A flexible transformation method, system, device and storage medium based on "optical storage flexible direct charging" distributed power supply station

Abstract

The application discloses a kind of based on " light storage soft direct filling " distributed power supply station flexible reconstruction method, system, equipment and storage medium, it is related to distributed power supply flexible reconstruction technical field, including based on distributed power supply data determines reconstruction direction, integrates light storage and fills power supply;According to the reconstruction direction determined, energy management control strategy is executed;Combined with distributed power supply data and prediction result, control strategy is adjusted.The method of the application ensures that stable power supply can be maintained under different weather and light conditions, and can effectively reduce electricity cost and improve power supply reliability, the system can better adapt to environmental changes and demand, can predict and adjust the dependence on external power purchase in advance, so as to realize the best power supply effect.

Description

Technical Field

[0001] This invention relates to the field of flexible transformation technology for distributed power supply, specifically to a method, system, equipment, and storage medium for flexible transformation of distributed power supply stations based on "photovoltaic-storage-flexible-direct-charging". Background Technology

[0002] In traditional distributed power supply designs for prisons, schools, and rural and pastoral areas, most focus on external power supply systems that directly purchase electricity from the grid company, lacking the utilization of renewable energy sources such as solar photovoltaic power generation and energy storage for self-generated power. Distributed power users cannot integrate and balance internal and external power supply resources to effectively reduce the cost of distributed power supply. In addition, existing power supply systems may lack flexible energy management and control strategies to adapt to different environments and demand changes, and their distribution systems exhibit closed-loop design with open-loop operation, resulting in problems such as power imbalance in feeders within the distribution network, insufficient capacity expansion capabilities, and reduced power supply reliability.

[0003] Therefore, there is an urgent need for a reliable "photovoltaic-storage-flexible-direct-charging" distributed power supply flexible transformation method and system to solve the problems of insufficient balance and integration of multiple power supply resources (such as solar energy and purchased power) in the existing distributed power supply design methods, as well as how to maintain power supply stability under varying solar radiation conditions and maximize energy utilization efficiency and effectively reduce power supply costs; and to solve problems such as power imbalance of feeders in the distribution network, insufficient capacity expansion capability of power supply, and reduced power supply reliability. Summary of the Invention

[0004] In view of the above-mentioned problems, the present invention is proposed.

[0005] Therefore, the technical problem solved by this invention is that existing distributed power supply design methods have insufficient balance and integration of various power supply resources, which can effectively reduce power supply costs, solve the problem of power imbalance in the distribution network feeders, and address the issue of how to maintain power supply stability under varying solar radiation conditions.

[0006] To address the aforementioned technical problems, this invention provides the following technical solution: a flexible transformation method for distributed power stations based on "photovoltaic-storage-flexible-direct-charging" technology, comprising determining the transformation direction based on distributed power supply data, integrating photovoltaic, energy storage, charging, and power supply; executing energy management and control strategies according to the determined transformation direction; and adjusting the control strategies in conjunction with distributed power supply data and prediction results.

[0007] As a preferred embodiment of the flexible transformation method for distributed power stations based on "photovoltaic storage flexible direct charging" described in this invention, the method of determining the transformation direction includes: recording the actual output and theoretical maximum output in the same time period, calculating the energy conversion efficiency; if the energy conversion efficiency is less than a predetermined value, judging the solar radiation stability; if the energy conversion efficiency is greater than a predetermined value, evaluating the grid frequency stability.

[0008] As a preferred embodiment of the flexible transformation method for distributed power stations based on "photovoltaic-storage-flexible direct charging" described in this invention, the evaluation of grid frequency stability includes: Record the power grid frequency data for the same time period, calculate the frequency deviation, and if both the frequency deviation and the data deviation are greater than or equal to their preset thresholds, it is determined to be a direction for variable speed constant frequency transformation. If the frequency deviation exceeds the preset threshold but the data deviation does not exceed the preset threshold, check the frequency sensor, perform resonance analysis, and adjust the control strategy.

