New energy power connection system

Abstract

The invention discloses a new energy power connection system. The new energy power connection system relates to the technical field of power connection, and comprises a power connection preparation module, a power line connection module, a system monitoring module and a supervision module. Acquiring inversion conversion efficiency by analyzing input end data and output end data of an off-grid inverter, performing data normalization processing on power indexes of the power connection system to acquire a risk assessment index, and analyzing a corresponding operation state and an abnormal condition by monitoring the risk assessment index of the power connection system in real time; and finally, real-time monitoring and automatic management are performed on the power connection system, so that the effect of improving the accuracy of power development operation supervision based on new energy is achieved, and the problem of low accuracy of power development operation supervision based on new energy in the prior art is solved.

Description

[0001] This application is a divisional application of the application filed on August 14, 2024, with application number 202411111189.1 and invention name “A power connection system based on new energy”. Technical Field

[0002] The present invention relates to the technical field of power connection, and in particular to a new energy power connection system. Background Art

[0003] With the gradual depletion of traditional energy resources and the increasing severity of environmental problems, the development of new energy has become an inevitable trend. The large-scale use of traditional energy has inevitably led to serious environmental pollution problems. These environmental problems not only threaten human health, but also cause serious damage to the ecosystem. The development of new energy technology has become the key to solving these problems. Compared with traditional energy, new energy has lower production costs and higher economic benefits, and the market competitiveness of new energy technology is also constantly improving. At the same time, as an important infrastructure for power transmission and distribution, the importance of the power connection system is becoming increasingly prominent. The power connection system is not only responsible for transmitting the electricity generated by the power plant to each user, but also needs to ensure the stable, safe and efficient transmission of electricity. Secondly, scientific and technological progress has also provided strong support for the development of the power connection system. The application of new power electronic equipment, communication technology and artificial intelligence technology has not only improved the operating efficiency of the power connection system, but also reduced the operating cost, providing a strong guarantee for the sustainable development of the power connection system, making the power connection system have a higher level of intelligence and automation. With the rapid development of new energy and the continuous advancement of technology, the power connection system will continue to face new challenges and opportunities and play a more important role in the power connection system.

[0004] The existing power connection system uses new energy power generation equipment to convert natural energy into electrical energy, and power electronic equipment converts and regulates the electricity generated by new energy, thereby achieving stable power supply for the power connection system.

[0005] For example, an invention patent with announcement number CN104882753B announces an electric power connection system, including: an electric power connection rail and a socket board module matched therewith, the top opening of the electric power connection rail is provided with an electric power module slot, the two sides of the electric power module slot are respectively an insulating surface and a wiring surface, the wiring surface is provided with conductive copper bars connected to the neutral line, the ground line and the live line of the power supply in sequence from top to bottom, the conversion panel installation slot is located at the bottom of the slot of the electric power module slot, a plurality of conversion panels are arranged inside, a spring is arranged between the conversion panel and the bottom of the slot where the conversion panel is installed, the power storage interface is arranged at the bottom of the conversion panel installation slot, and can be electrically connected to the power storage module, the conversion panel is pushed into the electric power module slot by the action of the spring to contact with the conductive copper bar, or is pressed back into the conversion panel installation slot by the action of the socket board module to break contact with the conductive copper bar, thereby providing power conversion between the power storage module and the power supply.

[0006] For example, a new energy power connection device announced in the invention patent with announcement number: CN111834802B includes: a first power module and a second power module, a through hole is opened on the front surface of the second power module, a layer of rubber pad is fixedly connected to the inside of the through hole, a power line body is fixedly connected to the inside of the through hole, a through hole is also opened on the rear side surface of the first power module, a layer of rubber pad is also fixedly connected to the inner wall of the through hole opened on the rear side surface of the first power module, a power line body is also connected to the inside of the through hole opened on the rear side surface of the first power module, and the front surface of the first power module is connected to the second power module. A docking device is provided on the rear surface of the second power module, a protective device is provided on the first power module, and a locking mechanism is provided on the second power module. The protective device includes a slide groove, which is provided on the left surface of the first power module, and a slider is slidably connected inside the slide groove. A slide groove is also provided on the right surface of the first power module, and a slider is slidably connected inside the slide groove. The other end of the slider is fixedly connected to the protection module, and the other end of the slider is fixedly connected to the left and right inner walls of the protection module. The protection module is a rectangular parallelepiped and has no front and back surfaces. A layer of sealing gasket is fixedly connected to the inner walls at both ends of the front and back of the protection module.

[0007] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems:

[0008] In the prior art, since the top opening of the power connection rail is provided with a power module slot, the conversion panel is pushed into the power module slot by the spring to contact the conductive copper bar, or is pressed back into the conversion panel installation slot to contact the power storage interface, so that the power system automatically switches between the power storage module and the power module. The development and operation of new energy power involves a large amount of data collection and processing work. If the data collection is incomplete, inaccurate, or the data processing method is unscientific, it will lead to deviations in the supervision results, and there is a problem of low accuracy in the supervision of power development and operation based on new energy. Summary of the invention

[0009] The embodiment of the present application solves the problem of low accuracy of power development and operation supervision based on new energy in the prior art by providing a new energy power connection system, thereby improving the accuracy of power development and operation supervision based on new energy.

