated power station. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0015] Figure 1 A flowchart of a power plant energy efficiency management method based on photovoltaic, energy storage, and charging management provided in this application embodiment; Figure 2A flowchart illustrating the dynamic adjustment of the reference output current for a power plant energy efficiency management method based on photovoltaic-storage-charging management, provided in an embodiment of this application. Figure 3 This is a schematic diagram of the structure of a power plant energy efficiency management system based on photovoltaic, energy storage and charging management, provided in an embodiment of this application. Detailed Implementation

[0016] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0017] like Figure 1The diagram shows a flowchart of a power station energy efficiency management method based on photovoltaic-storage-charging management provided in this application embodiment. The method includes the following steps: S01, obtaining the reference output current of the power station's photovoltaic array; dynamically adjusting the current adjustment step size based on the deviation between the current operating point and the maximum power point under the current illumination environment; dynamically adjusting the reference output current in conjunction with the illumination intensity and photovoltaic module conversion efficiency to obtain the target output current. The current operating point refers to the actual operating point of the photovoltaic array under real-time conditions (i.e., the combination of real-time voltage and current), which is used to compare with the theoretical maximum power point under the current environment. The current adjustment step size is dynamically adjusted according to the deviation between the two, thereby driving the system to approach the maximum power point, laying the foundation for subsequent power allocation and energy storage scheduling; S02, calculating the total available power of each charging pile based on the sum of the real-time photovoltaic power and the energy storage discharge power corresponding to each charging pile; and all charging piles whose total available power reaches the required power. Marked as surplus charging piles, the difference between the total available power and the demand for electricity of each surplus charging pile is recorded as the surplus power of each surplus charging pile and stored in the energy storage device of the surplus charging pile; charging piles whose total available power does not reach the demand for electricity are marked as deficit charging piles, and the difference between the demand for electricity and the total available power of each surplus charging pile is recorded as the deficit power of each deficit charging pile, and the output current of deficit charging piles is dynamically adjusted. At the same time, combined with the deficit power, the surplus power of each surplus charging pile and historical dispatch parameters, the energy storage call allocation ratio is dynamically adjusted, and the surplus energy storage capacity is dispatched to provide temporary load support for deficit charging piles; S03, the photovoltaic absorption rate of each charging pile in the current power station energy efficiency management cycle is calculated, and the proportion of charging piles whose photovoltaic absorption rate reaches the preset photovoltaic absorption rate threshold is calculated; it is determined whether the proportion of charging piles reaches the preset proportion target. If so, the current benchmark output current is maintained; otherwise, the benchmark output current of the next power station energy efficiency management cycle is dynamically adjusted. The photovoltaic (PV) absorption rate refers to the proportion of PV power generated and consumed by each charging pile to its corresponding total PV power generation. In other words, it is the proportion of electricity generated by the PV array directly used for charging. This indicator is used to measure the local absorption level of PV power generation at the charging pile side. The higher the PV absorption rate, the higher the degree of direct utilization of PV power and the lower the dependence on energy storage systems and the power grid. It is a key parameter for evaluating the green electricity self-consumption rate and energy efficiency management effect of integrated PV-storage-charging power stations.

[0018] The photovoltaic (PV) array in a power plant is the core physical unit that enables power generation. It consists of several PV modules (solar panels) connected in series to form a "string," and then connected in parallel to form a large-scale DC power generation unit. Its core function is to directly convert solar radiation energy into DC power, which is then converted into AC power by an inverter to supply charging piles, energy storage systems, or be fed into the power grid. In practical engineering, the orientation, tilt angle, spacing, and shading of the array directly affect power generation efficiency and system stability. In integrated photovoltaic, energy storage, and charging scenarios, the accuracy of PV array output prediction, the optimization of its matching with energy storage capacity, and the coordinated scheduling based on time-of-use pricing and load curves are key technological foundations for improving green electricity self-consumption rate and project economics. In a power plant's PV array, PV modules exhibit nonlinear output characteristics. According to the maximum power transfer theorem, the operating point can only fall at the maximum power point when the equivalent input impedance of the inverter matches the output impedance of the PV array under the current illumination and temperature. Therefore, the inverter dynamically changes its equivalent input impedance by adjusting the duty cycle of the switching transistors in real time, actively "optimizing" to match the output characteristics of the photovoltaic array, thereby forcing the photovoltaic array to always output the maximum power under the current environmental conditions, achieving optimal energy conversion efficiency. The reference output current is an initial reference current value set during power plant energy efficiency management, serving as the starting point for photovoltaic array output adjustment. It is not the final actual output value, but rather a basic parameter dynamically adjusted within each energy efficiency management cycle, taking into account factors such as the deviation between the current operating point and the maximum power point, solar radiation intensity, and module conversion efficiency. This parameter is used to generate the target output current, thereby achieving active optimization of the photovoltaic array's operating point and maximum power point tracking. The target output current, within each energy efficiency management cycle, is the command current value generated by starting with the reference output current, dynamically adjusting the step size by real-time acquisition of the deviation between the current operating point and the maximum power point, and incorporating feedforward correction based on solar radiation intensity and photovoltaic module conversion efficiency. It is the optimal output target calculated by the maximum power point tracking algorithm, determining the actual operating current output by the photovoltaic array within that cycle.

[0019] In this embodiment, the present invention first obtains the reference output current of the photovoltaic array in the photovoltaic power generation stage, then dynamically adjusts the current step size based on the deviation between the operating point and the maximum power point, and integrates the irradiance and photovoltaic module conversion efficiency to complete the feedforward correction of the reference output current to obtain the target output current. Simultaneously, based on the target output current and the real-time operating voltage, the real-time photovoltaic power is calculated, and the equivalent input impedance of the inverter is further dynamically adjusted. This accurately matches the nonlinear output characteristics of the photovoltaic module, ensuring that the photovoltaic module always operates stably at the maximum power point under the current irradiance and temperature conditions, maximizing the power generation efficiency and energy conversion efficiency of the photovoltaic array, and guaranteeing stable and efficient output of real-time photovoltaic power from the power generation head. Secondly, in the charging pile load scheduling stage, the total available power is calculated based on the real-time photovoltaic power and energy storage capacity of each charging pile, accurately distinguishing between surplus and shortage charging piles, and collecting the power difference of surplus charging piles into the energy storage device for storage, while dynamically adjusting... By reducing the output current of charging piles with insufficient capacity and optimizing the energy storage allocation ratio based on insufficient power, surplus power, and historical dispatch parameters, the system can quickly achieve local storage of surplus power and temporary energy storage support for insufficient loads. This effectively balances the power supply and demand of each charging pile, avoiding power waste or insufficient power supply, and ensuring the stable operation of the charging load. Finally, in the energy efficiency closed-loop optimization stage, by statistically analyzing the photovoltaic absorption rate of each charging pile within the energy efficiency management cycle, the proportion of compliant charging piles is calculated, and this is used as a basis to determine whether to adjust the benchmark output current for the next cycle. This continuously improves the local absorption level of photovoltaic power generation at the charging pile side, increases the self-consumption rate of green electricity, reduces the power station's dependence on the energy storage system and the grid, and forms a closed-loop management mechanism for power generation regulation, load dispatch, and parameter optimization. This comprehensively improves the overall energy efficiency, operational stability, and project economy of the photovoltaic-storage-charging integrated power station, achieving an integrated and coordinated management effect of efficient photovoltaic utilization, reasonable energy storage allocation, and precise charging load support.

