Light-storage integrated collaborative optimization method and system applied to light-storage direct-flexible building

Abstract

The invention relates to the technical field of electric energy storage, and provides a light-storage integrated collaborative optimization method and system applied to a light-storage direct-flexible building. Obtaining construction information of a target building to construct a three-dimensional network; predicting irradiance distribution of the surface of the target building based on the cloud layer data and the three-dimensional network; dividing a high irradiation area and a low irradiation area according to the irradiance distribution and a set threshold value, and respectively arranging corresponding photovoltaic modules and power controllers in the high irradiation area and the low irradiation area; determining a net benefit function in the power generation and energy storage process based on the equipment parameters of the photovoltaic module, and determining the working power of the photovoltaic module according to the net benefit function; and based on the working power of the photovoltaic module, controlling the photovoltaic module to work through a power controller. By optimizing the layout and the working power of the photovoltaic module, the working state of the photovoltaic module is accurately controlled, the utilization rate of photovoltaic power generation is improved, the energy storage cost is reduced through intelligent control, and efficient utilization of energy is realized.

Description

Technical Field

[0001] The present invention belongs to the field of electric energy storage technology, and specifically relates to a photovoltaic-storage integrated collaborative optimization method and system applied to a photovoltaic-storage direct-flexible building. Background Art

[0002] As a new type of building energy system, the photovoltaic, storage, direct and flexible building is an important means to achieve energy conservation and emission reduction in the building sector and promote energy transformation. The photovoltaic, storage, direct and flexible building can interact with the municipal power grid to achieve two-way flow of electric energy and intelligent scheduling. Through the coordinated optimization of photovoltaic and storage integration, the relationship between building electricity consumption and grid power supply can be better coordinated, and the stability and security of the grid can be improved. The photovoltaic and storage integrated coordinated optimization method can achieve the organic combination of photovoltaic and energy storage systems and improve the utilization rate and stability of photovoltaic power generation. The photovoltaic, storage, direct and flexible building can also participate in the demand response of the grid, adjust the working strategy according to the dispatch instructions of the grid, and provide auxiliary services to the grid. At present, the technical maturity of the photovoltaic, storage, direct and flexible system still needs to be improved, especially in photovoltaic and energy storage. The control accuracy of photovoltaic modules is low, and the balance between photovoltaic and energy storage cannot be achieved, resulting in low photovoltaic energy efficiency.

[0003] In the prior art, Chinese patent CN114709878A discloses a photovoltaic storage coordinated configuration method, equipment and medium for a photovoltaic storage direct and flexible building. It includes: obtaining the photovoltaic output curve of the photovoltaic storage direct and flexible building; determining the energy storage configuration target specified by the user; selecting the load curve according to the energy storage configuration target; and configuring the photovoltaic energy storage capacity and energy storage charging and discharging power in the photovoltaic storage direct and flexible building according to the photovoltaic output curve and the load curve. By configuring the photovoltaic power generation curve of the photovoltaic storage direct and flexible building and the load curve actually obtained according to the energy storage configuration target, the actual power generation status and electricity demand of the photovoltaic storage direct and flexible building are combined, and the waste of energy storage capacity is avoided when configuring the photovoltaic power generation, the economy of the photovoltaic storage direct and flexible building is improved, and the rational use of renewable resources is achieved.

[0004] However, this method has the following limitations: 1. It relies solely on the photovoltaic output curve and load curve for configuration, completely ignoring the complex three-dimensional geometry of the building itself and the differences in illumination on each surface due to orientation, curvature, and shading. As a result, it can only provide a rough estimate when calculating available light resources, and cannot accurately reflect the true power generation potential of different parts; 2. The existing configuration scheme lacks classification and processing of the differences in light intensity in different areas of the building surface. PV panels and energy storage devices can only be uniformly deployed in a "one-size-fits-all" manner. It cannot fully utilize the performance of high-efficiency panels in areas with more abundant light, and it is easy to waste investment in areas with insufficient light, reducing the economic return of the overall system; 3. This method focuses on capacity matching and lacks a dynamic power scheduling mechanism and real-time optimization methods based on equipment operating characteristics. It cannot meet electricity demand while taking into account the cycle life and operating costs of the energy storage system. As a result, the energy storage equipment is prone to overcharging and discharging, premature life degradation, and it is difficult to achieve continuous maximization of the system's economic benefits. Summary of the Invention

[0005] The purpose of the present invention is to overcome the defects of the above-mentioned prior art and to provide a photovoltaic-storage integrated collaborative optimization method and system for photovoltaic-storage direct-flexible buildings.

[0006] The purpose of the present invention can be achieved by the following technical solutions: On the one hand, the present invention provides a photovoltaic-storage integrated collaborative optimization method applied to a photovoltaic-storage direct-flexible building, comprising the following steps: Acquiring structural information of a target building, and constructing a three-dimensional network based on the structural information; Acquire cloud data through satellite meteorology, and predict the irradiance distribution on the surface of the target building within a preset time based on the cloud data and the three-dimensional network; Dividing the high irradiation area and the low irradiation area according to the irradiance distribution and the set threshold, and arranging corresponding photovoltaic modules and power controllers in the high irradiation area and the low irradiation area respectively; Determining a net benefit function in a power generation and energy storage process based on device parameters of the photovoltaic assembly, and determining an operating power of the photovoltaic assembly according to the net benefit function; Based on the working power of the photovoltaic assembly, the operation of the photovoltaic assembly is controlled by the power controller.

[0007] Furthermore, the step of obtaining structural information of the target building and constructing a three-dimensional network based on the structural information specifically includes: Acquiring structural information of a target building, wherein the structural information includes position and orientation information and surface parameters of the target building; Determine the local curvature of the target building at each location based on the surface parameters , the formula is: in, Represents the coordinate information of the building surface, Represents the surface parameters corresponding to the points of interest extracted from the building surface, Indicates the coordinates of the point of interest, Indicates that the target building is The local curvature at Determine the sun direction vector corresponding to each moment based on the position and orientation information , based on the sun direction vector and the local curvature , determine the cosine value of the angle between the sun's rays and the surface normal vector as the illumination angle parameter : in, Is the illumination angle parameter, which indicates the angle between the sun's rays and the target building. The surface normal vector at time t The cosine of the angle between represents the partial derivative operation, express t The sun direction vector corresponding to the sun's position at the moment, t Indicates time, represents the magnitude of the sun direction vector; The local curvature and illumination angle parameters In combination, a grid modeling algorithm is used to generate a three-dimensional network model that includes both the building geometry and dynamic lighting characteristics to obtain a three-dimensional network.

