A method and system for integrated optimization of photovoltaic and energy storage for a direct flexible building

Abstract

The application relates to the technical field of electric energy storage, and provides a photovoltaic and energy storage integrated collaborative optimization method and system applied to a photovoltaic and energy storage direct flexible building. Three-dimensional network is constructed by obtaining construction information of a target building; irradiance distribution on the surface of the target building is predicted based on cloud layer data and the three-dimensional network; high irradiance areas and low irradiance areas are divided according to the irradiance distribution and a set threshold value, and corresponding photovoltaic modules and power controllers are arranged in the high irradiance areas and the low irradiance areas; a net benefit function in power generation and energy storage processes is determined based on equipment parameters of the photovoltaic modules, and working power of the photovoltaic modules is determined according to the net benefit function; and the photovoltaic modules are controlled to work through the power controllers based on the working power of the photovoltaic modules. The layout and working power of the photovoltaic modules are optimized, so that the working state of the photovoltaic modules 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] This invention belongs to the field of energy storage technology, specifically relating to a method and system for integrated photovoltaic-storage collaborative optimization applied to photovoltaic-storage-flexible buildings. Background Technology

[0002] As a new type of building energy system, photovoltaic-storage-direct-drive (PV-SHU) flexible building systems are an important means to achieve energy conservation and emission reduction in the building sector and promote energy transition. PV-SHU flexible buildings can interact with the municipal power grid, enabling bidirectional power flow and intelligent dispatch. Through integrated PV-SHU synergistic optimization, the relationship between building power consumption and grid power supply can be better coordinated, improving grid stability and security. The integrated PV-SHU synergistic optimization method can organically combine photovoltaic and energy storage systems, improving the utilization rate and stability of photovoltaic power generation. PV-SHU flexible buildings can also participate in grid demand response, adjusting their operating strategies according to grid dispatch instructions to provide ancillary services to the grid. Currently, the technological maturity of PV-SHU flexible systems still needs improvement, especially in the photovoltaic and energy storage aspects. The control precision of photovoltaic modules is relatively low, making it difficult to achieve a balance between photovoltaic and energy storage, resulting in low photovoltaic energy efficiency.

[0003] In the prior art, Chinese patent CN114709878A discloses a method, equipment, and medium for the coordinated configuration of photovoltaic (PV) and energy storage (ESS) in a photovoltaic-energy storage-flexible building (PV-ESS-Flexible Building). This includes: acquiring the PV output curve of the PV-ESS-Flexible Building; determining the user-specified energy storage configuration target; selecting a load curve based on the energy storage configuration target; and configuring the energy storage capacity and energy storage charging / discharging power of the PV in the PV-ESS-Flexible Building based on the PV output curve and the load curve. By configuring the PV using the PV output curve of the PV-ESS-Flexible Building and the load curve actually obtained based on the energy storage configuration target, the actual power generation and electricity demand of the PV-ESS-Flexible Building are combined. This avoids wasting energy storage capacity during PV configuration, improves the economic efficiency of the PV-ESS-Flexible Building, and achieves the rational utilization of renewable resources.

[0004] However, this method has the following limitations: 1. It relies solely on photovoltaic output and load curves for configuration, completely ignoring the complex three-dimensional geometry of the building itself and the differences in illumination caused by orientation, curvature, and shading on various surfaces. This results in only a rough estimate when calculating available light resources, failing to accurately reflect the true power generation potential of different parts; 2. Existing configuration schemes lack the ability to classify and process the differences in light intensity in different areas of the building surface. Photovoltaic modules and energy storage devices can only be uniformly deployed in a "one-size-fits-all" manner. This not only fails to fully utilize the performance of high-efficiency modules in areas with sufficient light but also easily leads to investment waste in areas with insufficient light, reducing the overall economic return of the system; 3. This method focuses on capacity matching and lacks dynamic power scheduling mechanisms and real-time optimization methods based on equipment operating characteristics. It cannot meet electricity demand while taking into account the cycle life and operating cost of the energy storage system, leading to the energy storage devices being prone to overcharging and discharging, premature lifespan decay, and difficulty in achieving the continuous maximization of system economic benefits. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the existing technology and provide a method and system for integrated optimization of light and energy storage in a flexible building system.

[0006] The objective of this invention can be achieved through the following technical solutions:

[0007] This invention provides a method for integrated synergistic optimization of photovoltaic-storage architecture applied to photovoltaic-storage-flexible buildings, comprising the following steps:

[0008] Obtain the structural information of the target building, and construct a three-dimensional network based on the structural information;

[0009] Cloud data is acquired via satellite meteorology. Based on the cloud data and the three-dimensional network, the irradiance distribution of the target building surface within a preset time period is predicted.

[0010] Based on the irradiance distribution and the set threshold, high irradiance area and low irradiance area are divided, and corresponding photovoltaic modules and power controllers are deployed in the high irradiance area and low irradiance area respectively.

[0011] The net benefit function in the power generation and energy storage process is determined based on the equipment parameters of the photovoltaic module, and the operating power of the photovoltaic module is determined based on the net benefit function.

[0012] The photovoltaic module is controlled to operate based on its operating power by the power controller.