[0010] The embodiment of the present application provides a new energy power connection system, including a power connection preparation module, a power line connection module, a system monitoring module and a supervision module; wherein the power connection preparation module is used to analyze the new energy of the designated wasteland to obtain new energy parameters, obtain the corresponding new energy potential evaluation index according to the new energy parameters, and feedback the construction plan and safety measures designed according to the new energy potential evaluation index to the preset personnel for the installation of the new energy power generation equipment, the new energy includes wind energy and solar energy, the new energy parameters include average sunshine duration, solar radiation intensity, average wind speed and wind energy density, and the new energy potential evaluation index is used to evaluate the new energy development potential of the designated wasteland; the power line connection module is used to connect the cable of the new energy power generation equipment to the corresponding interface of the off-grid inverter, and at the same time obtain the inverter conversion efficiency by analyzing the input end data and output end data of the off-grid inverter, and the off-grid inverter is used Direct current is converted into alternating current, the input end data includes input direct current power, electrical signal input distance and electrical signal input voltage, the output end data includes output alternating current power, electrical signal output distance and electrical signal output voltage, the inverter conversion efficiency is used to measure the energy conversion efficiency of the off-grid inverter in the process of converting direct current into alternating current; the system monitoring module is used to perform data normalization processing on the power indicators of the power connection system to obtain a risk assessment index, and at the same time analyze the corresponding operating status and abnormal conditions by real-time monitoring the risk assessment index of the power connection system, the power indicators include wind and solar abandonment risk indicators, steady-state frequency risk indicators and voltage collapse risk indicators, and the risk assessment index is used to assess the degree of risk faced by the power connection system during operation; the supervision module includes power sensors, which are used to monitor the power connection system in real time through deployed power sensors and perform automatic management of the power connection system.

[0011] Furthermore, the specific steps for obtaining the new energy potential assessment index are as follows: integrating and analyzing geographic information through a geographic information system method to generate a solar energy resource distribution map result, and obtaining the average sunshine duration and solar radiation intensity based on the solar energy resource distribution map result; obtaining the dynamic information and static information of the wind farm through a satellite remote sensing method and analyzing them to obtain the average wind speed and wind energy density, and the wind energy density is used to measure the average content of wind energy in a designated wasteland; obtaining a solar energy weight factor and a wind energy weight factor by analyzing the proportion of solar energy and wind energy in the energy structure, and the solar energy weight factor is used to quantify the proportion of solar energy in the energy supply, and the wind energy weight factor is used to quantify the proportion of wind energy in the energy supply; normalizing the average sunshine duration, solar radiation intensity, average wind speed and wind energy density, and obtaining the new energy potential assessment index in combination with the corresponding weight factors.

[0012] Furthermore, the new energy potential assessment index is calculated using the following formula:

[0013]

[0014] In the formula, XQ represents the new energy potential assessment index, e represents the natural constant, Y1 represents the average sunshine duration, Y2 represents the solar radiation intensity, F1 represents the average wind speed, F2 represents the wind energy density, and α Y is the solar energy weight factor, α F is the wind energy weight factor.

[0015] Furthermore, the specific process of obtaining dynamic and static information of a wind field by satellite remote sensing method is as follows: obtaining remote sensing data from satellite sensors, and filtering and denoising the remote sensing data; extracting wind field features from remote sensing images, wherein the wind field features include cloud movement and spatial distribution of wind speed; using machine learning methods to invert wind field parameters, and integrating the wind field parameters to obtain dynamic and static information of the wind field.

[0016] Furthermore, the off-grid inverter is composed of a photovoltaic unit, a charging control unit, a battery unit and an inverter unit; the photovoltaic unit is used to convert absorbed sunlight into direct current power; the charging control unit is used to manage and adjust the current and voltage flowing from the photovoltaic unit to the battery; the battery unit is used to store the electric energy generated by the photovoltaic unit and supply power to the load; the inverter unit is used to convert the direct current in the battery unit into alternating current.

[0017] Furthermore, the specific method for obtaining the inverter conversion efficiency is as follows: using a power analyzer to measure the DC power at the input end of the off-grid inverter to obtain the input DC power, and measuring the AC power at the output end of the off-grid inverter to obtain the output AC power; using an oscilloscope to measure the voltage and current at the input end of the off-grid inverter to obtain the electric signal input voltage and the electric signal input current, and measuring the voltage and current at the output end of the off-grid inverter to obtain the electric signal output voltage and the electric signal output current, and at the same time, by comparing the difference between the input current of the electric signal and the output current of the electric signal, the loss factor of the transmission medium is obtained; using a signal generator to measure the propagation time of the electric signal, and by obtaining the propagation speed of the electric signal, the electric signal output distance and the electric signal input distance are obtained; comparing the input end data and the output end data of the off-grid inverter and combining the electric signal output distance and the electric signal input distance to obtain the inverter conversion efficiency.

[0018] Furthermore, the specific method for obtaining the risk assessment index is as follows: combining the power generation of wind power and photovoltaic power during the power generation process and the actual allowable capacity of the power grid to obtain the wind and photovoltaic risk index, and the wind and photovoltaic risk index is the difference between the power generation of photovoltaic power during the power generation process and the actual allowable capacity of the power grid; according to the preset steady-state frequency characteristics of the power connection system and combined with the steady-state frequency of the power connection system and the corresponding reference value, the steady-state frequency risk index is obtained, and the steady-state frequency risk index is the difference between the steady-state frequency of the power connection system and the corresponding reference value; by drawing the voltage characteristic curve, the voltage collapse point is determined and the voltage collapse risk index is obtained, and the voltage collapse risk index is used to quantify the possibility and severity of voltage collapse in the power connection system under the current operating state; the hierarchical analysis method is used to determine the hierarchical weights of the power indicators, and the entropy weight method is used to weight the information entropy of each indicator to obtain the corresponding entropy weight, and the risk assessment index is obtained based on this analysis.