[0020] Furthermore, the target output current of the photovoltaic array in the power station is obtained as follows: Real-time acquisition of the operating voltage and current of the photovoltaic array at its current operating point, the current solar radiation intensity, and the photovoltaic module conversion efficiency; pre-definition of the reference output current, minimum current adjustment step size, and maximum current adjustment step size; matching the current solar radiation intensity with a preset power point mapping rule to obtain the maximum power point; calculating the voltage deviation and power deviation between the current operating point and the maximum power point. The power point mapping rule is a preset correspondence between solar radiation intensity and the voltage and power of the maximum power point, used to determine the theoretical maximum power point parameters of the photovoltaic array under the current environmental conditions based on the real-time acquired solar radiation intensity; weighted summation of the voltage and power deviations to obtain the comprehensive deviation; matching the comprehensive deviation with a preset step size adjustment mapping rule to obtain the current adjustment step size. The step size adjustment mapping rule is: dividing the comprehensive deviation into multiple continuous ranges, establishing a linear correspondence between the comprehensive deviation and the current adjustment step size in each range, so that the current adjustment step size increases linearly with the increase of the comprehensive deviation. If the current adjustment step size is within the range of the minimum and maximum current adjustment step sizes, then the current adjustment step size is directly used as the effective adjustment step size for the current power plant energy efficiency management cycle; otherwise, the current adjustment step size is limited to the nearest minimum or maximum current adjustment step size. The current solar radiation intensity and photovoltaic module conversion efficiency are matched with preset first and second current correction rules to obtain the first and second current correction ratios. The first current correction rule is a preset mapping rule between solar radiation intensity and the first current correction ratio, used to map the real-time collected solar radiation intensity to the corresponding first current correction ratio. The second current correction rule is a preset mapping rule between the real-time photovoltaic module conversion efficiency and the second current correction ratio, used to map the real-time collected photovoltaic module conversion efficiency to the corresponding second current correction ratio. Based on the first and second current correction ratios and the current adjustment step size, a reference current correction amount is calculated. Based on the reference current correction amount, the reference output current is dynamically corrected to obtain the target output current of the power plant photovoltaic array.

[0021] In this embodiment, the present invention achieves precise and adaptive adjustment of the target output current through accurate data acquisition, scientific calculation, and dynamic correction throughout the entire process. This provides core technical support for ensuring the stable operation of the photovoltaic array at its maximum power point and guaranteeing efficient real-time power output. The overall technical effect is reflected in many aspects and has significant practicality and superiority: First, by acquiring the operating voltage and current of the photovoltaic array at its current operating point in real time, as well as the current solar radiation intensity and photovoltaic module conversion efficiency, and pre-defining the reference output current and minimum and maximum current adjustment step sizes, a comprehensive and real-time parameter acquisition system is constructed. This ensures that all subsequent calculations and adjustments are based on real operating condition data, avoiding adjustment deviations caused by missing or lagging parameters from the source, and laying a solid foundation for the accurate acquisition of the target output current. Second, by matching the real-time solar radiation intensity with the preset power point mapping rules, the theoretical maximum power point parameters of the photovoltaic array under the current environmental conditions can be quickly and accurately determined. Then, by calculating the voltage deviation and power deviation between the current operating point and the maximum power point and performing a weighted summation to obtain the comprehensive deviation, it can comprehensively and objectively reflect the degree of deviation between the current operating point and the optimal operating state, breaking the limitations of traditional methods. This approach overcomes the limitations of a single deviation index, providing a scientific basis for the rational determination of the current adjustment step size. Furthermore, the current adjustment step size is obtained by matching the comprehensive deviation with the step size adjustment mapping rule. By dividing the comprehensive deviation into continuous ranges and establishing a linear correspondence, the adjustment step size changes linearly with the comprehensive deviation, achieving dynamic adaptation of the adjustment step size. Simultaneously, by limiting the step size within the minimum and maximum adjustment step size range, it effectively avoids system oscillations and operating point fluctuations caused by excessively large step sizes, as well as low optimization efficiency and inability to track the maximum power point in a timely manner caused by excessively small step sizes, ensuring the stability and efficiency of current regulation. In addition, by matching the irradiance and photovoltaic module conversion efficiency with the preset first and second current correction rules respectively, the corresponding current correction ratio is obtained. Then, the reference current correction amount is calculated, and the reference output current is dynamically corrected. This fully adapts to the operating conditions of real-time changes in irradiance and fluctuations in photovoltaic module conversion efficiency, achieving targeted correction of the reference output current. This ensures that the corrected target output current accurately matches the current environmental conditions and the operating characteristics of the photovoltaic module, effectively compensating for the shortcomings of relying solely on step size adjustment, which cannot simultaneously consider changes in the environment and the module's own characteristics.The entire acquisition process forms a closed-loop logic of parameter acquisition, deviation calculation, step size adjustment, and precise correction. The resulting target output current accurately guides the inverter to adjust its equivalent input impedance, ensuring that the photovoltaic modules always operate stably at their maximum power point under the current illumination and temperature conditions. This maximizes the power generation and energy conversion efficiency of the photovoltaic array. Simultaneously, it provides accurate and stable real-time photovoltaic power support for the subsequent calculation of the total available power of each charging pile and the power supply and demand balance scheduling. This further enhances the scientific nature, adaptability, and efficiency of the energy efficiency management method for the entire photovoltaic-storage-charging integrated power station, effectively solving problems such as adjustment lag, poor adaptability, and low optimization accuracy in traditional target current acquisition methods. It provides key technical support for the overall energy efficiency improvement and stable operation of the power station.

