Distributed photovoltaic power station equipment intelligent control system

Abstract

The invention belongs to the technical field of photovoltaic power generation control, and particularly discloses and provides a distributed photovoltaic power station equipment intelligent control system which comprises an environment information import module, an environment information import module, an equipment regulation and control judgment module, an equipment regulation and control confirmation module, an equipment early warning execution terminal and an equipment regulation and control execution terminal. Data are comprehensively collected through the environment information import module and the operation data import module, the comprehensive utilization efficiency of the data is improved, the equipment regulation and control judgment module accurately evaluates the state of a power station based on multi-dimensional data, the intelligent regulation and control capability is improved, an early warning mechanism is perfected, potential problems of equipment can be found in time, and the safety of the power station is improved. The equipment regulation and control confirmation and execution module ensures that the charging power of the energy storage equipment is accurately adjusted, and equipment damage is avoided; moreover, the modular design enables the system to have good expandability and maintainability, and facilitates the improvement of the energy utilization efficiency, operation reliability and stability of a photovoltaic power station.

Description

Technical Field

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

[0002] As a clean and renewable energy source, the utilization scale of solar energy is constantly expanding. Distributed photovoltaic power stations have the characteristics of wide distribution and flexible installation, and play an important role in the energy transformation process. With the increase in the number and scale of distributed photovoltaic power stations, the demand for equipment control is also constantly increasing.

[0003] The prior art, such as the distributed photovoltaic power generation control system and method based on artificial intelligence disclosed in the Chinese invention patent application with the application number 202410352700.0, first obtains the voltage signal collected by the sensor from the distributed photovoltaic power generation equipment at a preset sampling frequency, the environmental irradiance and power values at multiple preset time points within a predetermined time period collected by the sensor, and the energy storage capacity of the distributed photovoltaic power generation equipment at multiple preset 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 the distributed photovoltaic equipment needs to be adjusted, thereby realizing real-time monitoring and adjustment of the energy storage capacity, improving energy utilization efficiency, saving costs, improving 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 invention 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. Thereby, the problems that the data of the existing photovoltaic power station is not convenient to retain, not convenient for data debugging and optimization, and inconvenient for intelligent adjustment can be solved.

[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 changing actual environment, the 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, scientific nature 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 operation data import module for importing the inverter operation tracking logs and energy storage device operation 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 operation tracking logs and energy storage device operation 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 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 performing corresponding charging power adjustment 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, enhances the intelligent regulation ability and improves the early warning mechanism, enabling timely detection of potential problems of the equipment. 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 demonstrating 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 such as temperature, humidity and dust concentration, comprehensively considering the impact on the energy storage equipment. In the temperature analysis, it pays attention to the temperature difference, which is more detailed 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 environmental interference degree, 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 current lack of starting only from the control of the equipment itself, 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 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 the photovoltaic equipment in the complex and changeable actual environment, thus 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 drawings required for the description of the embodiments. Obviously, the 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 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 step flow of the present invention.

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

[0023] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the 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 judgment module, an equipment regulation confirmation module, an equipment warning execution terminal, and an equipment regulation execution terminal.

[0025] Among the above, the equipment regulation judgment module is respectively connected to the environmental information import module, the environmental information import module, the equipment regulation confirmation module, and the equipment warning execution terminal, and the equipment regulation confirmation module is also connected to the equipment regulation 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 count 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 , is the natural constant, is the set reference interval duration.

[0035] A5. 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 .

[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 incomplete 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 the 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, the environmental changes can be quickly responded to. By introducing the time dimension and flexibly evaluating the interference according to different time periods, resources can be more reasonably allocated. The reference environmental interference index is accurately corrected based on the past environmental interference compensation factor, and historical data is effectively used to optimize the evaluation results. Furthermore, the environmental interference degree can be evaluated more comprehensively, accurately, and in real time, 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 increases the proportion of electrical energy converted into heat during the charging process, reduces the charging efficiency, and the maximum allowable charging power will 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 devices to get damp, thereby reducing the electrical insulation performance and increasing the risks of short circuit and electric leakage. When the humidity is high, to avoid damage to the energy storage devices caused by 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 more dust, fine dust particles may enter the interior of the energy storage device and accumulate on the battery surface or in the heat dissipation channels, affecting the heat dissipation performance of the battery and causing the battery temperature to rise. To avoid damage to the battery due to excessive temperature, it is necessary to reduce the charging power. In an environment with a high salt fog concentration, such as along the coast, the salt fog is corrosive and will damage the metal components and electronic elements of the energy storage device, affecting the normal operation of the device. In such an environment, the charging system may take measures such as reducing the charging power to extend the service life of the device and ensure the safe operation of the device. 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 the long-term analysis factors. Furthermore, through comprehensive analysis in both long-term and current situations, the accuracy and reliability of the environmental interference index assessment are ensured.