[0013] Furthermore, the acquisition of the structural information of the target building and the construction of a three-dimensional network based on the structural information specifically includes:

[0014] Obtain the structural information of the target building, including the target building's location and orientation information and surface parameters;

[0015] Based on the surface parameters, determine the local curvature of the target building at each location. The formula is:

[0016]

[0017] in, Represents the coordinate information of the building surface. This represents the surface parameters corresponding to the points of interest extracted from the architectural surface. This represents the coordinates of the point of interest. Indicates the target building is located in Local curvature at that point;

[0018] Determine the solar direction vector at each moment based on the location and orientation information. Based on the solar direction vector and the local curvature Determine the cosine value of the angle between the sunlight and the surface normal vector, and use it as the illumination angle parameter. :

[0019]

[0020] in, The illumination angle parameter represents the angle between the sunlight and the target building. The surface normal vector at time t t The cosine of the angle between them; This represents the partial derivative operation. express t The solar direction vector corresponding to the sun's position at any given time. t Indicates time, The magnitude of the solar direction vector;

[0021] The local curvature With illumination angle parameters By combining these methods, a mesh modeling algorithm is used to generate a 3D network model that includes both architectural geometry and dynamic lighting features, thus obtaining a 3D network.

[0022] Furthermore, the step of determining the solar direction vector corresponding to each moment based on the position orientation information... Specifically, it includes:

[0023] Obtain the location and orientation information of the target building, including the latitude B and longitude L of the target building;

[0024] Calculate solar time based on the longitude L:

[0025]

[0026] in, When the sun is shining, For the local time of the target building, Standard longitude When it is an equation;

[0027] Based on solar time Calculate the solar hour angle The calculation formula is as follows:

[0028]

[0029] Based on the latitude B and the solar hour angle Calculate the solar altitude angle h(t) and solar azimuth angle. The calculation formula is as follows:

[0030]

[0031]

[0032] in, Indicates time t The solar declination angle, , Representing time respectively t The solar altitude angle and solar azimuth angle;

[0033] Based on the solar altitude angle With solar azimuth Construct the solar direction vector :

[0034]

[0035] in, express t The solar direction vector corresponding to the sun's position at any given time.

[0036] Furthermore, the step of acquiring cloud data via satellite meteorology, and predicting the irradiance distribution of the target building surface within a preset time period based on the cloud data and the three-dimensional network, specifically includes:

[0037] Acquire satellite meteorological data, including irradiance reference values ​​under cloudless conditions. The property coefficients of cloud layer absorption and transmission of solar radiation, including absorption coefficient. Transmission coefficient With scattering coefficient ;

[0038] Based on the irradiance reference value The three-dimensional network model constructed from the attribute coefficients and the target building, combined with the local curvature at each location. With illumination angle parameters Construct an irradiance model for the building surface to determine the irradiance at any given time. t Any location on the surface of the target building Irradiance at the location :

[0039]

[0040] in, Indicates in t Target building surface at all times The corresponding irradiance at that location Exponentiation of the natural constant. , These represent the roof height of the target building and the height of the top of the cloud, respectively. , These represent the altitudes respectively. The cloud absorption coefficient and transmission coefficient at that location The scattering coefficient of atmospheric molecules is represented. Indicates the target building is located in Local curvature at that point The illumination angle parameter represents the angle between the sunlight and the target building. The surface normal vector at time t t The cosine of the angle between them;

[0041] Based on the irradiance model, the irradiance at each location of the target building at each time point is determined, thus forming the irradiance distribution of the target building surface within a preset time period.

[0042] Furthermore, the step of dividing high-irradiance areas and low-irradiance areas based on the irradiance distribution and a set threshold specifically includes:

[0043] Obtain the irradiance distribution at various locations on the surface of the target building within a preset time period. The irradiance was then averaged over time to obtain the average irradiance value at each location:

[0044]

[0045] in, This indicates that within a preset time period T, the target building is in Average irradiance at the location, The total duration of the preset time period. Indicates in t Target building surface at all times The corresponding irradiance at that location;

[0046] Set irradiance threshold ,when At that time, the target building The area is designated as a high-irradiation zone; when At that time, the target building The area is designated as a low-irradiance zone.

[0047] Furthermore, the deployment of corresponding photovoltaic modules and power controllers in the high-irradiance and low-irradiance areas respectively specifically includes:

[0048] Based on the area and average irradiance of the high-irradiance zone, high-efficiency photovoltaic modules are deployed. The high-efficiency photovoltaic modules are equipped with high-capacity lithium batteries as energy storage units and corresponding power controllers.

[0049] Based on the area and average irradiance of the low-irradiance zone, adaptable and low-cost photovoltaic modules are deployed, supercapacitors are configured as fast-response energy storage devices, and corresponding power controllers are provided.

[0050] Furthermore, the determination of the net benefit function in the power generation and energy storage process based on the equipment parameters of the photovoltaic module specifically includes:

[0051] Based on the equipment parameters of the photovoltaic module, determine the power generation utility function of the photovoltaic module. :

[0052]

[0053] in, i The identifier for photovoltaic modules, Indicates photovoltaic modules i power, Indicates photovoltaic modules i The unit power generation revenue coefficient; Indicates photovoltaic modules i The marginal cost coefficient of power generation;

[0054] Based on the equipment parameters of the photovoltaic module, determine the energy storage cost function of the photovoltaic module. :

[0055]

[0056] in, Indicates photovoltaic modules i The energy storage cost coefficient; Indicates photovoltaic modules i The power sensitivity coefficient;

[0057] Based on the power generation utility function and the energy storage cost function, determine the photovoltaic module.i At power Net benefit function at time :

[0058]

[0059] in, They are Lagrange multipliers; n Indicates the total number of photovoltaic modules; This indicates the total load demand of the building's electrical system.

