An intelligent control system for distributed photovoltaic power station equipment

Abstract

The present invention belongs to the technical field of photovoltaic power generation control, and specifically discloses an intelligent control system for distributed photovoltaic power station equipment. The system includes: an environmental information import module, an environmental information import module, a device regulation judgment module, a device regulation confirmation module, a device early warning execution terminal, and a device regulation execution terminal. The present invention comprehensively collects data through the environmental information import module and the operation data import module, improving the efficiency of data comprehensive utilization. The device regulation judgment module accurately evaluates the power station status based on multi-dimensional data, improving the intelligent regulation ability and perfecting the early warning mechanism, and can timely discover potential problems of the equipment. The device regulation confirmation and execution module ensures the accuracy of the charging power adjustment of the energy storage equipment, avoiding equipment damage; and the modular design enables it to have good scalability and maintainability, which helps to improve the energy utilization efficiency, operation reliability and stability of the photovoltaic power station.

Description

Technical Field

[0001] The present invention belongs to the technical field of photovoltaic power generation control, and more specifically, relates to an intelligent control system for distributed photovoltaic power station equipment. Background Art

[0002] As a clean and renewable energy source, solar energy is being utilized on an expanding scale. Distributed photovoltaic power stations, characterized by wide distribution and flexible installation, play an important role in the energy transition process. With the increasing number and expanding scale of distributed photovoltaic power stations, the demand for equipment control is also continuously rising.

[0003] The prior art, such as the distributed photovoltaic power generation control system and method based on artificial intelligence disclosed in the Chinese patent application with the application number 202410352700.0, first obtains the voltage signals collected by sensors from distributed photovoltaic power generation equipment at a preset sampling frequency, the environmental irradiance and power values at multiple predetermined time points within a predetermined period collected by sensors, and the energy storage capacity of distributed photovoltaic power generation equipment at multiple predetermined time points. Then, using deep learning technology, feature extraction and correlation analysis are performed on the three, and finally, a classification result is obtained through a classifier to determine whether the energy storage capacity of distributed photovoltaic equipment needs to be adjusted, thereby achieving real-time monitoring and adjustment of the energy storage capacity, improving energy utilization efficiency, saving costs, enhancing system stability, and optimizing energy planning.

[0004] Another example of the prior art is an intelligent adjustment device for a distributed photovoltaic power station based on photovoltaic prediction disclosed in the Chinese patent application with the application number 202210954295.0, which includes a photovoltaic base point. The photovoltaic base point includes an installation platform, a fixing frame, and an adjustment component. The fixing frame is arranged above the installation platform, and a solar panel is fixedly connected to the middle of the top of the fixing frame. Photosensitive sensors are fixedly connected to the four corners of the top of the fixing frame, and a rotating frame is fixedly connected to the middle of the bottom of the fixing frame. The adjustment component includes a lifting mechanism arranged between the rotating frame and the installation platform, a deflection mechanism hinged between the installation platform and the fixing frame, and a rotating mechanism arranged at the bottom of the installation platform. The photovoltaic base point is connected to an intelligent adjustment system, which includes a photovoltaic prediction module, a central processing unit, and a remote control module connected in sequence. The output end of the remote control module is connected to the controlled end of the adjustment component. This can solve the problems of inconvenient data retention, inconvenient data debugging and optimization, and inconvenient intelligent adjustment in the use of existing photovoltaic power stations.

[0005] For the above technical solutions, obviously, there are still the following deficiencies in the current control of distributed photovoltaic power station equipment: 1. The collection of environmental factors is not comprehensive enough. Both technologies mainly focus on common factors such as light irradiance, and do not fully consider environmental factors such as sand and dust that have a significant impact on the performance of photovoltaic panels, resulting in obvious deviations in the evaluation of equipment, and thus unable to improve the accuracy and reliability of equipment control settings.

[0006] 2. Data is collected at a preset sampling frequency, but in a complex and changeable actual environment, a fixed sampling frequency may not be able to capture the rapid changes in the operating state of photovoltaic equipment in a timely manner, resulting in the omission of key information.

[0007] 3. Although the adjustment of energy storage capacity and the control of regulating components are mentioned, the current does not involve specific equipment control design, and the current control design mainly starts from the equipment itself of demand control, with less consideration of its front-end management equipment, unable to ensure the effectiveness, scientificity and accuracy of control, and thus unable to further improve energy utilization efficiency and energy conversion rate. Summary of the Invention

[0008] In view of this, to solve the problems raised in the above background technology, a distributed photovoltaic power station equipment intelligent control system is proposed.

[0009] The object of the present invention can be achieved through the following technical solutions: The present invention provides a distributed photovoltaic power station equipment intelligent control system, which includes: an environmental information import module for importing the past environmental tracking logs and current monitored environmental data in the area where the photovoltaic power station is located.

[0010] An operating data import module for importing the inverter operating tracking logs and energy storage device operating tracking logs in the photovoltaic power station.

[0011] An equipment regulation judgment module for confirming the environmental interference index, front-end equipment interference index and energy storage state interference index based on the past environmental tracking logs, current monitored environmental data, inverter operating tracking logs and energy storage device operating tracking logs, and accordingly judging the regulation demand for the charging settings of the energy storage device. If the judgment result is a demand, start the equipment regulation confirmation module; otherwise, make a judgment on whether to adjust the equipment monitoring. If it is judged to be adjusted, confirm the monitored and adjusted equipment and confirm the adjusted monitoring frequency of the monitored and adjusted equipment.

[0012] An equipment regulation confirmation module for confirming the energy storage device for adjusting the charging settings, denoted as the set-adjusted equipment, and confirming the adjusted charging power of the set-adjusted equipment.