[0041] In a specific embodiment, the proportion coefficient of the temperature interference duration ratio can be set to 0.5, the proportion coefficient of the humidity interference duration ratio can be set to 0.3, and the proportion coefficient of the dust continuous interference ratio can be set to 0.2.

[0042] Understandably, temperature has a relatively significant impact on the performance and life of the energy storage device. Too high or too low temperature will cause problems such as changes in the internal chemical reaction rate of the battery, increased internal resistance, and accelerated self-discharge, seriously affecting the charge and discharge efficiency and service life of the battery. In many cases, temperature anomalies are one of the main factors leading to failures and performance degradation of energy storage devices. Therefore, when comprehensively evaluating the past environmental interference degree, a relatively high proportion is given to the temperature interference duration ratio. The influence of humidity on the energy storage device is mainly reflected in the electrical insulation performance and the corrosion of metal components. A high-humidity environment may cause the internal electronic components of the device to be affected by moisture, resulting in a decrease in insulation performance and an increased risk of short circuits and electric leakage. At the same time, it will accelerate the corrosion of metal components, affecting the reliability and safety of the device. Although the influence of humidity is relatively important, compared with the direct and serious impact of temperature on battery performance, its proportion can be appropriately reduced. Secondly, the influence of dust on the energy storage device is mainly through entering the device interior, accumulating on the battery surface or in the heat dissipation channels, affecting the heat dissipation performance, and then causing the device temperature to rise, indirectly affecting the battery performance. Compared with temperature and humidity, the influence of dust is relatively indirect and slow, and may not cause serious performance degradation or failure of the energy storage device in the short term. Therefore, when calculating the past environmental interference degree, the proportion coefficient of the dust continuous interference ratio is relatively low and set to the minimum.

[0043] It should be added that the pre-set environmental interference score can be in a ten-point system or a hundred-point system, and no specific limitation is made 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 highest temperature exceeds the upper limit value of the interval, dividing it by the total number of monitoring days to obtain the high-temperature duration ratio.

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

[0048] A24, taking the maximum value from the high-temperature duration ratio and the low-temperature duration ratio, denoting it as the temperature interference duration ratio, setting the proportion coefficients of the temperature interference duration ratio, humidity interference duration ratio, and dust continuous 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 mean 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, taking time as the abscissa and output voltage as the ordinate to construct 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.

[0052] B4, calculating the mean value of the interval duration and output voltage difference of each fluctuation point to obtain the average fluctuation interval duration and 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 preset 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 transmitting it to the power grid or for local load use. In this process, the output power of the inverter will directly affect the charge and discharge 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 magnitude and stability of the inverter output power determine the charging power and speed of the energy storage device. If the inverter output power 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 charge and discharge 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 charge and discharge 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 use 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 use 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 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 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 time. 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 trigger safety accidents such as fires. The occurrence of overcurrent often means that there are significant 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 promptly capture possible abnormalities in the system. 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, 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. With 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 for each energy storage device, calculate the slope of the corresponding curve, and denote them as the SOH decay rate and the SOC decay rate respectively.

[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 between 0 and 1.

[0071] In a specific embodiment, perform normalization processing on 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, denoted as 、 、 and respectively. Exemplarily, when using an exponential function for statistics, the specific statistical formula is as follows: .

[0072] It can be understood that the normalization processing can adopt the maximum-minimum normalization processing 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 indices is greater than or equal to the corresponding set reference value, it is determined that there is a regulation demand. Otherwise, calculate the difference between each of these three indices and the corresponding set reference value.

[0075] 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 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, record 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 said inverter.

[0081] If the monitoring and adjustment device is an energy storage device, record 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 said 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 subsequent photovoltaic power generation components of the device.

[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 regarded 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 of the same type, 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] By confirming the adjusted charging power of the adjustment device in the embodiment of the present invention, 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 then 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 taken as 0.4. As a key component for storing and regulating electric energy, the state of the energy storage device itself is crucial for adjusting the charging power. The proportion coefficient of the energy storage interference compensation factor can be taken as 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 taken as 0.3.

[0094] In another specific embodiment, in a large-scale industrial and commercial distributed photovoltaic power station, the energy storage device capacity 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 kilowatts. 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. It can be set at 30%-50% of the reference charging power. For example, if the reference charging power is 2 kilowatts, the initial set charging power can be set at 0.6-1 kilowatt. Exemplarily, it can be set at 1 kilowatt. For energy storage devices that have been used for some time and have stable performance, the initial set charging power can be close to or equal to the reference charging power.