[0022] Furthermore, the specific steps for dynamically adjusting the equivalent input impedance of the inverter are as follows: The ratio of the real-time photovoltaic power to the theoretical maximum power value corresponding to the maximum power point is denoted as the photovoltaic array tracking efficiency. It is determined whether the photovoltaic array tracking efficiency has reached the preset target tracking efficiency. If not, the difference between the target tracking efficiency and the photovoltaic array tracking efficiency is denoted as the tracking efficiency deviation. Based on the tracking efficiency deviation, a preset step size correction mapping rule is matched to obtain the step size correction ratio. Based on the step size correction ratio, the dynamic adjustment of the current adjustment step size and the correction of the target output current are re-executed. The step size correction mapping rule is as follows: a correspondence is established between the tracking efficiency deviation and the step size correction ratio, so that the step size correction ratio monotonically increases with the increase of the absolute value of the tracking efficiency deviation, and the correction direction is opposite to the sign of the tracking efficiency deviation. When the tracking efficiency deviation is positive, it indicates that the current photovoltaic array tracking efficiency is lower than the target value, and the current adjustment step size needs to be increased to accelerate the tracking speed. When the tracking efficiency deviation is negative, it indicates that the current tracking efficiency is overshooting or close to the target value, and the current adjustment step size needs to be decreased to suppress steady-state oscillations, until... The system tracks and eliminates efficiency deviations. If the target efficiency is achieved, the AC active power at the inverter output is collected in real time, and the ratio of the AC active power to the real-time photovoltaic power is recorded as the inverter conversion efficiency. The system then determines whether the inverter conversion efficiency has reached the preset target efficiency. If so, no further processing is performed. Otherwise, the difference between the target conversion efficiency and the actual conversion efficiency is recorded as the conversion efficiency deviation. Based on the conversion efficiency deviation, a preset duty cycle adjustment mapping rule is matched to obtain the duty cycle adjustment ratio. The duty cycle of the inverter's switching transistors is dynamically adjusted based on this ratio to regulate the inverter's equivalent input impedance, thereby locking the photovoltaic module's operating voltage. The efficiency deviation duty cycle adjustment mapping rule is as follows: a correspondence is established between the conversion efficiency deviation and the duty cycle adjustment ratio, ensuring that the duty cycle adjustment ratio monotonically increases with the absolute value of the conversion efficiency deviation, and the adjustment direction is opposite to the sign of the conversion efficiency deviation. When the conversion efficiency deviation is positive, the duty cycle is decreased to reduce the equivalent input impedance; when the conversion efficiency deviation is negative, the duty cycle is increased to increase the equivalent input impedance, until the conversion efficiency deviation is eliminated.

[0023] In this embodiment, the present invention achieves precise and adaptive adjustment of the inverter's equivalent input impedance through a hierarchical closed-loop design of photovoltaic tracking efficiency control and inverter conversion efficiency control. This ensures that the photovoltaic array always operates at its maximum power point while maximizing the inverter's energy conversion efficiency, providing key technical support for the efficient and stable operation of integrated photovoltaic-storage-charging power stations. The overall technical effect is targeted, stable, and efficient, specifically reflected in the following core aspects: First, by defining the ratio of the real-time photovoltaic power to the theoretical maximum power value corresponding to the maximum power point as the photovoltaic array tracking efficiency, and using this efficiency as the core judgment indicator, a real-time photovoltaic maximum power point tracking effect is constructed. The monitoring mechanism can accurately identify the deviation between the current operating point of the photovoltaic array and its optimal state, breaking the limitations of traditional methods that rely solely on voltage and current parameters to judge tracking performance. This provides a direct and scientific basis for subsequent adjustments. Secondly, when the tracking efficiency of the photovoltaic array fails to reach the preset target, the tracking efficiency deviation is calculated, and a preset step-size correction mapping rule is matched to obtain the step-size correction ratio. The current is then readjusted to adjust the step size and correct the target output current. Furthermore, the step-size correction ratio monotonically increases with the absolute value of the tracking efficiency deviation, and the correction direction is opposite to the sign of the deviation. This design enables adaptive optimization of the adjustment step size; when the tracking efficiency is low, increasing the step size accelerates the optimization speed and avoids tracking lag. Subsequently, when the tracking efficiency overshoots, the step size is reduced to suppress steady-state oscillations, effectively solving the pain point of the inability to balance optimization speed and system stability in traditional fixed-step adjustment. This ensures that the photovoltaic array can quickly and stably track the maximum power point under the current environment, guaranteeing the maximum output of photovoltaic power in real time. Furthermore, once the photovoltaic array's tracking efficiency reaches the target, the inverter's output AC active power is collected in real time, and the inverter's conversion efficiency is calculated and compared with the preset target conversion efficiency. This achieves real-time monitoring of the inverter's own energy conversion effect, filling the technical gap of only focusing on photovoltaic tracking efficiency while ignoring inverter conversion losses. This forms a dual control system for photovoltaic power generation efficiency and inverter conversion efficiency. Furthermore, when the inverter's conversion efficiency fails to meet the target, the duty cycle adjustment ratio is obtained by calculating the conversion efficiency deviation and matching the preset duty cycle adjustment mapping rule. This dynamically adjusts the duty cycle of the inverter's switching transistors to change the equivalent input impedance. The duty cycle adjustment ratio increases monotonically with the absolute value of the conversion efficiency deviation, and the adjustment direction is opposite to the sign of the deviation. This precise adjustment method can achieve precise matching between the inverter's equivalent input impedance and the photovoltaic array's current output impedance, effectively locking the photovoltaic modules at the voltage corresponding to their maximum power point. This avoids photovoltaic power loss caused by impedance mismatch and significantly improves the inverter's energy conversion efficiency, reducing energy waste during the conversion process.The entire adjustment process forms a complete closed loop encompassing tracking efficiency monitoring, step size correction, target current optimization, conversion efficiency monitoring, duty cycle adjustment, and impedance matching. This layered and progressive control ensures both the maximum power output of the photovoltaic array and maximizes the inverter's conversion efficiency. It effectively solves problems such as poor adaptability, adjustment lag, and high energy loss in traditional inverter impedance adjustment. Simultaneously, it provides stable and efficient power support for the accurate calculation of the total available power of each charging pile and the power supply and demand balance scheduling. This further improves the energy efficiency management system of the integrated photovoltaic-storage-charging power station, enhances the overall energy utilization efficiency, operational stability, and economy of the power station, and provides reliable technical support for the long-term efficient operation and maintenance of the power station.

