BIPV intelligent design and optimization platform control system based on BIM

Abstract

The invention discloses a BIPV intelligent design and optimization platform control system based on BIM, and particularly relates to a BIPV intelligent design and optimization technology, which comprises a data batch division module, a BIPV data acquisition module, a BIPV data analysis module, a comprehensive evaluation module and a real-time early warning feedback module. The data batch division module is used for determining to-be-collected data as target data and dividing the target data into different batches according to an equitime division mode; the BIPV data acquisition module comprises a system performance data acquisition unit and an environment data acquisition unit; the BIPV data analysis module comprises a system performance data analysis unit and an environment data analysis unit; the comprehensive evaluation module comprises a BIPV intelligent design analysis unit; and the real-time early warning feedback module is used for establishing a BIPV intelligent design rationality index preset value and judging the BIPV intelligent design rationality index value according to the BIPV intelligent design rationality index preset value.

Description

Technical Field

[0001] The present invention relates to the field of BIPV intelligent design and optimization technology, and more specifically, to a BIM-based BIPV intelligent design and optimization platform control system. Background Art

[0002] With the rapid development of building information modeling (BIM) and building integrated photovoltaic (BIPV) technology, its application in green building design and construction is becoming more and more extensive. As an important part of future sustainable buildings, the design and optimization of BIPV are of great significance to improving building energy efficiency and promoting energy transformation.

[0003] The existing BIM-based BIPV intelligent design and optimization platform control system mainly includes: BIM data integration module, intelligent design optimization module, performance simulation analysis module and user interaction interface. Among them, the BIM data integration module is responsible for integrating multi-professional information such as architectural design, structure, and electrical to build a detailed building information model; the intelligent design optimization module uses advanced algorithms to optimize the layout and capacity of BIPV components to maximize the efficiency of photovoltaic power generation; the performance simulation analysis module evaluates the overall performance of the BIPV system by simulating the energy consumption and photovoltaic output of the building under different environmental conditions; the user interaction interface provides designers and engineers with an intuitive and easy-to-use operating platform to support the rapid iteration and optimization of design solutions.

[0004] However, in the existing BIPV design and optimization platform, the focus is often on the layout optimization and energy efficiency analysis of photovoltaic modules, while ignoring the dynamic interaction between the building's own energy consumption pattern and the operation of the BIPV system, resulting in limited adaptability and energy efficiency of the design scheme in practical applications. In addition, the lack of breadth and depth of data collection and analysis also limits the system's ability to accurately respond to complex environmental factors.

[0005] Therefore, there is an urgent need for an intelligent design and optimization platform control system that deeply integrates BIM and BIPV technologies to solve the problems of incomplete data collection, insufficient accuracy of analysis results, and disconnection between design and actual operation in the existing system. Summary of the invention

[0006] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a BIM-based BIPV intelligent design and optimization platform control system, which solves the problems raised in the above-mentioned background technology through the following scheme.

[0007] To achieve the above object, the present invention provides the following technical solution: a BIM-based BIPV intelligent design and optimization platform control system, comprising: Data batch division module: used to determine the data to be collected as target data, divide the target data into different batches according to equal time division, and mark them as 1, 2, ..., n in sequence; BIPV data acquisition module: including a system performance data acquisition unit and an environmental data acquisition unit, which are used to acquire target data in real time and transmit the acquired data to the data analysis module; the system performance data acquisition unit is used to acquire power generation performance data, operating status data and energy efficiency data; the environmental data acquisition unit is used to acquire meteorological condition data and building structure data; The BIPV data analysis module includes: a system performance data analysis unit and an environmental data analysis unit; used to analyze the data transmitted by the BIPV data acquisition module and transmit the analysis results to the comprehensive data evaluation module; the system performance data analysis unit includes a power generation performance data analysis node, an operation status data analysis node and an energy efficiency data analysis node; the environmental data analysis unit includes a meteorological condition data analysis node and a building structure data analysis node; Comprehensive evaluation module: including a BIPV intelligent design analysis unit, which is used to analyze the data transmitted by the BIPV data analysis module and transmit the analysis results to the real-time warning feedback module; Real-time early warning feedback module: used to establish a preset value of the BIPV intelligent design rationality index, judge the BIPV intelligent design rationality index value according to the preset value of the BIPV intelligent design rationality index, send a corresponding signal according to the judgment result and save the data in the database.