[0060] Furthermore, determining the operating power of the photovoltaic module based on the net benefit function specifically includes:

[0061] Step S401: Initialize the photovoltaic module's operating power vector and Lagrange multipliers ,in Indicates the photovoltaic module in the 0th iteration i The power;

[0062] Step S402: Based on the current power vector Based on the current power vector and the equipment parameters of each photovoltaic module, the net benefit function is used. Calculate the gradient of the net benefit function for each photovoltaic module. ;

[0063] Step S403: Update the photovoltaic module's operating power vector using an iterative optimization algorithm:

[0064]

[0065] in, The preset learning rate, This represents the partial derivative of the net benefit function with respect to power;

[0066] Step S404: Adjust the updated power value according to the power constraint conditions:

[0067]

[0068] in, , Photovoltaic modules i The minimum and maximum power limits allowed;

[0069] Step S405: Determine the iteration termination condition; if the change in the net benefit function value... If the power is less than the preset threshold, stop the iteration, output the optimal power vector, and determine the working power of each photovoltaic module; otherwise, let k=k+1 and return to step S402 to continue the iteration.

[0070] Furthermore, the step of controlling the operation of the photovoltaic module through the power controller based on the operating power of the photovoltaic module specifically includes:

[0071] Based on the operating power of the photovoltaic module, generate configuration instructions;

[0072] The configuration command is sent to the power controller via the communication interface;

[0073] The power controller receives and parses the configuration instructions to control the photovoltaic modules to operate.

[0074] Another aspect of the present invention provides an integrated photovoltaic-storage collaborative optimization system for photovoltaic-storage buildings, comprising:

[0075] An acquisition unit is used to acquire the structural information of the target building and construct a three-dimensional network based on the structural information.

[0076] The irradiance unit is used to acquire cloud data through satellite meteorology, and based on the cloud data and the three-dimensional network, to predict the irradiance distribution of the target building surface within a preset time period.

[0077] The deployment unit is used to divide the high irradiance zone and the low irradiance zone according to the irradiance distribution and the set threshold, and to deploy corresponding photovoltaic modules and power controllers in the high irradiance zone and the low irradiance zone respectively.

[0078] An efficiency unit is used to determine the net benefit function in the power generation and energy storage process based on the equipment parameters of the photovoltaic module, and to determine the operating power of the photovoltaic module based on the net benefit function;

[0079] A control unit is used to control the operation of the photovoltaic module through the power controller based on the operating power of the photovoltaic module.

[0080] Compared with the prior art, the present invention has the following advantages:

[0081] (1) Based on the predicted irradiance distribution and set thresholds, this invention divides the building surface into high-irradiance and low-irradiance zones, which helps optimize the placement of photovoltaic modules and enable them to make full use of solar resources. Placing high-efficiency photovoltaic modules in high-irradiance zones maximizes the use of solar radiation; while using lower-efficiency but lower-cost photovoltaic modules in low-irradiance zones, or combining them with other energy utilization methods, further enhances the efficiency of photovoltaic power generation and reduces system costs. Simultaneously, deploying corresponding power controllers in each zone enables precise control of the photovoltaic module's operating status, reducing the risk of damage to photovoltaic modules due to poor lighting conditions and improving the power generation efficiency and energy utilization rate of the photovoltaic modules.

[0082] (2) This invention employs a mesh modeling algorithm to construct a three-dimensional network model that includes both building geometry and dynamic lighting characteristics, making the prediction of incident angles, shadow occlusion, and light intensity for various parts of the building more accurate. This refined modeling allows for the differentiation of lighting differences caused by different curvatures and orientations in the simulation, significantly improving the resolution and reliability of irradiance prediction. This provides reliable data support for subsequent photovoltaic module selection and high / low irradiance zone delineation, eliminating reliance on simplified planar assumptions or empirical coefficients. Improved accuracy in high / low irradiance zone delineation further enhances the overall efficiency of photovoltaic power generation and reduces system costs.

[0083] (3) By constructing an irradiance model, this invention overcomes the problem of low accuracy in predicting illumination under complex weather scenarios by relying solely on the irradiance constant or empirical correction coefficient on sunny days. This enables accurate quantification of the illumination intensity of each area on the building surface under adverse weather conditions such as cloudy or overcast days, providing reliable input data for subsequent component layout and power optimization.

[0084] (4) After obtaining high-resolution time-varying irradiance data, the present invention performs time-domain averaging of the irradiance within a preset time period, calculates the average irradiance at each location, and compares it with a preset threshold to achieve precise division between high-irradiance and low-irradiance 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 irradiance conditions. This not only improves the rationality of photovoltaic module layout and power generation efficiency, but also avoids excessive investment in inefficient areas, effectively reducing the total system cost and improving overall economic efficiency.

[0085] (5) This invention addresses the problem in existing technologies where using the same specifications of modules and energy storage strategies in high-irradiance areas can lead to insufficient capacity release of modules in strong-light areas, low return on investment for modules in weak-light areas, and a sharp decline in the lifespan of large-capacity batteries under frequent shallow-cycle conditions. The regionalized configuration of this invention optimizes this situation: the combination of high-efficiency modules and lithium batteries in high-irradiance areas can efficiently collect and store abundant peak power, while the economical modules in low-irradiance areas and the supercapacitors with accelerated response can quickly smooth out power generation fluctuations and reduce the number of deep charge and discharge cycles of the batteries. This not only significantly 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 a site-specific investment strategy, and maintains the stability and reliability of power output under variable weather conditions.

