A 5G-based intelligent management system and method for new energy stations

Abstract

The present invention discloses a 5G-based new energy station intelligent management system and method, which relates to the technical field of new energy station management, including a mirror field area initial design unit, a mirror field model construction unit, a mirror field layout optimization unit, a component parameter analysis unit and a fault detection unit. The present invention analyzes the voltage value and current value of each node of the photovoltaic component through the component parameter analysis unit to obtain corresponding related parameters, and provides data support for subsequent analysis of the component operation status. At the same time, in the parameter analysis process, in order to prevent large errors, the results of each cycle are constrained by Gaussian weighting method, so that the relevant parameter values ​​finally obtained have high accuracy. The fault detection unit analyzes the data obtained in real time by the intelligent gateway device to determine the operation status of the photovoltaic component. When individual components are blocked, the system can promptly inform the operator to ensure the safe and efficient operation of the equipment.

Description

Technical Field

[0001] The present invention relates to the field of new energy station management technology, and specifically to a 5G-based new energy station smart management system and method. Background Art

[0002] Smart management systems for new energy stations usually optimize the layout of power generation equipment to ensure optimal light utilization efficiency, and use sensors and other equipment to monitor energy production in real time to ensure normal equipment operation. The invention patent with application number 202310595535.7 discloses "a 5G-based smart management system and method for new energy stations. The invention can determine multiple evaluation intervals according to the operating cycle of the distribution equipment, and then calculate the changing trend value of the distribution equipment operation according to the historical operating parameters of each evaluation interval, so that the calculation result of the changing trend value of the distribution equipment is more accurate, and the changing trend value of the distribution equipment operation can also be verified to screen out old historical operating parameters and avoid deviations in the estimated operating parameters calculated based on them, thereby providing managers with an accurate data support."

[0003] The above-mentioned existing technology solves the problem that old data in historical operating data may affect the equipment evaluation results. However, when the system is running, since the layout of the new energy power generation equipment is not optimized, some equipment may not have high working efficiency. At the same time, the parameters of power generation equipment such as photovoltaic modules are not analyzed. If the operating status of the equipment needs to be obtained, a large number of sensors must be deployed to obtain relevant monitoring data, and maintenance costs will also be required later. Summary of the invention

[0004] The purpose of the present invention is to provide a 5G-based new energy station intelligent management system and method to solve the problems raised in the above background technology.

[0005] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a 5G-based new energy station intelligent management system, including a fault detection unit;

[0006] A mirror field area initial setting unit, wherein the mirror field area initial setting unit obtains an initial radius value, a height, a width and a position spacing factor of a designated solar power station, determines a radius change value, and calculates a radius value of a next ring segment according to a radius value and a change value of a current ring segment. If the radius value does not meet the shielding lossless condition, a new radius change value is calculated according to a height of the heliostat and a relative distance between a heat absorption tower and the heliostat. The radius value of the next ring segment is analyzed using the radius change value, and after extracting a maximum spacing factor, the ring segments are screened according to the maximum spacing factor.

[0007] A mirror field model construction unit, wherein the mirror field model construction unit constructs a heliostat field model using simulation software, selects a target heliostat, calculates a regional position where the target heliostat has shielding and coverage loss, selects all heliostats to be measured in the regional position, determines the vertex projection coordinates of the heliostat to be measured, calculates the shielding total value and the coverage total value of the target heliostat according to the position information, and analyzes the work efficiency corresponding to different time periods according to the shielding total value and the coverage total value of each heliostat;

[0008] A mirror field layout optimization unit, wherein the mirror field layout optimization unit calculates the average annual efficiency of each heliostat according to the corresponding work efficiency in different time periods, analyzes the area occupied by the mirror field using the center point position coordinates of the heliostat, constructs an objective function based on these data, optimizes and solves it, determines the position spacing factor and the maximum spacing factor corresponding to the maximum objective function value, and optimizes the original heliostat field layout according to the position spacing factor and the maximum spacing factor;

[0009] A component parameter analysis unit, wherein the component parameter analysis unit uses sensors to monitor the voltage and current of each photovoltaic component node in a specified photovoltaic power station, determines the relevant parameters corresponding to the photovoltaic component after setting the total number of particles and dimensions, initializes the position and speed of each particle using a mapping equation, calculates the corresponding condition value according to the current position of the particle, and updates the individual optimal position and the collective optimal position, determines the corresponding speed and position in the next cycle according to the individual optimal position and the collective optimal position of each particle, outputs the collective optimal position before the weighted method is executed in the last cycle, determines the actual relevant parameter values ​​corresponding to each node voltage and current according to the collective optimal position, and constructs a component parameter analysis model through multiple groups of node voltages, currents and relevant parameter values.

[0010] Preferably, the mirror field area initial setting unit includes a radius change analysis module, a threshold calculation module, a radius change update module and a ring segment determination module. After the radius change analysis module obtains the initial radius value, the height, width and position separation factor of the specified solar power station, the characteristic length corresponding to the current mirror field is analyzed by the height and width of the heliostat, and the distance value between the first heliostat and the center of the adjacent heliostat in different ring segments is calculated according to the width and position separation factor of the heliostat by using the separation value analysis algorithm, and the radius change value is calculated by combining these data. After the threshold calculation module analyzes the radius value in the second ring segment according to the initial radius value and the radius change value, the radius value of the next ring segment is calculated according to the radius value and the change value of the current ring segment. After determining the height of the heat absorption tower, the height of the heat absorber and the height of the center of the heliostat from the ground, these data are used to determine the unobstructed area. The change threshold in the case of blocking loss, if the current change value is greater than or equal to the change threshold, the radius change update module determines that the radius value meets the blocking lossless condition, otherwise it is determined that the radius value does not meet the blocking lossless condition, and calculates a new radius change value according to the height of the heliostat and the relative distance between the heat absorption tower and the heliostat, and uses the radius change value to analyze the radius value of the next ring segment, after the ring segment determination module extracts the maximum spacing factor, the radius values ​​of different ring segments and the distance values ​​between the first heliostat in each ring segment and the center of its adjacent heliostat are used for calculation to obtain the distance values ​​between each heliostat in different ring segments, and the ratio between the last distance value and the first distance value in each ring segment is counted, if there is a ratio greater than the maximum spacing factor, the remaining ring segments outside the current ring segment are deleted, otherwise no operation is performed, and the phase separation value analysis algorithm is specifically as follows:

[0011]

[0012] in, Indicates In the ring distance values, Indicates In the ring distance values, Indicates In the ring distance values, represents the width of the heliostat, represents the position separation factor, Indicates The azimuth angle of the heliostats in each ring segment, Indicates In the ring The radius value, Indicates In the ring The radius value, Indicates In the ring distance value.