[0009] If the data deviation exceeds the preset threshold, but the frequency deviation does not exceed the preset threshold, perform a diagnosis of temporary faults or external interference, conduct power quality analysis, and implement an adjustment strategy to enhance system stability. If the frequency deviation and data deviation are within the allowable range, a second review is conducted to re-examine the data and determine whether there are any omissions or misjudgments. If all indicators meet the preset requirements, routine maintenance is performed.

[0010] As a preferred embodiment of the flexible transformation method for distributed power stations based on "photovoltaic-storage-flexible direct charging" described in this invention, the integrated photovoltaic-storage-charging power supply includes: acquiring historical sunshine data and power load data; using historical data to assess the maximum potential capacity of photovoltaic power generation; calculating the total energy supply at different time points; establishing a model based on historical data to predict future power generation capacity and purchased power supply; determining the optimal capacity required for energy storage batteries; determining the standby time T; considering the standby time; combining photovoltaic and energy storage battery systems; establishing a comprehensive energy management system; and optimizing the configuration of photovoltaic modules according to power generation potential and load demand.

[0011] As a preferred embodiment of the flexible transformation method for distributed power stations based on "photovoltaic storage flexible direct charging" described in this invention, the energy management and control strategy includes: when determining the direction of solar management and solar stabilization, solar monitoring sensors are installed on the main road to monitor solar intensity in real time and wirelessly transmit the data to the central control system; a three-dimensional model of solar intensity is visualized using a geographic information system; the photovoltaic power generation working mode is adjusted; a neural network strategy, a hydraulic drive system, and multi-mode switching are applied to cope with changes in solar intensity; in conjunction with the solar monitoring system, when fluctuations exceed a threshold, the power station demand is balanced by adjusting the photovoltaic panel angle control and purchasing external electricity; a machine learning algorithm is used to predict future solar intensity, and the photovoltaic panel angle strategy is adjusted accordingly.

[0012] As a preferred embodiment of the flexible transformation method for distributed power stations based on "photovoltaic-storage-flexible direct charging" described in this invention, the adjustment control strategy includes: when it is determined that adjustments to the photovoltaic panel configuration, angle, or expansion direction are to be considered, adjusting the angle of the photovoltaic panels using real-time solar irradiance data; optimizing the arrangement of photovoltaic panels during periods of insufficient solar irradiance; and adjusting the number of photovoltaic panels based on historical solar irradiance data and power demand. When it is determined that the transformation direction is constant frequency, fine-tuning of the frequency is performed using the output of the photovoltaic system and the battery energy storage system. When it is determined that the frequency sensor needs to be checked and resonance analysis is performed, the frequency sensor is periodically calibrated and maintained when adjusting the control strategy to ensure... To ensure data accuracy, when frequency anomalies are detected, backup sensors are activated and fault location is performed. Control algorithms are optimized, and speed and output are adjusted based on real-time data. When a temporary fault or external interference is detected, power quality analysis is conducted. When implementing strategies to enhance system stability, power quality analysis is performed in conjunction with grid conditions and user needs. Power quality is improved through reactive power compensation equipment and filters, and the system is simulated and stress-tested. When routine maintenance is detected, a data backtracking mechanism is established to re-analyze historical data. Fault prediction and diagnosis are performed using artificial intelligence algorithms, and backup sensors and data sources are introduced into the data analysis.

[0013] As a preferred embodiment of the flexible transformation method for distributed power stations based on "photovoltaic storage flexible direct charging" described in this invention, the frequency fine-tuning includes: if the adjusted angle exceeds the upper limit threshold, the photovoltaic system will be used as the basic output, and the energy storage system will be used for frequency fine-tuning; if the adjusted angle is lower than the lower limit threshold, the photovoltaic system will reduce its output and increase the amount of purchased electricity to balance the stability of the system.

[0014] Another objective of this invention is to provide a flexible transformation system for distributed power stations based on "photovoltaic-storage-flexible-direct-charging" technology. This system can determine the transformation direction based on distributed power supply data, integrate photovoltaic, energy storage, charging, and power supply, and solve the problem of insufficient balance and integration of multiple power supply resources in current distributed power supply design technologies.