[0086] (6) Based on the conversion efficiency, cost coefficient, lifespan parameters of photovoltaic modules, and the charging and discharging efficiency of energy storage systems, this invention establishes a power generation utility function and an energy storage cost function, and constructs a comprehensive net benefit function accordingly. It then quantitatively compares the economic benefits and costs under different power outputs, and determines the optimal operating power of each module by solving for the maximum value of this function. This method overcomes the drawbacks of traditional methods that simply set power based on peak value or experience, achieving a dynamic balance between power generation revenue and energy storage costs. It fully taps the potential of photovoltaic power generation while avoiding accelerated aging of energy storage equipment due to overcharging and discharging, thereby significantly improving the overall economic benefits and equipment lifespan of the system. It ensures the stable operation of the photovoltaic system and meets energy demands. It reduces energy waste and equipment failure risks caused by improper control, achieves precise control of the photovoltaic module's operating status, and improves the system's stability and reliability. Attached Figure Description

[0087] Figure 1 The flowchart illustrating a method for integrated photovoltaic-storage collaborative optimization applied to a photovoltaic-storage building in one embodiment of this application is shown.

[0088] Figure 2 The flowchart illustrating the construction of a three-dimensional network is shown in one embodiment of this application.

[0089] Figure 3 The illustration shows a schematic diagram of an integrated photovoltaic-storage collaborative optimization system applied to a photovoltaic-storage building with flexible and direct energy storage in one embodiment of this application.

[0090] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application is shown. Detailed Implementation

[0091] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0092] Example 1:

[0093] The implementation details of the technical solution of this application are described below:

[0094] Figure 1 A flowchart illustrating an embodiment of this application of a photovoltaic-storage integrated collaborative optimization method for buildings with flexible and direct photovoltaic systems is shown. (Refer to...) Figure 1As shown, the integrated photovoltaic-storage collaborative optimization method applied to photovoltaic-storage-flexible buildings includes at least steps S110 to S150, which are described in detail below:

[0095] In step S110, the structural information of the target building is obtained, and a three-dimensional network is constructed based on the structural information.

[0096] In this application, structural information of the target building is acquired through sensors or data files. This structural information includes, but is not limited to, key data such as the building's geometric dimensions, orientation, and surface parameters of each surface. Subsequently, this structural information is used as input and processed by software tools to construct a three-dimensional network model that accurately reflects the spatial structure and appearance characteristics of the target building.

[0097] like Figure 2 As shown, in one embodiment of this application, obtaining the structural information of the target building and constructing a three-dimensional network based on the structural information includes:

[0098] S210, Obtain the structural information of the target building, the structural information including the target building's location and orientation information and surface parameters;

[0099] S220, Based on the surface parameters, determine the local curvature of the target building at each location;

[0100] S230, Based on the position orientation information and the local curvature, determine the illumination angle parameters;

[0101] S240, Modeling is performed based on the local curvature and the illumination angle parameters to generate a three-dimensional network corresponding to the target building.

[0102] In one embodiment of this application, the structural information of the target building is obtained, wherein the structural information includes the location and orientation information and surface parameters of the target building.

[0103] After obtaining the construction information, the local curvature of the target building at each location is determined based on the surface parameters. for:

[0104]

[0105] in, Represents the coordinate information of the building surface. This represents the surface parameters corresponding to the points of interest extracted from the architectural surface. i,j The coordinates of the point of interest.

[0106] Next, the solar direction vector at each moment is determined based on the position and orientation information. Based on the solar direction vector and the local curvature, the cosine value of the angle between the sunlight and the surface normal vector is determined as the illumination angle parameter.

[0107]

[0108] in, This represents the partial derivative operation. express t The solar direction vector corresponding to the sun's position at any given time. t Indicates time.

[0109] Specifically, determining the solar direction vector at each moment based on the location and orientation information includes:

[0110] Obtain the location and orientation information of the target building, including the latitude B and longitude L of the target building;

[0111] Calculate solar time based on the longitude L:

[0112]

[0113] in, When the sun is shining, For the local time of the target building, Standard longitude When it is an equation;

[0114] Based on solar time Calculate the solar hour angle The calculation formula is as follows:

[0115]

[0116] Based on the latitude B and the solar hour angle Calculate the solar altitude angle h(t) and solar azimuth angle. The calculation formula is as follows:

[0117]

[0118]

[0119] in, Indicates time t The solar declination angle, , Representing time respectively t The solar altitude angle and solar azimuth angle;

[0120] Based on the solar altitude angle With solar azimuth Construct the solar direction vector :

[0121]

[0122] in, express t The solar direction vector corresponding to the sun's position at any given time.

[0123] After determining the local curvature and illumination angle parameters of the target building, a model is created based on these parameters. The local curvature and illumination angle are combined to generate a 3D network corresponding to the target building. In this embodiment, the 3D network obtained by modeling includes both the building's structural information and the illumination angle at different times.