[0013] An equipment regulation execution terminal for making corresponding charging power adjustments based on the adjusted charging power of the adjusted equipment.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: (1) The present invention comprehensively collects data through the environmental information import module and the operation data import module, improving the efficiency of comprehensive data utilization. The equipment regulation judgment module accurately evaluates the power station status based on multi-dimensional data, enhancing the intelligent regulation ability and improving the early warning mechanism, enabling timely detection of potential equipment problems. The equipment regulation confirmation and execution module ensures accurate adjustment of the charging power of the energy storage equipment, avoiding equipment damage. Moreover, the modular design endows it with good scalability and maintainability, reducing the operation and maintenance costs, and showing significant advantages in aspects such as data utilization, intelligent regulation, early warning, and operation and maintenance, which helps to improve the energy utilization efficiency, operation reliability, and stability of the photovoltaic power station.

[0015] (2) The present invention analyzes the environmental interference index, thereby providing a reliable basis for setting the regulation demand judgment for the charging of the energy storage equipment. At the same time, it also solves the problem of insufficient comprehensive collection of current environmental factors, fully considering environmental factors such as sand and dust that have a significant impact on the performance of photovoltaic panels, avoiding obvious deviations in the subsequent evaluation of the charging setting of the energy storage equipment, and improving the accuracy and reliability of the subsequent charging setting of the energy storage equipment.

[0016] (3) When analyzing the environmental interference index, the present invention comprehensively extracts multi-dimensional environmental data of temperature, humidity, and dust concentration, comprehensively considering the impact on the energy storage equipment. And in the temperature analysis, it pays attention to the temperature difference, which is more meticulous than only looking at the average or single temperature value. At the same time, it combines past and current environmental data to judge the interference degree in real time, can quickly respond to environmental changes, introduces the time dimension, flexibly evaluates the interference according to different time periods, more reasonably allocates resources, and accurately corrects the reference environmental interference index based on the past environmental interference compensation factor, effectively using historical data to optimize the evaluation results. Furthermore, it can more comprehensively, accurately, and real-time evaluate the degree of environmental interference, providing strong support for the management and operation of the energy storage equipment.

[0017] (4) By confirming and adjusting the charging power of the equipment, the present invention solves the deficiency of the current specific equipment control design. It not only considers the environment but also takes into account the impact of the front-end inverter corresponding to the energy storage equipment, avoiding the lack of only starting from the equipment itself in current demand control, ensuring the effectiveness, scientificity, and accuracy of the control, and at the same time can further improve the energy utilization rate and energy conversion rate.

[0018] (5) By confirming and monitoring the adjustment equipment and confirming the adjustment monitoring frequency of the monitoring and adjustment equipment, the present invention effectively solves the problems existing in collecting data according to the preset sampling frequency, facilitating timely capture of the rapid changes in the operation status of photovoltaic equipment in a complex and changeable actual environment, thereby avoiding omission of key information and providing strong guarantee for the normal operation of the subsequent photovoltaic power generation components of the equipment. Description of the Drawings

[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0020] Figure 1 It is a schematic diagram of the connection of the system modules of the present invention.

[0021] Figure 2 It is a schematic diagram of the overall implementation steps flow of the present invention.

[0022] Figure 3 It is a schematic diagram of the specific process for equipment regulation and control judgment. Specific embodiments

[0023] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0024] Please refer to Figure 1 and Figure 2 As shown, the present invention provides an intelligent control system for distributed photovoltaic power station equipment, which includes: an environmental information import module, an environmental information import module, an equipment regulation and control judgment module, an equipment regulation and control confirmation module, an equipment warning execution terminal, and an equipment regulation and control execution terminal.

[0025] Among the above, the equipment regulation and control judgment module is respectively connected to the environmental information import module, the environmental information import module, the equipment regulation and control confirmation module, and the equipment warning execution terminal, and the equipment regulation and control confirmation module is also connected to the equipment regulation and control execution terminal.

[0026] The environmental information import module is used to import the past environmental tracking logs and current monitored environmental data in the area where the photovoltaic power station is located.

[0027] Specifically, the past environmental tracking logs record the temperature, humidity, and dust concentration data sets for each monitoring day. The temperature data set records the temperature at each monitoring time point, the humidity data set records the humidity at each monitoring time point, and the dust concentration data set records the dust concentration at each monitoring time point.

[0028] The operation data import module is used to import the inverter operation tracking logs and energy storage device operation tracking logs in the photovoltaic power station.

[0029] Specifically, the real-time output voltage of each operation monitoring of each inverter, the overcurrent times of each inverter, and the duration of each overcurrent are recorded in the inverter operation tracking log. The cumulative operation duration of each energy storage device, the SOH measurement value, the SOC measurement value within each monitoring period, and the charge and discharge power at each monitoring are recorded in the energy storage device operation tracking log.

[0030] Please refer to Figure 3 As shown, the device regulation judgment module is used to confirm the environmental interference index, the front-end device interference index, and the energy storage state interference index based on the past environmental tracking log, the current monitoring environmental data, the inverter operation tracking log, and the energy storage device operation tracking log, and accordingly judge the regulation requirement for the charging setting of the energy storage device. If the judgment result is a requirement, the device regulation confirmation module is started; otherwise, a judgment is made on whether to adjust the device monitoring. If it is judged to be adjusted, the monitored and adjusted device is confirmed, and the adjusted monitoring frequency of the monitored and adjusted device is confirmed.

[0031] Specifically, the specific confirmation process of the environmental interference index is as follows: A1. Extract the temperature, humidity, and dust concentration data sets of each monitoring day from the past environmental tracking log.