[0008] Preferably, the power generation performance data include the photovoltaic cell spectral response matching rate Sp, the system maximum power point tracking accuracy ratio St and the system power generation efficiency Se under partial shading conditions; the operating status data include the inverter start-up response time Ir, the system hot spot effect ratio Hr and the system self-cleaning efficiency Sc; the energy efficiency ratio data include the inverter conversion efficiency Ic, the cable transmission loss rate Cl and the system energy efficiency ratio Er.

[0009] Preferably, the meteorological condition data include the total horizontal radiation Ht, the atmospheric scattering rate As and the atmospheric transmittance At; the building structure data include the roof inclination angle Ra, the roof material reflectivity Rm and the building shadow shielding rate Bs.

[0010] Preferably, the power generation performance data analysis node is used to establish a power generation performance data calculation model, import the power generation performance data transmitted by the BIPV data acquisition module into the power generation performance data calculation model, and obtain the power generation performance characteristic coefficient value; the power generation performance data calculation model is specifically expressed as: , in, Indicates the power generation performance characteristic coefficient value calculated for the i-th time, Sp i St represents the spectral response matching rate of the photovoltaic cell collected for the i-th time. i represents the system maximum power point tracking accuracy ratio for the i-th acquisition, Se i It represents the power generation efficiency of the system under partial shading conditions collected for the i-th time; i means starting from the i-th number, and n means ending at the n-th number.

[0011] Preferably, the operation status data analysis node is used to establish an operation status data calculation model, import the operation status data transmitted by the BIPV data acquisition module into the operation status data calculation model, and obtain the operation status characteristic coefficient value; the operation status data calculation model is specifically expressed as: , in, Indicates the characteristic coefficient value of the operating state calculated for the i-th time, Ir i Indicates the inverter startup response time collected for the i-th time, Hr i represents the system hot spot effect ratio of the i-th acquisition, Sc i It represents the system self-cleaning efficiency collected for the i-th time; i means starting from the i-th number, and n means ending at the n-th number.

[0012] Preferably, the energy efficiency ratio data analysis node is used to establish an energy efficiency ratio data calculation model, import the energy efficiency ratio data transmitted by the BIPV data acquisition module into the energy efficiency ratio data calculation model, and obtain the energy efficiency ratio characteristic coefficient value; the energy efficiency ratio data calculation model is specifically expressed as: , in, Indicates the energy efficiency ratio characteristic coefficient value calculated for the i-th time, Ic i represents the inverter startup response time collected for the i-th time, Cl i represents the cable transmission loss rate collected for the i-th time, Er i Represents the system energy efficiency ratio of the i-th collection.

[0013] Preferably, the meteorological condition data analysis node is used to establish a meteorological condition data calculation model, and the meteorological condition data transmitted by the BIPV data acquisition module is imported into the meteorological condition data calculation model to obtain the meteorological environment characteristic coefficient value; the meteorological condition data calculation model is specifically expressed as: , in, Indicates the meteorological environment characteristic coefficient value calculated for the i-th time, Ht i Indicates the total horizontal radiation collected for the i-th time, As iIndicates the atmospheric scattering rate collected for the i-th time, At i Indicates the atmospheric transmittance collected for the i-th time; i means starting from the i-th number, and n means ending at the n-th number.

[0014] Preferably, the building structure data analysis node is used to establish a building structure data calculation model, import the building structure data transmitted by the BIPV data acquisition module into the building structure data calculation model, and obtain the building structure characteristic coefficient value; the building structure data calculation model is specifically expressed as: , in, Represents the building structure characteristic coefficient value calculated for the i-th time, Ra i Indicates the roof inclination angle collected for the i-th time, Rm i Indicates the reflectivity of the roof material collected for the i-th time, Bs i The building shadow occlusion rate collected for the i-th time.