[0095] The device control 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 control judgment module accurately evaluates the power station status based on multi-dimensional data, enhancing the intelligent control ability and improving the early warning mechanism, and can timely detect potential problems of the device. The device control confirmation and execution module ensures the accuracy of the charging power adjustment of the energy storage device, avoiding device damage. And the modular design endows it with good scalability and maintainability, reducing the operation and maintenance cost, and showing significant advantages in aspects such as data utilization, intelligent control, 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 all fall within the protection scope of the present invention.

Claims

1. A distributed photovoltaic power station equipment intelligent control system, characterized in that: include: Environmental information import module, importing past environmental tracking logs and current monitoring environment data; Operation data import module, importing inverter and energy storage equipment operation tracking logs; The equipment control judgment module confirms the environmental interference index, the front-end equipment interference index and the energy storage state interference index, and judges the demand for energy storage equipment charging setting control. If it is determined to be a demand, the equipment control confirmation module is started. Otherwise, it determines whether the equipment monitoring is adjusted or not. If it is determined to be adjusted, it confirms the monitoring adjustment equipment and adjusts the monitoring frequency. The steps of confirming the environmental interference index include: extracting the temperature, humidity, and dust concentration data sets of each monitoring day from the past environmental tracking log, and calculating the past environmental interference compensation factor; Extract the current temperature and humidity from the current monitored environment data, and calculate the current environmental interference degree based on the current time point; The current environmental interference degree is multiplied by the preset environmental interference score to obtain the baseline environmental interference index, and then corrected according to the past environmental interference compensation factor to obtain the final environmental interference index; The device control confirmation module confirms that the charging setting adjusts the energy storage device, records it as setting the adjustment device, and confirms the adjustment charging power of the setting adjustment device; The device control execution terminal makes corresponding charging power adjustments based on the adjusted charging power of the adjustment device.

2. According to claim 1, a distributed photovoltaic power station equipment intelligent control system is characterized by: The calculating 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 value, the current environmental interference degree is set to 1; If the current temperature and humidity are within the range, and the current time point is within or after the preset temperature attention period, the current environmental interference is set to 0. If the current time point is before the temperature attention period, calculate the interval between the current time point and the temperature attention period. ,Will As the current environmental interference degree, denoted as , is a natural constant, To set the reference interval duration; The current environmental interference degree is multiplied by the preset environmental interference score to obtain the baseline environmental interference index, which is then corrected based on the past environmental interference compensation factor, and the corrected result is used as the final environmental interference index. .

3. According to claim 1, a distributed photovoltaic power station equipment intelligent control system is characterized by: The statistical past environmental interference compensation factor includes: Find the highest and lowest temperatures from the temperature data set and calculate the difference, and calculate the average monitoring values ​​from the humidity and dust concentration data sets; The number of monitoring days with the maximum temperature exceeding the upper limit of the interval was counted and divided by the total number of monitoring days to obtain the high temperature duration ratio; Count the number of monitoring days when the minimum temperature exceeds the lower limit of the suitable operating temperature range, and calculate the low temperature duration ratio according to the high temperature duration ratio calculation method; Compare the average monitored humidity and average monitored dust concentration of each monitoring day with the interference value set for the energy storage device, count the number of monitoring days that exceed the corresponding interference value, and divide it by the total number of monitoring days to obtain the humidity interference duration ratio and dust interference duration ratio; Take the maximum value from the high temperature duration ratio and the low temperature duration ratio, record it as the temperature interference duration ratio, set the proportion coefficients of the temperature interference duration ratio, humidity interference duration ratio and dust duration interference ratio, and calculate the past environmental interference compensation factor through weighted average.

4. The distributed photovoltaic power station equipment intelligent control system according to claim 2 is characterized by: The specific confirmation process of the front-end device interference index is as follows: Extract the real-time output voltage of each inverter during each operation monitoring, as well as the number of overcurrents of each inverter and the duration of each overcurrent from the inverter operation tracking log; Calculate the mean of each overcurrent duration to obtain the average overcurrent duration, normalize the number of overcurrents and the average overcurrent duration, use the result as the overcurrent evaluation variable, and import the Sigmoid function to output the overcurrent interference degree of each inverter; With time as the horizontal axis and output voltage as the vertical axis, the output voltage change curve of each inverter operation monitoring is constructed, and the number of fluctuation points in the curve, the interval length of each fluctuation point and the output voltage difference are extracted; Calculate the mean of the interval duration and the output voltage difference of each fluctuation point to obtain the average fluctuation interval duration and the average fluctuation output voltage difference, and determine the voltage fluctuation assessment variable according to the definition of the overcurrent assessment variable; The number of fluctuation points, average fluctuation interval duration, and average fluctuation output voltage difference are normalized, and the results are used as voltage fluctuation evaluation variables and imported into the Sigmoid function to output the voltage fluctuation interference degree of each inverter during each operation monitoring. Filter out the voltage fluctuation interference degree during the current operation monitoring, and calculate the average voltage fluctuation interference degree of each inverter; Set the weight coefficients of overcurrent interference, average voltage fluctuation interference and current voltage fluctuation interference, calculate the interference of each inverter by weighted average, and select the maximum interference; Multiply the preset device interference score by the maximum interference level to obtain the front-end device interference index.