[0015] As a preferred embodiment of the flexible transformation system for distributed power stations based on "photovoltaic-storage-flexible-direct-charging" described in this invention, it includes: an energy acquisition module, an energy storage module, an intelligent scheduling module, and a visual maintenance module; the energy acquisition module is used to collect power station data and process information to determine the transformation direction and provide decision-making basis for the intelligent scheduling module; the energy storage module is used to execute energy management and control strategies based on the collected power station data and prediction results; the intelligent scheduling module is used to perform system scheduling based on data analysis and energy management strategies, and to make intelligent adjustments based on the stability of solar radiation and the stability of grid frequency; the visual maintenance module provides a user interface, allowing operators to view various data in real time, and is responsible for system testing and verification after adjustments.

[0016] Another objective of this invention is to provide a flexible retrofit device for distributed power stations based on "photovoltaic-storage-flexible-direct-charging" technology, comprising a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the steps of the flexible retrofit method for distributed power stations based on "photovoltaic-storage-flexible-direct-charging".

[0017] Another object of the present invention is to provide a storage medium for flexible transformation of distributed power stations based on "photovoltaic storage flexible direct charging", which stores a computer program. When the computer program is executed by a processor, it implements the steps of the method for flexible transformation of distributed power stations based on "photovoltaic storage flexible direct charging".

[0018] The beneficial effects of this invention are: The "photovoltaic-storage-flexible direct charging" distributed power station flexible transformation method provided by this invention integrates solar (photovoltaic) and purchased electricity to ensure stable power supply under different weather and electricity cost conditions. Flexible energy management and control strategies enable the system to better adapt to environmental changes and demands. The system's real-time monitoring and data analysis capabilities can predict and adjust dependence on solar energy in advance, thereby achieving optimal power supply performance. Furthermore, the adoption of flexible interconnection devices (FID) enables flexible power flow control among multiple feeders, achieving load balancing, optimizing grid power supply capacity, and improving distribution network reliability and equipment utilization. This invention achieves significantly better results in improving energy efficiency, enhancing system stability, and reducing power supply costs. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 The above is an overall flowchart of a flexible transformation method for distributed power stations based on "photovoltaic storage flexible direct charging" provided in Embodiment 1 of the present invention.

[0021] Figure 2 This is a topology diagram of a multi-terminal flexible controller based on a flexible transformation method for distributed power stations using a "photovoltaic-storage-flexible-direct-charging" system, provided in Embodiment 1 of the present invention. Detailed Implementation

[0022] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0023] Example 1, referring to Figures 1-2 As one embodiment of the present invention, a method for flexible transformation of distributed power stations based on "photovoltaic-storage-flexible direct charging" is provided, comprising: S1: Determine the transformation direction based on distributed power supply data, and integrate photovoltaic, energy storage, and charging power supply.

[0024] Specifically, determining the direction of the transformation includes recording the actual output and theoretical maximum output for the same time period, calculating the energy conversion efficiency, judging the solar stability if the energy conversion efficiency is less than the predetermined value, and assessing the grid frequency stability if the energy conversion efficiency is greater than the predetermined value.

[0025] The distributed power supply data includes the power and peak / valley values ​​of the distributed power supply, electricity price, energy conversion efficiency, historical sunshine conditions, and the cost of photovoltaic and energy storage.

[0026] To determine the stability of solar radiation, obtain solar radiation intensity data for the same time period, analyze the correlation between solar radiation and actual power generation, and determine solar radiation instability if the fluctuation of solar radiation intensity is greater than or equal to a preset threshold, and then carry out solar radiation management and solar radiation stabilization. If the solar radiation data is lower than the preset threshold, consider adjusting the configuration of photovoltaic panels, adjusting the angle, or expanding the direction of photovoltaic panels.