[0015] Preferably, the BIPV intelligent design analysis unit is used to establish a BIPV intelligent design calculation model, and import the power generation performance characteristic coefficient value, the operating state characteristic coefficient value, the energy efficiency ratio characteristic coefficient value, the meteorological environment characteristic coefficient value and the building structure characteristic coefficient value transmitted by the BIPV data analysis module into the BIPV intelligent design calculation model to obtain the BIPV intelligent design rationality index value; the BIPV intelligent design calculation model is specifically expressed as: , Where S represents the calculated BIPV intelligent design rationality index value, represents the characteristic coefficient value of power generation performance calculated for the i-th time, represents the characteristic coefficient value of the operating state calculated for the i-th time, represents the energy efficiency ratio characteristic coefficient value calculated for the i-th time, represents the meteorological environment characteristic coefficient value calculated for the i-th time, Indicates the minimum value of the calculated meteorological environment characteristic coefficient, Indicates the maximum value of the calculated meteorological environment characteristic coefficient, represents the building structure characteristic coefficient value calculated for the i-th time, Indicates the minimum value of the calculated building structure characteristic coefficient, Indicates the calculated maximum value of the building structure characteristic coefficient; i means starting from the i-th number, and n means ending at the n-th number.

[0016] Preferably, the preset value of the BIPV intelligent design rationality index is marked as S def , when S>=S defWhen S is equal to or greater than the preset value of the BIPV intelligent design rationality index, a normal signal is issued, indicating that the BIPV intelligent design status is relatively reasonable; when S def When , it means that the BIPV intelligent design rationality index value is less than the preset value of the BIPV intelligent design rationality index, a warning signal will be issued to the relevant technical personnel, which indicates that the intelligent design status of the BIPV is unreasonable, and the BIPV intelligent design rationality index value will be recorded and uploaded to the database.

[0017] Technical effects and advantages of the present invention: 1. The present invention divides the target data into multiple fine batches through the data batch division module, which greatly enhances the pertinence and practicality of data organization and processing; through the BIPV data acquisition module, it collects power generation performance data, operating status data, energy efficiency ratio data, meteorological condition data and building structure data from multiple aspects, realizes multi-dimensional and multi-directional data acquisition, effectively avoids data one-sidedness, and builds a solid foundation for subsequent design optimization and in-depth analysis; 2. The present invention uses the BIPV data analysis module to conduct in-depth mining and intelligent analysis of the collected data, calculate the power generation performance characteristic coefficient value, the operating status characteristic coefficient value, the energy efficiency ratio characteristic coefficient value, the meteorological environment characteristic coefficient value and the building structure characteristic coefficient value, and intuitively reveals the potential advantages and improvement directions of the BIPV system in design and operation; 3. The present invention integrates and comprehensively evaluates the output results of the BIPV data analysis module through a comprehensive evaluation module, further improving the accuracy and practical value of the design optimization solution; through the real-time monitoring and real-time early warning feedback module, the analysis and optimization results are displayed in real time and an early warning function is provided, which is convenient for designers, engineers and management to instantly grasp the design and operation status of the BIPV system and realize efficient and intelligent design, optimization and management decisions. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a schematic diagram of the overall structure of the present invention. DETAILED DESCRIPTION

[0019] 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.

[0020] As attached Figure 1 ​A BIM-based BIPV intelligent design and optimization platform control system is shown, including a data batch division module, a BIPV data acquisition module, a BIPV data analysis module, a comprehensive evaluation module, and a real-time early warning feedback module.

[0021] The data batch division module is used to determine the data to be collected as target data, divide the target data into different batches in an equal time division manner, and mark them as 1, 2, ..., n in sequence; What needs to be specifically explained in this embodiment is that the equal time division method is used to divide each target data according to its characteristics through the background information management system, and each target data is divided into different collection times according to its real-time requirements, and a system database is established to store it.

[0022] The BIPV data acquisition module includes a system performance data acquisition unit and an environmental data acquisition unit, which are used to collect target data in real time and transmit the collected data to the data analysis module; the system performance data acquisition unit is used to collect power generation performance data, operating status data and energy efficiency data; the environmental data acquisition unit is used to collect meteorological condition data and building structure data.