[0032] A2. Find the highest and lowest temperatures from the temperature data set and calculate the difference. At the same time, calculate the average monitoring values from the humidity and dust concentration data sets respectively, and accordingly calculate the past environmental interference compensation factor.

[0033] A3. Extract the current temperature and humidity from the current monitoring environmental data. If the current temperature exceeds the suitable operation range of the energy storage device, or the current humidity exceeds the corresponding set interference value, set the current environmental interference degree to 1.

[0034] A4. If both the current temperature and the current humidity do not exceed the range, and the current time point is within or after the preset temperature attention time period, set the current environmental interference degree to 0. If the current time point is before the temperature attention time period, calculate the interval duration between the current time point and the temperature attention time period , and use as the current environmental interference degree, denoted as , where e is the natural constant, and is the set reference interval duration.

[0035] A5. Multiply the current environmental interference degree by the preset environmental interference score to obtain the reference environmental interference index, and then correct it according to the past environmental interference compensation factor, and use the corrected result as the final environmental interference index .

[0036] In the embodiments of the present invention, by analyzing the environmental interference index, a reliable basis is provided for judging the regulation requirements for charging energy storage devices. At the same time, the problem of insufficient comprehensive collection of current environmental factors is solved. Environmental factors such as dust that have a significant impact on the performance of photovoltaic panels are fully considered, avoiding obvious deviations in the subsequent evaluation of the charging settings of energy storage devices, and improving the accuracy and reliability of the subsequent charging settings of energy storage devices.

[0037] When analyzing the environmental interference index in the embodiments of the present invention, multi-dimensional environmental data such as temperature, humidity, and dust concentration are comprehensively extracted to comprehensively consider the impact on energy storage devices. In temperature analysis, the temperature difference is concerned, which is more detailed than only looking at the average or single temperature value. At the same time, by combining past and current environmental data to judge the interference degree in real time, it can quickly respond to environmental changes, introduce the time dimension, flexibly evaluate interference according to different time periods, allocate resources more reasonably, and accurately correct the reference environmental interference index based on past environmental interference compensation factors, effectively using historical data to optimize the evaluation results. Furthermore, it can more comprehensively, accurately, and real-time evaluate the degree of environmental interference, providing strong support for the management and operation of energy storage devices.

[0038] It is understandable that temperature has a great impact on the charging process of energy storage devices. Different types of energy storage devices, such as lithium batteries and lead-acid batteries, have a certain temperature adaptation range. In a low-temperature environment, the chemical reaction rate inside the battery slows down, the viscosity of the electrolyte increases, and the ion diffusion ability decreases, resulting in an increase in the internal resistance of the battery. This makes the proportion of electrical energy converted into heat during the charging process increase, the charging efficiency decrease, and the maximum allowable charging power also decrease accordingly. For example, lithium batteries may trigger a protection mechanism at low temperatures to limit the charging power to prevent battery damage. In a high-temperature environment, although the chemical reaction rate of the battery may increase in the short term, too high a temperature will accelerate the aging and self-discharge rate of the battery, and may even cause safety problems such as thermal runaway. To ensure the safety and life of the battery, the charging power usually needs to be reduced.

[0039] It is understandable that environmental humidity will affect the electrical performance and safety of energy storage devices. A high-humidity environment may cause the electronic components and metal parts in the energy storage device to be affected by moisture, thereby reducing the electrical insulation performance and increasing the risk of short circuits and electric leakage. When the humidity is high, to avoid damage to the energy storage device due to electrical faults, the charging system may automatically reduce the charging power or take other protection measures. In addition, humidity may also affect the chemical reactions inside the battery, having a long-term impact on the performance and life of the battery and indirectly affecting the setting of the charging power.

[0040] Understandably, in an environment with a lot of sand and dust, fine sand and dust particles may enter the interior of the energy storage device, accumulate on the battery surface or in the heat dissipation channel, affect the heat dissipation performance of the battery, and cause the battery temperature to rise. In order to avoid damage to the battery due to excessive temperature, the charging power needs to be reduced. In an environment with high salt fog concentration such as the coast, the salt fog is corrosive and will damage the metal parts and electronic components of the energy storage device, affecting the normal operation of the equipment. In this environment, the charging system may take measures such as reducing the charging power to extend the service life of the equipment and ensure the safe operation of the equipment. Therefore, the three parameters of temperature, humidity and dust concentration are selected as the main consideration parameters, and temperature and humidity are selected as the current main analysis factors, and temperature, humidity and dust concentration are selected as long-term analysis factors, and then through a comprehensive analysis under both long-term and current conditions, the accuracy and reliability of the environmental interference index evaluation are ensured.

[0041] In a specific embodiment, the coefficient of the temperature interference duration ratio may be 0.5, the coefficient of the humidity interference duration ratio may be 0.3, and the coefficient of the dust interference duration ratio may be 0.2.

[0042] Understandably, temperature has a significant impact on the performance and life of energy storage equipment. Too high or too low temperature will cause changes in the chemical reaction rate inside the battery, increase internal resistance, accelerate self-discharge, and seriously affect the charging and discharging efficiency and service life of the battery. In many cases, abnormal temperature is one of the main factors leading to failure and performance degradation of energy storage equipment. Therefore, when comprehensively evaluating the degree of environmental interference in the past, a relatively high proportion of temperature interference is given. The impact of humidity on energy storage equipment is mainly reflected in electrical insulation performance and corrosion of metal parts. High humidity environment may cause moisture to the electronic components inside the equipment, reduce insulation performance, and increase the risk of short circuit and leakage. At the same time, it will accelerate the corrosion of metal parts and affect the reliability and safety of the equipment. Although the impact of humidity is more important, compared with the direct and serious impact of temperature on battery performance, its proportion can be appropriately reduced. Secondly, the impact of dust on energy storage equipment is mainly through entering the interior of the equipment, accumulating on the battery surface or in the heat dissipation channel, affecting the heat dissipation performance, and then causing the temperature of the equipment to rise, indirectly affecting the battery performance. Compared with temperature and humidity, the impact of dust is relatively indirect and slow, and may not cause serious performance degradation or failure of energy storage equipment in the short term. Therefore, when calculating the past environmental interference degree, the coefficient of the dust continuous interference ratio is relatively low and set to the minimum.