[0008] Furthermore, the sun direction vector corresponding to each moment is determined according to the position orientation information. , specifically including: Obtain the location and orientation information of the target building, including the latitude B and longitude L of the target building; Calculate solar time based on the longitude L: in, For solar time, is the local time of the target building, is the standard longitude, When is the equation; Based on solar time Calculating the solar hour angle , and its calculation formula is: Based on the latitude B, the solar hour angle , calculate the solar altitude angle h(t) and the solar azimuth angle , and its calculation formula is: in, Indicates time t The solar declination angle, 、 Respectively indicate time t The solar altitude angle and solar azimuth angle; Based on the sun altitude angle Azimuth angle to the sun , construct the sun direction vector : in, express t The sun direction vector corresponding to the sun's position at that moment.

[0009] Furthermore, the cloud data is obtained through satellite meteorology, and based on the cloud data and the three-dimensional network, the irradiance distribution on the surface of the target building within a preset time is predicted, which specifically includes: Obtain satellite meteorological data, including irradiance reference values ​​in a cloudless state , cloud properties of solar radiation absorption and transmission, including absorption coefficient , transmission coefficient and scattering coefficient ; Based on the irradiance reference value , attribute coefficients and the three-dimensional network model constructed by the target building, combined with the local curvature at each location and illumination angle parameters , build the irradiance model of the building surface and determine the t Any position on the target building surface Irradiance at : in, Indicates t Target building surface at all times The corresponding irradiance at represents the exponential operation of a natural constant, 、 Represent the roof height of the target building and the height of the cloud top, respectively. 、 Respectively indicate the height The cloud absorption coefficient and transmission coefficient at represents the scattering coefficient of atmospheric molecules, Indicates that the target building is The local curvature at Is the illumination angle parameter, which indicates the angle between the sun's rays and the target building. The surface normal vector at time t The cosine of the angle between Based on the irradiance model, the irradiance corresponding to each position of the target building at each time point is determined to form the irradiance distribution on the surface of the target building within the preset time.

[0010] Furthermore, dividing the high irradiation area and the low irradiation area according to the irradiance distribution and the set threshold value specifically includes: Get the irradiance distribution at each location on the target building surface within a preset time , and perform time domain averaging on the irradiance to obtain the average irradiance value at each location: in, Indicates that within the preset time period T, the target building The average irradiance at is the total duration of the preset time period, Indicates t Target building surface at all times The corresponding irradiance at Setting the irradiance threshold ,when When the target building The area is classified as a high radiation area; When the target building The area is classified as low radiation zone.

[0011] Furthermore, the corresponding photovoltaic modules and power controllers are respectively arranged in the high irradiation area and the low irradiation area, specifically including: According to the area and average irradiance of the high irradiation zone, high-efficiency photovoltaic modules are arranged, wherein the high-efficiency photovoltaic modules are equipped with high-capacity lithium batteries as energy storage units and are equipped with corresponding power controllers; According to the area and average irradiance of the low irradiation zone, photovoltaic modules with strong adaptability and low cost are arranged, supercapacitors are configured as fast-response energy storage devices, and corresponding power controllers are equipped.

[0012] Furthermore, the determining of the net benefit function in the power generation and energy storage process based on the device parameters of the photovoltaic module specifically includes: Determine the power generation utility function of the photovoltaic module based on the device parameters of the photovoltaic module : in, i Indicates the logo of photovoltaic modules. Represents photovoltaic modules i Power, Represents photovoltaic modules i Unit power generation profit coefficient; Represents photovoltaic modules i The marginal cost coefficient of power generation; Determine the energy storage cost function of the photovoltaic module based on the device parameters of the photovoltaic module : in, Represents photovoltaic modules i Energy storage cost coefficient; Represents photovoltaic modules i Power sensitivity coefficient; Determine the photovoltaic components based on the power generation utility function and the energy storage cost function i At power The net benefit function : in, is the Lagrange multiplier; n Indicates the total number of PV panels; Represents the total load demand of the building's electrical system.

[0013] Furthermore, determining the operating power of the photovoltaic module according to the net benefit function specifically includes: Step S401: Initialize the photovoltaic module working power vector and Lagrange multipliers ,in Indicates that the photovoltaic module in the 0th iteration i Power; Step S402: Based on the current power vector , according to the current power vector and the equipment parameters of each photovoltaic module, through the net benefit function Calculate the gradient of the net benefit function for each photovoltaic module ; Step S403: Update the photovoltaic module operating power vector using an iterative optimization algorithm: in, is the preset learning rate, represents the partial derivative of the net benefit function with respect to power; Step S404: Adjust the updated power value according to the power constraint condition: in, 、 Photovoltaic modules i The minimum and maximum power limits allowed; Step S405: Determine the iteration termination condition. If the change in the net benefit function value is If it is less than the preset threshold, the iteration is stopped, the optimal power vector is output, and the operating power of each photovoltaic module is determined; otherwise, k=k+1 is set and the process returns to step S402 to continue the iteration.

[0014] Furthermore, controlling the operation of the photovoltaic assembly by the power controller based on the operating power of the photovoltaic assembly specifically includes: generating a configuration instruction based on the operating power of the photovoltaic module; sending the configuration instruction to the power controller via a communication interface; The power controller receives and analyzes the configuration instruction and controls the operation of the photovoltaic assembly.

[0015] Another aspect of the present invention provides a photovoltaic-storage integrated collaborative optimization system for a photovoltaic-storage direct-flexible building, comprising: an acquisition unit, configured to acquire structural information of a target building and construct a three-dimensional network based on the structural information; an irradiance unit, configured to obtain cloud data through satellite meteorology, and predict the irradiance distribution on the surface of the target building within a preset time based on the cloud data and the three-dimensional network; a layout unit, configured to divide the area into a high irradiation area and a low irradiation area according to the irradiance distribution and a set threshold, and to layout corresponding photovoltaic modules and power controllers in the high irradiation area and the low irradiation area, respectively; an efficiency unit, configured to determine a net benefit function in a power generation and energy storage process based on device parameters of the photovoltaic assembly, and determine an operating power of the photovoltaic assembly according to the net benefit function; A control unit is used to control the operation of the photovoltaic assembly through the power controller based on the operating power of the photovoltaic assembly.