[0023] In this embodiment, it is specifically necessary to explain that the power generation performance data includes the photovoltaic cell spectral response matching rate Sp, the system maximum power point tracking accuracy ratio St and the system power generation efficiency Se under partial shading conditions; the operating status data includes the inverter start-up response time Ir, the system hot spot effect ratio Hr and the system self-cleaning efficiency Sc; the energy efficiency ratio data includes the inverter conversion efficiency Ic, the cable transmission loss rate Cl and the system energy efficiency ratio Er.

[0024] The photovoltaic cell spectral response matching rate can evaluate the photovoltaic cell's ability to absorb and convert sunlight of different wavelengths, and is an important way to evaluate the utilization rate of light energy. The collection method is: use a spectral response tester, connect it to the output end of the photovoltaic cell, emit light of different wavelengths through the instrument, and measure the current output of the photovoltaic cell under different wavelengths of light, compare the measurement results with the standard solar spectrum, and calculate the photovoltaic cell spectral response matching rate; the system maximum power point tracking accuracy ratio can evaluate the efficiency of the BIPV system maximum power point tracking (MPPT) algorithm, and the collection method is: use a power meter and a simulated light source to simulate the output of the BIPV system under different lighting conditions, and adjust the intensity of the simulated light source to make the BIPV system work at different power points, and record the actual output power and theoretical maximum power point of the system. Then, the ratio of the actual output power to the theoretical maximum power point is calculated to obtain the maximum power point tracking accuracy ratio; the system power generation efficiency under the partial shading condition can intuitively reflect the influence of shading on the system power generation efficiency, and the collection method is: under simulated or actual partial shading conditions, use a sunshade or a sunshade net to simulate the shading situation, measure the power generation of the BIPV system under shading conditions, and compare it with the power generation under no shading conditions. By calculating the ratio between the power generation, the system power generation efficiency under partial shading conditions can be obtained; the inverter startup response time can reflect the speed from the inverter receiving the startup signal to the actual start of work, and its collection method is: sending a startup signal to the inverter, and using a high-precision timer to record the actual output time after the inverter receives the signal, and calculating the time difference to obtain the inverter startup response time; the system hot spot effect ratio can evaluate the decrease in power generation efficiency caused by local overheating of photovoltaic cells in the BIPV system, and its collection method is: using an infrared thermal imager to regularly scan the surface of the BIPV system, and using the infrared thermal imager to capture the temperature distribution image of the surface of the BIPV system, and using the image processing algorithm to identify the hot spot area, and calculate the ratio of the area of ​​the hot spot area to the area of ​​the entire BIPV system, and obtain The system hot spot effect ratio is obtained; the system self-cleaning efficiency can evaluate the effect of the BIPV system self-cleaning function on the improvement of power generation efficiency, and the collection method is as follows: by comparing the power generation data of the BIPV system before and after cleaning, the power generation data of the BIPV system is recorded as a baseline before cleaning, and then the BIPV system is cleaned and the power generation data is recorded again, and the improvement ratio of the power generation after cleaning relative to that before cleaning is calculated to obtain the system self-cleaning efficiency; the inverter conversion efficiency can reflect the conversion efficiency of the inverter under different loads, and the collection method is as follows: use a power meter and a variable load device to simulate the output of the inverter under different load conditions, and make the inverter work at different output power points by adjusting the load size of the variable load device, and record the input power and output power of the inverter.Then, the ratio of input power to output power is calculated to obtain the conversion efficiency under different loads; the cable transmission loss rate can evaluate the influence of cable length on the energy transmission loss of the BIPV system, and its collection method is: measure and record the transmission loss data on cables of different lengths, select a cable of known length as the test object, and then input a certain power signal at one end of the cable, and measure the received power signal strength at the other end, and calculate the difference between the input power and the received power to obtain the transmission loss of the cable section. Finally, the transmission loss data of cables of different lengths are analyzed by regression to obtain the transmission loss coefficient; the system energy efficiency ratio can evaluate the energy efficiency level of the BIPV system, and its collection method is: calculate by monitoring the power generation and total energy consumption data of the BIPV system to obtain the system energy efficiency ratio.

[0025] The meteorological condition data include the total horizontal radiation Ht, the atmospheric scattering rate As and the atmospheric transmittance At; the building structure data include the roof inclination angle Ra, the roof material reflectivity Rm and the building shadow shielding rate Bs.