[0013] Preferably, the mirror field model construction unit includes a heliostat numbering module, a loss area analysis module and a projection coordinate calculation module. The heliostat numbering module uses simulation software to construct a solar position model and a heliostat field model according to the actual solar altitude angle, azimuth angle and the distance values ​​between each heliostat, and then analyzes the direction vectors corresponding to the incident light and the reflected light according to the solar position and the spatial position of the center point of the heliostat, and uses the direction vectors corresponding to the incident light and the reflected light to infer the pitch and horizontal rotation angles of each heliostat and the spatial position of each vertex in the mirror, and numbers each heliostat. After selecting the target heliostat, the loss area analysis module uses the characteristic length of the heliostat to construct a corresponding characteristic circle. A two-dimensional coordinate system is constructed with the center of the characteristic circle as the origin, the direction angle between the incident light and the reflected light in the current coordinate system is determined, and the regional position where the target heliostat has shielding and coverage loss is calculated according to the characteristic length and the direction angle. After the projection coordinate calculation module counts the numbers of all heliostats in the regional position, these heliostats are used as heliostats to be measured, and after determining the spatial positions of the center points of the heliostat to be measured and the target heliostat, a projection analysis algorithm is used to construct a plane equation passing through the vertex of the heliostat to be measured and having the same normal vector as the target heliostat. The projection coordinates corresponding to the vertex are analyzed according to the plane equation and the plane equation of the target heliostat. The simulation software is specifically a solar collector simulation software, and the projection analysis algorithm is specifically:

[0014]

[0015] in, Indicates the solar mirror to be measured Middle The projected horizontal coordinate of the vertex, Indicates the solar mirror to be measured Middle The projected ordinate of the vertex, Indicates the solar mirror to be measured Middle The projected vertical coordinate of the vertex, Indicates the solar mirror to be measured Middle The horizontal coordinate of the vertex, Indicates the solar mirror to be measured Middle The vertical coordinate of the vertex, Indicates the solar mirror to be measured Middle The vertical coordinate of the vertex, represents the coefficients of the constructed plane equation, represents the target heliostat plane equation coefficient, represents the plane normal vector of the target heliostat, represents the unit vector of the incident light, represents the horizontal axis vector of the incident light, represents the vertical axis vector of the incident light, Represents the vertical axis vector of the incident light ray.

[0016] Preferably, the mirror field model construction unit further includes a coverage area output module, a total loss value determination module and an efficiency analysis module. After the coverage area output module determines the vertex projection coordinates of the heliostat to be measured, a target coordinate system is constructed with the center point of the target heliostat as the origin, the projection coordinates in the vertex space coordinate system are converted into projection coordinates in the target coordinate system, and the coverage area of ​​the heliostat to be measured on the target heliostat is calculated according to the projection coordinates of each vertex and the vertex coordinates of the target heliostat. If the coverage area of ​​the heliostat to be measured is zero, the total loss value determination module determines that the heliostat is not the heliostat to be measured, otherwise it determines the position information of the coverage area, calculates the total coverage value according to the position information of all coverage areas, replaces the unit vector of the incident light with the unit vector of the reflected light, and obtains the total coverage value after executing the same steps. The efficiency analysis module determines the average solar altitude angle and azimuth corresponding to each time period in different seasons, and uses MATLAB software to analyze the working efficiency of each heliostat in different time periods according to the total coverage value, total coverage value, solar altitude angle and azimuth of a single heliostat.

[0017] Preferably, the mirror field layout optimization unit includes an objective function generation module, a factor determination module, a layout adjustment module and a position information display module. The objective function generation module counts the corresponding working efficiency of each heliostat in different time periods, calculates the annual average efficiency of each heliostat according to these data, constructs a first objective function according to the annual average efficiency of each heliostat, analyzes the area occupied by the mirror field according to the coordinates of the center point position of the heliostat, and constructs a second objective function using these data. After receiving the associated parameters, the factor determination module sets the number of mirror field layout schemes generated and the number of cycles, optimizes and solves the objective function, and calculates the annual average efficiency of each heliostat according to the annual average efficiency of each heliostat. After the round cycle is completed, two objective function values ​​and the corresponding position spacing factor and maximum spacing factor are determined, and the associated parameters include the width, length and characteristic length of the heliostat, tower height, absorber height, minimum ring segment radius, solar altitude angle and azimuth corresponding to different time periods. The layout adjustment module selects the position spacing factor and the maximum spacing factor corresponding to the maximum objective function value, and adjusts the original heliostat field layout according to the position spacing factor and the maximum spacing factor to obtain an optimized heliostat field model. The position information display module determines the position information and number of each heliostat after optimization, and outputs it through a visual interface.

[0018] Preferably, the component parameter analysis unit includes a real-time data monitoring module, a conditional function construction module, an optimal position analysis module, a particle information modification module, a parameter determination module and an analysis model generation module. The real-time data monitoring module uses sensors to monitor the voltage and current of each photovoltaic component node in the specified photovoltaic power station, and transmits the obtained data to a database for storage. After the conditional function construction module sets the total number of particles and the particle dimension, it determines the relevant parameters corresponding to the photovoltaic component, and constructs the corresponding conditional optimization function according to the association between the relevant parameters and the node voltage and current, wherein the relevant parameters include equivalent parallel resistance, equivalent series resistance, diode reverse saturation current, photocurrent and quality factor. After the optimal position analysis module sets the inertia weight, learning factor and number of cycles, it uses the mapping equation to initialize the position and speed of each particle, calculates the corresponding condition value according to the current position of the particle, and updates the individual optimal position and collective optimal position. The collective optimal position is adjusted by Gaussian weighting method, and the original collective optimal position is replaced by the adjusted result. The particle information modification module determines the corresponding speed and position in the next cycle according to the individual optimal position and collective optimal position of each particle, and judges whether the speed and position of any particle exceed the threshold value. If the speed and position of any particle exceed the threshold value, the mapping equation is used to modify it, otherwise the new speed and position are used to calculate the corresponding condition value. The parameter determination module repeats the operation until the number of cycles is reached, and the collective optimal position before the weighting method is executed in the last cycle is output. According to the collective optimal position, the actual relevant parameter values ​​corresponding to each node voltage and current are output. The analysis model generation module uses MATLAB software to analyze multiple groups of node voltages, currents and related parameter values, so as to construct a component parameter analysis model. The sensor is specifically a LEM voltage sensor and a CE-IJ03 current sensor.