[0124] The above process, by acquiring the structural information of the target building and constructing a 3D network based on this information, can accurately simulate the building's geometry and lighting conditions. This provides a solid foundation for subsequent irradiance prediction and photovoltaic module placement, thus ensuring the effectiveness of the entire optimization process.

[0125] In step S120, cloud data is acquired through satellite meteorology, and based on the cloud data and the three-dimensional network, the irradiance distribution of the target building surface within a preset time period is predicted.

[0126] In this embodiment, cloud data from satellites is acquired and analyzed. This data records detailed information such as cloud distribution, thickness, and movement speed. Subsequently, using this cloud data and a previously constructed 3D network model of the target building, a lighting simulation is run. Considering factors such as the sun's position, cloud shading effects, and the geometry and orientation of the building surfaces, the irradiance distribution on each surface of the target building is predicted within a preset time period. This provides accurate lighting prediction data for subsequent optimized configuration of photovoltaic modules.

[0127] In one embodiment of this application, cloud data is acquired via satellite meteorology, and based on the cloud data and the three-dimensional network, the irradiance distribution inside each part of the target building within a preset time period is predicted, including:

[0128] Cloud data is acquired through satellite meteorology, including irradiance baseline values ​​under cloudless conditions and attribute coefficients of cloud absorption and transmission of solar radiation.

[0129] Based on the aforementioned irradiance reference value and the aforementioned three-dimensional network, and combined with the attribute coefficients of cloud layer absorption and transmission of solar radiation, an irradiance model of the building surface is generated.

[0130] The irradiance distribution of the target building surface within a preset time period is determined based on the irradiance model.

[0131] In one embodiment of this application, cloud data is acquired via satellite meteorology, including obtaining a baseline irradiance value under cloudless conditions from historical meteorological data. Optionally, this embodiment uses the exoatmospheric solar irradiance constant. It serves as a benchmark value for irradiance, used to characterize the standard solar irradiance intensity outside the Earth's atmosphere.

[0132] Subsequently, based on the irradiance reference value and the three-dimensional network, namely the attribute coefficients of cloud absorption and transmission of solar radiation, an irradiance model of the building surface is generated. for:

[0133]

[0134] in, Indicates in t Building surface at all times ( x,y The corresponding irradiance at point ) Indicates the reference value for irradiance. Exponentiation of the natural constant. , These represent the building height and the cloud top height, respectively. Represents the integral variable; and The coefficients represent the properties of clouds in terms of absorption and transmission of solar radiation, where... The absorption coefficient represents the ability of clouds to absorb solar radiation. It represents the scattering coefficient, which originates from the scattering effect of atmospheric molecules on shortwave radiation; The transmittance coefficient of clouds is used to characterize the proportion of radiation that clouds allow to pass through.

[0135] After constructing a radiation model of the building surface, the irradiance at each location 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 a preset time period can be obtained.

[0136] The above process, by combining historical meteorological data, three-dimensional networks, and the absorption and transmission properties of solar radiation by clouds, accurately predicts the irradiance distribution of each surface of the target building within a preset time period. The irradiance distribution reflects the power generation potential of photovoltaic modules at different time periods and locations, thus improving the accuracy and real-time performance of irradiance prediction.

[0137] In step S130, based on the irradiance distribution and the set threshold, a high irradiance zone and a low irradiance zone are divided, and corresponding photovoltaic modules and power controllers are deployed in the high irradiance zone and the low irradiance zone, respectively.

[0138] In this embodiment, the irradiance value at each location point is traversed, and the surface of the target building is divided into high-irradiance and low-irradiance zones based on its relative magnitude with a threshold. Subsequently, a deployment plan is automatically generated based on these zone divisions and the layout rules for photovoltaic modules and power controllers. In high-irradiance zones, it is recommended to install high-efficiency photovoltaic modules and configure corresponding power controllers to maximize energy output; while in low-irradiance zones, it is possible to select more adaptable or cost-effective module configurations, while adjusting the parameters of the power controllers to optimize energy utilization.

[0139] In one embodiment of this application, based on the irradiance distribution and a set threshold, a high-irradiance zone and a low-irradiance zone are divided, and corresponding photovoltaic modules and power controllers are deployed in the high-irradiance zone and the low-irradiance zone respectively, including:

[0140] Obtain the irradiance distribution at various locations on the surface of the target building within a preset time period. The irradiance was then averaged over time to obtain the average irradiance value at each location:

[0141]

[0142] in, This indicates that within a preset time period T, the target building is in Average irradiance at the location, The total duration of the preset time period. Indicates in t Target building surface at all times The corresponding irradiance at that location;

[0143] Set irradiance threshold ,when At that time, the target building The area is designated as a high-irradiation zone; when At that time, the target building The area is designated as a low-irradiance zone.

[0144] Photovoltaic modules and power controllers are respectively deployed in the high-irradiance zone and the low-irradiance zone.

[0145] In one embodiment of this application, based on the irradiance corresponding to each location in the irradiance distribution, when the irradiance corresponding to the location is greater than or equal to a set threshold, the location is classified as a high irradiance zone; when the irradiance corresponding to the location is less than the set threshold, the location is classified as a low irradiance zone.

[0146] After this, the results of dividing the high-irradiance and low-irradiance areas are stored using appropriate data structures, such as two-dimensional arrays or image masks.