[0026] The total horizontal radiation can measure the total solar radiation energy received on the horizontal plane, and is used to evaluate the potential power generation of the BIPV system. The collection method is: use a global radiation meter to monitor and record the total horizontal radiation for a long time on the roof of a building or in an open area; the atmospheric scattering rate can reflect the impact of scattering in the atmosphere on sunlight, and is used to more accurately calculate the actual received radiation of the BIPV system. The collection method is: use a scattered radiation meter to measure and record the ratio of scattered radiation to total radiation at the location of the building; the atmospheric transmittance can reflect the ability of the atmosphere to transmit sunlight, and is used to accurately calculate the power generation of the BIPV system. The collection method is: use a sun photometer or a spectrometer to measure and record the transmittance of sunlight of different wavelengths at the location of the building; the roof inclination angle can determine the installation inclination of the BIPV system to maximize the reception of solar radiation. The collection method is: use an inclinometer or an electronic compass to measure at different locations on the roof of the building and record the inclination angle; the roof material reflectivity can evaluate the degree of reflection of the roof material to sunlight and optimize the layout of the BIPV system. The collection method is: use a reflectometer to measure at different locations on the roof of the building. The reflectometer will emit a beam of light to the roof material and measure the intensity of the reflected light to calculate the reflectivity; the building shadow occlusion rate can analyze the impact of the obstructions around the building on the BIPV system and optimize the system layout. The acquisition method is: use drones or 3D scanning technology to obtain a three-dimensional image of the building and the surrounding environment. Then, through professional 3D modeling and analysis software, the image is processed to identify the shadow part of the building and calculate the shadow occlusion rate.

[0027] The BIPV data analysis module includes a system performance data analysis unit and an environmental data analysis unit; it is used to analyze the data transmitted by the BIPV data acquisition module and transmit the analysis results to the comprehensive data evaluation module; the system performance data analysis unit includes a power generation performance data analysis node, an operating status data analysis node and an energy efficiency ratio data analysis node; the environmental data analysis unit includes a meteorological condition data analysis node and a building structure data analysis node.

[0028] In this embodiment, it is specifically required to be explained that: the power generation performance data analysis node is used to establish a power generation performance data calculation model, and the power generation performance data transmitted by the BIPV data acquisition module is imported into the power generation performance data calculation model to obtain the power generation performance characteristic coefficient value; the power generation performance data calculation model is specifically expressed as: , in, Indicates the power generation performance characteristic coefficient value calculated for the i-th time, Sp i St represents the spectral response matching rate of the photovoltaic cell collected for the i-th time. i represents the system maximum power point tracking accuracy ratio for the i-th acquisition, Se i It represents the power generation efficiency of the system under partial shading conditions collected for the i-th time; i means starting from the i-th number, and n means ending at the n-th number.

[0029] In this embodiment, it is specifically required to be explained that: the operation status data analysis node is used to establish an operation status data calculation model, and the operation status data transmitted by the BIPV data acquisition module is imported into the operation status data calculation model to obtain the operation status characteristic coefficient value; the operation status data calculation model is specifically expressed as: , in, Indicates the characteristic coefficient value of the operating state calculated for the i-th time, Ir i Indicates the inverter startup response time collected for the i-th time, Hr i represents the system hot spot effect ratio of the i-th acquisition, Sc i It represents the system self-cleaning efficiency collected for the i-th time; i means starting from the i-th number, and n means ending at the n-th number.

[0030] In this embodiment, it is specifically required to be explained that: the energy efficiency ratio data analysis node is used to establish an energy efficiency ratio data calculation model, and the energy efficiency ratio data transmitted by the BIPV data acquisition module is imported into the energy efficiency ratio data calculation model to obtain the energy efficiency ratio characteristic coefficient value; the energy efficiency ratio data calculation model is specifically expressed as: , in, Indicates the energy efficiency ratio characteristic coefficient value calculated for the i-th time, Ic i represents the inverter startup response time collected for the i-th time, Cl i represents the cable transmission loss rate collected for the i-th time, Er i Represents the system energy efficiency ratio of the i-th collection.