[0016] Compared with the prior art, the present invention has the following advantages: (1) The present invention divides the building surface into high-irradiation areas and low-irradiation areas based on the predicted irradiance distribution and the set threshold, which helps to optimize the layout of photovoltaic modules so that they can make full use of light resources. High-efficiency photovoltaic modules are deployed in high-irradiation areas to maximize the use of solar radiation; in low-irradiation areas, less efficient but lower-cost photovoltaic modules are used, or combined with other energy utilization methods. This differentiated layout not only improves the overall efficiency of photovoltaic power generation, but also reduces system costs. At the same time, corresponding power controllers are deployed in each area to achieve precise control of the working status of the photovoltaic modules, reducing the risk of damage to the photovoltaic modules due to poor lighting conditions and improving the power generation efficiency and energy utilization of the photovoltaic modules.

[0017] (2) The present invention uses a grid modeling algorithm to construct a three-dimensional network model that includes both building geometry and dynamic lighting characteristics, making the prediction of the incident angle, shadow obstruction, and light intensity of various parts of the building more accurate. Through this refined modeling, it is possible to distinguish the differences in illumination caused by different curvatures and orientations in the simulation, significantly improving the resolution and reliability of irradiance prediction, and providing reliable data support for subsequent photovoltaic module selection and high and low irradiation zone division, no longer relying on simplified plane assumptions or empirical coefficients. Improving the accuracy of the high and low irradiation zone division can further improve the overall efficiency of photovoltaic power generation and reduce system costs.

[0018] (3) By constructing an irradiance model, the present invention overcomes the problem of low illumination prediction accuracy in complex weather scenarios when relying solely on sunny day irradiance constants or empirical correction coefficients. This allows the illumination intensity of various areas on the building surface to be accurately quantified under adverse meteorological conditions such as cloudy or overcast days, providing reliable input data for subsequent component layout and power optimization.

[0019] (4) After obtaining high-resolution time-varying irradiance data, the present invention performs time-domain averaging on the irradiance within a preset time period, calculates the average irradiance at each location, and compares this average irradiance with a preset threshold value to achieve accurate division between high-irradiation and low-irradiation areas. Through this regionalized processing based on high-precision dynamic irradiance, high-efficiency or economical photovoltaic modules and corresponding energy storage devices can be selected in a targeted manner under different irradiation conditions. This not only improves the rationality of photovoltaic module layout and power generation efficiency, but also avoids excessive investment in low-efficiency areas, effectively reducing the total system cost and improving overall economic efficiency.

[0020] (5) The present invention solves the problem in the prior art that, by setting up different photovoltaic modules in high and low irradiation zones, the use of modules and energy storage strategies of the same specifications can easily lead to the inability to fully release the production capacity of modules in strong light zones, a low return on investment for modules in weak light zones, and a sharp drop in the life of large-capacity batteries under frequent shallow cycles. The regional configuration of the present invention is optimized for this situation: the combination of high-efficiency modules and lithium batteries in high-irradiation zones can efficiently collect and store abundant peak power, while the supercapacitors with accelerated response of economical modules in low-irradiation zones can quickly smooth out power generation fluctuations and reduce the number of deep charge and discharge times of the battery. This not only greatly improves the overall utilization rate of photovoltaic power generation and the cycle life of the energy storage system, but also significantly reduces the initial cost of the system through an investment strategy tailored to local conditions, and maintains the stability and reliability of power output under changing meteorological conditions.

[0021] (6) Based on the conversion efficiency, cost coefficient, life parameters of photovoltaic modules and the charging and discharging efficiency of energy storage systems, the present invention establishes a power generation utility function and an energy storage cost function, and uses this to construct a comprehensive net benefit function. The economic benefits and costs under different power outputs are quantitatively compared, and the optimal operating power of each module is determined by solving the maximum value of this function. This method overcomes the drawbacks of the traditional method of simply setting power according to peak value or experience, and achieves a dynamic balance between power generation benefits and energy storage costs. It can fully tap the potential of photovoltaic power generation and avoid the accelerated aging of energy storage equipment caused by excessive charging and discharging, thereby greatly improving the overall economic benefits and equipment life of the system. It ensures that the photovoltaic system can operate stably and meet energy needs. It reduces the risk of energy waste and equipment failure caused by improper control, achieves precise control of the working state of photovoltaic modules, and improves the stability and reliability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 A flowchart of a photovoltaic-storage integrated collaborative optimization method applied to a photovoltaic-storage direct-flexible building in one embodiment of the present application is schematically shown.

[0023] Figure 2 The flowchart of constructing a three-dimensional network in one embodiment of the present application is schematically shown.

[0024] Figure 3 A schematic diagram of a photovoltaic-storage integrated collaborative optimization system applied to a photovoltaic-storage direct-flexible building in one embodiment of the present application is shown schematically.

[0025] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing an electronic device according to an embodiment of the present application is shown. DETAILED DESCRIPTION

[0026] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0027] Example 1: The implementation details of the technical solution of this application are described in detail below: Figure 1 The flowchart of the photovoltaic storage integrated collaborative optimization method applied to photovoltaic storage direct-flexible building according to one embodiment of the present application is shown. Figure 1 As shown, the photovoltaic storage integrated collaborative optimization method applied to the photovoltaic storage direct-flexible building includes at least steps S110 to S150, which are described in detail as follows: In step S110 , structural information of a target building is acquired, and a three-dimensional network is constructed based on the structural information.

[0028] In this application, structural information of a target building is acquired through sensors or data files. This information includes, but is not limited to, key data such as the building's geometric dimensions, location and orientation, and surface parameters. This information is then processed by software tools using it as input to construct a 3D network model that accurately reflects the target building's spatial structure and appearance.

[0029] like Figure 2 As shown, in one embodiment of the present application, obtaining structural information of a target building and constructing a three-dimensional network based on the structural information include: S210, acquiring structural information of a target building, wherein the structural information includes position and orientation information and surface parameters of the target building; S220, determining the local curvature corresponding to each position of the target building based on the curved surface parameters; S230, determining an illumination angle parameter based on the position orientation information and the local curvature; S240: Modeling is performed based on the local curvature and the illumination angle parameter to generate a three-dimensional network corresponding to the target building.

[0030] In one embodiment of the present application, structural information of a target building is obtained, wherein the structural information includes position and orientation information and surface parameters of the target building.

[0031] After obtaining the structural information, the local curvature of the target building at each location is determined based on the surface parameters. for: in, Represents the coordinate information of the building surface, Represents the surface parameters corresponding to the points of interest extracted from the building surface, i,j Indicates the coordinates of the point of interest.

[0032] Then, the sun direction vector corresponding to each moment is determined according to the position and orientation information. Based on the sun direction vector and the local curvature, the cosine value corresponding to the angle between the sun's rays and the surface normal vector is determined as the illumination angle parameter: in, represents the partial derivative operation, express t The sun direction vector corresponding to the sun's position at the moment, t Indicates time.