[0019] Furthermore, a specific method for obtaining the voltage collapse risk index is as follows: setting a preset observation point of the power connection system, and obtaining a voltage value of the preset observation point through power flow calculation, wherein the preset observation point is a branch node of the power connection system; changing the active power of the preset observation point by a preset power increment within a preset active power range to obtain a corresponding voltage value, and drawing a corresponding voltage characteristic curve; analyzing the voltage stability of the power connection system and the corresponding critical value through the inflection point in the drawn voltage characteristic curve, thereby obtaining a voltage collapse risk index.

[0020] Furthermore, the risk assessment index is calculated using the following formula:

[0021]

[0022] In the formula, DG represents the risk assessment index, i represents the weight number of the power index, i = 1, 2, 3, R1 represents the risk index of wind and solar power abandonment, R2 represents the steady-state frequency risk index, R3 represents the voltage collapse risk index, and w A,1 represents the hierarchical weight of the wind and solar power abandonment risk indicators, w E,1 represents the entropy weight of the wind and solar power abandonment risk index, w A,2 represents the hierarchical weight of the steady-state frequency risk indicator, w E,2 represents the entropy weight of the steady-state frequency risk indicator, w A,3 represents the hierarchical weight of voltage collapse risk index, w E,3 represents the entropy weight of the voltage collapse risk indicator, w A,i represents the hierarchical weight of the i-th power index, w E,i Represents the entropy weight of the i-th power index.

[0023] Furthermore, the specific steps of the automated management are: obtaining the corresponding mean and standard deviation by analyzing the power data of the historical time period, and obtaining the power parameter threshold in combination with the real-time power parameters collected by the power sensor in real time; comparing and analyzing whether the real-time power parameters are greater than the power parameter threshold, and automatically adjusting the power parameters if so, otherwise continuing to monitor the real-time power parameters of the power connection system.

[0024] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0025] 1. Obtain the corresponding new energy potential assessment index through new energy parameters, then obtain the inverter conversion efficiency by analyzing the input and output data of the off-grid inverter, and then perform data normalization processing on the power indicators of the power connection system to obtain the risk assessment index. At the same time, analyze the corresponding operating status and abnormal conditions through real-time monitoring of the risk assessment index of the power connection system, and finally perform real-time monitoring and automatic management of the power connection system, thereby realizing real-time monitoring of the risk assessment index of the power connection system, and then realizing the improvement of the accuracy of power development and operation supervision based on new energy, and effectively solving the problem of low accuracy of power development and operation supervision based on new energy in the prior art.

[0026] 2. The average sunshine duration and solar radiation intensity are obtained through the results of the solar energy resource distribution map, and the dynamic and static information of the wind field are analyzed to obtain the average wind speed and wind energy density. Finally, the new energy potential evaluation index is obtained by combining the corresponding weight factors, thereby realizing the numerical evaluation of new energy potential and achieving a more accurate evaluation of new energy potential.

[0027] 3. The voltage value of the preset observation point is obtained through power flow calculation, and then the active power of the preset observation point is changed by the preset power increment within the preset active power range to obtain the corresponding voltage value. Finally, the voltage stability of the power connection system and the corresponding critical value are analyzed through the inflection point in the drawn voltage characteristic curve to obtain the voltage collapse risk index, thereby realizing the numerical assessment of the risk of the power connection system, and then realizing a more accurate assessment of the risk of the power connection system. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 A schematic diagram of the structure of a new energy power connection system provided in an embodiment of the present application;

[0029] Figure 2 A flow chart for obtaining wind farm dynamic information and static information provided in an embodiment of the present application;

[0030] Figure 3 A flowchart of automated management provided for an embodiment of the present application. DETAILED DESCRIPTION

[0031] The embodiment of the present application solves the problem of low accuracy of power development and operation supervision based on new energy in the prior art by providing a new energy power connection system. New energy parameters are obtained by analyzing the new energy in the designated wasteland, and the corresponding new energy potential evaluation index is obtained according to the new energy parameters. At the same time, the construction plan and safety measures designed according to the new energy potential evaluation index are fed back to the preset personnel to install the new energy power generation equipment. Then, the cable of the new energy power generation equipment is connected to the corresponding interface of the off-grid inverter. At the same time, the input end data and the output end data of the off-grid inverter are analyzed to obtain the inverter conversion efficiency, and the power indicators of the power connection system are normalized to obtain the risk assessment index. Then, the corresponding operating status and abnormal conditions are analyzed by real-time monitoring of the risk assessment index of the power connection system. Finally, the deployed power sensors are used to monitor the power connection system in real time, and the power connection system is automatically managed, thereby improving the accuracy of power development and operation supervision based on new energy.

[0032] The technical solution in the embodiment of the present application is to solve the problem of low accuracy of the above-mentioned supervision of power development and operation based on new energy. The overall idea is as follows:

[0033] The corresponding new energy potential assessment index is obtained through new energy parameters and the new energy power generation equipment is installed. Then, the inverter conversion efficiency is obtained by analyzing the input and output data of the off-grid inverter, and the power indicators of the power connection system are normalized to obtain the risk assessment index. Then, the corresponding operating status and abnormal conditions are analyzed through real-time monitoring of the risk assessment index of the power connection system. Finally, the power connection system is monitored in real time and automatically managed, thereby improving the accuracy of power development and operation supervision based on new energy.