[0027] Assessing grid frequency stability involves recording grid frequency data over the same time period, calculating frequency deviation, and determining if both frequency deviation and data deviation are greater than or equal to their preset thresholds. If the frequency deviation exceeds the preset threshold but the data deviation does not, the frequency sensor is checked, resonance analysis is performed, and the control strategy is adjusted. If the data deviation exceeds the preset threshold but the frequency deviation does not, temporary faults or external interference are diagnosed, power quality analysis is conducted, and strategies to enhance system stability are implemented. If both frequency deviation and data deviation are within acceptable limits, a second review is performed to re-examine the data and determine if any omissions or misjudgments exist. If all indicators meet the preset requirements, routine maintenance is performed.

[0028] It should be noted that the integrated photovoltaic-storage-charging-power supply includes: acquiring historical sunshine data and power load data; using historical data to assess the maximum potential capacity of photovoltaic power generation; calculating the total energy supply at different points in time; building a model based on historical data to predict future power generation capacity and purchased power supply; determining the optimal capacity required for energy storage batteries; determining the standby time T; considering the standby time; combining photovoltaic and energy storage battery systems; establishing a comprehensive energy management system; and optimizing the configuration of photovoltaic modules based on power generation potential and load demand.

[0029] The "photovoltaic-storage-flexible-direct-charging" distributed power supply system selects photovoltaic modules based on historical sunshine conditions, optimizes their configuration and angle, selects photovoltaic panels based on actual sunshine and their stability, and designs energy storage battery systems based on the photovoltaic power generation capacity and actual electricity load.

[0030] The photovoltaic power generation capacity is expressed as follows: , in, Indicates total energy supply. Indicates time Photovoltaic power generation capacity This indicates the power supplied by externally purchased electricity.

[0031] The energy storage battery system design is represented as follows: , in, Indicates battery capacity, Indicates time Actual electricity load Indicates total energy supply. and Indicates the time frame under consideration.

[0032] The reserve time T includes analyzing historical power load data, particularly load fluctuations during peak and off-peak periods. It identifies periods of insufficient power generation in historical data, including decreases in photovoltaic power generation due to weather changes or reductions in purchased electricity due to increased market electricity prices. It also assesses the additional purchased electricity required to meet load demand during these periods of insufficient power generation.

[0033] Based on the worst-case scenario of insufficient power generation, the backup time T is determined based on historical load fluctuations and the frequency and duration of insufficient power generation to ensure that the energy storage battery can continue to supply power under similar circumstances. The required energy storage battery capacity is calculated based on the backup time T and peak load demand.

[0034] The "photovoltaic-storage-flexible-direct-charging" distributed power supply system achieves multi-terminal flexible control through the flexible interconnection device FID, such as... Figure 2The architecture shown has transformer 1 pointing to the DC step-up transformer for power generation, transformer 2 pointing to the AC step-down transformer for purchased power, flexible interconnection device (FID) in the middle, and user side, energy storage and photovoltaic power generation on the right, thus forming a multi-terminal energy routing architecture.

[0035] It should also be noted that by analyzing distributed power supply data, the direction of system transformation can be determined, photovoltaic, energy storage and charging systems can be integrated to solve technical problems such as low power supply efficiency, solar radiation fluctuations and grid frequency instability, achieve efficient and reliable energy management and optimized allocation, reduce operating costs and promote the efficient use of renewable energy.

[0036] S2: Implement energy management and control strategies based on the determined transformation direction.

[0037] Specifically, the energy management and control strategies include: when determining the direction of sunshine management and sunshine stabilization, setting up sunshine monitoring sensors on the main road to monitor sunshine intensity in real time and wirelessly transmitting the data to the central control system; using a geographic information system to visualize the three-dimensional model of sunshine; adjusting the photovoltaic power generation operating mode; applying neural network strategies, hydraulic drive systems, and multi-mode switching to cope with changes in sunshine intensity; combining with the sunshine monitoring system, when fluctuations exceed the threshold, balancing the power plant's demand by adjusting the photovoltaic panel angle control and purchasing external electricity; using machine learning algorithms to predict future sunshine amount and adjusting the photovoltaic panel angle strategy accordingly.