[0024] Further, the specific steps for dynamically adjusting the output current of charging piles with insufficient capacity are as follows: The total available power of each charging pile with insufficient capacity is compared with a preset minimum sustaining power threshold. If the total available power of any charging pile with insufficient capacity does not reach the minimum sustaining power threshold, the output current of that charging pile is directly adjusted to the preset minimum current value. If the total available power of any charging pile with insufficient capacity reaches the minimum sustaining power threshold, the total available power of that charging pile is matched with a preset reference current mapping rule to obtain a reference output current. The reference current mapping rule is as follows: A correspondence is established between the remaining total available power of the charging pile and the reference output current, so that the reference output current monotonically increases with the increase of the remaining total available power of the charging pile, used to determine the basic output current value of the charging pile based on the current level of remaining total available power. The insufficient power is compared with the preset minimum current value. A first current regulation coefficient is obtained by matching a current regulation rule. The first current regulation rule is a mapping relationship between a preset power deficit and the first current regulation coefficient, which makes the first current regulation coefficient increase non-linearly with the increase of the power deficit. This is used to introduce a primary regulation weight related to the magnitude of the power deficit based on the reference output current. The power consumption rate is then matched with a preset second current regulation rule to obtain a second current regulation coefficient. The second current regulation rule is a mapping relationship between a preset power consumption rate and the second current regulation coefficient, which makes the second current regulation coefficient increase with the acceleration of the power consumption rate. This is used to dynamically compensate the output current according to the rate of change of the power deficit. The reference output current is dynamically corrected based on the first and second current regulation coefficients to obtain the output current of the charging pile with the power deficit.

[0025] In this embodiment, the present invention dynamically adjusts the output current of charging piles with insufficient capacity. First, the total available power of each charging pile with insufficient capacity is compared with the minimum maintenance power threshold. For charging piles that do not meet the threshold, the output current is directly adjusted to the preset minimum current value. This ensures the minimum stable operating conditions of the charging piles from the source, avoiding problems such as charging pile shutdown and power supply abnormalities caused by insufficient available power, and maintaining the basic working state of the charging piles. For charging piles with sufficient total available power, the reference output current is first obtained by matching the remaining total available power with the reference output current according to the monotonically increasing mapping rule. The basic power supply current can be accurately determined according to the real-time remaining available power of the charging pile, realizing the basic adaptation between the output current and available power, avoiding energy waste or insufficient power supply caused by current and power mismatch. Then, the primary adjustment weight is introduced by the first current adjustment coefficient of the nonlinearly increasing mapping of the insufficient power, which can adapt to the differences in insufficient power. By adapting to the changing characteristics of power deficit, this system avoids the problems of lag or over-adjustment caused by linear regulation, making the current regulation more closely match the actual size of the power deficit. At the same time, a second current regulation coefficient, which is positively mapped to the power consumption rate, achieves dynamic compensation of the output current. This allows for rapid response to the rate of change of power deficit and timely adaptive adjustment of the current, improving the real-time performance and sensitivity of the regulation. Finally, the reference output current is dynamically corrected based on the two types of regulation coefficients, ultimately obtaining an output current adapted to the current operating conditions. Overall, this system achieves refined and dynamic adjustment of the output current of the charging pile with power deficit. It not only fully matches the real-time power distribution status of the photovoltaic-storage charging station, but also takes into account both the size and rate of change of the power deficit. This significantly improves the accuracy and rationality of the power station's energy efficiency allocation, optimizes the overall energy efficiency management effect of the photovoltaic-storage charging station, and ensures the stability and reliability of the power supply to the charging pile, avoiding energy loss caused by unreasonable allocation of power resources.

[0026] Further, the specific steps for dynamically adjusting the energy storage dispatch allocation ratio are as follows: First, calculate the total required capacity for this energy storage dispatch by multiplying the deficit power of the deficient charging piles by the preset dispatch cycle duration. Second, take the smaller value between the surplus power of each surplus charging pile and the dispatchable capacity of its supporting energy storage device, and then dynamically calculate the dispatchable power of each surplus charging pile based on the current state of charge and depth of discharge of the energy storage. Third, obtain the distance between each surplus charging pile and the deficient charging pile, and select surplus charging piles whose distance does not reach the preset distance threshold as dispatchable charging piles. Fourth, dynamically allocate and distribute the energy storage based on the distance of each dispatchable charging pile and historical dispatch parameters. The scheduling priority order is as follows: Based on the total demand capacity, the dispatchable power of each dispatchable charging pile, and the allocation scheduling priority order, the energy storage call allocation ratio is dynamically allocated. Based on the total demand capacity and the total dispatchable power of each dispatchable charging pile, a weighted allocation is performed in combination with the allocation scheduling priority order, giving priority to surplus charging piles with higher priority to undertake a larger proportion of scheduling tasks, until the total demand capacity is completely covered or the dispatchable power of all dispatchable charging piles is exhausted. Based on the energy storage call allocation ratio, the corresponding capacity of electrical energy is dispatched from the supporting energy storage devices of each dispatchable charging pile and fed into the common DC bus to provide load support for charging piles with shortages.

[0027] In this embodiment, the present invention dynamically adjusts the energy storage dispatch allocation ratio. First, it calculates the total energy storage dispatch demand based on the shortage power of the charging piles and the dispatch cycle duration. This accurately quantifies the actual power demand of the power station's energy storage dispatch, avoiding insufficient energy storage to support the load or excessive dispatch leading to idle and wasted energy storage resources due to deviations in demand calculation. Then, it calculates the dispatchable power by combining the surplus power of each surplus charging pile with the dispatchable capacity of the supporting energy storage device. This clearly defines the actual power supply capacity of each surplus energy storage, providing accurate data support for subsequent energy storage allocation. By obtaining the distance between each surplus charging pile and the charging piles with shortages and selecting devices that do not meet the preset distance threshold as dispatchable charging piles, the power transmission path can be effectively shortened, significantly reducing line losses and voltage deviations during power transmission, and improving power transmission efficiency and utilization. Based on the distance and historical data of the dispatchable charging piles... The scheduling parameters dynamically determine the scheduling priority, prioritizing efficient short-distance transmission while also considering the operational stability and lifespan of energy storage devices based on historical scheduling data, thus avoiding uneven equipment load caused by single-dimensional scheduling. Furthermore, by dynamically allocating the energy storage call ratio based on total demand capacity, dispatchable power, and priority, refined and rational allocation of energy storage resources can be achieved. This ensures that energy storage scheduling is fully adapted to the real-time power supply and demand status of the power station, maximizing the utilization of surplus energy storage resources. Finally, according to the allocation ratio, corresponding capacity of electricity is dispatched from the supporting energy storage devices to the common DC bus, enabling rapid and accurate load support for charging piles with insufficient capacity, timely filling charging power gaps, ensuring the continuous and stable operation of charging piles, and simultaneously achieving efficient collaborative allocation of energy storage resources within the photovoltaic-energy storage charging station. This reduces dependence on the external power grid, improves the overall energy efficiency management level and power supply reliability of the power station, and optimizes the overall energy utilization efficiency of the power station.