[0031] In this embodiment, it is specifically required to be explained that: the meteorological condition data analysis node is used to establish a meteorological condition data calculation model, and the meteorological condition data transmitted by the BIPV data acquisition module is imported into the meteorological condition data calculation model to obtain the meteorological environment characteristic coefficient value; the meteorological condition data calculation model is specifically expressed as: , in, Indicates the meteorological environment characteristic coefficient value calculated for the i-th time, Ht i Indicates the total horizontal radiation collected for the i-th time, As i Indicates the atmospheric scattering rate collected for the i-th time, At i Indicates the atmospheric transmittance collected for the i-th time; i means starting from the i-th number, and n means ending at the n-th number.

[0032] In this embodiment, it is specifically required to be explained that: the building structure data analysis node is used to establish a building structure data calculation model, and the building structure data transmitted by the BIPV data acquisition module is imported into the building structure data calculation model to obtain the building structure characteristic coefficient value; the building structure data calculation model is specifically expressed as: , in, Represents the building structure characteristic coefficient value calculated for the i-th time, Ra i Indicates the roof inclination angle collected for the i-th time, Rm i Indicates the reflectivity of the roof material collected for the i-th time, Bs i The building shadow occlusion rate collected for the i-th time.

[0033] The comprehensive evaluation module includes a BIPV intelligent design analysis unit, which is used to analyze the data transmitted by the BIPV data analysis module and transmit the analysis results to the real-time early warning feedback module.

[0034] In this embodiment, it is specifically required to be explained that: the BIPV intelligent design analysis unit is used to establish a BIPV intelligent design calculation model, and the power generation performance characteristic coefficient value, the operating state characteristic coefficient value, the energy efficiency ratio characteristic coefficient value, the meteorological environment characteristic coefficient value and the building structure characteristic coefficient value transmitted by the BIPV data analysis module are imported into the BIPV intelligent design calculation model to obtain the BIPV intelligent design rationality index value; the BIPV intelligent design calculation model is specifically expressed as: , Where S represents the calculated BIPV intelligent design rationality index value, represents the characteristic coefficient value of power generation performance calculated for the i-th time, represents the characteristic coefficient value of the operating state calculated for the i-th time, represents the energy efficiency ratio characteristic coefficient value calculated for the i-th time, represents the meteorological environment characteristic coefficient value calculated for the i-th time, Indicates the minimum value of the calculated meteorological environment characteristic coefficient, Indicates the maximum value of the calculated meteorological environment characteristic coefficient, represents the building structure characteristic coefficient value calculated for the i-th time, Indicates the minimum value of the calculated building structure characteristic coefficient, Indicates the calculated maximum value of the building structure characteristic coefficient; i means starting from the i-th number, and n means ending at the n-th number.

[0035] The real-time early warning feedback module is used to establish a preset value of the BIPV intelligent design rationality index, judge the BIPV intelligent design rationality index value according to the preset value of the BIPV intelligent design rationality index, send a corresponding signal according to the judgment result and save the data in the database.

[0036] In this embodiment, it should be specifically noted that: the preset value of the BIPV intelligent design rationality index is marked as S def , when S>=S def When S is equal to or greater than the preset value of the BIPV intelligent design rationality index, a normal signal is issued, indicating that the BIPV intelligent design status is relatively reasonable; when S def When , it means that the BIPV intelligent design rationality index value is less than the preset value of the BIPV intelligent design rationality index, a warning signal will be issued to the relevant technical personnel, which indicates that the intelligent design status of the BIPV is unreasonable, and the BIPV intelligent design rationality index value will be recorded and uploaded to the database.

[0037] ​The present invention divides the target data into multiple fine batches through the data batch division module, which greatly enhances the pertinence and practicality of data organization and processing; through the BIPV data acquisition module, the power generation performance data, operation status data, energy efficiency ratio data, meteorological condition data and building structure data are collected in multiple aspects, realizing multi-dimensional and multi-directional data collection, effectively avoiding the one-sidedness of the data, and building a solid foundation for subsequent design optimization and in-depth analysis; through the BIPV data analysis module, the collected data is deeply mined and intelligently analyzed, and the power generation performance characteristic coefficient value, the operation status characteristic coefficient value, the energy efficiency ratio characteristic coefficient value, the meteorological environment characteristic coefficient value and the building structure characteristic coefficient value are calculated, which intuitively reveals the potential advantages and improvement directions of the BIPV system in design and operation; through the comprehensive evaluation module, the output results of the BIPV data analysis module are integrated and comprehensively evaluated, further improving the accuracy and practical value of the design optimization scheme; through the real-time monitoring and real-time early warning feedback module, the analysis and optimization results are displayed in real time and an early warning function is provided, which is convenient for designers, engineers and management to instantly grasp the design and operation status of the BIPV system and realize efficient and intelligent design, optimization and management decisions.