[0033] The sun direction vector corresponding to each moment is determined according to the position and orientation information, specifically including: Obtain the location and orientation information of the target building, including the latitude B and longitude L of the target building; Calculate solar time based on the longitude L: in, For solar time, is the local time of the target building, is the standard longitude, When is the equation; Based on solar time Calculating the solar hour angle , and its calculation formula is: Based on the latitude B, the solar hour angle , calculate the solar altitude angle h(t) and the solar azimuth angle , and its calculation formula is: in, Indicates time t The solar declination angle, 、 Respectively indicate time t The solar altitude angle and solar azimuth angle; Based on the sun altitude angle Azimuth angle to the sun , construct the sun direction vector : in, express t The sun direction vector corresponding to the sun's position at that moment.

[0034] After determining the local curvature and illumination angle parameters of the target building, modeling is performed based on these parameters. The local curvature and illumination angle are combined to generate a three-dimensional network corresponding to the target building. The three-dimensional network modeled in this embodiment includes both the building's structural information and the illumination angle conditions corresponding to different times.

[0035] This process, by acquiring structural information about the target building and constructing a 3D network based on this information, accurately simulates the building's geometry and lighting conditions. This provides a solid foundation for subsequent irradiance prediction and PV panel layout, ensuring the effectiveness of the entire optimization process.

[0036] In step S120, cloud data is acquired through satellite meteorology, and based on the cloud data and the three-dimensional network, the irradiance distribution on the target building surface within a preset time is predicted.

[0037] In this embodiment, satellite cloud data is acquired and analyzed. This data details key information such as cloud distribution, thickness, and movement speed. Subsequently, a lighting simulation is run using this cloud data and a previously constructed 3D network model of the target building. This simulation takes into account factors such as the sun's position, cloud obstruction, and the building's surface geometry and orientation. The simulation then predicts the irradiance distribution on each surface of the target building within a preset time period, providing accurate lighting prediction data for subsequent optimized photovoltaic module configuration.

[0038] In one embodiment of the present application, cloud data is obtained through satellite meteorology, and based on the cloud data and the three-dimensional network, the irradiance distribution of each interior of the target building within a preset time is predicted, including: Obtain cloud data through satellite meteorology, the cloud data including the irradiance baseline value in a cloudless state and the attribute coefficients of cloud layer for solar radiation absorption and transmission; Based on the irradiance reference value and the three-dimensional network, combined with the attribute coefficients of cloud layer to solar radiation absorption and transmission, an irradiance model of the building surface is generated; The irradiance distribution on the target building surface within a preset time is determined based on the irradiance model.

[0039] In one embodiment of the present application, cloud data is obtained through satellite meteorology, including obtaining the irradiance baseline value in a cloudless state from historical meteorological data. Optionally, the solar irradiance constant outside the atmosphere is used in this embodiment. As a benchmark value of irradiance, it is used to characterize the standard solar radiation intensity outside the Earth's atmosphere.

[0040] Then, based on the irradiance reference value and the three-dimensional network, that is, the attribute coefficients of cloud layer to solar radiation absorption and transmission, an irradiance model of the building surface is generated. for: in, Indicates t Moment building surface ( x,y ) corresponds to the irradiance, Indicates the irradiance reference value, represents the exponential operation of a natural constant, 、 Represent the building height and cloud top height respectively, represents the integral variable; and Represents the attribute coefficient of cloud layer to solar radiation absorption and transmission, where It represents the absorption coefficient of the cloud layer, which indicates the cloud layer's ability to absorb solar radiation; represents the scattering coefficient, which comes from the scattering effect of atmospheric molecules on shortwave radiation; It represents the transmission coefficient of the cloud layer, which is used to characterize the proportion of radiation allowed to pass through the cloud layer.

[0041] After constructing the radiation model of the building surface, the irradiance corresponding to each position of the building at each time point is determined based on the irradiance model. By combining this information, the irradiance distribution of the target building surface within the preset time can be obtained.

[0042] The above process, by combining historical meteorological data, three-dimensional networks and the absorption and transmission properties of clouds to solar radiation, accurately predicts the irradiance distribution on each surface of the target building within a preset time. The irradiance distribution reflects the power generation potential of photovoltaic modules in different time periods and locations, thereby improving the accuracy and real-time performance of irradiance prediction.

[0043] In step S130, a high irradiation area and a low irradiation area are divided according to the irradiance distribution and the set threshold, and corresponding photovoltaic modules and power controllers are respectively arranged in the high irradiation area and the low irradiation area.

[0044] In this embodiment, the irradiance value at each location is traversed and, based on its relative magnitude to a threshold, the surface of the target building is divided into high-irradiation and low-irradiation areas. Subsequently, a layout plan is automatically generated based on the division of these areas and the layout rules for photovoltaic modules and power controllers. In high-irradiation areas, it is recommended to install high-efficiency photovoltaic modules and configure corresponding power controllers to maximize energy output; in low-irradiation areas, a more adaptable or cost-effective module configuration may be installed, while the power controller parameters may be adjusted to optimize energy utilization.

[0045] In one embodiment of the present application, according to the irradiance distribution and the set threshold, a high irradiation area and a low irradiation area are divided, and corresponding photovoltaic modules and power controllers are respectively arranged in the high irradiation area and the low irradiation area, including: Get the irradiance distribution at each location on the target building surface within a preset time , and perform time domain averaging on the irradiance to obtain the average irradiance value at each location: in, Indicates that within the preset time period T, the target building The average irradiance at is the total duration of the preset time period, Indicates t Target building surface at all times The corresponding irradiance at Setting the irradiance threshold ,when When the target building The area is classified as a high radiation area; When the target building The area is classified as low radiation zone.

[0046] Corresponding photovoltaic modules and power controllers are respectively arranged in the high irradiation area and the low irradiation area.

[0047] In one embodiment of the present application, based on the irradiance corresponding to each position in the irradiance distribution, when the irradiance corresponding to the position is greater than or equal to a set threshold, the position is divided into a high irradiation area; when the irradiance corresponding to the position is less than the set threshold, the position is divided into a low irradiation area.

[0048] Afterwards, the results of the region division into high irradiation area and low irradiation area are stored through corresponding data structures, such as a two-dimensional array or an image mask.

[0049] Based on the delineation of high and low irradiation zones, a PV module layout plan is generated. Specifically, the number, type, arrangement, and installation location of PV modules can be determined based on information such as irradiance. Furthermore, factors such as the spacing between PV modules, shadowing, orientation, and tilt angle can be considered to optimize power generation efficiency.