[0043] It should be added that the preset environmental interference score may be a ten-point system or a hundred-point system, which is not specifically limited here.

[0044] It should also be added that correcting the reference environmental interference index based on the past environmental interference compensation factor is to multiply the sum of 1 and the past environmental interference compensation factor by the reference environmental interference index.

[0045] Further, the past environmental interference compensation factor is statistically calculated in step A2, including: A21, counting the number of monitoring days when the maximum temperature exceeds the upper limit value of the interval, dividing it by the total number of monitoring days to obtain the high-temperature persistence ratio.

[0046] A22, counting the number of monitoring days when the minimum temperature exceeds the lower limit value of the suitable operating temperature interval, and obtaining the low-temperature persistence ratio according to the calculation method of the high-temperature persistence ratio.

[0047] A23, respectively comparing the average monitoring humidity and average monitoring dust concentration of each monitoring day with the corresponding interference values set for the energy storage device, counting the number of monitoring days exceeding the corresponding interference values, and dividing it by the total number of monitoring days to obtain the humidity interference persistence ratio and the dust persistence interference ratio.

[0048] A24, taking the maximum value from the high-temperature persistence ratio and the low-temperature persistence ratio, denoting it as the temperature interference persistence ratio, setting the proportion coefficients of the temperature interference persistence ratio, humidity interference persistence ratio, and dust persistence interference ratio, and calculating the past environmental interference compensation factor through weighted average.

[0049] Specifically, the specific confirmation process of the front-end device interference index is as follows: B1, extracting the real-time output voltage of each operation monitoring of each inverter, the number of overcurrent times of each inverter, and the duration of each overcurrent from the inverter operation tracking log.

[0050] B2, calculating the average value of the duration of each overcurrent to obtain the average overcurrent duration, normalizing the number of overcurrent times and the average overcurrent duration, using the result as the overcurrent evaluation variable, and importing it into the Sigmoid function to output the overcurrent interference degree of each inverter.

[0051] B3, constructing the output voltage change curve of each operation monitoring of each inverter with time as the abscissa and output voltage as the ordinate, and extracting the number of fluctuation points, the interval duration of each fluctuation point, and the output voltage difference in the curve.

[0052] B4, calculating the average value of the interval duration and output voltage difference of each fluctuation point to obtain the average fluctuation interval duration and the average fluctuation output voltage difference, and determining the voltage fluctuation evaluation variable according to the definition method of the overcurrent evaluation variable.

[0053] B5, normalizing the number of fluctuation points, the average fluctuation interval duration, and the average fluctuation output voltage difference, using the result as the voltage fluctuation evaluation variable, and importing it into the Sigmoid function to output the voltage fluctuation interference degree of each inverter during each operation monitoring.

[0054] B6. Screen out the voltage fluctuation interference degree during current operation monitoring, and calculate the average voltage fluctuation interference degree of each inverter.

[0055] B7. Set the weight coefficients of overcurrent interference degree, average voltage fluctuation interference degree, and current voltage fluctuation interference degree, calculate the interference degree of each inverter through weighted average, and screen out the maximum interference degree from them.

[0056] B8. Multiply the pre-set device interference score by the maximum interference degree to obtain the front-end device interference index.

[0057] It should be added that the inverter is responsible for converting the direct current generated by the photovoltaic panel into alternating current, and then delivering it to the power grid or for local load use. In this process, the output power of the inverter will directly affect the charging and discharging power of the energy storage device. When the photovoltaic power is excessive, the excess power output by the inverter needs to be stored in the energy storage device. At this time, factors such as the output power size and stability of the inverter determine the charging power and speed of the energy storage device. If the output power of the inverter fluctuates greatly, it may cause the charging process of the energy storage device to be unstable, affecting the life and performance of the battery. On the contrary, when the power grid or load needs the energy storage device to discharge, the inverter needs to convert the direct current released by the energy storage device into appropriate alternating current, and its conversion efficiency and power regulation ability will affect the discharge effect and efficiency of the energy storage device. At the same time, the operation of the inverter will affect the power quality, and the power quality will in turn affect the control of the energy storage device. For example, the alternating current output by the inverter may have problems such as voltage deviation, frequency fluctuation, and harmonics. If these power quality problems exceed the tolerance range of the energy storage device, it may cause abnormal charging and discharging control of the energy storage device, affecting the normal operation of the device. High-order harmonics may cause the internal electronic components of the energy storage device to heat up, accelerate aging, and even cause failures. In addition, the instability of voltage and frequency may also cause the charging and discharging control strategy of the energy storage device to be unable to be accurately executed, affecting the performance and life of the energy storage device. Therefore, the working conditions of the inverter need to be considered when designing the charging power of the energy storage device.

[0058] It should be added that the specific process of normalizing the number of overcurrent occurrences and the average overcurrent duration is as follows: 1) Normalize the number of overcurrent occurrences: Subtract the number of overcurrent occurrences from the set reference number of overcurrent occurrences, divide the difference by the set reference number of overcurrent occurrences, and take the result as the normalized result of the number of overcurrent occurrences.