[0019] Preferably, the fault detection unit includes a real-time data analysis module, a short-circuit determination module, an abnormality determination module, a covering determination module and an early warning prompt module. The real-time data analysis module uses an intelligent gateway device to obtain the voltage and current of a specified photovoltaic component node, and uses a component parameter analysis model to determine the relevant parameter values ​​corresponding to the current voltage value and the current value. The short-circuit determination module divides the operating state of the photovoltaic component into five types, namely, a normal state, a short-circuit state, an abnormal state, a small-area covering state and a large-area covering state. If the equivalent series resistance, the equivalent parallel resistance and the quality factor of the photovoltaic component are proportional to the original parameter values, and the proportional values ​​of the three parameters are the same, it is determined that there is a short-circuit state in the current photovoltaic component. The abnormality determination module sets a minimum parallel value and a maximum series value. If the equivalent parallel resistance is less than the minimum parallel value and the equivalent series resistance is greater than the maximum series value, it is determined. There is an abnormal state in the current photovoltaic component. The covering judgment module uses the SRF classification model to receive the voltage, current and related parameter values ​​of the current photovoltaic component, analyzes them as characteristic parameters, and outputs the proportion of shadow obstruction in the component. If the proportion is zero, it is determined that the current component is not in an obstruction state. If the proportion is greater than zero and less than the threshold, it is determined that the current component is in a small area obstruction state. If the proportion is greater than or equal to the threshold, it is determined that the current component is in a large area obstruction state. The early warning prompt module determines that the component is in a normal state when the component voltage, current and related parameter values ​​are all within the set range and are not in a short circuit state, abnormal state, small area obstruction state and large area obstruction state. If the component voltage, current and related parameter values ​​are not within the set range, an alarm prompt information will be issued. The smart gateway device is specifically a Four-Faith 5G industrial smart gateway.

[0020] The 5G-based new energy station intelligent management method comprises the following steps:

[0021] S1. Initial layout of the mirror field: After obtaining the initial radius value, heliostat height, width and position spacing factor of the specified solar power station, determine the radius change value, and calculate the radius value of the next ring segment according to the radius value and change value of the current ring segment. If the radius value does not meet the shading lossless condition, calculate a new radius change value according to the height of the heliostat and the relative distance between the heat absorption tower and the heliostat. Use the radius change value to analyze the radius value of the next ring segment, extract the maximum spacing factor, and screen the ring segments according to the maximum spacing factor.

[0022] S2. Calculating the working efficiency of the heliostat: After constructing a heliostat field model using simulation software, select a target heliostat, and calculate the regional position where the target heliostat has shielding and coverage loss, select all the heliostats to be measured in the regional position, determine the vertex projection coordinates of the heliostat to be measured, and then calculate the total shielding value and the total coverage value of the target heliostat according to these position information, and analyze the working efficiency corresponding to different time periods according to the total shielding value and the total coverage value of each heliostat;

[0023] S3. Optimizing the layout of the heliostat field: Calculate the average annual efficiency of each heliostat based on the corresponding work efficiency in different time periods, and analyze the area occupied by the mirror field using the coordinates of the center point of the heliostat. After constructing the objective function based on these data, optimize and solve it, determine the position spacing factor and the maximum spacing factor corresponding to the maximum objective function value, and optimize the original heliostat field layout according to the position spacing factor and the maximum spacing factor;

[0024] S4. Constructing a component parameter analysis model: using sensors to monitor the voltage and current of each photovoltaic component node in a specified photovoltaic power station, after setting the total number of particles and dimensions, determining the relevant parameters corresponding to the photovoltaic component, initializing the position and speed of each particle using a mapping equation, calculating the corresponding condition value according to the current position of the particle, and updating the individual optimal position and the collective optimal position, determining the corresponding speed and position in the next cycle according to the individual optimal position and the collective optimal position of each particle, outputting the collective optimal position before the weighted method is executed in the last cycle, determining the actual relevant parameter values ​​corresponding to the voltage and current of each node according to the collective optimal position, and constructing a component parameter analysis model through multiple sets of node voltages, currents and relevant parameter values;

[0025] S5. Detect component operation status: Use the component parameter analysis model to determine the relevant parameter values ​​corresponding to the current PV component voltage and current values, use the SRF classification model to analyze the voltage, current and related parameter values ​​of the current PV component, and output the proportion of shadow occlusion in the component. If the proportion is greater than zero and less than the threshold, the current component is determined to be in a small-area occlusion state. If the proportion is greater than or equal to the threshold, the current component is determined to be in a large-area occlusion state. If the component voltage, current and related parameter values ​​are not within the set range, an alarm prompt message will be issued.

[0026] Compared with the prior art, the present invention has the following beneficial effects:

[0027] The present invention analyzes the heliostat ring around the heat absorption tower through the mirror field area initial setting unit, determines the radius change value corresponding to each mirror ring, so that the mirror field can accommodate more heliostats. As the number of rings increases, the fixed radius change value may cause the heliostats on the outer ring to be blocked too much by other heliostats, affecting the working performance. Therefore, the unit is provided with a floating change threshold. Once the radius change value does not meet the conditions, a new change value will be generated to replace the current change value, and the spacing distance between each heliostat is also constrained to avoid wasting the floor area of ​​the mirror field due to excessive spacing. The mirror field model framework unit is used to generate a corresponding mirror field model according to the layout plan initially set, and the working efficiency of each heliostat in different time periods is refined, so that the mirror field layout optimization unit can construct a corresponding objective function, and the objective function is used to determine the optimal layout in the current mirror field, so as to ensure that the heliostats have higher working efficiency under a smaller floor area.

[0028] The present invention analyzes the voltage and current values ​​of each node of the photovoltaic component through a component parameter analysis unit to obtain corresponding related parameters, which provides data support for the subsequent analysis of the component operation status. At the same time, in the parameter analysis process, in order to prevent large errors, the result of each cycle is constrained by the Gaussian weighting method, so that the final related parameter value has a high accuracy. The fault detection unit analyzes the data obtained in real time by the intelligent gateway device to determine the operation status of the photovoltaic component. When individual components are blocked, the system can promptly inform the operator to ensure the safe and efficient operation of the equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 Provides a schematic diagram of the overall system flow for an embodiment of the present invention;

[0030] Figure 2 An internal module block diagram of a mirror field area initial setting unit provided in an embodiment of the present invention;

[0031] Figure 3 An internal module block diagram of a mirror field model construction unit provided in an embodiment of the present invention;

[0032] Figure 4 An internal module block diagram of a mirror field layout optimization unit provided in an embodiment of the present invention;

[0033] Figure 5 An internal module block diagram of a component parameter analysis unit provided in an embodiment of the present invention;

[0034] Figure 6 This is a block diagram of the internal modules of a fault detection unit provided in an embodiment of the present invention.