[0028] The specific steps for dynamically allocating scheduling priority based on the distance and historical scheduling parameters of each schedulable charging pile are as follows: Historical scheduling parameters include scheduling success rate, average scheduling speed, and total scheduling power; the distance of each schedulable charging pile is matched with a preset distance priority mapping rule to obtain an initial priority score for each schedulable charging pile. The distance priority mapping rule establishes a correspondence between the distance between schedulable charging piles and available charging piles and the initial priority score, making the initial priority score monotonically decrease as the distance increases, used to determine the basic scheduling priority of each schedulable charging pile based on spatial proximity; a weighted summation is performed based on the historical scheduling parameters of each schedulable charging pile to obtain a comprehensive scheduling score for each schedulable charging pile; and the final scheduling score is determined based on the historical scheduling parameters of each schedulable charging pile. The comprehensive scheduling score of each charging pile is matched with a preset score correction mapping rule to obtain the scheduling priority correction coefficient of each schedulable charging pile. The score correction mapping rule is as follows: a correspondence is established between the comprehensive scheduling score and the scheduling priority correction coefficient, so that the correction coefficient increases monotonically with the increase of the comprehensive scheduling score. This is used to dynamically adjust the initial priority based on historical scheduling performance. Charging piles with higher scheduling success rate, faster average scheduling speed, and larger total scheduling power receive higher correction coefficients. Based on the scheduling priority correction coefficient of each schedulable charging pile, the initial priority score of each schedulable charging pile is dynamically corrected to obtain the scheduling priority index of each schedulable charging pile. The schedulable charging piles are sorted in reverse order according to the scheduling priority index to obtain the allocation scheduling priority order.

[0029] In this embodiment, the present invention dynamically allocates scheduling priority based on the distance of schedulable charging piles and historical scheduling parameters. First, it incorporates scheduling success rate, average scheduling speed, and total scheduling power into the historical scheduling parameter framework. This comprehensively characterizes the historical scheduling performance of each charging pile from multiple dimensions, including scheduling reliability, scheduling response efficiency, and scheduling power supply capacity, providing a complete and practical reference for priority assessment. An initial priority score is obtained by matching the distance between each schedulable charging pile and the missing charging piles according to a preset distance priority mapping rule. The score monotonically decreases with increasing distance, prioritizing spatially adjacent charging piles to achieve basic scheduling advantages. This reduces power transmission losses and shortens the scheduling response path from a physical transmission perspective, laying the spatial layout foundation for subsequent efficient energy storage scheduling. Then, a comprehensive scheduling score is obtained by weighted summing of the multi-dimensional historical scheduling parameters of each charging pile. Finally, a scheduling priority correction coefficient is obtained by matching the comprehensive scheduling score with a score correction mapping rule, ensuring that the historical scheduling... Charging piles with better performance receive a higher correction coefficient, which effectively compensates for the one-sidedness of prioritizing based solely on distance. This takes into account the actual scheduling capabilities and operational stability of the equipment, avoiding problems such as scheduling failures and response delays caused by poor historical scheduling performance. Subsequently, the initial priority score is dynamically corrected using this correction coefficient to obtain a scheduling priority index that takes into account spatial proximity and historical scheduling reliability. The final allocation order of scheduling priorities is then determined by reverse sorting, enabling scientific and refined dynamic allocation of scheduling priorities. This not only ensures the transmission efficiency and low loss advantages of energy storage scheduling, but also fully leverages historical operating data to select equipment with superior scheduling performance, significantly improving the success rate and response speed of energy storage scheduling. It avoids the problems of unreasonable scheduling and unbalanced resource allocation caused by single-dimensional priority determination, thereby making subsequent energy storage call allocation more targeted and reasonable. This further optimizes the energy storage collaborative scheduling effect within the photovoltaic-energy storage charging station, improving the accuracy of power station energy efficiency management and overall operational reliability.

[0030] like Figure 2The diagram shows a flowchart of the dynamic adjustment of the reference output current in the power plant energy efficiency management method based on photovoltaic-storage-charging management provided in this application embodiment. The specific steps for dynamically adjusting the reference output current in the next power plant energy efficiency management cycle are as follows: charging piles whose photovoltaic absorption rate has not reached the preset photovoltaic absorption rate threshold are recorded as low absorption charging piles, and the average photovoltaic absorption rate of each low absorption charging pile is calculated; the difference between the preset photovoltaic absorption rate threshold and the average photovoltaic absorption rate is recorded as the average absorption rate deviation; based on the average absorption rate deviation, a preset absorption rate deviation reference correction mapping rule is matched to obtain the reference current correction coefficient. The absorption rate deviation reference correction mapping rule is as follows: a correspondence is established between the average absorption rate deviation and the reference current correction coefficient, so that the reference current correction coefficient increases monotonically with the increase of the average absorption rate deviation, which is used to make a global step adjustment of the reference output current in the next cycle according to the overall deviation of the low absorption charging piles. The difference between the preset photovoltaic absorption rate threshold and the minimum photovoltaic absorption rate of each low-absorption charging pile is recorded as the minimum absorption rate deviation. Based on the minimum absorption rate deviation, a preset absorption rate deviation limit correction mapping rule is matched to obtain the limit current correction coefficient. The absorption rate deviation limit correction mapping rule is as follows: establish a correspondence between the minimum absorption rate deviation and the limit current correction coefficient, so that the limit current correction coefficient increases non-linearly with the increase of the minimum absorption rate deviation, and the correction magnitude is greater than the reference current correction coefficient. It is used to perform boundary forced correction of the reference output current according to the deviation degree of the worst individual in the low-absorption charging pile, so as to ensure that the photovoltaic absorption rate of all charging piles converges quickly to above the preset threshold. The reference current correction coefficient is obtained by weighted summation of the reference current correction coefficient and the limit current correction coefficient. The reference output current of the next power station energy efficiency management cycle is dynamically corrected based on the reference current correction coefficient.