[0050] For example, because high-irradiation areas generate more energy and are suitable for storing large amounts of electricity, large-capacity lithium batteries can be deployed in these areas. Meanwhile, low-irradiation areas experience large fluctuations and require fast-response power smoothing, requiring supercapacitors that charge and discharge quickly. This approach optimizes the configuration of PV modules in different areas, balancing module lifespan with energy efficiency and cost-effectiveness.

[0051] For example, after the illumination angle parameters are calculated through the above process, the illumination angle can be maximized so that the surface normal vector of the photovoltaic module is aligned with the direction of the sun as much as possible, thereby improving the energy capture efficiency of the photovoltaic module.

[0052] At the same time, based on the division results of high and low irradiation areas, a corresponding power controller layout plan is generated. In this embodiment, the power controller is used to regulate the output power of the photovoltaic system. The power controller layout plan specifically includes factors such as the type, number, installation location, and connection method of the power controller with other equipment, and ensures that the power controller can operate stably under different irradiation conditions.

[0053] The above process divides the building surface into high-irradiation and low-irradiation areas based on the predicted irradiance distribution and set thresholds, helping to optimize the placement of photovoltaic modules so that they can fully utilize sunlight resources. High-efficiency photovoltaic modules are deployed in high-irradiation areas to maximize the use of solar radiation; low-irradiation areas use less efficient but lower-cost photovoltaic modules, or combine them with other energy utilization methods. This differentiated layout not only improves the overall efficiency of photovoltaic power generation but also reduces system costs. At the same time, a corresponding power controller is deployed in each area to achieve precise control of the operating status of the photovoltaic modules, reducing the risk of damage to the modules due to poor lighting conditions and improving the power generation efficiency and energy utilization rate of the photovoltaic modules.

[0054] In step S140 , a net benefit function in the power generation and energy storage process is determined based on the device parameters of the photovoltaic assembly, and the operating power of the photovoltaic assembly is determined according to the net benefit function.

[0055] In this example, a power generation utility function and an energy storage cost function are constructed based on PV module parameters such as conversion efficiency, cost, and lifespan, as well as the capacity and charge / discharge efficiency of the energy storage system. This function then synthesizes a net benefit function that comprehensively considers both power generation revenue and energy storage costs. While meeting energy requirements and system constraints, an iterative search is performed to find the optimal PV module operating power configuration that maximizes the net benefit function, thereby maximizing the economic benefits of the PV system.

[0056] In one embodiment of the present application, determining a net benefit function in a power generation and energy storage process based on device parameters of the photovoltaic assembly, and determining the operating power of the photovoltaic assembly according to the net benefit function includes: Determining a power generation utility function and an energy storage cost function of the photovoltaic assembly based on equipment parameters of the photovoltaic assembly; Determining a net benefit function based on the power generation utility function and the energy storage cost function; The operating power of the photovoltaic assembly is determined based on the net benefit function.

[0057] In one embodiment of the present application, based on the device parameters of the photovoltaic module, the power generation utility function of the photovoltaic module is determined. for: in, i Indicates the logo of photovoltaic modules. Represents photovoltaic modules i Power, Represents photovoltaic modules i Unit power generation revenue coefficient, in yuan / kilowatt-hour (yuan / kWh), is used to quantify the direct economic benefits brought by unit power generation; Represents photovoltaic modules i The marginal cost coefficient of power generation is derived through historical data analysis and is expressed in yuan / kilowatt-hour² (yuan / kWh²). It is used to curb over-allocation of power and avoid diminishing returns due to excessive power.

[0058] At the same time, based on the equipment parameters of the photovoltaic module, the energy storage cost function of the photovoltaic module is determined for: in, Represents photovoltaic modules i The energy storage cost coefficient, expressed in RMB, can be determined by the initial purchase cost, maintenance cost, and life cycle cost of the PV modules to reflect the fixed cost of the energy storage system; Represents photovoltaic modules iThe power sensitivity coefficient is used to dynamically quantify the exponential impact of increasing the power of photovoltaic modules on costs, such as the negative impact of power increase on the life and operating costs of energy storage systems.

[0059] Then, the photovoltaic components are determined according to the power generation utility function and the energy storage cost function. i At power The net benefit function for: in, is the Lagrange multiplier, with the unit being yuan / kilowatt-hour (yuan / kWh); n Indicates the total number of PV panels; Indicates the total load demand of the building's electrical system in kilowatts (kW).

[0060] After determining the net benefit function, the maximum value of the net benefit function is obtained. The power corresponding to the maximum value of the net benefit function is the operating power of the photovoltaic module, which includes: Step S401: Initialize the photovoltaic module working power vector and Lagrange multipliers ,in Indicates that the photovoltaic module in the 0th iteration i Power; Step S402: Based on the current power vector , according to the current power vector and the equipment parameters of each photovoltaic module, through the net benefit function Calculate the gradient of the net benefit function for each photovoltaic module ; Step S403: Update the photovoltaic module operating power vector using an iterative optimization algorithm: in, is the preset learning rate, represents the partial derivative of the net benefit function with respect to power; Step S404: Adjust the updated power value according to the power constraint condition: in, 、 Photovoltaic modules i The minimum and maximum power limits allowed; Step S405: Determine the iteration termination condition. If the change in the net benefit function value is When it is less than the preset threshold ε, the iteration is stopped, the optimal power vector is output, and the operating power of each photovoltaic module is determined; otherwise, let k=k+1 and return to step S402 to continue the iteration, where 、 They represent the system net benefit function values ​​calculated in the kth and k-1th iterations respectively.

[0061] The above process determines the power generation utility function and energy storage cost function based on the PV module equipment parameters, and then constructs a net benefit function, which helps evaluate the economic benefits of the PV system at different operating powers. By maximizing the net benefit function, the optimal operating power of the PV modules can be determined. This ensures that the PV system achieves maximum economic benefits while meeting energy requirements. This reduces energy waste and equipment loss caused by inappropriate operating power, thereby improving the economic benefits and energy efficiency of the PV system.

[0062] In step S150 , the photovoltaic assembly is controlled to operate by the power controller based on the operating power of the photovoltaic assembly.

[0063] In this embodiment, after determining the operating power of the PV panels, corresponding control instructions are generated and sent to the power controller via a communication interface. Upon receiving the instructions, the power controller uses a built-in parsing algorithm to convert them into specific control signals, thereby precisely adjusting the operating state of the PV panels, such as voltage and current, to ensure that they generate power at the specified power.

[0064] In one embodiment of the present application, controlling the operation of the photovoltaic assembly by the power controller based on the operating power of the photovoltaic assembly includes: generating a configuration instruction based on the operating power of the photovoltaic module; sending the configuration instruction to the power controller via a communication interface; The power controller receives and analyzes the configuration instruction and controls the operation of the photovoltaic assembly.