[0034] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0035] like Figure 1 As shown, it is a structural schematic diagram of a new energy power connection system provided in an embodiment of the present application. A new energy power connection system provided in an embodiment of the present application includes a power connection preparation module, a power line connection module, a system monitoring module and a supervision module; wherein the power connection preparation module is used to analyze the new energy of the designated wasteland to obtain new energy parameters, obtain the corresponding new energy potential evaluation index according to the new energy parameters, and feedback the construction plan and safety measures designed according to the new energy potential evaluation index to the preset personnel for the installation of the new energy power generation equipment, the new energy includes wind energy and solar energy, the new energy parameters include average sunshine duration, solar radiation intensity, average wind speed and wind energy density, and the new energy potential evaluation index is used to evaluate the new energy development potential of the designated wasteland; the power line connection module is used to connect the cable of the new energy power generation equipment to the corresponding interface of the off-grid inverter, and at the same time, by analyzing the input end data and output end data of the off-grid inverter Obtain the inverter conversion efficiency. The off-grid inverter is used to convert direct current into alternating current. The input end data includes input direct current power, electrical signal input distance and electrical signal input voltage. The output end data includes output alternating current power, electrical signal output distance and electrical signal output voltage. The inverter conversion efficiency is used to measure the energy conversion efficiency of the off-grid inverter in the process of converting direct current into alternating current. The system monitoring module is used to perform data normalization processing on the power indicators of the power connection system to obtain a risk assessment index. At the same time, the corresponding operating status and abnormal conditions are analyzed by real-time monitoring of the risk assessment index of the power connection system. The power indicators include wind and solar power abandonment risk indicators, steady-state frequency risk indicators and voltage collapse risk indicators. The risk assessment index is used to assess the degree of risk faced by the power connection system during operation. The supervision module includes power sensors, which are used to monitor the power connection system in real time through deployed power sensors and to automatically manage the power connection system.

[0036] In this embodiment, the new energy power generation equipment includes solar panels and wind turbines; the new energy power connection system utilizes new energy power generation technology, new energy access and grid connection technology, and the intelligent and automated technology of the power connection system, and can also cooperate with multi-energy complementary technology; the new energy power generation technology covers a variety of renewable energy power generation methods such as solar power generation, wind power generation, and hydropower generation, and uses natural resources to convert into electrical energy, which is the basis of the new energy power connection system. Other new energy sources can be taken into consideration in combination with actual conditions; the new energy access and grid connection technology converts direct current into alternating current through specific equipment and technology, such as inverters, so as to access and integrate into the traditional power connection system. This process also involves complex power electronics technology and control technology; the intelligent and automated technology of the power connection system can realize intelligent monitoring and management of the power connection system through advanced sensors, controllers and other equipment, and intelligent and automated technologies have been widely used in the power connection system; in addition, energy complementary technology can realize the coordinated operation of multiple energy sources, optimize energy utilization, improve the stability and reliability of the power connection system, and solve the intermittent and instability of new energy power generation; and realize the improvement of the low accuracy of power development and operation supervision based on new energy.

[0037] Furthermore, the specific steps for obtaining the new energy potential assessment index are as follows: integrate and analyze geographic information through the geographic information system method to generate a solar energy resource distribution map result, and obtain the average sunshine duration and solar radiation intensity based on the solar energy resource distribution map result; obtain the dynamic information and static information of the wind field through the satellite remote sensing method and analyze them to obtain the average wind speed and wind energy density, and the wind energy density is used to measure the average content of wind energy in the designated wasteland; obtain the solar energy weight factor and wind energy weight factor by analyzing the proportion of solar energy and wind energy in the energy structure, and the solar energy weight factor is used to quantify the proportion of solar energy in the energy supply, and the wind energy weight factor is used to quantify the proportion of wind energy in the energy supply; normalize the average sunshine duration, solar radiation intensity, average wind speed and wind energy density, and obtain the new energy potential assessment index in combination with the corresponding weight factors.

[0038] In this embodiment, wind energy density refers to the average content of wind energy per unit area per unit time. A higher wind energy density means that more wind energy can be obtained per unit area. The main features of the off-grid inverter are a wider input voltage range, a narrower output voltage range, and better output waveform quality. It is suitable for occasions with higher requirements on voltage fluctuations. In addition, the off-grid inverter can operate independently, is not affected by grid fluctuations, and has an island protection function. When a grid failure occurs, the inverter can automatically cut off the connection with the grid. The off-grid inverter is widely used in solar photovoltaic power generation systems, wind power generation systems, ship power supply systems, communication facility power supply systems, and emergency power supply systems. They can convert the DC power generated by distributed power sources into AC power, and output it to the grid or load after boosting through a transformer, solving the problem of how distributed power sources are connected to the grid, so that they can be integrated into the grid for operation; and the reliability of the power connection system is improved.

[0039] Furthermore, in addition to being obtained through resource surveys and assessments, the new energy potential assessment index can also be calculated more accurately. The new energy potential assessment index is calculated using the following formula:

[0040]

[0041] In the formula, XQ represents the new energy potential assessment index, e represents the natural constant, Y1 represents the average sunshine duration, Y2 represents the solar radiation intensity, F1 represents the average wind speed, F2 represents the wind energy density, and α Y is the solar energy weight factor, α F is the wind energy weight factor.

[0042] In this embodiment, the method for evaluating solar energy resources mainly includes ground observation method and remote sensing method; the ground observation method sets up solar radiation observation stations, uses radiometers and other equipment for long-term observation, obtains solar radiation data, and thus evaluates solar energy resources. The advantage of this method is that the data is accurate and reliable, and can provide detailed solar radiation information, but the disadvantage is that the observation station requires a lot of manpower and material resources, and the cost is relatively high; the remote sensing method is an evaluation method that uses remote sensing satellites to obtain solar radiation data, which can realize a macro-evaluation of solar energy resources. Its advantages are wide coverage and convenient data acquisition, but its disadvantages are relatively low data accuracy and cannot provide detailed ground solar radiation information.