[0031] In this embodiment, the present invention dynamically adjusts the reference output current for the next power station energy efficiency management cycle. First, charging piles with photovoltaic absorption rates below the threshold are designated as low-absorption charging piles, and their average photovoltaic absorption rate is calculated. This allows for precise understanding of the gap between the overall photovoltaic absorption level of the charging piles and the target value within the current cycle, providing a reliable basis for global optimization of the reference output current. By calculating the average absorption rate deviation between the preset photovoltaic absorption rate threshold and the average photovoltaic absorption rate, and matching the corresponding mapping rules, a reference current correction coefficient that monotonically increases with the deviation is obtained. Based on the overall deviation of the low-absorption charging piles, the reference output current for the next cycle can be globally adjusted step-by-step. This gradually improves the overall utilization efficiency of photovoltaic energy while ensuring a smooth transition of the charging load, avoiding the impact of large current fluctuations on charging equipment and the power grid. Simultaneously, the minimum absorption rate deviation between the preset threshold and the minimum photovoltaic absorption rate within the low-absorption charging piles is calculated. Based on the deviation matching limit correction mapping rule, a limit current correction coefficient with nonlinear increasing and larger correction magnitude is obtained. This can perform boundary forced correction for individual charging piles with the worst absorption performance, quickly make up for extreme absorption shortcomings, prevent the absorption capacity of individual equipment from being continuously low and dragging down the overall energy efficiency of the power station, and ensure that the photovoltaic absorption rate of all charging piles quickly converges to above the preset threshold. Finally, the two types of correction coefficients are weighted and summed to obtain the comprehensive reference current correction coefficient, and the reference output current for the next cycle is dynamically corrected. This achieves both global overall optimization of photovoltaic absorption level and limit constraint correction for the worst absorption condition. The dual adjustment mechanism makes the setting of the reference output current more scientific and reasonable, which can steadily improve the photovoltaic absorption rate, reduce curtailment loss and grid power dependence, and ensure the stability and consistency of charging output of each charging pile. This significantly enhances the adaptive adjustment capability of photovoltaic-storage charging station energy efficiency management and overall energy utilization efficiency.

[0032] The dynamic adjustment of the reference output current also includes a current adaptive correction mechanism based on the convergence speed of photovoltaic grid absorption rate. Specifically, this involves: acquiring the average grid absorption rate deviation and the minimum grid absorption rate deviation within a preset first statistical period, constructing two sets of time series data; using the least squares method or the difference method to perform linear regression fitting on the two sets of time series data to obtain the slope of the average grid absorption rate deviation change and the slope of the minimum grid absorption rate deviation change; and then performing a weighted summation of the slopes of the average grid absorption rate deviation change and the minimum grid absorption rate deviation change to obtain a comprehensive convergence speed index; if the comprehensive convergence speed index reaches a preset convergence speed index threshold, it indicates that the photovoltaic grid absorption rate has reached its maximum value. The photovoltaic grid connection rate is rapidly approaching the preset photovoltaic grid connection rate threshold, maintaining the reference current correction coefficient unchanged. If the comprehensive convergence speed index fails to reach the preset convergence speed index threshold and the duration does not exceed the preset second statistical period, it indicates that the photovoltaic grid connection rate adjustment speed is too slow. The reference current correction coefficient is dynamically adjusted according to the preset reference current adjustment step size to accelerate the adjustment range of the reference output current. If the comprehensive convergence speed index fails to reach the preset convergence speed index threshold and the duration exceeds the preset second statistical period, it indicates that the grid connection rate deviation continues to expand and the adjustment mechanism fails, triggering a grid connection rate abnormality alarm. At the same time, the reference output current is locked to the preset minimum safety threshold.

[0033] In this embodiment, the present invention obtains the average and minimum absorption rate deviations within the first statistical period and constructs corresponding time series data by adding a current adaptive correction mechanism based on the convergence speed of photovoltaic absorption rate during the dynamic adjustment of the reference output current. The least squares method or the difference method is used to perform linear regression fitting to obtain the slopes of the two types of deviations. A weighted summation is then performed to obtain a comprehensive convergence speed index, which can accurately quantify the actual rate at which the photovoltaic absorption rate approaches the preset threshold, objectively reflecting the adjustment effectiveness of the current reference current correction strategy and providing a quantitative basis for subsequent differentiated regulation. When the comprehensive convergence speed index meets the standard, the reference current correction coefficient remains unchanged, avoiding unnecessary current adjustments that could cause charging output oscillations and ensuring the stability of the charging pile's operating conditions and the power distribution of the power station. When the comprehensive convergence speed index fails to meet the standard and the duration does not exceed the second statistical period, the reference current correction coefficient is dynamically adjusted according to a preset step size to increase the absorption rate. The adjustment range can specifically address the issues of lag and slow convergence in photovoltaic (PV) grid connection rate adjustment, accelerating the rate of convergence towards the target threshold and improving energy efficiency optimization efficiency. When the comprehensive convergence speed indicator fails to meet the standard and times out, an abnormal grid connection rate alarm is triggered in a timely manner, and the reference output current is locked to the minimum safety threshold. This not only quickly alerts maintenance personnel to investigate adjustment failures but also prevents the grid connection rate deviation from continuing to expand, leading to increased PV curtailment losses, a significant decline in power plant energy efficiency, or even equipment malfunctions, through safety current threshold constraints. This mechanism forms a closed-loop adaptive adjustment logic of quantitative assessment, graded control, and anomaly protection. It not only compensates for the lag in correcting the current based solely on the grid connection rate deviation but also takes into account both the energy efficiency optimization rate and the power plant's operational safety. This significantly improves the dynamic adaptive capability, anti-interference capability, and operational reliability of the PV-storage-charging station energy efficiency management system, ensuring a stable and efficient PV grid connection rate control process with fault fallback protection capabilities.

[0034] like Figure 3The diagram shows the structure of a power plant energy efficiency management system based on photovoltaic-storage-charging management provided in this application embodiment. It includes: a photovoltaic array maximum power point tracking (MPPT) adjustment module, a photovoltaic-storage-charging collaborative power allocation and scheduling module, and a photovoltaic absorption rate closed-loop feedback adjustment module. The MPPT adjustment module obtains the reference output current of the power plant's photovoltaic array, dynamically adjusts the current adjustment step size based on the deviation between the current operating point and the maximum power point, and dynamically adjusts the reference output current based on the irradiance and photovoltaic module conversion efficiency to obtain the target output current. It calculates the real-time photovoltaic power based on the target output current and the real-time operating voltage, and dynamically adjusts the inverter's equivalent input impedance based on the inverter's conversion efficiency to ensure the photovoltaic modules operate at the voltage corresponding to the maximum power point under the current irradiance conditions. The photovoltaic-storage-charging collaborative power allocation and scheduling module calculates the real-time photovoltaic power and the energy storage release capacity of each charging pile based on the real-time photovoltaic power and the energy storage release capacity of each charging pile. The system calculates the total available power; marks charging piles whose total available power reaches the required power as surplus charging piles, calculates the surplus power of each surplus charging pile and stores it in the energy storage device of that surplus charging pile; marks charging piles whose total available power does not reach the required power as deficit charging piles, calculates the deficit power of each deficit charging pile and dynamically adjusts the output current of the deficit charging pile, and dynamically adjusts the energy storage call allocation ratio by combining the deficit power, the surplus power of each surplus charging pile and historical scheduling parameters, and schedules surplus energy storage capacity to provide temporary load support for deficit charging piles; the photovoltaic absorption rate closed-loop feedback adjustment module is used to calculate the photovoltaic absorption rate of each charging pile in the current power station energy efficiency management cycle, calculate the proportion of charging piles whose photovoltaic absorption rate reaches the preset photovoltaic absorption rate threshold; determine whether the proportion of charging piles reaches the preset proportion target, if so, maintain the current benchmark output current, otherwise dynamically adjust the benchmark output current of the next power station energy efficiency management cycle.