Claims

1. A BIM-based BIPV intelligent design and optimization platform control system, characterized in that: include: Data batch division module: used to determine the data to be collected as target data, divide the target data into different batches according to equal time division, and mark them as 1, 2, ..., n in sequence; BIPV data acquisition module: including system performance data acquisition unit and environmental data acquisition unit, used to collect target data in real time and transmit the collected data to the data analysis module; The system performance data acquisition unit is used to collect power generation performance data, operation status data and energy efficiency ratio data; The environmental data acquisition unit is used to collect meteorological condition data and building structure data; The BIPV data analysis module includes: a system performance data analysis unit and an environmental data analysis unit; used to analyze the data transmitted by the BIPV data acquisition module and transmit the analysis results to the comprehensive data evaluation module; the system performance data analysis unit includes a power generation performance data analysis node, an operation status data analysis node and an energy efficiency data analysis node; the environmental data analysis unit includes a meteorological condition data analysis node and a building structure data analysis node; Comprehensive evaluation module: including a BIPV intelligent design analysis unit, which is used to analyze the data transmitted by the BIPV data analysis module and transmit the analysis results to the real-time warning feedback module; Real-time early warning feedback module: used to establish a preset value of the BIPV intelligent design rationality index, judge the BIPV intelligent design rationality index value according to the preset value of the BIPV intelligent design rationality index, send a corresponding signal according to the judgment result and save the data in the database.

2. According to claim 1, a BIM-based BIPV intelligent design and optimization platform control system is characterized by: The power generation performance data include the photovoltaic cell spectral response matching rate Sp, the system maximum power point tracking accuracy ratio St and the system power generation efficiency Se under partial shading conditions; the operating status data include the inverter start-up response time Ir, the system hot spot effect ratio Hr and the system self-cleaning efficiency Sc; the energy efficiency ratio data include the inverter conversion efficiency Ic, the cable transmission loss rate Cl and the system energy efficiency ratio Er.

3. The BIM-based BIPV intelligent design and optimization platform control system according to claim 1 is characterized by: The meteorological condition data include the total horizontal radiation Ht, the atmospheric scattering rate As and the atmospheric transmittance At; the building structure data include the roof inclination angle Ra, the roof material reflectivity Rm and the building shadow shielding rate Bs.

4. The BIM-based BIPV intelligent design and optimization platform control system according to claim 1 is characterized by: The power generation performance data analysis node is used to establish a power generation performance data calculation model, import the power generation performance data transmitted by the BIPV data acquisition module into the power generation performance data calculation model, and obtain the power generation performance characteristic coefficient value; the power generation performance data calculation model is specifically expressed as: ， in, Indicates the power generation performance characteristic coefficient value calculated for the i-th time, Sp i St represents the spectral response matching rate of the photovoltaic cell collected for the i-th time. i It represents the system maximum power point tracking accuracy ratio of the i-th acquisition, Se i It represents the power generation efficiency of the system under partial shading conditions collected for the i-th time; i means starting from the i-th number, and n means ending at the n-th number.

5. The BIM-based BIPV intelligent design and optimization platform control system according to claim 1, characterized in that: The operation status data analysis node is used to establish an operation status data calculation model, import the operation status data transmitted by the BIPV data acquisition module into the operation status data calculation model, and obtain the operation status characteristic coefficient value; the operation status data calculation model is specifically expressed as: ， in, Indicates the characteristic coefficient value of the operating state calculated for the i-th time, Ir i Indicates the inverter startup response time collected for the i-th time, Hr i represents the system hot spot effect ratio of the i-th acquisition, Sc i It represents the system self-cleaning efficiency collected for the i-th time; i means starting from the i-th number, and n means ending at the n-th number.