[0059] 2) Normalize the average overcurrent duration: Calculate the difference between the average overcurrent duration and the set reference overcurrent duration, divide the difference by the set reference overcurrent duration, and then take the result as the normalized result of the average overcurrent duration.

[0060] In a specific embodiment, the reference overcurrent times for inverters used in general small-scale distributed photovoltaic power stations can be set to 5-10 times per year. Small inverters have relatively small power, and the tolerance of their internal components is limited, so overcurrent damage to the equipment is more obvious. If the overcurrent times are too frequent, it may accelerate component aging and even cause serious failures. That is, the reference overcurrent times can be set to a value that is determined specifically based on the current cumulative operating time. For example, when it is currently in the middle of the year, the reference overcurrent times can be set to 5 times. For inverters in large-scale industrial and commercial distributed photovoltaic power stations, due to their large power, higher overcurrent tolerance is usually considered during design and manufacturing, and the reference overcurrent times can be set to 10-20 times per year. When it is currently in the middle of the year, the reference overcurrent times can be set to 20 times.

[0061] In another specific embodiment, the reference overcurrent duration can be set to a value not exceeding 5-10 seconds each time. The reference overcurrent duration can be set to a value of 10 seconds. The components inside the inverter will be subjected to large currents and heat. If the duration is too long, it is easy to cause the components to overheat and be damaged. Taking the lithium battery energy storage system as an example, a long-term overcurrent may cause the battery temperature to rise sharply, affecting the performance and life of the battery, and even causing safety hazards. For some special inverters with strong overcurrent tolerance, such as inverters that use advanced heat dissipation technology and high-specification components, the reference overcurrent duration can be appropriately extended to 10-15 seconds. By way of example, it can be set to 15 seconds.

[0062] It should be added that defining each voltage fluctuation evaluation variable specifically refers to normalizing the number of fluctuation points, the average fluctuation interval duration and the average fluctuation output voltage difference, and using the normalized results as each voltage fluctuation evaluation variable. The normalization method is the same as the normalization method for the number of overcurrents and the average overcurrent duration, and both involve subtracting a set reference value and dividing the difference by the corresponding set reference value. The specific normalization process is not described or illustrated.

[0063] In a specific embodiment, for a small-scale distributed photovoltaic power station, since the power generation is relatively small and the output stability is relatively high, the number of reference fluctuation points can be set to 20. For a large-scale industrial and commercial distributed photovoltaic power station, with a large power generation capacity and a more complex operating environment, it may be affected by various factors, resulting in more frequent and complex output fluctuations. The number of reference fluctuation points can be set to 50. In a general photovoltaic power generation system, the reference fluctuation interval duration can be set to 15 minutes. This time range can better balance the monitoring frequency of system fluctuations and the data processing volume. If the fluctuation interval duration is too short, a large amount of data will be generated, increasing the difficulty of data processing and analysis. If it is too long, it may not be able to capture the rapid changes in the system in a timely manner. For a conventional distributed photovoltaic power generation system with a rated output voltage of 220V or 380V, the reference fluctuation output voltage difference can be set to ±5% - ±10% of the rated voltage. For example, for a 220V system, the fluctuation output voltage difference can be set to ±11V - ±22V. Specifically, it can be set to 22V.

[0064] In a specific embodiment, overcurrent causes more direct and serious damage to the inverter, which may lead to overheating and damage of internal components of the inverter, and even cause safety accidents such as fires. The occurrence of overcurrent often means that there are relatively large abnormalities in the system, so the weight coefficient is set to be the largest. The current voltage fluctuation interference degree reflects the operating state of the inverter at the current moment and can capture the possible abnormalities in the system in a timely manner. The weight coefficient is set to be the second. Long-term voltage fluctuations will affect the performance and efficiency of the inverter and accelerate the aging of internal components. By calculating the average voltage fluctuation interference degree, the operating stability of the inverter over a period of time can be reflected. The weight coefficient is set to be relatively small. Exemplarily, the weight coefficients of the overcurrent interference degree, the average voltage fluctuation interference degree, and the current voltage fluctuation interference degree can be set to 0.45, 0.25, and 0.3 respectively.

[0065] Specifically, the specific confirmation process of the energy storage state interference index is as follows: D1. Extract the cumulative operating duration of each energy storage device, the SOH measurement value, the SOC measurement value within each monitoring period, and the charge and discharge power at each monitoring time from the operation tracking log of the energy storage device.

[0066] D2. Count the number of monitoring times when the charge and discharge power exceeds the set reference charge and discharge power interval, and divide it by the total number of monitoring times to obtain the charge and discharge power deviation ratio.

[0067] D3. Calculate the standard deviation of the charge and discharge power at each monitoring time to obtain the charge and discharge power fluctuation degree of each energy storage device.

[0068] D4. Taking the monitoring period as the abscissa and the SOH measurement value and the SOC measurement value as the ordinates respectively, construct the SOH decay rate change curve and the SOC measurement value change curve of each energy storage device, and calculate the slope of the corresponding curve, which are respectively denoted as the SOH decay rate and the SOC decay rate.

[0069] D5. Obtain the energy storage interference degree of each energy storage device through a statistical function, and calculate the energy storage state interference index according to the analysis method of the front-end device interference index.

[0070] It should be added that in a specific embodiment, the statistical function can adopt a linear statistical function and an exponential statistical function, and in order to maintain the consistency of the analysis results, the value ranges of both the linear statistical function and the exponential statistical function are set to be between 0 and 1.

[0071] In a specific embodiment, normalize the charge-discharge power deviation ratio, the charge-discharge power fluctuation degree, the SOH decay rate, and the SOC decay rate respectively, and use the processing results as the energy storage interference evaluation variables, which are respectively denoted as 、 、 and , exemplarily, when using an exponential function for statistics, the specific statistical formula is as follows: .