[0043] Specifically, the methods for evaluating wind energy resources mainly include satellite remote sensing methods, numerical simulation methods and measured data analysis methods; the satellite remote sensing method uses satellite remote sensing data to obtain dynamic and static information of wind fields, and combines it with geographic information system methods for analysis and modeling, so as to evaluate the distribution and changes of wind energy resources; the numerical simulation method uses numerical simulation tools such as computational fluid dynamics models and climate models, combined with parameters such as geographical, meteorological and wind field characteristics, to deduce the details and complexity of wind energy resources; the measured data analysis method obtains existing measured data of wind energy resources, conducts statistical analysis and trend research on it, finds out the spatial and temporal characteristics of wind energy resources, as well as possible seasonal or interannual change trends, and achieves a more accurate assessment of new energy.

[0044] Further, such as Figure 2 As shown, it is a flow chart for obtaining the dynamic information and static information of the wind field provided in the embodiment of the present application. The specific process of obtaining the dynamic information and static information of the wind field by satellite remote sensing method is: obtaining remote sensing data from satellite sensors, and filtering and denoising the remote sensing data; extracting wind field characteristics from remote sensing images, and the wind field characteristics include cloud movement and spatial distribution of wind speed; using machine learning methods to invert wind field parameters, and integrating the wind field parameters to obtain dynamic information and static information of the wind field.

[0045] In this embodiment, satellite sensors are key devices for acquiring remote sensing data. They are carried on satellites and can capture various information on the earth's surface. When the satellite orbits the earth, the sensors on it will continuously collect electromagnetic wave signals reflected or emitted by the surface and convert these signals into digital data. These data contain various information on the surface, such as terrain, vegetation, water bodies, cities, etc. The process of acquiring remote sensing data usually includes steps such as satellite orbit design, sensor parameter setting, data reception and preprocessing. After the data is received, a series of data correction and enhancement processing are required to eliminate sensor errors and atmospheric interference and improve the accuracy and availability of the data. Remote sensing images are obtained by satellite sensors. The images formed after the acquired data are processed intuitively show the various features of the earth's surface. Extracting wind field features from remote sensing images mainly depends on image processing and feature extraction technology. The remote sensing images are preprocessed, including denoising, enhancement and segmentation, to improve the quality and clarity of the image. Then, image processing algorithms such as edge detection and texture analysis are used to extract feature information related to the wind field. These features may include wind direction, wind speed, wind field structure, etc. In the feature extraction process, it may be necessary to combine multi-source data and multi-phase data to improve the accuracy and reliability of feature extraction. At the same time, the influence of different land object types and wind field types on feature extraction also needs to be considered.

[0046] Specifically, machine learning methods play an important role in inverting wind field parameters. By learning a large amount of remote sensing data and wind field observation data, the machine learning model can establish a mapping relationship between remote sensing image features and wind field parameters. In the inversion process, it is first necessary to build a suitable machine learning model, such as a neural network, support vector machine, etc., and then use the known wind field observation data to train the model so that the model can learn the ability to extract wind field features from remote sensing images. After training, the model can be applied to new remote sensing image data. By inputting remote sensing image features, the model can output the corresponding wind field parameters, including wind speed, wind direction, etc., which can be used in meteorological forecasting, wind energy resource assessment and other fields. It should be noted that the accuracy and reliability of wind field parameters inverted by machine learning methods are affected by many factors, such as the quality of remote sensing data, model selection and training, complexity of land object types, etc. Therefore, in practical applications, these factors need to be considered comprehensively and appropriately optimized and adjusted; more accurate acquisition of dynamic and static information of wind fields is achieved.

[0047] Furthermore, the off-grid inverter consists of a photovoltaic unit, a charging control unit, a battery unit and an inverter unit; the photovoltaic unit is used to convert absorbed sunlight into direct current power; the charging control unit is used to manage and adjust the current and voltage flowing from the photovoltaic unit to the battery; the battery unit is used to store the electric energy generated by the photovoltaic unit and supply power to the load; the inverter unit is used to convert the direct current in the battery unit into alternating current.

[0048] In this embodiment, the working principle of the off-grid inverter is based on power electronics technology and control theory, and mainly includes an input circuit, a DC voltage boosting circuit, an inverter circuit and a control circuit. The input circuit connects the DC power generated by the solar panel to the inverter, the DC voltage boosting circuit boosts the DC voltage to a level suitable for the inverter, the inverter circuit converts the DC power into AC power, and the control circuit automatically adjusts the on-off time of the switch tube according to changes in parameters such as input voltage, output voltage and current, thereby achieving improved stability of the output voltage and output current.

[0049] Furthermore, a specific method for obtaining the inverter conversion efficiency is as follows: using a power analyzer to measure the DC power at the input end of the off-grid inverter to obtain the input DC power, and measuring the AC power at the output end of the off-grid inverter to obtain the output AC power; using an oscilloscope to measure the voltage and current at the input end of the off-grid inverter to obtain the electric signal input voltage and the electric signal input current, and measuring the voltage and current at the output end of the off-grid inverter to obtain the electric signal output voltage and the electric signal output current, and at the same time, by comparing the difference between the input current of the electric signal and the output current of the electric signal, the loss factor of the transmission medium is obtained; using a signal generator to measure the propagation time of the electric signal, and by obtaining the propagation speed of the electric signal, the electric signal output distance and the electric signal input distance are obtained; comparing the input end data and the output end data of the off-grid inverter and combining the electric signal output distance and the electric signal input distance to obtain the inverter conversion efficiency.