[0065] In one embodiment of the present application, after determining the operating power of a photovoltaic module, configuration instructions are generated for a power controller based on the operating power. The configuration instructions include information such as adjusting the operating power of the photovoltaic module. A communication connection is established with the power controller via a communication interface, and the configuration instructions are sent to the power controller in a specific communication protocol format. Upon receiving the instructions, the power controller interprets and executes the corresponding control operations, subsequently controlling the photovoltaic module to operate at the operating power.

[0066] The above process generates configuration instructions based on the PV module's operating power and sends them to the power controller via a communication interface, enabling remote and precise control of the PV module's operating status. The power controller receives and interprets the configuration instructions, controlling the PV modules to generate power at the specified operating power, ensuring stable operation of the PV system and meeting energy requirements. This reduces the risk of energy waste and equipment failure caused by improper control, achieves precise control of the PV module's operating status, and improves system stability and reliability.

[0067] In one embodiment of the present application, after controlling the photovoltaic assembly to operate by the power controller based on the operating power of the photovoltaic assembly, the method further includes: Obtain the working parameters of photovoltaic modules; The operating parameters are displayed on a display of the control platform.

[0068] In one embodiment of the present application, a data acquisition module acquires real-time operating parameters from sensors or data acquisition interfaces on photovoltaic modules. The data acquisition module connects to the photovoltaic modules via a wired or wireless connection to ensure real-time and accurate data. The data acquisition module reads key operating parameters from the photovoltaic modules, including but not limited to voltage, current, power, and temperature.

[0069] The collected operating parameters are transmitted to the control platform via a data transmission channel (such as a local area network, wide area network, or serial communication). After receiving the data, the control platform performs data analysis and processing, converting the raw data into a format that can be used for display.

[0070] Optionally, the processed operating parameters are displayed to the user in a graphical or textual manner, and the operating states of different time scales, different parameters or different photovoltaic modules are displayed through multiple interfaces or views.

[0071] Optionally, depending on the control platform configuration and user preferences, the operating parameters of the PV modules can be displayed in real time on the display. This display can be in the form of numerical values, charts, and alarm indications, allowing users to intuitively understand the operating status of the PV modules.

[0072] The above process, by acquiring real-time operating parameters of PV modules, provides data support for system monitoring and maintenance. The control platform's display intuitively displays these parameters to users, enabling operators to intuitively understand the system's operating status and promptly identify and address potential issues. This enables real-time monitoring and management of PV module operating status, improving system monitoring and maintenance efficiency.

[0073] The technical solution of the present application obtains structural information of the target building and constructs a three-dimensional network based on the structural information; obtains cloud data through satellite meteorology, and predicts the irradiance distribution on the surface of the target building within a preset time based on the cloud data and the three-dimensional network; divides the area into high irradiation areas and low irradiation areas according to the irradiance distribution and a set threshold, and respectively arranges corresponding photovoltaic modules and power controllers in the high irradiation areas and low irradiation areas; determines the net benefit function in the power generation and energy storage process based on the equipment parameters of the photovoltaic modules, and determines the working power of the photovoltaic modules based on the net benefit function; and controls the operation of the photovoltaic modules through the power controller based on the working power of the photovoltaic modules. By accurately predicting the irradiance distribution on the surface of the target building and intelligently dividing the high irradiation areas and low irradiation areas according to the irradiance distribution, the layout and working power of the photovoltaic modules are optimized to accurately control the working state of the photovoltaic modules, which not only improves the utilization rate of photovoltaic power generation, but also reduces the energy storage cost through intelligent control, thereby achieving efficient energy utilization and cost optimization.

[0074] Example 2: The following describes an embodiment of a device of the present application, which can be used to implement the integrated photovoltaic and storage collaborative optimization method for a photovoltaic, storage, and flexible building described in the aforementioned embodiment of the present application. It is understood that the device can be a computer program (including program code) running on a computer device, for example, the device is an application software; the device can be used to execute the corresponding steps of the method provided in the embodiment of the present application. For details not disclosed in the embodiment of the device of the present application, please refer to the aforementioned embodiment of the integrated photovoltaic and storage collaborative optimization method for a photovoltaic, storage, and flexible building described in the present application.

[0075] Figure 3 A block diagram of a photovoltaic-storage integrated collaborative optimization system applied to a photovoltaic-storage direct-flexible building according to an embodiment of the present application is shown.

[0076] Reference Figure 3 As shown, according to one embodiment of the present application, a photovoltaic storage integrated collaborative optimization system applied to a photovoltaic storage direct-flexible building includes: An acquisition unit 310 is configured to acquire structural information of a target building and construct a three-dimensional network based on the structural information; The irradiance unit 320 is configured to obtain cloud data through satellite meteorology, and predict the irradiance distribution on the target building surface within a preset time based on the cloud data and the three-dimensional network; a layout unit 330 for dividing the area into a high irradiation area and a low irradiation area according to the irradiance distribution and a set threshold, and respectively arranging corresponding photovoltaic modules and power controllers in the high irradiation area and the low irradiation area; An efficiency unit 340 is configured to determine a net benefit function in a power generation and energy storage process based on device parameters of the photovoltaic assembly, and determine an operating power of the photovoltaic assembly according to the net benefit function; The control unit 350 is configured to control the operation of the photovoltaic assembly through the power controller based on the operating power of the photovoltaic assembly.

[0077] In the present application, based on the aforementioned scheme, the method of obtaining the structural information of the target building and constructing a three-dimensional network based on the structural information includes: obtaining the structural information of the target building, the structural information including the position orientation information and surface parameters of the target building; determining the local curvature corresponding to the target building at each position based on the surface parameters; determining the illumination angle parameters based on the position orientation information and the local curvature; and performing modeling based on the local curvature and the illumination angle parameters to generate a three-dimensional network corresponding to the target building.

[0078] In the present application, based on the aforementioned scheme, cloud data is obtained through satellite meteorology, and based on the cloud data and the three-dimensional network, the irradiance distribution of each interior of the target building within a preset time is predicted, including: obtaining cloud data through satellite meteorology, the cloud data including the irradiance reference value in a cloudless state, and the attribute coefficients of the cloud layer for solar radiation absorption and transmission; based on the irradiance reference value and the three-dimensional network, combined with the attribute coefficients of the cloud layer for solar radiation absorption and transmission, generating an irradiance model for the building surface; based on the irradiance model, determining the irradiance distribution of the target building surface within a preset time.