[0038] It should be noted that optimizing the photovoltaic module configuration before implementing energy management control strategies includes collecting and analyzing historical sunshine data to assess the maximum potential capacity of photovoltaic and purchased electricity, analyzing historical and forecast data of electricity load, especially demand during peak and off-peak periods, and using software tools to simulate different photovoltaic module configuration schemes to evaluate their effectiveness in meeting electricity demand.

[0039] Taking into account geographical location, climate conditions, and seasonal variations, the optimal photovoltaic module type, quantity, angle, location, and scale are selected based on simulation results.

[0040] The selected configuration was integrated into the photovoltaic-storage-flexible direct charging system and tested to ensure stable operation under various conditions.

[0041] In the photovoltaic-storage-flexible direct charging system, the photovoltaic modules are high-efficiency and optimized based on historical sunshine data to maximize photoelectric conversion efficiency. The installation angle is adjusted according to geographical location and seasonal changes to achieve optimal sunshine reception. The system selects appropriate photovoltaic module capacity based on actual sunshine and its stability to ensure optimal energy conversion efficiency under different sunshine conditions. Based on the predicted capacity of photovoltaic and purchased electricity and the actual power load of the power station, a scalable, high-cycle-life energy storage battery system is selected to ensure continuous power supply and provide additional energy during peak demand periods. The "photovoltaic-storage-flexible direct charging" system further utilizes an integrated control unit for real-time adjustment and optimization to achieve efficient energy utilization and ensure the stability of the power distribution network.

[0042] It should also be noted that by integrating real-time solar monitoring, 3D modeling, neural networks and machine learning algorithms, the angle of photovoltaic panels is dynamically adjusted and the external power purchase strategy is optimized to solve the problems of power supply instability and load matching caused by solar fluctuations, achieve efficient energy conversion and precise supply and demand balance, improve the system's adaptability and power supply reliability, reduce dependence on the external power grid, and extend the service life of equipment.

[0043] S3: Adjust the control strategy based on distributed power supply data and prediction results.

[0044] Specifically, the adjustment control strategy includes adjusting the angle of the photovoltaic panels or the direction of their expansion based on real-time sunshine data when it is determined that adjustments to the configuration, angle, or expansion direction of the photovoltaic panels are to be made; optimizing the arrangement of the photovoltaic panels during periods when sunshine is below the threshold; and adjusting the number of photovoltaic panels based on historical sunshine data and electricity demand.

[0045] Equipped with a solar radiation sensor and sunshine duration monitoring system, it can obtain real-time sunshine intensity and angle.

[0046] An automated tracking system automatically adjusts the angle of photovoltaic panels based on solar radiation data and seasonal variations to ensure they always face the sun and achieve optimal irradiance. Machine learning algorithms predict future solar trajectories based on historical solar radiation data, developing automated adjustment strategies to optimize solar radiation capture efficiency. The optimal distance between photovoltaic panels is determined based on monitored solar intensity to minimize the effects of shading and reflection.

[0047] Using optical simulation software, the configuration of photovoltaic panels is simulated to further optimize their arrangement and angle to achieve the best sunlight reception. During periods of insufficient sunlight, the tilt angle of the photovoltaic panels is adjusted to obtain more sunshine hours. Based on historical sunshine data, current power demand, and system efficiency, the required photovoltaic panel area is calculated. Geographical location, weather patterns, and power demand fluctuations are analyzed to assess whether it is necessary to increase the number of photovoltaic panels. An expansion plan is designed, and based on the existing system configuration and land use, the location, arrangement, and connection method of the new photovoltaic panels are determined. All the data from the above steps are integrated into the central control system. Using advanced data analysis and algorithms, the system automatically judges and executes the optimal photovoltaic panel configuration, angle adjustment, and expansion strategy to ensure that the system always operates in the best condition.

[0048] When the direction of constant frequency transformation is determined, the speed adjustment strategy is implemented through the frequency converter to adapt to the real-time load changes of the power grid, and the frequency is fine-tuned using the output of the photovoltaic system and the battery energy storage system. When the direction of frequency sensor inspection is determined, resonance analysis is performed, and the control strategy is adjusted, the frequency sensor is calibrated and maintained regularly to ensure the accuracy of the data. When a frequency anomaly is detected, the backup sensor is activated and the fault is located, the control algorithm is optimized, and the speed and output are adjusted according to the real-time data.