[0072] It can be understood that the normalization process can adopt the maximum-minimum normalization method.

[0073] Another specifically, judging the regulation demand for the charging setting of the energy storage device includes: comparing the environmental interference index, the front-end device interference index, and the energy storage state interference index with the corresponding set reference values respectively.

[0074] If any one of the three indexes is greater than or equal to the corresponding set reference value, it is determined that there is a regulation demand; otherwise, calculate the differences between these three indexes and the corresponding set reference values respectively.

[0075] Taking the environmental interference index, the front-end device interference index, and the energy storage state interference index as evaluation interference indicators, count the number of evaluation interference indicators whose differences are less than the set safety index difference.

[0076] If the number of evaluation interference indicators is greater than or equal to 2, take the demand as the judgment result; otherwise, take the non-demand as the judgment result.

[0077] Furthermore, judging whether to adjust the device monitoring includes: taking that the interference degree of a certain inverter is greater than the set reference interference degree as condition 1, and taking that the energy storage interference degree of a certain energy storage device is greater than the set reference energy storage interference degree as condition 2.

[0078] If there is a condition that holds among Conditions 1 and 2, the judgment result will be adjusted; otherwise, the judgment result will not be adjusted.

[0079] Furthermore, confirm the monitoring and adjustment device and confirm the adjustment monitoring frequency of the monitoring and adjustment device, including: if the interference degree of an inverter is greater than the set reference interference degree, determine this inverter as the monitoring and adjustment device; if the energy storage interference degree of an energy storage device is greater than the set reference energy storage interference degree, determine this energy storage device as the monitoring and adjustment device.

[0080] If the monitoring and adjustment device is an inverter, denote the interference degree of this inverter and the set reference interference degree as and , and take as the adjustment monitoring frequency, which is the initial set monitoring frequency of the inverter.

[0081] If the monitoring and adjustment device is an energy storage device, denote the energy storage interference degree of the energy storage device and the set reference energy storage interference degree as and , and take as the adjustment monitoring frequency, which is the initial set monitoring frequency of the energy storage device.

[0082] By confirming the monitoring and adjustment device and the adjustment monitoring frequency of the monitoring and adjustment device in the embodiments of the present invention, the problems existing in collecting data according to the preset sampling frequency are effectively solved, which is convenient for timely capturing the rapid changes in the operating state of photovoltaic devices in a complex and changeable actual environment, thereby avoiding the omission of key information and providing a strong guarantee for the normal operation of the photovoltaic power generation components of subsequent devices.

[0083] The device regulation confirmation module is used to confirm the energy storage device for charging setting adjustment, denoted as the setting adjustment device, and confirm the adjustment charging power of the setting adjustment device.

[0084] Specifically, confirming the energy storage device for charging setting adjustment includes: if the environmental interference index is greater than or equal to the set reference environmental interference index, all energy storage devices in the area where the photovoltaic power station is located are used as the energy storage devices for charging setting adjustment.

[0085] Mark the inverter with an interference degree greater than the corresponding set reference interference degree as an interference inverter, and denote the energy storage device associated with the interference inverter as the front-end interference energy storage device.

[0086] Denote the energy storage device with an energy storage interference degree greater than the corresponding set reference energy storage interference degree as the body interference energy storage device.

[0087] Compare the main body interference energy storage device and the front-end interference energy storage device, eliminate the duplicate energy storage devices, and determine the remaining energy storage devices after filtering as the energy storage devices for charging setting adjustment.

[0088] Further, confirm the adjusted charging power of the setting adjustment device, including: G1. Take as the environmental compensation factor, as the set reference environmental interference index.

[0089] G2. Denote the energy storage interference degree of the adjustment device and the interference degree of the corresponding associated inverter as and respectively. Similarly set the energy storage interference compensation factor and the inverter interference compensation factor according to the setting method of the environmental compensation factor.

[0090] G3. Set the proportion coefficients of the environmental compensation factor, the energy storage interference compensation factor, and the inverter interference compensation factor, and perform weighted average calculation. Take the calculation result as the charging power adjustment factor, and denote it as .

[0091] G4. Confirm the adjusted charging power , , and as the preset reference charging power and the initial setting charging power respectively.

[0092] In the embodiment of the present invention, by confirming the adjusted charging power of the adjustment device, the deficiencies in the current specific device control design are solved. It not only considers the environment but also takes into account the influence of the energy storage device on the corresponding front-end inverter, avoiding the lack of only starting from the device itself in current demand control, ensuring the effectiveness, scientificity, and accuracy of control, and at the same time being able to further improve the energy utilization rate and energy conversion rate.

[0093] It should be added that the influence of environmental factors on distributed photovoltaic power stations is relatively extensive and direct. For example, environmental parameters such as temperature, humidity, and light intensity will affect the power generation efficiency of photovoltaic panels, and thus affect the charging process of energy storage devices and the operating state of inverters. Therefore, the proportion coefficient of the environmental compensation factor can be set to 0.4. As a key component for storing and regulating electric energy, the state of the energy storage device is crucial for the adjustment of charging power. The proportion coefficient of the energy storage interference compensation factor can be set to 0.3. The inverter plays a key role in converting direct current to alternating current in the photovoltaic power generation system, and its performance and operating state directly affect the conversion efficiency and quality of electric energy. Similarly, the proportion coefficient of the inverter interference compensation factor can be set to 0.3.