[0050] In this embodiment, the inverter conversion efficiency can be obtained not only through experimental testing, but also through more accurate calculation. The inverter conversion efficiency is calculated using the following formula:

[0051]

[0052] Where NZ represents the inverter conversion efficiency, P out Indicates the output AC power, P in represents the input DC power, n represents the loss factor of the transmission medium, D out Indicates the electrical signal output distance, D in Indicates the electrical signal input distance, V out Represents the electrical signal output voltage, V in Represents the electrical signal input voltage; represents the loss of transmission distance and medium loss factor, represents the voltage-based transmission loss, It represents the transmission loss based on power. The loss caused by voltage is greater than the loss caused by power. At the same time, the loss caused by the transmission distance of the electrical signal is related to the loss factor of the transmission medium, which realizes a more accurate evaluation of the inverter conversion efficiency.

[0053] Furthermore, the specific method for obtaining the risk assessment index is as follows: combining the power generation of wind power and photovoltaic power during the power generation process and the actual allowable capacity of the power grid to obtain the wind and photovoltaic risk index, which is the difference between the power generation of photovoltaic power during the power generation process and the actual allowable capacity of the power grid; obtaining the steady-state frequency risk index according to the preset steady-state frequency characteristics of the power connection system and combining the steady-state frequency of the power connection system and the corresponding reference value, which is the difference between the steady-state frequency of the power connection system and the corresponding reference value; determining the voltage collapse point by drawing the voltage characteristic curve and obtaining the voltage collapse risk index, which is used to quantify the possibility and severity of voltage collapse in the power connection system under the current operating state; using the hierarchical analysis method to determine the hierarchical weights of the power indicators, and using the entropy weight method to weight the information entropy of each indicator to obtain the corresponding entropy weight, and analyzing it to obtain the risk assessment index.

[0054] In this embodiment, the voltage characteristic curve is used to describe the changing relationship between the voltage value and the active power; the voltage collapse point refers to the key point of a serious accident caused by a vicious drop in voltage in the power system; when the power connection system is operating normally, the reactive power output of the power supply and the reactive power consumption of the load and the network reactive loss should be balanced. If the power supply or reactive power compensation capacity is insufficient, the voltage at the load end will be forced to decrease. When the voltage drops to a critical value, the voltage value will continue to decrease and cannot be restored. This critical value is the voltage collapse point. Voltage collapse will cause a large amount of load loss, and even cause large-scale power outages or system collapse. Therefore, for the stability and safety analysis of the power system, determining the voltage collapse point is of great significance.

[0055] Specifically, the analytic hierarchy process is a decision-making method that decomposes elements that are always related to decision-making into levels such as goals, criteria, and plans, and conducts qualitative and quantitative analysis on this basis. It regards a complex multi-objective decision-making problem as a system, decomposes the goal into multiple goals or criteria, and then decomposes it into several levels of multiple indicators. The single ranking and total ranking of the levels are calculated through the fuzzy quantification method of qualitative indicators, which is used as a systematic method for optimizing decision-making of goals and multiple plans. It is suitable for target systems with hierarchical and staggered evaluation indicators, and decision-making problems whose target values ​​are difficult to describe quantitatively; the entropy weight method is an objective weighting method. The basic principle is based on the concept of entropy in information theory. Entropy is a measure of the degree of disorder of a system, and information is a measure of the degree of order of a system. In the entropy weight method, for a certain indicator, the entropy value can be used to judge its degree of dispersion. The greater the degree of dispersion of the indicator, the greater the influence of the indicator on the comprehensive evaluation. By calculating the entropy value of each indicator, the weight of each indicator can be further obtained, providing a basis for the comprehensive evaluation of multiple indicators; the comprehensive weight analysis of multiple indicators is realized.

[0056] Furthermore, a specific method for obtaining the voltage collapse risk index is as follows: set a preset observation point of the power connection system, and obtain the voltage value of the preset observation point through power flow calculation, the preset observation point being a branch node of the power connection system; change the active power of the preset observation point by a preset power increment within a preset active power range to obtain a corresponding voltage value, and draw a corresponding voltage characteristic curve; analyze the voltage stability of the power connection system and the corresponding critical value through the inflection point in the drawn voltage characteristic curve, and obtain the voltage collapse risk index accordingly.

[0057] In this embodiment, in practical applications, power flow calculation is often used to determine the voltage collapse point. The basic idea of ​​this method is to start from the current working point, and as the load increases, the prediction calibration operator is continuously used to solve the power flow until the voltage collapse point is obtained. The voltage collapse point is a key concept in the stability analysis of the power system. Its determination is of great significance for preventing voltage collapse accidents and ensuring the normal operation of the power system; the safety of the power connection system is improved.

[0058] Furthermore, in addition to being obtained through Monte Carlo simulation, the risk assessment index can also be calculated more accurately. The risk assessment index is calculated using the following formula:

[0059]

[0060] In the formula, DG represents the risk assessment index, i represents the weight number of the power index, i = 1, 2, 3, R1 represents the risk index of wind and solar power abandonment, R2 represents the steady-state frequency risk index, R3 represents the voltage collapse risk index, and w A,1 represents the hierarchical weight of the wind and solar power abandonment risk indicators, w E,1 represents the entropy weight of the wind and solar power abandonment risk index, w A,2 represents the hierarchical weight of the steady-state frequency risk indicator, w E,2 represents the entropy weight of the steady-state frequency risk indicator, w A,3 represents the hierarchical weight of voltage collapse risk index, w E,3 represents the entropy weight of the voltage collapse risk indicator, w A,i represents the hierarchical weight of the i-th power index, w E,i Represents the entropy weight of the i-th power index.