[0035] In the figure: 1. Mirror field area initial setting unit; 101. Radius change analysis module; 102. Threshold calculation module; 103. Radius change update module; 104. Ring segment determination module; 2. Mirror field model construction unit; 201. Heliostat numbering module; 202. Loss area analysis module; 203. Projection coordinate calculation module; 204. Cover area output module; 205. Total loss value determination module; 206. Efficiency analysis module; 3. Mirror field layout optimization unit; 301. Objective function generation module; 302. Factor determination module Module; 303, layout adjustment module; 304, position information display module; 4, component parameter analysis unit; 401, real-time data monitoring module; 402, conditional function construction module; 403, optimal position analysis module; 404, particle information modification module; 405, parameter determination module; 406, analysis model generation module; 5, fault detection unit; 501, real-time data analysis module; 502, short circuit determination module; 503, abnormality determination module; 504, covering determination module; 505, early warning prompt module. DETAILED DESCRIPTION

[0036] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0037] See also Figure 1-Figure 6 , the present invention provides a technical solution: a 5G-based new energy station intelligent management system, including a fault detection unit 5;

[0038] The mirror field area initial setting unit 1 obtains the initial radius value, the height, width and position spacing factor of the designated solar power station, determines the radius change value, and calculates the radius value of the next ring segment according to the radius value and change value of the current ring segment. If the radius value does not meet the shielding lossless condition, a new radius change value is calculated according to the height of the heliostat and the relative distance between the heat absorption tower and the heliostat. The radius value of the next ring segment is analyzed using the radius change value. After extracting the maximum spacing factor, the ring segments are screened according to the maximum spacing factor.

[0039] The mirror field model construction unit 2 constructs the heliostat field model by using simulation software, selects the target heliostat, calculates the regional position where the target heliostat has shielding and coverage loss, selects all the heliostats to be measured in the regional position, determines the vertex projection coordinates of the heliostat to be measured, calculates the total shielding value and the total coverage value of the target heliostat according to the position information, and analyzes the work efficiency corresponding to different time periods according to the total shielding value and the total coverage value of each heliostat;

[0040] The mirror field layout optimization unit 3 calculates the annual average efficiency of each heliostat according to the corresponding work efficiency in different time periods, analyzes the area occupied by the mirror field using the center point position coordinates of the heliostat, constructs the objective function through these data, optimizes and solves it, determines the position spacing factor and the maximum spacing factor corresponding to the maximum objective function value, and optimizes the original heliostat field layout according to the position spacing factor and the maximum spacing factor;

[0041] Component parameter analysis unit 4, component parameter analysis unit 4 uses sensors to monitor the voltage and current of each photovoltaic component node in the specified photovoltaic power station, after setting the total number of particles and dimensions, determines the relevant parameters corresponding to the photovoltaic component, uses mapping equations to initialize the position and speed of each particle, calculates the corresponding condition value according to the current position of the particle, and updates the individual optimal position and the collective optimal position, determines the corresponding speed and position in the next cycle according to the individual optimal position and the collective optimal position of each particle, outputs the collective optimal position before the weighted method is executed in the last cycle, determines the actual relevant parameter values ​​corresponding to each node voltage and current according to the collective optimal position, and constructs a component parameter analysis model through multiple groups of node voltages, currents and related parameter values.

[0042] The mirror field area initial setting unit 1 includes a radius change analysis module 101, a threshold calculation module 102, a radius change update module 103 and a ring segment determination module 104. The radius change analysis module 101 obtains the initial radius value, the height, width and position separation factor of the specified solar power station, and then analyzes the characteristic length corresponding to the current mirror field through the height and width of the heliostat. The distance value between the first heliostat and the center of the adjacent heliostat in different ring segments is calculated according to the width and position separation factor of the heliostat by using the separation value analysis algorithm, and the radius change value is calculated by combining these data. The threshold calculation module 102 analyzes the radius value in the second ring segment according to the initial radius value and the radius change value, and then calculates the radius value of the next ring segment according to the radius value and the change value of the current ring segment. After determining the height of the heat absorption tower, the height of the heat absorber and the height of the center of the heliostat from the ground, these data are used to calculate the radius change value. The change threshold in the case of no shading loss is determined. If the current change value is greater than or equal to the change threshold, the radius change updating module 103 determines that the radius value meets the shading lossless condition. Otherwise, the radius value does not meet the shading lossless condition. A new radius change value is calculated according to the height of the heliostat and the relative distance between the heat absorption tower and the heliostat. The radius value of the next ring segment is analyzed using the radius change value. After extracting the maximum spacing factor, the ring segment determination module 104 uses the radius values ​​of different ring segments and the distance values ​​between the first heliostat in each ring segment and the center of its adjacent heliostat to calculate and obtain the distance values ​​between each heliostat in the different ring segments. The ratio between the last distance value and the first distance value in each ring segment is counted. If there is a ratio greater than the maximum spacing factor, the remaining ring segments other than the current ring segment are deleted. Otherwise, no operation is performed. The phase separation value analysis algorithm is specifically as follows:

[0043]

[0044] in, Indicates In the ring distance values, Indicates In the ring distance values, Indicates In the ring distance values, represents the width of the heliostat, represents the position separation factor, Indicates The azimuth angle of the heliostats in each ring segment, Indicates In the ring The radius value, Indicates In the ring The radius value, Indicates In the ring distance values;