5. The distributed photovoltaic power station equipment intelligent control system according to claim 4 is characterized by: The specific confirmation process of the energy storage state interference index is as follows: Extract the accumulated operation time of each energy storage device, the SOH measurement value and SOC measurement value in each monitoring cycle, and the charge and discharge power during each monitoring from the energy storage device operation tracking log; Count the number of times the charge and discharge power exceeds the set reference charge and discharge power range, divide it by the total number of monitoring times, and get the charge and discharge power deviation ratio; The standard deviation of the charge and discharge power during each monitoring is calculated to obtain the charge and discharge power fluctuation of each energy storage device; With the monitoring period as the horizontal axis and the SOH measured value and SOC measured value as the vertical axis, the SOH decay rate change curve and SOC measured value change curve of each energy storage device are constructed, and the corresponding curve slopes are calculated and recorded as the SOH decay rate and SOC decay rate respectively; The energy storage interference degree of each energy storage device is obtained through statistical functions, and the energy storage state interference index is calculated according to the analysis method of the front-end device interference index.

6. A distributed photovoltaic power station equipment intelligent control system according to claim 2, characterized in that: The determining of the energy storage device charging setting regulation demand 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 of the three indexes is greater than or equal to the corresponding set reference value, it is determined that there is a need for regulation. Otherwise, the difference between the three indexes and the corresponding set reference value is calculated respectively; The environmental interference index, front-end device interference index and energy storage state interference index are used as evaluation interference indicators, and the number of evaluation interference indicators whose difference is less than the set safety index difference is counted; If the number of interference evaluation indicators is greater than or equal to 2, the demand is taken as the judgment result, otherwise the non-demand is taken as the judgment result.

7. The distributed photovoltaic power station equipment intelligent control system according to claim 5, characterized in that: The step of confirming the charging setting and adjusting the energy storage device comprises: 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 charging settings to adjust the energy storage devices; Marking an inverter whose interference degree is greater than the corresponding set reference interference degree as an interference inverter, and recording the energy storage device associated with the interference inverter as a front-end interference energy storage device; The energy storage device whose energy storage interference degree is greater than the corresponding set reference energy storage interference degree is recorded as the main body interference energy storage device; The main body interference energy storage device and the front-end interference energy storage device are compared, the repeated identical energy storage devices are eliminated, and the remaining energy storage devices after filtering are determined as the charging setting adjustment energy storage devices.

8. The distributed photovoltaic power station equipment intelligent control system according to claim 7, characterized in that: The step of confirming and setting the adjustment of charging power of the device includes: Will As an environmental compensation factor, To set the reference environment interference index; The energy storage interference degree of the adjustment device and the interference degree of the corresponding associated inverter are respectively recorded as and , set the energy storage interference compensation factor and the inverter interference compensation factor in the same way as the environment compensation factor; Set the ratio of environmental compensation factor, energy storage interference compensation factor and inverter interference compensation factor, and perform weighted average calculation. The calculation result is used as the charging power adjustment factor and recorded as ; Confirm the settings to adjust the charging power of the device , , and They are the preset reference charging power and the initial setting charging power respectively.

9. The distributed photovoltaic power station equipment intelligent control system according to claim 5, characterized in that: The determination of whether to perform equipment monitoring and adjustment includes: The existence of an inverter with an interference level greater than a set reference interference level is taken as condition 1, and the existence of an energy storage device with an energy storage interference level greater than a set reference energy storage interference level is taken as condition 2; If any of conditions 1 and 2 are met, the judgment result is adjusted, otherwise the judgment result is not adjusted.

10. The distributed photovoltaic power station equipment intelligent control system according to claim 8, characterized in that: The confirming monitoring and adjusting equipment and adjusting the monitoring frequency include: If the interference degree of a certain inverter is greater than the set reference interference degree, the inverter is determined as a monitoring and adjustment device; if the energy storage interference degree of a certain energy storage device is greater than the set reference energy storage interference degree, the energy storage device is determined as a monitoring and adjustment device; If the monitoring and adjustment device is an inverter, the interference degree of the inverter and the set reference interference degree are recorded as and ,Will As an adjustment to the monitoring frequency, Initially set monitoring frequency for the inverter; If the monitoring and adjustment device is an energy storage device, the energy storage interference degree of the energy storage device and the set reference energy storage interference degree are recorded as and ,Will As an adjustment to the monitoring frequency, Initially set the monitoring frequency for the energy storage device.

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