[0035] This application provides an electronic device, including one or more processors and one or more memories. The one or more memories store at least one computer program, which is loaded and executed by the one or more processors to implement a power plant energy efficiency management method based on photovoltaic-storage-charging management.

Claims

1. A power plant energy efficiency management method based on photovoltaic-storage-charging management, characterized in that, Includes the following steps: S01, obtain the reference output current of the photovoltaic array of the power station, dynamically adjust the current adjustment step size based on the deviation between the current operating point and the maximum power point, and dynamically adjust the reference output current in combination with the light radiation intensity and the photovoltaic module conversion efficiency to obtain the target output current; The real-time photovoltaic power is calculated based on the target output current and real-time operating voltage. The equivalent input impedance of the inverter is dynamically adjusted in combination with the inverter conversion efficiency so that the photovoltaic module operates at the voltage corresponding to the maximum power point under the current illumination conditions, ensuring that the photovoltaic array stably outputs the real-time photovoltaic power under the current operating conditions. S02, calculate the total available power of each charging pile based on the real-time photovoltaic power and energy storage release power corresponding to each charging pile; mark the charging piles whose total available power reaches the required power as surplus charging piles, count the surplus power of each surplus charging pile and store it in the energy storage device of the surplus charging pile; mark the charging piles whose total available power does not reach the required power as deficit charging piles, count the deficit power of each deficit charging pile and dynamically adjust the output current of the deficit charging piles, and combine the deficit power, the surplus power of each surplus charging pile and historical scheduling parameters to dynamically adjust the energy storage call allocation ratio, and schedule the surplus energy storage capacity to provide temporary load support for the deficit charging piles. S03, calculate the photovoltaic absorption rate of each charging pile in the current power station energy efficiency management cycle, calculate the proportion of charging piles whose photovoltaic absorption rate reaches the preset photovoltaic absorption rate threshold; determine whether the proportion of charging piles has reached the preset proportion target. If so, maintain the current benchmark output current; otherwise, dynamically adjust the benchmark output current for the next power station energy efficiency management cycle.

2. The power plant energy efficiency management method based on photovoltaic-storage-charging management as described in claim 1, characterized in that: The target output current of the photovoltaic array in the power station is obtained as follows: Real-time acquisition of the operating voltage and current of the photovoltaic array at the current operating point, the current light radiation intensity and the conversion efficiency of the photovoltaic module, and predefined reference output current, minimum current adjustment step size and maximum current adjustment step size; The current light radiation intensity is matched with the preset power point mapping rule to obtain the maximum power point, and the voltage deviation and power deviation between the current operating point and the maximum power point are calculated. The combined deviation is obtained by weighted summation of the voltage deviation and power deviation. The current adjustment step size is obtained by matching the comprehensive deviation with the preset step size adjustment mapping rule. It is then determined whether the current adjustment step size is within the range of the minimum current adjustment step size and the maximum current adjustment step size. If it is, the current adjustment step size is directly used as the effective adjustment step size of the current power plant energy efficiency management cycle. Otherwise, the current adjustment step size is limited to the nearest minimum current adjustment step size or the maximum current adjustment step size. The current light radiation intensity and photovoltaic module conversion efficiency are matched with the preset first current correction rule and second current correction rule respectively to obtain the first current correction ratio and the second current correction ratio. Based on the first current correction ratio, the second current correction ratio, and the current adjustment step size, the reference current correction amount is calculated. Based on the reference current correction amount, the reference output current is dynamically corrected to obtain the target output current of the power station photovoltaic array.

3. The power plant energy efficiency management method based on photovoltaic-storage-charging management as described in claim 1, characterized in that: The specific steps for dynamically adjusting the equivalent input impedance of the inverter are as follows: The ratio of the real-time photovoltaic power to the theoretical maximum power value corresponding to the maximum power point is denoted as the photovoltaic array tracking efficiency. Determine whether the tracking efficiency of the photovoltaic array has reached the preset target tracking efficiency. If it has not been reached, the difference between the target tracking efficiency and the tracking efficiency of the photovoltaic array is recorded as the tracking efficiency deviation. Based on the tracking efficiency deviation, a preset step size correction mapping rule is matched to obtain the step size correction ratio. Based on the step size correction ratio, the dynamic adjustment of the current adjustment step size and the correction of the target output current are re-executed. If the target is reached, the AC active power on the inverter output side is collected in real time, and the ratio of the AC active power to the real-time photovoltaic power is recorded as the inverter conversion efficiency. Determine whether the inverter conversion efficiency has reached the preset target conversion efficiency. If so, no additional processing is performed. Otherwise, the difference between the inverter target conversion efficiency and the inverter conversion efficiency is recorded as the conversion efficiency deviation. Based on the conversion efficiency deviation, a preset duty cycle adjustment mapping rule is matched to obtain the duty cycle adjustment ratio. Based on the duty cycle adjustment ratio, the switching duty cycle of the inverter is dynamically adjusted to adjust the equivalent input impedance of the inverter, thereby locking the operating voltage of the photovoltaic module.

4. The power plant energy efficiency management method based on photovoltaic-storage-charging management as described in claim 1, characterized in that: The specific steps for dynamically adjusting the output current of the charging pile with insufficient capacity are as follows: The total available power of each charging pile with insufficient capacity is compared with the preset minimum maintenance power threshold. If the total available power of any charging pile with insufficient capacity does not reach the minimum maintenance power threshold, the output current of the charging pile with insufficient capacity is directly adjusted to the preset minimum current value. If the total available power of any charging pile with insufficient capacity reaches the minimum maintenance power threshold, the total available power of the charging pile with insufficient capacity is matched with the preset reference current mapping rule to obtain the reference output current; the insufficient power is matched with the preset first current adjustment rule to obtain the first current adjustment coefficient. The power consumption rate is matched with the preset second current regulation rule to obtain the second current regulation coefficient; The reference output current is dynamically corrected based on the first current regulation coefficient and the second current regulation coefficient to obtain the output current of the charging pile with insufficient capacity.