[0061] In this embodiment, the hierarchical analysis method is used to determine the hierarchical weights of the power indicators, and the entropy weight method is used to weight the information entropy of each indicator to obtain the corresponding entropy weight. At the same time, the wind power and photovoltaic power generation in the power generation process and the actual allowable capacity of the power grid are combined to obtain the wind and photovoltaic abandonment risk index, and the steady-state frequency risk index is obtained according to the preset steady-state frequency characteristics of the power connection system and combined with the steady-state frequency of the power connection system and the corresponding reference value. Then, the voltage collapse point is determined by drawing the voltage characteristic curve and the voltage collapse risk index is obtained; when the risk assessment index is abnormal, an early warning signal is automatically issued, and the early warning signal can be in the form of sound, text, image or email, so as to notify relevant personnel in time. The content of the early warning signal should include the specific value of the risk assessment index, the type of abnormality, the possible impact and the recommended countermeasures, and each early warning signal issued is recorded, including the issuance time, the receiving personnel, the processing situation, etc., for subsequent audit and reporting. At the same time, a risk assessment report can be generated regularly to summarize the risk change trend and the effect of the countermeasures. Finally, according to the actual effect and feedback of the early warning signal, the risk assessment model, the threshold setting and the generation and sending mechanism of the early warning signal are continuously optimized and adjusted; the accuracy and effectiveness of the early warning signal are improved.

[0062] Further, such as Figure 3 As shown, it is a flowchart of the automated management provided in an embodiment of the present application, and the specific steps of the automated management are: obtaining the corresponding mean value and standard deviation by analyzing the power data of the historical time period, and obtaining the power parameter threshold in combination with the real-time power parameters collected by the power sensor in real time; comparing and analyzing whether the real-time power parameter is greater than the power parameter threshold, and automatically adjusting the power parameter if greater, otherwise continuing to monitor the real-time power parameters of the power connection system.

[0063] In this embodiment, the power parameter threshold is obtained by taking the average value after statistics of power data in a historical time period; the power sensor includes a voltage sensor, a current sensor, a power sensor and a temperature sensor, the voltage sensor is used to measure the voltage in the circuit, the current sensor is used for current measurement and protection in the power connection system, the power sensor is used to measure the power, active power and reactive power in the circuit, and the temperature sensor is used to monitor the temperature of the transformer and capacitor in the power connection system; real-time monitoring of the power connection system is realized.

[0064] The technical solution in the above-mentioned embodiment of the present application has at least the following technical effects or advantages: relative to a connector structure for preventing poor contact for new energy vehicles announced in the invention patent with announcement number: CN111697390B, the embodiment of the present application obtains the average sunshine duration and solar radiation intensity through the results of the solar resource distribution map, and analyzes the dynamic information and static information of the wind field to obtain the average wind speed and wind energy density, and finally obtains the new energy potential evaluation index in combination with the corresponding weight factor, thereby realizing the numerical evaluation of the new energy potential, and thus realizing a more accurate evaluation of the new energy potential; relative to a connector structure of a three-wire harness for a new energy vehicle announced in the invention patent with announcement number: CN116231383B, the embodiment of the present application obtains the voltage value of a preset observation point through flow calculation, and then changes the active power of the preset observation point by a preset power increment within a preset active power range to obtain the corresponding voltage value, and finally analyzes the voltage stability of the power connection system and the corresponding critical value through the inflection point in the drawn voltage characteristic curve to obtain the voltage collapse risk index, thereby realizing the numerical evaluation of the risk of the power connection system, and thus realizing a more accurate evaluation of the risk of the power connection system.