6. The BIM-based BIPV intelligent design and optimization platform control system according to claim 1 is characterized by: The energy efficiency ratio data analysis node is used to establish an energy efficiency ratio data calculation model, import the energy efficiency ratio data transmitted by the BIPV data acquisition module into the energy efficiency ratio data calculation model, and obtain the energy efficiency ratio characteristic coefficient value; the energy efficiency ratio data calculation model is specifically expressed as: ， in, Indicates the energy efficiency ratio characteristic coefficient value calculated for the i-th time, Ic i represents the inverter startup response time collected for the i-th time, Cl i represents the cable transmission loss rate collected for the i-th time, Er i Represents the system energy efficiency ratio of the i-th collection.

7. The BIM-based BIPV intelligent design and optimization platform control system according to claim 1 is characterized by: The meteorological condition data analysis node is used to establish a meteorological condition data calculation model, import the meteorological condition data transmitted by the BIPV data acquisition module into the meteorological condition data calculation model, and obtain the meteorological environment characteristic coefficient value; the meteorological condition data calculation model is specifically expressed as: ， in, Indicates the meteorological environment characteristic coefficient value calculated for the i-th time, Ht i Indicates the total horizontal radiation collected for the i-th time, As i Indicates the atmospheric scattering rate collected for the i-th time, At i Indicates the atmospheric transmittance collected for the i-th time; i means starting from the i-th number, and n means ending at the n-th number.

8. The BIM-based BIPV intelligent design and optimization platform control system according to claim 1 is characterized by: The building structure data analysis node is used to establish a building structure data calculation model, import the building structure data transmitted by the BIPV data acquisition module into the building structure data calculation model, and obtain the building structure characteristic coefficient value; the building structure data calculation model is specifically expressed as: ， in, Represents the building structure characteristic coefficient value calculated for the i-th time, Ra i Indicates the roof inclination angle collected for the i-th time, Rm i Indicates the reflectivity of the roof material collected for the i-th time, Bs i The building shadow occlusion rate collected for the i-th time.

9. The BIM-based BIPV intelligent design and optimization platform control system according to claim 1, characterized in that: The BIPV intelligent design analysis unit is used to establish a BIPV intelligent design calculation model, and import the power generation performance characteristic coefficient value, operating state characteristic coefficient value, energy efficiency ratio characteristic coefficient value, meteorological environment characteristic coefficient value and building structure characteristic coefficient value transmitted by the BIPV data analysis module into the BIPV intelligent design calculation model to obtain the BIPV intelligent design rationality index value; the BIPV intelligent design calculation model is specifically expressed as: ， Where S represents the calculated BIPV intelligent design rationality index value, represents the characteristic coefficient value of power generation performance calculated for the i-th time, represents the characteristic coefficient value of the operating state calculated for the i-th time, represents the energy efficiency ratio characteristic coefficient value calculated for the i-th time, represents the meteorological environment characteristic coefficient value calculated for the i-th time, Indicates the minimum value of the calculated meteorological environment characteristic coefficient, Indicates the maximum value of the calculated meteorological environment characteristic coefficient, represents the building structure characteristic coefficient value calculated for the i-th time, Indicates the minimum value of the calculated building structure characteristic coefficient, Indicates the calculated maximum value of the building structure characteristic coefficient; i means starting from the i-th number, and n means ending at the n-th number.

10. The BIM-based BIPV intelligent design and optimization platform control system according to claim 1, characterized in that: The preset value of the BIPV intelligent design rationality index is marked as S def , when S>=S def When , it means that the BIPV intelligent design rationality index value is greater than or equal to the preset value of the BIPV intelligent design rationality index, and a normal signal is issued, which indicates that the BIPV intelligent design status is relatively reasonable; When S def When , it means that the BIPV intelligent design rationality index value is less than the preset value of the BIPV intelligent design rationality index, a warning signal will be issued to the relevant technical personnel, which indicates that the intelligent design status of the BIPV is unreasonable, and the BIPV intelligent design rationality index value will be recorded and uploaded to the database.​

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