[0079] In the present application, based on the above-mentioned scheme, the high irradiation area and the low irradiation area are divided according to the irradiance distribution and the set threshold, and corresponding photovoltaic components and power controllers are respectively arranged in the high irradiation area and the low irradiation area, including: according to the irradiance corresponding to each position in the irradiance distribution, when the irradiance corresponding to the position is greater than or equal to the set threshold, the position is divided into the high irradiation area; when the irradiance corresponding to the position is less than the set threshold, the position is divided into the low irradiation area; and corresponding photovoltaic components and power controllers are respectively arranged in the high irradiation area and the low irradiation area.

[0080] In the present application, based on the aforementioned scheme, the net benefit function in the power generation and energy storage process is determined based on the equipment parameters of the photovoltaic component, and the working power of the photovoltaic component is determined according to the net benefit function, including: determining the power generation utility function and energy storage cost function of the photovoltaic component based on the equipment parameters of the photovoltaic component; determining the net benefit function based on the power generation utility function and the energy storage cost function; and determining the working power of the photovoltaic component based on the net benefit function.

[0081] In the present application, based on the aforementioned scheme, the operation of the photovoltaic component is controlled by the power controller based on the working power of the photovoltaic component, including: generating a configuration instruction based on the working power of the photovoltaic component; sending the configuration instruction to the power controller through the communication interface; the power controller receives and parses the configuration instruction to control the operation of the photovoltaic component.

[0082] In the present application, based on the aforementioned solution, after controlling the operation of the photovoltaic component through the power controller based on the working power of the photovoltaic component, it also includes: obtaining the working parameters of the photovoltaic component; and displaying the working parameters on the display of the control platform.

[0083] The technical solution of the present application obtains structural information of the target building and constructs a three-dimensional network based on the structural information; obtains cloud data through satellite meteorology, and predicts the irradiance distribution on the surface of the target building within a preset time based on the cloud data and the three-dimensional network; divides the area into high irradiation areas and low irradiation areas according to the irradiance distribution and a set threshold, and respectively arranges corresponding photovoltaic modules and power controllers in the high irradiation areas and low irradiation areas; determines the net benefit function in the power generation and energy storage process based on the equipment parameters of the photovoltaic modules, and determines the working power of the photovoltaic modules based on the net benefit function; and controls the operation of the photovoltaic modules through the power controller based on the working power of the photovoltaic modules. By accurately predicting the irradiance distribution on the surface of the target building and intelligently dividing the high irradiation areas and low irradiation areas according to the irradiance distribution, the layout and working power of the photovoltaic modules are optimized to accurately control the working state of the photovoltaic modules, which not only improves the utilization rate of photovoltaic power generation, but also reduces the energy storage cost through intelligent control, thereby achieving efficient energy utilization and cost optimization.

[0084] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing an electronic device according to an embodiment of the present application is shown.

[0085] It should be noted that the computer system of the electronic device in this embodiment is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0086] In this embodiment, the computer system includes a central processing unit 401, which can perform various appropriate actions and processes based on programs stored in read-only memory 402 or programs loaded from storage unit 408 into random access memory 403, such as executing the integrated photovoltaic and storage collaborative optimization method for photovoltaic and storage direct-flexible buildings described in the above embodiment. Random access memory 403 also stores various programs and data required for system operation. Central processing unit 401, read-only memory 402, and random access memory 403 are interconnected via bus 404. Input / output interface 405 is also connected to bus 404.

[0087] The following components are connected to the input / output interface 405: an input section 406 including a keyboard, mouse, and the like; an output section 407 including devices such as a cathode ray tube (CRT), a liquid crystal display (LCD), and speakers; a storage section 408 including devices such as a hard disk; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card or a modem. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to the input / output interface 405 as needed. Removable media 411, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 410 as needed, so that computer programs read from the removable media can be installed in the storage section 408 as needed.

[0088] In particular, according to an embodiment of the present application, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present application includes a computer program product that includes a computer program carried on a computer-readable medium, the computer program including a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network via the communication section 409 and / or installed from a removable medium 411. When the computer program is executed by the central processing unit 401, the various functions defined in the system of the present application are performed.

[0089] If the above functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0090] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and such modifications or substitutions are intended to be within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection of the claims.

Claims

1. A photovoltaic-storage integrated collaborative optimization method applied to a photovoltaic-storage direct-flexible building, characterized in that: The following steps are involved: Acquiring structural information of a target building, and constructing a three-dimensional network based on the structural information; Acquire cloud data through satellite meteorology, and predict the irradiance distribution on the surface of the target building within a preset time based on the cloud data and the three-dimensional network; Dividing the high irradiation area and the low irradiation area according to the irradiance distribution and the set threshold, and arranging corresponding photovoltaic modules and power controllers in the high irradiation area and the low irradiation area respectively; Determining a net benefit function in a power generation and energy storage process based on device parameters of the photovoltaic assembly, and determining an operating power of the photovoltaic assembly according to the net benefit function; Based on the working power of the photovoltaic assembly, the operation of the photovoltaic assembly is controlled by the power controller.

2. The photovoltaic-storage integrated collaborative optimization method applied to a photovoltaic-storage direct-flexible building according to claim 1 is characterized in that: The step of obtaining structural information of a target building and constructing a three-dimensional network based on the structural information specifically includes: Acquiring structural information of a target building, wherein the structural information includes position and orientation information and surface parameters of the target building; Determine the local curvature of the target building at each location based on the surface parameters , the formula is: in, Represents the coordinate information of the building surface, Represents the surface parameters corresponding to the points of interest extracted from the building surface, Indicates the coordinates of the point of interest, Indicates that the target building is The local curvature at Determine the sun direction vector corresponding to each moment based on the position and orientation information , based on the sun direction vector and the local curvature , determine the cosine value of the angle between the sun's rays and the surface normal vector as the illumination angle parameter : in, Is the illumination angle parameter, which indicates the angle between the sun's rays and the target building. The surface normal vector at time t The cosine of the angle between represents the partial derivative operation, express t The sun direction vector corresponding to the sun's position at the moment, t Indicates time, represents the magnitude of the sun direction vector; The local curvature and illumination angle parameters In combination, a grid modeling algorithm is used to generate a three-dimensional network model that includes both the building geometry and dynamic lighting characteristics to obtain a three-dimensional network.