[0049] When diagnosing a temporary fault or external interference, power quality analysis is performed, and strategies to enhance system stability are implemented. Power quality analysis is combined with grid conditions and user needs. Power quality is improved through reactive power compensation equipment and filters, and the system is simulated and stress-tested.

[0050] When the maintenance is determined to be routine, a data backtracking mechanism is established to re-analyze historical data and combine it with artificial intelligence algorithms to perform fault prediction and fault diagnosis. Backup sensors and data sources are introduced into the data analysis to reduce the impact of single point of failure.

[0051] It should be noted that frequency fine-tuning includes the following: if the adjusted angle exceeds the upper threshold, the photovoltaic system will be used as the base output, and the energy storage system will be used for frequency fine-tuning; if the adjusted angle is lower than the lower threshold, the photovoltaic system will reduce its output and increase the amount of purchased electricity to balance the stability of the system.

[0052] The system uses fuzzy logic to adaptively adjust the weight parameters. Based on historical operating data, current real-time data, and external environmental factors, the system adaptively adjusts the weight parameters and adjusts the energy management and control strategy according to changes in frequency and power parameters. When an anomaly is detected in the system operation, the fault detection module is activated to locate and diagnose the fault, and the fault is processed and corrected using backup sensors and advanced control algorithms.

[0053] It should also be noted that by integrating real-time monitoring data with machine learning predictions, the system utilizes automatic tracking, fuzzy logic adaptive algorithms, and frequency fine-tuning strategies to dynamically optimize the angle and operating mode of photovoltaic panels, solve the problem of power supply instability caused by solar radiation fluctuations and grid frequency deviations, achieve efficient energy capture and regulation, and improve power supply quality and overall energy efficiency.

[0054] Example 2 is an embodiment of the present invention, which provides a flexible transformation method for distributed power stations based on "photovoltaic storage flexible direct charging". In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiment.

[0055] First, two experimental sites (Site A and Site B) were selected. Site A used a power supply system based on "photovoltaic-storage-flexible direct charging," while Site B used a traditional power supply system. The experiment lasted for three months, covering different sunshine conditions and peak electricity demand periods. Sites A and B are geographically close and have similar climate conditions and sunshine resources. Site A was equipped with a photovoltaic-storage-flexible direct charging power supply system, including high-efficiency photovoltaic modules, energy storage batteries, real-time monitoring sensors, and an energy management system. Site B used a traditional external power purchase system, equipped with sensors to record total power supply, self-generated power, purchased power, energy conversion efficiency, system operation stability (number of failures), and overall power supply cost.

[0056] The total power supply, self-generated power ratio, and purchased power are recorded daily for distributed power generation. The energy conversion efficiency and comprehensive power supply cost are calculated respectively. Location A adjusts the angle of photovoltaic panels and the charging and discharging strategy of energy storage batteries in real time and predicts future solar intensity to optimize energy distribution. Location B maintains the traditional power supply method. Under high load or low solar conditions, the number of failures and response time of the two systems are recorded to evaluate system stability. Refer to Table 1 for the recording and analysis of experimental data.