[0147] Based on the division of high-irradiance and low-irradiance areas, a photovoltaic module deployment plan is generated. Specifically, the number, type, arrangement, and installation location of photovoltaic modules can be determined based on information such as irradiance. In addition, factors such as the spacing between photovoltaic modules, shading, orientation, and tilt angle can be considered to optimize power generation efficiency.

[0148] For example, because high-irradiance areas generate more energy and are suitable for storing large amounts of electrical energy, large-capacity lithium batteries can be configured in high-irradiance areas; while low-irradiance areas experience greater fluctuations and require rapid power smoothing, where supercapacitors charge and discharge quickly, so supercapacitors are configured. This method optimizes the configuration of photovoltaic modules in different regions, balancing the lifespan and energy efficiency of the photovoltaic modules.

[0149] For example, after calculating the illumination angle parameters through the above process, the illumination angle can be maximized so that the surface normal vector of the photovoltaic module is aligned with the sun as much as possible, thereby improving the energy capture efficiency of the photovoltaic module.

[0150] Simultaneously, based on the division of high-irradiance and low-irradiance areas, a corresponding power controller deployment scheme is generated. In this embodiment, the power controller is used to regulate the output power of the photovoltaic system. The power controller deployment scheme specifically includes factors such as the type, quantity, installation location, and connection method with other equipment of the power controller, ensuring that the power controller can operate stably under different irradiance conditions.

[0151] The above process, based on the predicted irradiance distribution and set thresholds, divides the building surface into high-irradiance and low-irradiance zones. This helps optimize the placement of photovoltaic (PV) modules, ensuring they fully utilize solar resources. Deploying high-efficiency PV modules in high-irradiance zones maximizes solar radiation utilization; while lower-efficiency but cheaper PV modules, or modules combined with other energy utilization methods, are used in low-irradiance zones. This differentiated layout not only improves the overall efficiency of PV power generation but also reduces system costs. Simultaneously, deploying corresponding power controllers in each zone enables precise control of the PV module's operating status, reducing the risk of damage due to poor lighting conditions and improving the PV module's power generation efficiency and energy utilization rate.

[0152] In step S140, the net benefit function in the power generation and energy storage process is determined based on the equipment parameters of the photovoltaic module, and the operating power of the photovoltaic module is determined according to the net benefit function.

[0153] In this embodiment, based on the equipment parameters of photovoltaic modules, such as conversion efficiency, cost, and lifespan, as well as the capacity and charge / discharge efficiency of the energy storage system, a power generation utility function and an energy storage cost function are constructed. These are then synthesized into a net benefit function that comprehensively considers both power generation revenue and energy storage cost. Under the premise of meeting energy demand and system constraints, the system iteratively searches for the photovoltaic module operating power that maximizes the net benefit function, thereby finding the optimal operating power configuration and maximizing the economic benefits of the photovoltaic system.

[0154] In one embodiment of this application, determining the net benefit function in the power generation and energy storage process based on the equipment parameters of the photovoltaic module, and determining the operating power of the photovoltaic module according to the net benefit function, includes:

[0155] Based on the equipment parameters of the photovoltaic module, the power generation utility function and energy storage cost function of the photovoltaic module are determined;

[0156] The net benefit function is determined based on the power generation utility function and the energy storage cost function;

[0157] The operating power of the photovoltaic module is determined based on the net benefit function.

[0158] In one embodiment of this application, the power generation utility function of the photovoltaic module is determined based on the device parameters of the photovoltaic module. for:

[0159]

[0160] in, i The identifier for photovoltaic modules, Indicates photovoltaic modules i power, Indicates photovoltaic modules i The unit power generation revenue coefficient, with the unit being yuan / kWh, is used to quantify the direct economic benefits brought by a unit of power generation. Indicates photovoltaic modules i The marginal cost coefficient for power generation, derived from historical data analysis, is expressed in yuan / kWh² and is used to suppress excessive power allocation and prevent diminishing returns due to excessive power.

[0161] Simultaneously, based on the equipment parameters of the photovoltaic module, the energy storage cost function of the photovoltaic module is determined. for:

[0162]

[0163] in, Indicates photovoltaic modules iThe energy storage cost coefficient, expressed in yuan, can be determined by the initial purchase cost, maintenance costs, and life cycle cost of photovoltaic modules to reflect the fixed cost of the energy storage system. Indicates photovoltaic modules i The power sensitivity coefficient is used to dynamically quantify the exponential impact of increased photovoltaic module power on cost, such as the negative impact of power increase on the lifespan and operating costs of energy storage systems.

[0164] Subsequently, based on the power generation utility function and the energy storage cost function, the photovoltaic module is determined. i At power Net benefit function at time for:

[0165]

[0166] in, It is a Lagrange multiplier, and the unit is yuan / kWh. n Indicates the total number of photovoltaic modules; This indicates the total load demand of the building's electrical system, expressed in kilowatts (kW).