[0094] In another specific embodiment, in a large-scale industrial and commercial distributed photovoltaic power station, the capacity of the energy storage device is usually several hundred to several thousand kilowatt-hours or even larger. For such energy storage devices, the reference charging power can be set at 200 kW. When the energy storage device is newly put into use, in order to effectively activate and protect the battery, the initial set charging power is usually relatively low, which can be set at 30%-50% of the reference charging power. For example, if the reference charging power is 2 kW, the initial set charging power can be set at 0.6-1 kW. Exemplarily, it can be set at 1 kW. For an energy storage device that has been used for some time and has stable performance, the initial set charging power can be close to or equal to the reference charging power.

[0095] The device regulation execution terminal is used to adjust the corresponding charging power based on the adjusted charging power of the adjustment device.

[0096] In the embodiment of the present invention, the environmental information import module and the operation data import module comprehensively collect data, improving the efficiency of comprehensive data utilization. The device regulation judgment module accurately evaluates the power station status based on multi-dimensional data, improving the intelligent regulation ability and perfecting the early warning mechanism, and can timely detect potential problems of the device. The device regulation confirmation and execution module ensures the accuracy of the charging power adjustment of the energy storage device, avoiding device damage. Moreover, the modular design endows it with good scalability and maintainability, reducing the operation and maintenance costs, and showing significant advantages in aspects such as data utilization, intelligent regulation, early warning and operation and maintenance, which helps to improve the energy utilization efficiency, operation reliability and stability of the photovoltaic power station.

[0097] The above content is only an example and illustration of the concept of the present invention. Those skilled in the art of the present technology can make various modifications or supplements or use similar methods to replace the specific embodiments described, as long as they do not deviate from the concept of the invention or exceed the scope defined by the present invention, they should fall within the protection scope of the present invention.

Claims

1. An intelligent control system for distributed photovoltaic power station equipment, characterized in that, It includes: An environmental information import module for importing past environmental tracking logs and current monitored environmental data; An operating data import module for importing the operating tracking logs of inverters and energy storage devices; A device regulation judgment module for confirming the environmental interference index, the front-end device interference index, and the energy storage state interference index, judging the regulation requirements for the charging settings of the energy storage device. If the judgment is a requirement, start the device regulation confirmation module. Otherwise, judge whether to adjust the device monitoring. If the judgment is to adjust, confirm the monitored adjustment device and the adjusted monitoring frequency; The steps for confirming the environmental interference index include: extracting the temperature, humidity, and dust concentration data sets of each monitoring day from the past environmental tracking logs and statistically calculating the past environmental interference compensation factor; Extracting the current temperature and humidity from the current monitored environmental data and calculating the current environmental interference degree in combination with the current time point; Multiplying the current environmental interference degree by the preset environmental interference score to obtain the baseline environmental interference index, and then correcting it according to the past environmental interference compensation factor to obtain the final environmental interference index; A device regulation confirmation module for confirming that the charging settings adjust the energy storage device, denoted as the setting adjustment device, and confirming the adjusted charging power of the setting adjustment device; A device regulation execution terminal for performing corresponding charging power adjustment based on the adjusted charging power of the adjustment device; The calculation of the current environmental interference degree includes: If the current temperature exceeds the suitable operating range of the energy storage device, or the current humidity exceeds the corresponding set interference range, set the current environmental interference degree to 1; If both the current temperature and the current humidity are within the range, and the current time point is within or after the preset temperature attention time period, set the current environmental interference degree to 0. If the current time point is before the temperature attention time period, calculate the time interval between the current time point and the temperature attention time period , take as the current environmental interference degree, denoted as , is the natural constant, is the set reference interval duration; Multiply the current environmental interference degree by the preset environmental interference score to obtain the baseline environmental interference index, and then correct it according to the past environmental interference compensation factor, and use the corrected result as the final environmental interference index 。 2. The intelligent control system for distributed photovoltaic power station equipment according to claim 1, characterized in that: The statistical calculation of the past environmental interference compensation factor includes: Finding the highest and lowest temperatures from the temperature data set and calculating the difference, and simultaneously calculating the average monitored values from the humidity and dust concentration data sets respectively; Statistically calculating the number of monitoring days when the highest temperature exceeds the upper limit value of the suitable operating temperature range, dividing by the total number of monitoring days to obtain the high-temperature persistence ratio; Statistically calculating the number of monitoring days when the lowest temperature exceeds the lower limit value of the suitable operating temperature range, and calculating the low-temperature persistence ratio according to the calculation method of the high-temperature persistence ratio; Respectively comparing the average monitored humidity and average monitored dust concentration of each monitoring day with the interference values set for the energy storage device, statistically calculating the number of monitoring days exceeding the corresponding interference values, dividing by the total number of monitoring days to obtain the humidity interference persistence ratio and the dust interference persistence ratio; Taking the maximum value from the high-temperature persistence ratio and the low-temperature persistence ratio, denoted as the temperature interference persistence ratio, setting the proportion coefficients of the temperature interference persistence ratio, the humidity interference persistence ratio, and the dust interference persistence ratio, and calculating the past environmental interference compensation factor through weighted average.