[0057] Table 1 Experimental Data Recording Table

[0058] Data shows that the overall power supply cost at location A is lower than that at location B under all experimental conditions. For example, when the total power supply is 1200 kWh, the unit cost at location A is 0.32 yuan / kWh, while at location B it is 0.45 yuan / kWh, a cost reduction of approximately 28.9%. This indicates that the photovoltaic-storage flexible direct charging system reduces energy usage costs by optimizing the self-generation ratio. In the comparison of energy conversion efficiency, the efficiency of the system at location A consistently remains above 85%, while the efficiency at location B is only 65% ​​at its highest. This difference stems from the photovoltaic-storage flexible direct charging system's ability to optimize and adjust photovoltaic module configuration in real time. During the experiment, no issues arose at location A. Location A experienced 3, 4, and 2 failures respectively, while Location B experienced 3, 4, and 2 failures respectively. This indicates that the photovoltaic-storage-flexible direct charging system improves system stability through intelligent regulation, avoiding power outages caused by fluctuations in solar radiation or load changes. The photovoltaic-storage-flexible direct charging system utilizes historical data for machine learning prediction, dynamically adjusting the angle of photovoltaic panels and energy storage strategies, thereby improving resource utilization. Under a power supply of 1350kWh, Location A's self-generated electricity reached 1050kWh, while Location B only generated 350kWh, demonstrating the innovation of this invention. Location A reduced its dependence on external power purchases, lowered carbon emissions and environmental burden, and met the requirements of sustainable development.

[0059] Example 3 is an embodiment of the present invention, which provides a flexible transformation system for distributed power stations based on "photovoltaic storage flexible direct charging", including an energy acquisition module, an energy storage module, an intelligent scheduling module and a visual maintenance module.

[0060] The energy acquisition module is used to collect data from power stations and process information to determine the direction of transformation and to provide decision-making basis for the intelligent dispatch module.

[0061] The energy storage module is used to execute energy management and control strategies based on the collected power station data and forecast results.

[0062] The intelligent scheduling module is used to schedule the system based on data analysis and energy management strategies, and to make intelligent adjustments based on the stability of sunshine and the stability of the power grid frequency.

[0063] The visual maintenance module provides a user interface that allows operators to view various data in real time and is responsible for system testing and verification after adjustments.

[0064] This embodiment also provides a computer device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the flexible transformation method of the distributed power station based on "photovoltaic storage flexible direct charging" proposed in the above embodiment.

[0065] This embodiment also provides a computer-readable storage medium storing a computer program thereon. When the computer program is executed by a processor, it implements the flexible transformation method of distributed power supply stations based on "photovoltaic storage flexible direct charging" proposed in the above embodiment.

[0066] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0067] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0068] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0069] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0070] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for flexible retrofitting of distributed power stations based on "photovoltaic-storage-flexible-direct-charging" is characterized by, include: Based on distributed power supply data, determine the direction of transformation and integrate photovoltaic, energy storage, charging and power supply; Implement energy management and control strategies according to the determined transformation direction; Adjust the control strategy based on distributed power supply data and forecast results; Assessing grid frequency stability includes, Record the power grid frequency data for the same time period, calculate the frequency deviation, and if both the frequency deviation and the data deviation are greater than or equal to their preset thresholds, it is determined to be a direction for variable speed constant frequency transformation. If the frequency deviation exceeds the preset threshold for frequency deviation, but the data deviation does not exceed the preset threshold for data deviation, check the frequency sensor, perform resonance analysis, and adjust the control strategy. If the data deviation exceeds the preset threshold for data deviation, but the frequency deviation does not exceed the preset threshold for frequency deviation, a diagnosis of temporary faults or external interference is performed, power quality analysis is conducted, and an adjustment strategy to enhance system stability is implemented. If the frequency deviation and data deviation are within the allowable range, a second review is conducted to re-examine the data and determine whether there are any omissions or misjudgments. If all indicators meet the preset requirements, routine maintenance is performed. The adjustment control strategy includes: When considering adjusting the configuration, angle, or expansion direction of photovoltaic panels, the angle of the photovoltaic panels is adjusted based on real-time sunshine data. During periods when sunshine is below the threshold, the arrangement of photovoltaic panels is optimized, and the number of photovoltaic panels is adjusted based on historical sunshine data and electricity demand. When the direction is determined to be constant frequency transformation, the frequency is fine-tuned using the output of the photovoltaic system and the battery energy storage system. When it is determined that the frequency sensor needs to be checked, resonance analysis should be performed, and control strategy should be adjusted, the frequency sensor should be calibrated and maintained regularly to ensure the accuracy of the data. When a frequency abnormality is detected, the backup sensor should be activated and the fault location should be performed. The control algorithm should be optimized and the speed and output should be adjusted according to real-time data. When it is determined that a temporary fault or external interference is being diagnosed, power quality analysis is performed, and strategies to enhance system stability are implemented. Power quality analysis is combined with grid conditions and user needs. Power quality is improved through reactive power compensation equipment and filters. The system is then simulated and stress-tested. When the maintenance is determined to be routine, a data backtracking mechanism is established to re-analyze historical data, combine it with artificial intelligence algorithms to perform fault prediction and fault diagnosis, and introduce backup sensors and data sources into the data analysis.