3. The photovoltaic-storage integrated collaborative optimization method applied to a photovoltaic-storage direct-flexible building according to claim 2 is characterized in that: The sun direction vector corresponding to each moment is determined according to the position orientation information , specifically including: Obtain the location and orientation information of the target building, including the latitude B and longitude L of the target building; Calculate solar time based on the longitude L: in, For solar time, is the local time of the target building, is the standard longitude, When is the equation; Based on solar time Calculating the solar hour angle , and its calculation formula is: Based on the latitude B, the solar hour angle , calculate the solar altitude angle h(t) and the solar azimuth angle , and its calculation formula is: in, Indicates time t The solar declination angle, 、 Respectively indicate time t The solar altitude angle and solar azimuth angle; Based on the sun altitude angle Azimuth angle to the sun , construct the sun direction vector : in, express t The sun direction vector corresponding to the sun's position at that moment.

4. The photovoltaic-storage integrated collaborative optimization method for a photovoltaic-storage direct-flexible building according to claim 1 is characterized in that: The step of acquiring cloud data through satellite meteorology and predicting the irradiance distribution on the target building surface within a preset time based on the cloud data and the three-dimensional network specifically includes: Obtain satellite meteorological data, including irradiance reference values ​​in a cloudless state , cloud properties of solar radiation absorption and transmission, including absorption coefficient , transmission coefficient and scattering coefficient ; Based on the irradiance reference value , attribute coefficients and the three-dimensional network model constructed by the target building, combined with the local curvature at each location and illumination angle parameters , build the irradiance model of the building surface and determine the t Any position on the target building surface Irradiance at : in, Indicates t Target building surface at all times The corresponding irradiance at represents the exponential operation of a natural constant, 、 Represent the roof height of the target building and the height of the cloud top, respectively. 、 Respectively indicate the height The cloud absorption coefficient and transmission coefficient at represents the scattering coefficient of atmospheric molecules, Indicates that the target building is The local curvature at Is the illumination angle parameter, which indicates the angle between the sun's rays and the target building. The surface normal vector at time t The cosine of the angle between Based on the irradiance model, the irradiance corresponding to each position of the target building at each time point is determined to form the irradiance distribution on the surface of the target building within the preset time.

5. The photovoltaic-storage integrated collaborative optimization method applied to a photovoltaic-storage direct-flexible building according to claim 1 is characterized in that: The dividing of the high irradiation area and the low irradiation area according to the irradiance distribution and the set threshold value specifically includes: Get the irradiance distribution at each location on the target building surface within a preset time , and perform time domain averaging on the irradiance to obtain the average irradiance value at each location: in, Indicates that within the preset time period T, the target building The average irradiance at is the total duration of the preset time period, Indicates t Target building surface at all times The corresponding irradiance at Setting the irradiance threshold ,when When the target building The area is classified as a high radiation area; When the target building The area is classified as low radiation zone.

6. The photovoltaic-storage integrated collaborative optimization method for a photovoltaic-storage direct-flexible building according to claim 1 or 5, characterized in that: The corresponding photovoltaic modules and power controllers are respectively arranged in the high irradiation area and the low irradiation area, specifically including: According to the area and average irradiance of the high irradiation zone, high-efficiency photovoltaic modules are arranged, wherein the high-efficiency photovoltaic modules are equipped with high-capacity lithium batteries as energy storage units and are equipped with corresponding power controllers; According to the area and average irradiance of the low irradiation zone, photovoltaic modules with strong adaptability and low cost are arranged, supercapacitors are configured as fast-response energy storage devices, and corresponding power controllers are equipped.

7. The photovoltaic-storage integrated collaborative optimization method for a photovoltaic-storage direct-flexible building according to claim 1 is characterized in that: The determining of the net benefit function in the power generation and energy storage process based on the device parameters of the photovoltaic module specifically includes: Determine the power generation utility function of the photovoltaic module based on the device parameters of the photovoltaic module : in, i Indicates the logo of photovoltaic modules. Represents photovoltaic modules i Power, Represents photovoltaic modules i Unit power generation profit coefficient; Represents photovoltaic modules i The marginal cost coefficient of power generation; Determine the energy storage cost function of the photovoltaic module based on the device parameters of the photovoltaic module : in, Represents photovoltaic modules i Energy storage cost coefficient; Represents photovoltaic modules i Power sensitivity coefficient; Determine the photovoltaic components based on the power generation utility function and the energy storage cost function i At power The net benefit function : in, is the Lagrange multiplier; n Indicates the total number of PV panels; Represents the total load demand of the building's electrical system.

8. The photovoltaic-storage integrated collaborative optimization method for a photovoltaic-storage direct-flexible building according to claim 1 is characterized in that: Determining the operating power of the photovoltaic assembly according to the net benefit function specifically includes: Step S401: Initialize the photovoltaic module working power vector and Lagrange multipliers ,in Indicates that the photovoltaic module in the 0th iteration i Power; Step S402: Based on the current power vector , according to the current power vector and the equipment parameters of each photovoltaic module, through the net benefit function Calculate the gradient of the net benefit function for each photovoltaic module ; Step S403: Update the photovoltaic module operating power vector using an iterative optimization algorithm: in, is the preset learning rate, represents the partial derivative of the net benefit function with respect to power; Step S404: Adjust the updated power value according to the power constraint condition: in, 、 Photovoltaic modules i The minimum and maximum power limits allowed; Step S405: Determine the iteration termination condition. If the change in the net benefit function value is If it is less than the preset threshold, the iteration is stopped, the optimal power vector is output, and the operating power of each photovoltaic module is determined; otherwise, k=k+1 is set and the process returns to step S402 to continue the iteration.

9. The photovoltaic-storage integrated collaborative optimization method for a photovoltaic-storage direct-flexible building according to claim 1 is characterized in that: The controlling the operation of the photovoltaic assembly by the power controller based on the operating power of the photovoltaic assembly specifically includes: generating a configuration instruction based on the operating power of the photovoltaic module; sending the configuration instruction to the power controller via a communication interface; The power controller receives and analyzes the configuration instruction and controls the operation of the photovoltaic assembly.

10. A photovoltaic storage integrated collaborative optimization system applied to photovoltaic storage direct-flexible buildings, characterized in that: include: an acquisition unit, configured to acquire structural information of a target building and construct a three-dimensional network based on the structural information; an irradiance unit, configured to obtain cloud data through satellite meteorology, and predict the irradiance distribution on the surface of the target building within a preset time based on the cloud data and the three-dimensional network; a layout unit, configured to divide the area into a high irradiation area and a low irradiation area according to the irradiance distribution and a set threshold, and to layout corresponding photovoltaic modules and power controllers in the high irradiation area and the low irradiation area, respectively; an efficiency unit, configured to determine a net benefit function in a power generation and energy storage process based on device parameters of the photovoltaic assembly, and determine an operating power of the photovoltaic assembly according to the net benefit function; A control unit is used to control the operation of the photovoltaic assembly through the power controller based on the operating power of the photovoltaic assembly.

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