[0167] After determining the net benefit function, the maximum value of the net benefit function is calculated. The power corresponding to the maximum net benefit function value is the operating power of the photovoltaic module, which specifically includes:

[0168] Step S401: Initialize the photovoltaic module's operating power vector and Lagrange multipliers ,in Indicates the photovoltaic module in the 0th iteration i The power;

[0169] Step S402: Based on the current power vector Based on the current power vector and the equipment parameters of each photovoltaic module, the net benefit function is used. Calculate the gradient of the net benefit function for each photovoltaic module. ;

[0170] Step S403: Update the photovoltaic module's operating power vector using an iterative optimization algorithm:

[0171]

[0172] in, The preset learning rate, This represents the partial derivative of the net benefit function with respect to power;

[0173] Step S404: Adjust the updated power value according to the power constraint conditions:

[0174]

[0175] in, , Photovoltaic modules i The minimum and maximum power limits allowed;

[0176] Step S405: Determine the iteration termination condition; if the change in the net benefit function value... If the power is less than the preset threshold ε, stop the iteration, output the optimal power vector, and determine the operating power of each photovoltaic module; otherwise, let k = k + 1, return to step S402 to continue the iteration, where... , These represent the net benefit function values ​​of the system calculated in the k-th and (k-1)-th iterations, respectively.

[0177] The above process, based on the equipment parameters of photovoltaic modules, determines the power generation utility function and energy storage cost function, and then constructs the net benefit function, which helps to evaluate the economic benefits of photovoltaic systems under different operating power levels. By maximizing the net benefit function, the optimal operating power of the photovoltaic modules can be determined. This ensures that the photovoltaic system maximizes economic benefits while meeting energy demands. It reduces energy waste and equipment damage caused by inappropriate operating power, and improves the economic efficiency and energy utilization efficiency of the photovoltaic system.

[0178] In step S150, the photovoltaic module is controlled to operate by the power controller based on its operating power.

[0179] In this embodiment, after determining the operating power of the photovoltaic module, a corresponding control command is generated and sent to the power controller via the communication interface. Upon receiving the command, the power controller uses a built-in parsing algorithm to convert the command into specific control signals, thereby precisely adjusting the operating state of the photovoltaic module, such as voltage and current, to generate electricity at the specified power.

[0180] In one embodiment of this application, controlling the operation of the photovoltaic module through the power controller based on the operating power of the photovoltaic module includes:

[0181] Based on the operating power of the photovoltaic module, generate configuration instructions;

[0182] The configuration command is sent to the power controller via the communication interface;

[0183] The power controller receives and parses the configuration instructions to control the photovoltaic modules to operate.

[0184] In one embodiment of this application, after determining the operating power of the photovoltaic module, a configuration instruction for the power controller is generated based on the operating power. This configuration instruction includes 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 instruction is sent to the power controller in a specific communication protocol format. Upon receiving the instruction, the power controller parses and executes the corresponding control operation, and then controls the photovoltaic module to operate at the operating power.

[0185] The above process, based on the photovoltaic (PV) module's operating power, generates configuration commands and sends them to the power controller via a communication interface, achieving remote and precise control of the PV module's operating status. The power controller receives and parses the configuration commands, controlling the PV modules to generate electricity at the specified operating power, ensuring the stable operation of the PV system and meeting energy demands. This reduces energy waste and equipment failure risks caused by improper control, achieves precise control of the PV module's operating status, and improves the system's stability and reliability.

[0186] In one embodiment of this application, after controlling the photovoltaic module to operate based on the operating power of the photovoltaic module through the power controller, the method further includes:

[0187] Obtain the operating parameters of the photovoltaic module;

[0188] The operating parameters are displayed on the monitor of the control platform.

[0189] In one embodiment of this application, a data acquisition module obtains real-time operating parameters from sensors or data acquisition interfaces of the photovoltaic module. The data acquisition module is connected to the photovoltaic module via wired or wireless means to ensure the real-time nature and accuracy of the data. The data acquisition module reads key operating parameters from the photovoltaic module, including but not limited to voltage, current, power, and temperature.

[0190] The collected operating parameters are transmitted to the control platform via data transmission channels (such as LAN, WAN, or serial communication). After receiving the data, the control platform parses and processes it, converting the raw data into a format suitable for display.

[0191] Optionally, the processed operating parameters can be displayed to the user in a graphical or textual manner, and the operating status of different time scales, different parameters, or different photovoltaic modules can be displayed through multiple interfaces or views.

[0192] Optionally, depending on the control platform configuration and user selection, the operating parameters of the photovoltaic modules can be displayed on the screen in real time. Display formats include numerical displays, graphical representations, and alarm indicators, allowing users to intuitively understand the operating status of the photovoltaic modules.

[0193] The above process, by acquiring the operating parameters of the photovoltaic modules in real time, provides data support for system monitoring and maintenance. These parameters are then displayed intuitively on the control platform's monitor, allowing maintenance personnel to understand the system's operating status and promptly identify and address potential problems. This enables real-time monitoring and management of the photovoltaic module's operating status, improving the efficiency of system monitoring and maintenance.

[0194] This application's technical solution involves acquiring structural information of a target building and constructing a three-dimensional network based on that information; obtaining cloud data via satellite meteorology and predicting the irradiance distribution on the target building's surface within a preset timeframe based on the cloud data and the three-dimensional network; dividing the area into high-irradiance and low-irradiance zones according to the irradiance distribution and a set threshold, and deploying corresponding photovoltaic modules and power controllers in each zone; determining the net benefit function for power generation and energy storage based on the photovoltaic module's equipment parameters, and determining the photovoltaic module's operating power based on the net benefit function; and controlling the photovoltaic module's operation using the power controller based on its operating power. By accurately predicting the irradiance distribution on the target building's surface and intelligently dividing it into high-irradiance and low-irradiance zones, the layout and operating power of the photovoltaic modules are optimized to precisely control their operating status. This not only improves the utilization rate of photovoltaic power generation but also reduces energy storage costs through intelligent control, thereby achieving efficient energy utilization and cost optimization.