2. The flexible transformation method for distributed power stations based on "photovoltaic-storage-flexible direct charging" as described in claim 1, characterized in that: The determination of the direction of transformation includes, Record the actual output and theoretical maximum output for the same time period, calculate the energy conversion efficiency, and if the energy conversion efficiency is less than the predetermined value, determine the solar radiation stability; if the energy conversion efficiency is greater than the predetermined value, evaluate the grid frequency stability.

3. The flexible transformation method for distributed power stations based on "photovoltaic-storage-flexible direct charging" as described in claim 1 or 2, characterized in that: The integrated photovoltaic energy storage charging power supply includes, Acquire historical sunshine data and power load data, use historical data to assess the maximum potential capacity of photovoltaic power generation, calculate the total energy supply at different points in time, build models based on historical data, and predict future power generation capacity and purchased power supply. Determine the optimal capacity required for the energy storage battery, determine the backup time T, consider the backup time, combine the photovoltaic and energy storage battery systems, establish an integrated energy management system, and optimize the configuration of photovoltaic modules based on power generation potential and load demand.

4. The flexible transformation method for distributed power stations based on "photovoltaic-storage-flexible direct charging" as described in claim 3, characterized in that: The implementation of the energy management and control strategy includes, When determining the direction for solar management and stabilization, solar monitoring sensors are installed on the main channels to monitor solar intensity in real time and wirelessly transmit the data to the central control system. A three-dimensional model of solar intensity is visualized using a geographic information system. The photovoltaic power generation mode is adjusted, and neural network strategies, hydraulic drive systems, and multi-mode switching are applied to cope with changes in solar intensity. Combined with the solar monitoring system, when fluctuations exceed the threshold, the power plant's demand is balanced by adjusting the angle control of the photovoltaic panels and purchasing external electricity. Machine learning algorithms are used to predict future solar intensity and adjust the photovoltaic panel angle strategy accordingly.

5. The flexible transformation method for distributed power stations based on "photovoltaic-storage-flexible direct charging" as described in claim 4, characterized in that: The frequency fine-tuning includes, If the adjusted angle exceeds the upper limit threshold, the photovoltaic system will serve as the basic output, and the energy storage system will be used for frequency fine-tuning. If the adjusted angle is lower than the lower threshold, the photovoltaic system will reduce its output and increase the amount of electricity purchased from outside the system to balance the system's stability.

6. A flexible retrofit system for distributed power stations based on "photovoltaic-storage-flexible-direct-charging" technology, employing the flexible retrofit method for distributed power stations based on "photovoltaic-storage-flexible-direct-charging" as described in any one of claims 1 to 5, characterized in that: It includes an energy acquisition module, an energy storage module, an intelligent scheduling module, and a visual maintenance module; The energy acquisition module is used to collect data from the power station and process information to provide a basis for determining the direction of transformation and for the intelligent dispatch module to make decisions. The energy storage module is used to execute energy management and control strategies based on the collected power station data and forecast results; The intelligent scheduling module is used to perform system scheduling based on data analysis and energy management strategies, and to make intelligent adjustments based on the stability of solar radiation and the stability of power grid frequency. The visualization maintenance module provides a user interface that allows operators to view various data in real time and is responsible for system testing and verification after adjustments.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the flexible transformation method for distributed power stations based on "photovoltaic storage flexible direct charging" as described in any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the flexible transformation method for distributed power stations based on "photovoltaic storage flexible direct charging" as described in any one of claims 1 to 5.

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