[0045] The mirror field model construction unit 2 includes a heliostat numbering module 201, a loss area analysis module 202, and a projection coordinate calculation module 203. The heliostat numbering module 201 uses simulation software to construct a solar position model and a heliostat field model according to the actual solar altitude angle, azimuth angle, and the distance value between each heliostat, and then analyzes the direction vectors corresponding to the incident light and the reflected light according to the solar position and the spatial position of the center point of the heliostat, and uses the direction vectors corresponding to the incident light and the reflected light to calculate the pitch and horizontal rotation angles of each heliostat and the spatial position of each vertex in the mirror, and numbers each heliostat. After the loss area analysis module 202 selects the target heliostat, it uses the characteristic length of the heliostat to construct the corresponding A characteristic circle is constructed with the center of the characteristic circle as the origin to construct a two-dimensional coordinate system, determine the direction angle between the incident light and the reflected light in the current coordinate system, calculate the regional position of the target heliostat where there is shielding and coverage loss according to the characteristic length and the direction angle, and the projection coordinate calculation module 203 counts the numbers of all heliostats in the regional position, takes these heliostats as the heliostats to be measured, determines the spatial positions of the heliostats to be measured and the center points of the target heliostat, and uses the projection analysis algorithm to construct a plane equation passing through the vertex of the heliostat to be measured and having the same normal vector as the target heliostat, and analyzes the projection coordinates corresponding to the vertex according to the plane equation and the plane equation of the target heliostat. The simulation software is specifically the solar collector simulation software, and the projection analysis algorithm is specifically:

[0046]

[0047] in, Indicates the solar mirror to be measured Middle The projected horizontal coordinate of the vertex, Indicates the solar mirror to be measured Middle The projected ordinate of the vertex, Indicates the solar mirror to be measured Middle The projected vertical coordinate of the vertex, Indicates the solar mirror to be measured Middle The horizontal coordinate of the vertex, Indicates the solar mirror to be measured Middle The vertical coordinate of the vertex, Indicates the solar mirror to be measured Middle The vertical coordinate of the vertex, represents the coefficients of the constructed plane equation, represents the target heliostat plane equation coefficient, represents the plane normal vector of the target heliostat, represents the unit vector of the incident light, represents the horizontal axis vector of the incident light, represents the vertical axis vector of the incident light, Represents the vertical axis vector of the incident light;

[0048] The mirror field model construction unit 2 also includes a coverage area output module 204, a total loss value determination module 205 and an efficiency analysis module 206. After the coverage area output module 204 determines the vertex projection coordinates of the heliostat to be measured, it constructs a target coordinate system with the center point of the target heliostat as the origin, converts the projection coordinates in the vertex space coordinate system into the projection coordinates in the target coordinate system, and calculates the coverage area of ​​the heliostat to be measured on the target heliostat according to the projection coordinates of each vertex and the vertex coordinates of the target heliostat. If the total loss value determination module 205 determines the coverage area of ​​the heliostat to be measured, the total loss value determination module 205 determines the coverage area of ​​the heliostat to be measured. If it is zero, it is determined that the heliostat is not the heliostat to be measured, otherwise the position information of the covered area is determined, and the total coverage value is calculated according to the position information of all covered areas, and the unit vector of the incident light is replaced by the unit vector of the reflected light, and the total coverage value is obtained after executing the same steps. The efficiency analysis module 206 determines the average solar altitude angle and azimuth angle corresponding to each time period in different seasons, and uses MATLAB software to analyze the working efficiency of each heliostat in different time periods according to the total coverage value, total coverage value, solar altitude angle and azimuth angle of a single heliostat;

[0049] The mirror field layout optimization unit 3 includes an objective function generation module 301, a factor determination module 302, a layout adjustment module 303 and a position information display module 304. The objective function generation module 301 counts the corresponding working efficiency of each heliostat in different time periods, calculates the annual average efficiency of each heliostat according to these data, constructs a first objective function according to the annual average efficiency of each heliostat, analyzes the area of ​​the mirror field according to the center point position coordinates of the heliostat, and constructs a second objective function using these data. After receiving the associated parameters, the factor determination module 302 sets the number of mirror field layout schemes generated and the number of cycles, and optimizes the objective function. Solution, after each cycle, two objective function values ​​and corresponding position spacing factors and maximum spacing factors are determined, and the associated parameters include the width, length and characteristic length of the heliostat, tower height, absorber height, minimum ring segment radius, solar altitude angle and azimuth angle corresponding to different time periods. The layout adjustment module 303 selects the position spacing factor and the maximum spacing factor corresponding to the maximum objective function value, and adjusts the original heliostat field layout according to the position spacing factor and the maximum spacing factor to obtain an optimized heliostat field model. The position information display module 304 determines the position information and number of each heliostat after optimization, and outputs it through a visual interface;

[0050] The component parameter analysis unit 4 includes a real-time data monitoring module 401, a conditional function construction module 402, an optimal position analysis module 403, a particle information modification module 404, a parameter determination module 405 and an analysis model generation module 406. The real-time data monitoring module 401 uses sensors to monitor the voltage and current of each photovoltaic component node in the specified photovoltaic power station, and transmits the obtained data to a database for storage. After the conditional function construction module 402 sets the total number of particles and the particle dimension, it determines the relevant parameters corresponding to the photovoltaic component, and constructs the corresponding conditional optimization function according to the correlation between the relevant parameters and the node voltage and current, wherein the relevant parameters include equivalent parallel resistance, equivalent series resistance, diode reverse saturation current, photocurrent and quality factor. After the optimal position analysis module 403 sets the inertia weight, learning factor and number of cycles, it uses the mapping equation to initialize the position and speed of each particle, calculates the corresponding condition value according to the current position of the particle, and updates the individual optimal position and collective optimal position. The optimal position is adjusted by using the Gaussian weighting method, and the original collective optimal position is replaced by the adjusted result. The particle information modification module 404 determines the corresponding speed and position in the next cycle according to the individual optimal position and the collective optimal position of each particle, and judges whether the speed and position of any particle exceed the threshold. If the speed and position of any particle exceed the threshold, the mapping equation is used to modify it, otherwise the new speed and position are used to calculate the corresponding condition value. The parameter determination module 405 repeats the operation until the number of cycles is reached, and the collective optimal position before the weighting method is executed in the last cycle is output. According to the collective optimal position, the actual relevant parameter values ​​corresponding to each node voltage and current are output. The analysis model generation module 406 uses MATLAB software to analyze multiple groups of node voltages, currents and related parameter values, so as to construct a component parameter analysis model. The sensors are specifically LEM voltage sensors and CE-IJ03 current sensors, and the condition optimization function is specifically:

[0051]

[0052]

[0053]

[0054] in, Indicates The actual voltage value of each PV module node, Indicates The actual current value of each PV module node, represents the equivalent parallel resistance, represents the equivalent series resistance, Represents the diode reverse saturation current, represents the photogenerated current, represents the quality factor, represents the Boltzmann constant, Indicates the absolute temperature of the component, represents the electron charge, Indicates the wiring voltage, Indicates The conditional value of the current position of each particle, Indicates The particle position coordinates, Indicates the total number of nodes, Represents parameters;