5. The power plant energy efficiency management method based on photovoltaic-storage-charging management as described in claim 1, characterized in that: The specific steps for dynamically adjusting the energy storage allocation ratio are as follows: Based on the power deficit of the charging piles and the preset scheduling cycle duration, the total demand capacity of this energy storage scheduling is calculated. Based on the surplus power of each surplus charging pile and the dispatchable capacity of the supporting energy storage device, the dispatchable power of each surplus charging pile is calculated. Obtain the distance between each surplus charging pile and the shortage charging pile, and filter the surplus charging piles whose distance does not reach the preset distance threshold as schedulable charging piles. The scheduling priority order is dynamically allocated based on the distance and historical scheduling parameters of each schedulable charging pile. Based on the total demand capacity, the schedulable power of each schedulable charging pile, and the allocation priority order, the energy storage call allocation ratio is dynamically allocated. Based on the energy storage allocation ratio, corresponding capacity of electrical energy is dispatched from the energy storage devices of each schedulable charging pile and fed into the common DC bus to provide load support for charging piles with insufficient capacity.

6. The power plant energy efficiency management method based on photovoltaic-storage-charging management as described in claim 5, characterized in that: The specific steps for dynamically allocating scheduling priority order based on the distance and historical scheduling parameters of each schedulable charging pile are as follows: The historical scheduling parameters include scheduling success rate, average scheduling speed, and total scheduling power. The distance of each schedulable charging pile is matched with a preset distance priority mapping rule to obtain the initial priority score of each schedulable charging pile. The comprehensive scheduling score of each schedulable charging pile is obtained by weighted summation based on the historical scheduling parameters of each schedulable charging pile. The scheduling priority correction coefficient of each schedulable charging pile is obtained by matching the comprehensive scheduling score of each schedulable charging pile with the preset score correction mapping rule. The initial priority score of each schedulable charging pile is dynamically corrected based on the scheduling priority correction coefficient of each schedulable charging pile to obtain the scheduling priority index of each schedulable charging pile. The schedulable charging piles are then sorted in reverse order according to the scheduling priority index to obtain the allocation scheduling priority order.

7. The power plant energy efficiency management method based on photovoltaic-storage-charging management as described in claim 1, characterized in that: The specific steps for dynamically adjusting the reference output current for the next power plant energy efficiency management cycle are as follows: Charging piles whose photovoltaic absorption rate does not reach the preset photovoltaic absorption rate threshold are recorded as low absorption charging piles, and the average photovoltaic absorption rate of each low absorption charging pile is calculated. The difference between the preset photovoltaic absorption rate threshold and the average photovoltaic absorption rate is recorded as the average absorption rate deviation. Based on the average absorption rate deviation, a preset absorption rate deviation benchmark correction mapping rule is matched to obtain the benchmark current correction coefficient. The difference between the preset photovoltaic absorption rate threshold and the minimum photovoltaic absorption rate in each low absorption charging pile is recorded as the minimum absorption rate deviation. Based on the minimum absorption rate deviation, a preset absorption rate deviation limit correction mapping rule is matched to obtain the limit current correction coefficient. The reference current correction coefficient is obtained by weighted summation of the reference current correction coefficient and the limiting current correction coefficient. The reference output current for the next power plant energy efficiency management cycle is then dynamically corrected based on the reference current correction coefficient.

8. The power plant energy efficiency management method based on photovoltaic-storage-charging management as described in claim 7, characterized in that: The process of dynamically adjusting the reference output current for the next power plant energy efficiency management cycle also includes a current adaptive correction mechanism based on the convergence speed of photovoltaic absorption rate, specifically: Obtain the average absorption rate deviation and minimum absorption rate deviation within the preset first statistical period, and construct two sets of time series data respectively; Linear regression fitting was performed on the two sets of time series data to obtain the slope of the average absorption rate deviation and the slope of the minimum absorption rate deviation. The average absorption rate deviation and the minimum absorption rate deviation were then weighted and summed to obtain a comprehensive convergence speed index. If the overall convergence speed index reaches the preset convergence speed index threshold, the reference current correction coefficient remains unchanged. If the overall convergence speed index does not reach the preset convergence speed index threshold and the duration does not exceed the preset second statistical period, the reference current correction coefficient is dynamically adjusted according to the preset reference current adjustment step size to accelerate the adjustment range of the reference output current. If the overall convergence speed index fails to reach the preset convergence speed index threshold and the duration exceeds the preset second statistical period, an abnormal absorption rate alarm is triggered, and the reference output current is locked to the preset minimum safety threshold.

9. A system applying the power plant energy efficiency management method based on photovoltaic-storage-charging management as described in any one of claims 1-8, characterized in that, include: Photovoltaic array maximum power tracking regulation module, photovoltaic-storage-charging coordinated power allocation and scheduling module, photovoltaic absorption rate closed-loop feedback regulation module; The photovoltaic array maximum power tracking adjustment module is used to obtain the reference output current of the photovoltaic array of the power station, dynamically adjust the current adjustment step size based on the deviation between the current operating point and the maximum power point, and dynamically adjust the reference output current in combination with the irradiance and the conversion efficiency of the photovoltaic module to obtain the target output current. The real-time photovoltaic power is calculated based on the target output current and the real-time operating voltage. The equivalent input impedance of the inverter is dynamically adjusted in combination with the inverter conversion efficiency so that the photovoltaic module operates at the voltage corresponding to the maximum power point under the current irradiance conditions. The photovoltaic-storage-charging collaborative power allocation and scheduling module is used to calculate the total available power of each charging pile based on the real-time photovoltaic power and the energy storage release power corresponding to each charging pile; to mark the charging piles whose total available power reaches the required power as surplus charging piles, to count the surplus power of each surplus charging pile and store it in the energy storage device of the surplus charging pile; to mark the charging piles whose total available power does not reach the required power as deficit charging piles, to count the deficit power of each deficit charging pile and to dynamically adjust the output current of the deficit charging pile, and to dynamically adjust the energy storage call allocation ratio by combining the deficit power, the surplus power of each surplus charging pile and historical scheduling parameters, and to schedule the surplus energy storage capacity to provide temporary load support for the deficit charging piles. The photovoltaic absorption rate closed-loop feedback adjustment module is used to statistically analyze the photovoltaic absorption rate of each charging pile in the current power station energy efficiency management cycle, calculate the proportion of charging piles whose photovoltaic absorption rate reaches the preset photovoltaic absorption rate threshold, determine whether the proportion of charging piles reaches the preset proportion target, if so, maintain the current benchmark output current, otherwise dynamically adjust the benchmark output current of the next power station energy efficiency management cycle.

10. A power plant energy efficiency management computing device based on photovoltaic-storage-charging management, characterized in that, include: One or more processors; A storage device for storing one or more programs, which, when executed by one or more processors, cause the one or more processors to implement the power plant energy efficiency management method based on photovoltaic-storage-charging management as described in any one of claims 1 to 8.

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