[0065] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0066] The present invention is described with reference to flowcharts and / or block diagrams of systems, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0067] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0068] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0069] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0070] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A new energy power connection system, characterized in that: It includes a power connection preparation module, a power line connection module, a system monitoring module and a supervision module; The power connection preparation module is used to analyze the new energy of the designated wasteland to obtain new energy parameters, obtain the corresponding new energy potential evaluation index according to the new energy parameters, and feed back the construction plan and safety measures designed according to the new energy potential evaluation index to the preset personnel for the installation of the new energy power generation equipment, the new energy includes wind energy and solar energy, the new energy parameters include average sunshine duration, solar radiation intensity, average wind speed and wind energy density, and the new energy potential evaluation index is used to evaluate the new energy development potential of the designated wasteland; The power line connection module is used to connect the cable of the new energy power generation equipment to the corresponding interface of the off-grid inverter, and at the same time, the inverter conversion efficiency is obtained by analyzing the input end data and the output end data of the off-grid inverter. The off-grid inverter is used to convert direct current into alternating current. The input end data includes input direct current power, electrical signal input distance and electrical signal input voltage. The output end data includes output alternating current power, electrical signal output distance and electrical signal output voltage. The inverter conversion efficiency is used to measure the energy conversion efficiency of the off-grid inverter in the process of converting direct current into alternating current; The system monitoring module is used to perform data normalization processing on the power indicators of the power connection system to obtain a risk assessment index, and at the same time analyze the corresponding operating status and abnormal conditions by real-time monitoring of the risk assessment index of the power connection system. The power indicators include wind and solar abandonment risk indicators, steady-state frequency risk indicators and voltage collapse risk indicators. The risk assessment index is used to assess the degree of risk faced by the power connection system during operation; The specific method for obtaining the voltage collapse risk indicator is as follows: Setting a preset observation point of the power connection system, and obtaining a voltage value of the preset observation point by power flow calculation, wherein the preset observation point is a branch node of the power connection system; Changing the active power of a preset observation point by a preset power increment within a preset active power interval to obtain a corresponding voltage value, and drawing a corresponding voltage characteristic curve; The voltage stability of the power connection system and the corresponding critical value are analyzed by the inflection points in the drawn voltage characteristic curve, and the voltage collapse risk index is obtained accordingly; The supervision module includes a power sensor, which is used to monitor the power connection system in real time through the deployed power sensors and automatically manage the power connection system;. The specific steps for obtaining the new energy potential assessment index are as follows: Integrate and analyze geographic information through geographic information system methods to generate solar energy resource distribution map results, and obtain average sunshine duration and solar radiation intensity based on the solar energy resource distribution map results; The dynamic and static information of the wind field is obtained by satellite remote sensing method and analyzed to obtain the average wind speed and wind energy density, wherein the wind energy density is used to measure the average content of wind energy in the designated wasteland; By analyzing the proportion of solar energy and wind energy in the energy structure, a solar energy weight factor and a wind energy weight factor are obtained, wherein the solar energy weight factor is used to quantify the proportion of solar energy in the energy supply, and the wind energy weight factor is used to quantify the proportion of wind energy in the energy supply; The average sunshine duration, solar radiation intensity, average wind speed and wind energy density are normalized, and the new energy potential assessment index is obtained by combining the corresponding weight factors; The new energy potential assessment index is calculated using the following formula: In the formula, XQ represents the new energy potential assessment index, e represents the natural constant, Y1 represents the average sunshine duration, Y2 represents the solar radiation intensity, F1 represents the average wind speed, F2 represents the wind energy density, and α Y is the solar energy weight factor, α F is the wind energy weight factor; The specific process of obtaining the dynamic information and static information of the wind farm by satellite remote sensing method is as follows: Acquire remote sensing data from satellite sensors and filter and denoise the remote sensing data; Extracting wind field features from remote sensing images, wherein the wind field features include cloud movement and spatial distribution of wind speed; Use machine learning methods to invert wind farm parameters, and integrate wind farm parameters to obtain dynamic and static information of the wind farm; The off-grid inverter is composed of a photovoltaic unit, a charging control unit, a battery unit and an inverter unit; The photovoltaic unit is used to convert absorbed sunlight into direct current electrical energy; The charging control unit is used to manage and adjust the current and voltage flowing from the photovoltaic unit to the battery; The battery unit is used to store the electric energy generated by the photovoltaic unit and supply power to the load; The inverter unit is used to convert the direct current in the battery unit into alternating current; The specific method for obtaining the inverter conversion efficiency is as follows: Use a power analyzer to measure the DC power at the input end of the off-grid inverter to obtain the input DC power, and measure the AC power at the output end of the off-grid inverter to obtain the output AC power; The voltage and current are measured at the input end of the off-grid inverter by an oscilloscope to obtain the electric signal input voltage and the electric signal input current, and the voltage and current are measured at the output end of the off-grid inverter to obtain the electric signal output voltage and the electric signal output current, and the loss factor of the transmission medium is obtained by comparing the difference between the electric signal input current and the electric signal output current; The signal generator is used to measure the propagation time of the electric signal, and the output distance and input distance of the electric signal are obtained by obtaining the propagation speed of the electric signal; The input data and output data of the off-grid inverter are compared and the inverter conversion efficiency is obtained by combining the electrical signal output distance and the electrical signal input distance.

2. A new energy power connection system as claimed in claim 1, characterized in that: The specific method for obtaining the risk assessment index is as follows: The wind and solar power abandonment risk index is obtained by combining the power generation of wind power and photovoltaic power in the power generation process and the actual allowable capacity of the power grid. The wind and solar power abandonment risk index is the difference between the power generation of photovoltaic power in the power generation process and the actual allowable capacity of the power grid; A steady-state frequency risk index is obtained according to a preset steady-state frequency characteristic of the power connection system and in combination with the steady-state frequency of the power connection system and a corresponding reference value, wherein the steady-state frequency risk index is a difference between the steady-state frequency of the power connection system and the corresponding reference value; Determine the voltage collapse point by drawing the voltage characteristic curve and obtain the voltage collapse risk index, wherein the voltage collapse risk index is used to quantify the possibility and severity of voltage collapse in the power connection system under the current operating state; The hierarchical analysis method is used to determine the hierarchical weights of power indicators, and the entropy weight method is used to weight the information entropy of each indicator to obtain the corresponding entropy weight, based on which the risk assessment index is analyzed.

3. A new energy power connection system as claimed in claim 1, characterized in that: The risk assessment index is calculated using the following formula: In the formula, DG represents the risk assessment index, i represents the weight number of the power index, i = 1, 2, 3, R1 represents the risk index of wind and solar power abandonment, R2 represents the steady-state frequency risk index, R3 represents the voltage collapse risk index, and w A,1 represents the hierarchical weight of the wind and solar power abandonment risk indicators, w E,1 represents the entropy weight of the wind and solar power abandonment risk index, w A,2 represents the hierarchical weight of the steady-state frequency risk indicator, w E,2 represents the entropy weight of the steady-state frequency risk indicator, w A,3 represents the hierarchical weight of voltage collapse risk index, w E,3 represents the entropy weight of the voltage collapse risk indicator, w A,i represents the hierarchical weight of the i-th power index, w E,i Represents the entropy weight of the i-th power index.

4. A new energy power connection system as claimed in claim 1, characterized in that: The specific steps of the automated management are: By analyzing the power data of the historical time period, the corresponding average value and standard deviation are obtained, and the power parameter threshold is obtained by combining the real-time power parameters collected by the power sensor in real time; Compare and analyze whether the real-time power parameters are greater than the power parameter threshold, and if so, automatically adjust the power parameters; otherwise, continue to monitor the real-time power parameters of the power connection system.

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