[0055] The mapping equation is specifically:

[0056]

[0057]

[0058] in, represents the updated position variable, represents the updated speed variable, Indicates control variables, represents the control parameter, represents the maximum position threshold, represents the minimum position threshold, Indicates the maximum speed threshold, Indicates the minimum speed threshold;

[0059] The fault detection unit 5 includes a real-time data analysis module 501, a short-circuit determination module 502, an abnormality determination module 503, a covering determination module 504 and an early warning prompt module 505. The real-time data analysis module 501 uses the intelligent gateway device to obtain the voltage and current of the specified photovoltaic component node, and uses the component parameter analysis model to determine the relevant parameter values ​​corresponding to the current voltage value and the current value. The short-circuit determination module 502 divides the operating state of the photovoltaic component into five types, namely normal state, short-circuit state, abnormal state, small-area covering state and large-area covering state. If the equivalent series resistance, equivalent parallel resistance and quality factor of the photovoltaic component are proportional to the original parameter values, and the proportional values ​​of the three parameters are the same, it is determined that there is a short-circuit state in the current photovoltaic component. The abnormality determination module 503 sets the minimum parallel value and the maximum series value. If the equivalent parallel resistance is less than the minimum parallel value and the equivalent When the series resistance is greater than the maximum series value, it is determined that there is an abnormal state in the current photovoltaic component. The covering determination module 504 uses the SRF classification model to receive the voltage, current and related parameter values ​​of the current photovoltaic component, and analyzes them as characteristic parameters to output the proportion of shadow shading in the component. If the proportion is zero, it is determined that the current component is not in a shading state. If the proportion is greater than zero and less than the threshold, it is determined that the current component is in a small area shading state. If the proportion is greater than or equal to the threshold, it is determined that the current component is in a large area shading state. The early warning prompt module 505 determines that the component is in a normal state when the component voltage, current and related parameter values ​​are all within the set range and are not in a short circuit state, abnormal state, small area shading state and large area shading state. If the component voltage, current and related parameter values ​​are not within the set range, an alarm prompt message will be issued;

[0060] A 5G-based new energy station intelligent management method includes the following steps:

[0061] S1. Initial layout of the mirror field: After obtaining the initial radius value, heliostat height, width and position spacing factor of the specified solar power station, determine the radius change value, and calculate the radius value of the next ring segment according to the radius value and change value of the current ring segment. If the radius value does not meet the shading lossless condition, calculate a new radius change value according to the height of the heliostat and the relative distance between the heat absorption tower and the heliostat. Use the radius change value to analyze the radius value of the next ring segment, extract the maximum spacing factor, and screen the ring segments according to the maximum spacing factor.

[0062] S2. Calculating the working efficiency of the heliostat: After constructing a heliostat field model using simulation software, select a target heliostat, and calculate the regional position where the target heliostat has shielding and coverage loss, select all the heliostats to be measured in the regional position, determine the vertex projection coordinates of the heliostat to be measured, and then calculate the total shielding value and the total coverage value of the target heliostat according to these position information, and analyze the working efficiency corresponding to different time periods according to the total shielding value and the total coverage value of each heliostat;

[0063] S3. Optimizing the layout of the heliostat field: Calculate the average annual efficiency of each heliostat based on the corresponding work efficiency in different time periods, and analyze the area occupied by the mirror field using the coordinates of the center point of the heliostat. After constructing the objective function based on these data, optimize and solve it, determine the position spacing factor and the maximum spacing factor corresponding to the maximum objective function value, and optimize the original heliostat field layout according to the position spacing factor and the maximum spacing factor;

[0064] S4. Constructing a component parameter analysis model: using sensors to monitor the voltage and current of each photovoltaic component node in a specified photovoltaic power station, after setting the total number of particles and dimensions, determining the relevant parameters corresponding to the photovoltaic component, initializing the position and speed of each particle using a mapping equation, calculating the corresponding condition value according to the current position of the particle, and updating the individual optimal position and the collective optimal position, determining the corresponding speed and position in the next cycle according to the individual optimal position and the collective optimal position of each particle, outputting the collective optimal position before the weighted method is executed in the last cycle, determining the actual relevant parameter values ​​corresponding to the voltage and current of each node according to the collective optimal position, and constructing a component parameter analysis model through multiple sets of node voltages, currents and relevant parameter values;

[0065] S5. Detect component operation status: Use the component parameter analysis model to determine the relevant parameter values ​​corresponding to the current PV component voltage and current values, use the SRF classification model to analyze the voltage, current and related parameter values ​​of the current PV component, and output the proportion of shadow occlusion in the component. If the proportion is greater than zero and less than the threshold, the current component is determined to be in a small-area occlusion state. If the proportion is greater than or equal to the threshold, the current component is determined to be in a large-area occlusion state. If the component voltage, current and related parameter values ​​are not within the set range, an alarm prompt message will be issued.

[0066] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0067] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A 5G-based new energy station intelligent management system, comprising a fault detection unit (5), characterized in that: A mirror field area initialization unit (1), wherein the mirror field area initialization unit (1) obtains an initial radius value, a height, a width and a position spacing factor of a designated solar power station, determines a radius change value, and infers a radius value of a next ring segment according to the radius value and the change value of a current ring segment; if the radius value does not meet the shielding lossless condition, a new radius change value is calculated according to the height of the heliostat and the relative distance between the heat absorption tower and the heliostat; the radius value of the next ring segment is analyzed using the radius change value; after extracting the maximum spacing factor, the ring segments are screened according to the maximum spacing factor; A mirror field model construction unit (2), wherein the mirror field model construction unit (2) constructs a heliostat field model using simulation software, selects a target heliostat, calculates a regional position where the target heliostat has shielding and coverage loss, selects all heliostats to be measured within the regional position, determines the vertex projection coordinates of the heliostat to be measured, calculates the shielding total value and the coverage total value of the target heliostat based on the position information, and analyzes the work efficiency corresponding to different time periods based on the shielding total value and the coverage total value of each heliostat; A mirror field layout optimization unit (3), wherein the mirror field layout optimization unit (3) calculates the annual average efficiency of each heliostat according to the corresponding work efficiency in different time periods, analyzes the area occupied by the mirror field using the center point position coordinates of the heliostat, constructs an objective function based on these data, optimizes and solves the objective function, determines the position spacing factor and the maximum spacing factor corresponding to the maximum objective function value, and optimizes the original heliostat field layout according to the position spacing factor and the maximum spacing factor; A component parameter analysis unit (4) is provided, wherein the component parameter analysis unit (4) uses a sensor to monitor the voltage and current of each photovoltaic component node in a specified photovoltaic power station, determines the relevant parameters corresponding to the photovoltaic component after setting the total number of particles and dimensions, initializes the position and speed of each particle using a mapping equation, calculates the corresponding condition value according to the current position of the particle, and updates the individual optimal position and the collective optimal position, determines the corresponding speed and position in the next cycle according to the individual optimal position and the collective optimal position of each particle, outputs the collective optimal position before the weighted method is executed in the last cycle, determines the actual relevant parameter value corresponding to each node voltage and current according to the collective optimal position, and constructs a component parameter analysis model through multiple groups of node voltages, currents and relevant parameter values.