3. The intelligent control system for distributed photovoltaic power station equipment according to claim 1, characterized in that: The specific confirmation process of the front-end device interference index is as follows: Extracting the real-time output voltage of each operation monitoring of each inverter from the inverter operation tracking log, as well as the overcurrent times and the duration of each overcurrent of each inverter; Calculating the average value of the duration of each overcurrent to obtain the average overcurrent duration, normalizing the overcurrent times and the average overcurrent duration, using the result as the overcurrent evaluation variable, and importing it into the Sigmoid function to output the overcurrent interference degree of each inverter; Taking time as the abscissa and output voltage as the ordinate, constructing the output voltage change curve of each operation monitoring of each inverter, and extracting the number of fluctuation points, the interval duration of each fluctuation point, and the output voltage difference in the curve; Calculate the interval duration between each fluctuation point and the mean value of the output voltage difference to obtain the average fluctuation interval duration and the average fluctuation output voltage difference, and determine the voltage fluctuation evaluation variable according to the definition method of the overcurrent evaluation variable; Normalize the number of fluctuation points, the average fluctuation interval duration, and the average fluctuation output voltage difference, and use the result as the voltage fluctuation evaluation variable, and import it into the Sigmoid function to output the voltage fluctuation interference degree of each inverter during each operation monitoring; Screen out the voltage fluctuation interference degree during the current operation monitoring, and at the same time calculate the average voltage fluctuation interference degree of each inverter; Set the weight coefficients of the overcurrent interference degree, the average voltage fluctuation interference degree, and the current voltage fluctuation interference degree, calculate the interference degree of each inverter through weighted average, and screen out the maximum interference degree from them; Multiply the pre-set device interference score by the maximum interference degree to obtain the front-end device interference index.

4. The intelligent control system for distributed photovoltaic power station equipment according to claim 3, characterized in that: The specific confirmation process of the energy storage state interference index is as follows: Extract the cumulative operation duration of each energy storage device, the SOH measurement value, the SOC measurement value within each monitoring period, and the charge and discharge power at each monitoring time from the operation tracking log of the energy storage device; Count the number of monitoring times when the charge and discharge power exceeds the set reference charge and discharge power range, divide it by the total number of monitoring times to obtain the charge and discharge power deviation ratio; Calculate the standard deviation of the charge and discharge power at each monitoring time to obtain the charge and discharge power fluctuation degree of each energy storage device; Taking the monitoring period as the abscissa, and the SOH measurement value and the SOC measurement value as the ordinate respectively, construct the SOH decay rate change curve and the SOC measurement value change curve of each energy storage device, and calculate the corresponding curve slopes, which are respectively recorded as the SOH decay rate and the SOC decay rate; Obtain the energy storage interference degree of each energy storage device through a statistical function, and calculate the energy storage state interference index according to the analysis method of the front-end device interference index.

5. The intelligent control system for distributed photovoltaic power station equipment according to claim 1, characterized in that: The judgment of the charging setting regulation requirement of the energy storage device includes: Compare the environmental interference index, the front-end device interference index, and the energy storage state interference index with the corresponding set reference values respectively; If any one of the three indexes is greater than or equal to the corresponding set reference value, it is determined that there is a regulation requirement. On the contrary, calculate the difference between these three indexes and the corresponding set reference values respectively; Take the environmental interference index, the front-end device interference index, and the energy storage state interference index as evaluation interference indicators, and count the number of evaluation interference indicators whose difference is less than the set safety index difference; If the number of evaluation interference indicators is greater than or equal to 2, use "no demand" as the judgment result, otherwise use "demand" as the judgment result.

6. The intelligent control system for distributed photovoltaic power station equipment according to claim 4, wherein: The confirmation of the charging setting to adjust the energy storage device includes: If the environmental interference index is greater than or equal to the set reference environmental interference index, all the energy storage devices in the area where the photovoltaic power station is located are used as the energy storage devices for charging setting adjustment; Mark the inverters with interference degree greater than the corresponding set reference interference degree as interference inverters, and record the energy storage devices associated with the interference inverters as front-end interference energy storage devices; Record the energy storage devices with energy storage interference degree greater than the corresponding set reference energy storage interference degree as body interference energy storage devices; Compare the main body interference energy storage device and the front-end interference energy storage device, eliminate the duplicate same energy storage device, and determine the remaining energy storage device after filtering as the charging setting adjustment energy storage device.

7. The intelligent control system for distributed photovoltaic power station equipment according to claim 6, characterized in that: The adjustment of the charging power of the confirmation setting adjustment device includes: Taking as the environmental compensation factor, is the set reference environmental interference index; Let the energy storage interference degree of the setting adjustment device and the interference degree of the corresponding associated inverter be denoted as and respectively. Similarly, set the energy storage interference compensation factor and the inverter interference compensation factor according to the setting method of the environmental compensation factor; Set the proportion coefficients of the environmental compensation factor, the energy storage interference compensation factor, and the inverter interference compensation factor, and perform weighted average calculation. Take the calculation result as the charging power adjustment factor, and denote it as ; Confirm the adjusted charging power of the setting adjustment device , , and are the preset reference charging power and the initial set charging power, respectively.

8. An intelligent control system for distributed photovoltaic power station equipment according to claim 4, characterized in that: The judgment of whether to perform device monitoring adjustment includes: Taking that the interference degree of a certain inverter is greater than the set reference interference degree as condition 1, and taking that the energy storage interference degree of a certain energy storage device is greater than the set reference energy storage interference degree as condition 2; If there is a condition that holds in conditions 1 and 2, take adjustment as the judgment result, otherwise take non-adjustment as the judgment result.

9. The intelligent control system for distributed photovoltaic power station equipment according to claim 7, characterized in that: The confirmation of the monitoring adjustment device and the adjustment of the monitoring frequency includes: If the interference degree of a certain inverter is greater than the set reference interference degree, determine the inverter as the monitoring adjustment device. If the energy storage interference degree of a certain energy storage device is greater than the set reference energy storage interference degree, determine the energy storage device as the monitoring adjustment device; If the monitoring and adjustment device is an inverter, the interference degree of the inverter and the set reference interference degree are respectively denoted as and , and is used as the adjusted monitoring frequency, which is the initial set monitoring frequency of the inverter; If the monitoring and adjustment device is an energy storage device, denote the energy storage interference degree of the energy storage device and the set reference energy storage interference degree as and , and take as the adjusted monitoring frequency, which is the initial set monitoring frequency of the energy storage device.

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