2. According to claim 1, a 5G-based new energy station intelligent management system is characterized by: The mirror field area initial setting unit (1) comprises a radius change analysis module (101), a threshold calculation module (102), a radius change update module (103) and a ring segment determination module (104). The radius change analysis module (101) obtains the initial radius value, the height, width and position spacing factor of the designated solar power station, and then analyzes the characteristic length corresponding to the current mirror field through the height and width of the heliostat. The distance value between the first heliostat and the center of the adjacent heliostat in different ring segments is calculated based on the width and position spacing factor of the heliostat using a spacing value analysis algorithm, and the radius change value is calculated based on these data. The threshold calculation module (102) analyzes the radius value in the second ring segment based on the initial radius value and the radius change value, and then calculates the radius value of the next ring segment based on the radius value and the change value of the current ring segment, and determines the heat absorption tower height, the heat absorber height and the center of the heliostat. After the height above the ground is obtained, these data are used to determine the change threshold under the condition of no shielding loss. If the current change value is greater than or equal to the change threshold, the radius change updating module (103) determines that the radius value meets the shielding lossless condition. Otherwise, the radius value is determined not to meet the shielding lossless condition. A new radius change value is calculated according to the height of the heliostat and the relative distance between the heat absorption tower and the heliostat. The radius value of the next ring segment is analyzed using the radius change value. After extracting the maximum spacing factor, the ring segment determination module (104) uses the radius values ​​of different ring segments and the distance values ​​between the first heliostat in each ring segment and the center of its adjacent heliostat to calculate and obtain the distance values ​​between each heliostat in the different ring segments. The ratio between the last distance value and the first distance value in each ring segment is calculated. If there is a ratio greater than the maximum spacing factor, the remaining ring segments other than the current ring segment are deleted. Otherwise, no operation is performed.

3. According to a 5G-based new energy station intelligent management system according to claim 1, it is characterized by: The mirror field model construction unit (2) comprises a heliostat numbering module (201), a loss area analysis module (202) and a projection coordinate calculation module (203). The heliostat numbering module (201) uses simulation software to construct a solar position model and a heliostat field model according to the actual solar altitude angle, azimuth angle and the distance values ​​between each heliostat, and then analyzes the direction vectors corresponding to the incident light and the reflected light according to the solar position and the spatial position of the center point of the heliostat, and uses the direction vectors corresponding to the incident light and the reflected light to infer the pitch and horizontal rotation angles of each heliostat and the spatial position of each vertex in the mirror, and numbers each heliostat. The loss area analysis module (202) selects a target After the heliostat is located, a corresponding characteristic circle is constructed using the characteristic length of the heliostat, a two-dimensional coordinate system is constructed with the center of the characteristic circle as the origin, the direction angle between the incident light and the reflected light in the current coordinate system is determined, and the regional position where the target heliostat has shielding and coverage loss is calculated according to the characteristic length and the direction angle. The projection coordinate calculation module (203) counts the numbers of all heliostats in the regional position, takes these heliostats as heliostats to be measured, determines the spatial positions of the heliostats to be measured and the center points of the target heliostat, and constructs a plane equation passing through the vertex of the heliostat to be measured and having the same normal vector as the target heliostat using a projection analysis algorithm, and analyzes the projection coordinates corresponding to the vertex according to the plane equation and the plane equation of the target heliostat.

4. According to claim 3, a 5G-based new energy station intelligent management system is characterized by: The mirror field model construction unit (2) further comprises a coverage area output module (204), a total loss value determination module (205) and an efficiency analysis module (206). After the coverage area output module (204) determines the vertex projection coordinates of the heliostat to be measured, a target coordinate system is constructed with the center point of the target heliostat as the origin, the projection coordinates in the vertex space coordinate system are converted into projection coordinates in the target coordinate system, and the coverage area of ​​the heliostat to be measured on the target heliostat is calculated according to the vertex projection coordinates and the vertex coordinates of the target heliostat. If the total loss value determination module (205) determines the vertex projection coordinates of the heliostat to be measured, the target heliostat is covered by the coverage area output module (204). If the coverage area of ​​the heliostat is zero, it is determined that the heliostat is not the heliostat to be measured. Otherwise, the position information of the coverage area is determined. The total coverage value is calculated according to the position information of all the coverage areas. The unit vector of the incident light is replaced by the unit vector of the reflected light. The total coverage value is obtained after executing the same steps. The efficiency analysis module (206) determines the average solar altitude angle and azimuth angle corresponding to each time period in different seasons. The MATLAB software is used to analyze the working efficiency of each heliostat in different time periods according to the total coverage value, total coverage value, solar altitude angle and azimuth angle of a single heliostat.

5. According to a 5G-based new energy station intelligent management system according to claim 1, it is characterized by: The mirror field layout optimization unit (3) comprises an objective function generation module (301), a factor determination module (302), a layout adjustment module (303) and a position information display module (304). The objective function generation module (301) counts the corresponding working efficiency of each heliostat in different time periods, calculates the annual average efficiency of each heliostat based on these data, constructs a first objective function based on the annual average efficiency of each heliostat, analyzes the area occupied by the mirror field based on the position coordinates of the center point of the heliostat, and constructs a second objective function using these data. The factor determination module (302) receives the associated After the parameters are set, the number of mirror field layout schemes generated and the number of cycles are set, the objective function is optimized and solved, and two objective function values ​​and corresponding position spacing factors and maximum spacing factors are determined after each cycle. The layout adjustment module (303) selects the position spacing factor and the maximum spacing factor corresponding to the maximum objective function value, and adjusts the original heliostat field layout according to the position spacing factor and the maximum spacing factor to obtain an optimized heliostat field model. The position information display module (304) determines the position information and number of each heliostat after optimization, and outputs them through a visual interface.

6. According to a 5G-based new energy station intelligent management system according to claim 1, it is characterized by: The component parameter analysis unit (4) includes a real-time data monitoring module (401), a conditional function construction module (402), an optimal position analysis module (403), a particle information modification module (404), a parameter determination module (405) and an analysis model generation module (406). The real-time data monitoring module (401) uses sensors to monitor the voltage and current of each photovoltaic component node in a specified photovoltaic power station, and transmits the obtained data to a database for storage. After setting the total number of particles and the particle dimension, the conditional function construction module (402) determines the relevant parameters corresponding to the photovoltaic component, and constructs the corresponding conditional optimization function according to the relationship between the relevant parameters and the node voltage and current. After setting the inertia weight, the learning factor and the number of cycles, the optimal position analysis module (403) uses a mapping equation to initialize the position and speed of each particle, calculates the corresponding condition value according to the current position of the particle, and updates the individual optimal The collective optimal position is adjusted by Gaussian weighting method, and the original collective optimal position is replaced by the adjusted result. The particle information modification module (404) determines the speed and position corresponding to the next cycle according to the individual optimal position and the collective optimal position of each particle, and judges whether there is a particle whose speed and position exceed the threshold. If there is a particle whose speed and position exceed the threshold, it is modified by using the mapping equation, otherwise the corresponding condition value is calculated by using the new speed and position. The parameter determination module (405) repeats the operation until the number of cycles is reached, and outputs the collective optimal position before the weighting method is executed in the last cycle. According to the collective optimal position, the actual relevant parameter value corresponding to each node voltage and current is output. The analysis model generation module (406) uses MATLAB software to analyze multiple groups of node voltages, currents and related parameter values, thereby constructing a component parameter analysis model.

7. According to a 5G-based new energy station intelligent management system according to claim 1, it is characterized by: The fault detection unit (5) comprises a real-time data analysis module (501), a short-circuit determination module (502), an abnormality determination module (503), a covering determination module (504) and an early warning prompt module (505). The real-time data analysis module (501) uses an intelligent gateway device to obtain the voltage and current of a designated photovoltaic component node, and uses a component parameter analysis model to determine the relevant parameter values ​​corresponding to the current voltage value and the current value. The short-circuit determination module (502) divides the operation state of the photovoltaic component into five types, namely a normal state, a short-circuit state, an abnormal state, a small-area covering state and a large-area covering state. If the equivalent series resistance, the equivalent parallel resistance and the quality factor of the photovoltaic component are proportional to the original parameter values, and the proportional values ​​of the three parameters are the same, it is determined that a short-circuit state exists in the current photovoltaic component. The abnormality determination module (503) sets a minimum parallel value and a maximum series value. If the equivalent parallel resistance is less than When the minimum parallel value and the equivalent series resistance are greater than the maximum series value, it is determined that an abnormal state exists in the current photovoltaic component. The covering determination module (504) receives the voltage, current and related parameter values ​​of the current photovoltaic component using the SRF classification model, analyzes them as characteristic parameters, and outputs the proportion of shadow shading in the component. If the proportion is zero, it is determined that the current component is not in a shading state. If the proportion is greater than zero and less than a threshold, it is determined that the current component is in a small area shading state. If the proportion is greater than or equal to the threshold, it is determined that the current component is in a large area shading state. The early warning prompt module (505) determines that the component is in a normal state when the component voltage, current and related parameter values ​​are all within the set range and are not in a short circuit state, an abnormal state, a small area shading state and a large area shading state. If the component voltage, current and related parameter values ​​are not within the set range, an alarm prompt message will be issued.

8. A 5G-based smart management method for new energy stations, characterized in that: The smart management method is applicable to a 5G-based new energy station smart management system as described in any one of claims 1 to 7, and comprises the following steps: S1. Initial layout of the mirror field: After obtaining the initial radius value, heliostat height, width and position spacing factor of the specified solar power station, determine the radius change value, and calculate the radius value of the next ring segment according to the radius value and change value of the current ring segment. If the radius value does not meet the shading lossless condition, calculate a new radius change value according to the height of the heliostat and the relative distance between the heat absorption tower and the heliostat. Use the radius change value to analyze the radius value of the next ring segment, extract the maximum spacing factor, and screen the ring segments according to the maximum spacing factor. S2. Calculating the working efficiency of the heliostat: After constructing a heliostat field model using simulation software, select a target heliostat, and calculate the regional position where the target heliostat has shielding and coverage loss, select all the heliostats to be measured in the regional position, determine the vertex projection coordinates of the heliostat to be measured, and then calculate the total shielding value and the total coverage value of the target heliostat according to these position information, and analyze the working efficiency corresponding to different time periods according to the total shielding value and the total coverage value of each heliostat; S3. Optimizing the layout of the heliostat field: Calculate the average annual efficiency of each heliostat based on the corresponding work efficiency in different time periods, and analyze the area occupied by the mirror field using the coordinates of the center point of the heliostat. After constructing the objective function based on these data, optimize and solve it, determine the position spacing factor and the maximum spacing factor corresponding to the maximum objective function value, and optimize the original heliostat field layout according to the position spacing factor and the maximum spacing factor; S4. Constructing a component parameter analysis model: using sensors to monitor the voltage and current of each photovoltaic component node in a specified photovoltaic power station, after setting the total number of particles and dimensions, determining the relevant parameters corresponding to the photovoltaic component, initializing the position and speed of each particle using a mapping equation, calculating the corresponding condition value according to the current position of the particle, and updating the individual optimal position and the collective optimal position, determining the corresponding speed and position in the next cycle according to the individual optimal position and the collective optimal position of each particle, outputting the collective optimal position before the weighted method is executed in the last cycle, determining the actual relevant parameter values ​​corresponding to the voltage and current of each node according to the collective optimal position, and constructing a component parameter analysis model through multiple sets of node voltages, currents and relevant parameter values; S5. Detect component operation status: Use the component parameter analysis model to determine the relevant parameter values ​​corresponding to the current PV component voltage and current values, use the SRF classification model to analyze the voltage, current and related parameter values ​​of the current PV component, and output the proportion of shadow occlusion in the component. If the proportion is greater than zero and less than the threshold, the current component is determined to be in a small-area occlusion state. If the proportion is greater than or equal to the threshold, the current component is determined to be in a large-area occlusion state. If the component voltage, current and related parameter values ​​are not within the set range, an alarm prompt message will be issued.

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