[0195] Example 2:

[0196] The following describes an embodiment of the apparatus described in this application, which can be used to execute the integrated photovoltaic-storage collaborative optimization method for photovoltaic-storage-linear-flexible buildings as described in the above embodiments of this application. It is understood that the apparatus can be a computer program (including program code) running on a computer device, for example, the apparatus is application software; the apparatus can be used to execute the corresponding steps in the method provided in the embodiments of this application. For details not disclosed in the apparatus embodiments of this application, please refer to the above embodiments of the integrated photovoltaic-storage collaborative optimization method for photovoltaic-storage-linear-flexible buildings described in this application.

[0197] Figure 3 A block diagram of a photovoltaic-storage integrated collaborative optimization system for a building based on a direct-flexible photovoltaic building is shown according to an embodiment of this application.

[0198] Reference Figure 3 As shown, a photovoltaic-storage integrated collaborative optimization system for buildings with direct-drive and flexible photovoltaic systems, according to an embodiment of this application, includes:

[0199] Acquisition unit 310 is used to acquire the structural information of the target building and construct a three-dimensional network based on the structural information;

[0200] Irradiance unit 320 is used to acquire cloud data through satellite meteorology, and based on the cloud data and the three-dimensional network, predict the irradiance distribution of the target building surface within a preset time period;

[0201] The deployment unit 330 is used to divide the high irradiance zone and the low irradiance zone according to the irradiance distribution and the set threshold, and to deploy corresponding photovoltaic modules and power controllers in the high irradiance zone and the low irradiance zone respectively.

[0202] Efficiency unit 340 is used to determine the net benefit function in the power generation and energy storage process based on the equipment parameters of the photovoltaic module, and to determine the operating power of the photovoltaic module according to the net benefit function;

[0203] The control unit 350 is used to control the operation of the photovoltaic module through the power controller based on the operating power of the photovoltaic module.

[0204] In this application, based on the aforementioned scheme, the step 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 target building's position and orientation information and surface parameters; determining the local curvature of the target building at each position based on the surface parameters; determining the illumination angle parameters based on the position and orientation information and the local curvature; and modeling based on the local curvature and the illumination angle parameters to generate a three-dimensional network corresponding to the target building.

[0205] In this application, based on the aforementioned scheme, the step of acquiring cloud data via satellite meteorology and predicting the irradiance distribution of each interior of the target building within a preset time period based on the cloud data and the three-dimensional network includes: acquiring cloud data via satellite meteorology, wherein the cloud data includes a baseline irradiance value under cloudless conditions and attribute coefficients of cloud absorption and transmission of solar radiation; generating an irradiance model of the building surface based on the baseline irradiance value and the three-dimensional network, combined with the attribute coefficients of cloud absorption and transmission of solar radiation; and determining the irradiance distribution of the target building surface within a preset time period based on the irradiance model.

[0206] In this application, based on the aforementioned scheme, the step of dividing a high-irradiance zone and a low-irradiance zone according to the irradiance distribution and a set threshold, and deploying corresponding photovoltaic modules and power controllers in the high-irradiance zone and the low-irradiance zone respectively, includes: 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, classifying the position as a high-irradiance zone; when the irradiance corresponding to the position is less than the set threshold, classifying the position as a low-irradiance zone; and deploying corresponding photovoltaic modules and power controllers in the high-irradiance zone and the low-irradiance zone respectively.

[0207] In this application, based on the aforementioned scheme, determining the net benefit function in the power generation and energy storage process based on the equipment parameters of the photovoltaic module, and determining the operating power of the photovoltaic module based on the net benefit function, includes: determining the power generation utility function and energy storage cost function of the photovoltaic module based on the equipment parameters of the photovoltaic module; determining the net benefit function based on the power generation utility function and the energy storage cost function; and determining the operating power of the photovoltaic module based on the net benefit function.

[0208] In this application, based on the aforementioned scheme, controlling the operation of the photovoltaic module through the power controller based on the operating power of the photovoltaic module includes: generating a configuration instruction based on the operating power of the photovoltaic module; sending the configuration instruction to the power controller through a communication interface; and the power controller receiving and parsing the configuration instruction to control the operation of the photovoltaic module.

[0209] In this application, based on the aforementioned scheme, after controlling the photovoltaic module to work through the power controller based on the working power of the photovoltaic module, the method further includes: acquiring the working parameters of the photovoltaic module; and displaying the working parameters on the display of the control platform.

[0210] This application's technical solution involves acquiring structural information of a target building and constructing a three-dimensional network based on that information; obtaining cloud data via satellite meteorology and predicting the irradiance distribution on the target building's surface within a preset timeframe based on the cloud data and the three-dimensional network; dividing the area into high-irradiance and low-irradiance zones according to the irradiance distribution and a set threshold, and deploying corresponding photovoltaic modules and power controllers in each zone; determining the net benefit function for power generation and energy storage based on the photovoltaic module's equipment parameters, and determining the photovoltaic module's operating power based on the net benefit function; and controlling the photovoltaic module's operation using the power controller based on its operating power. By accurately predicting the irradiance distribution on the target building's surface and intelligently dividing it into high-irradiance and low-irradiance zones, the layout and operating power of the photovoltaic modules are optimized to precisely control their operating status. This not only improves the utilization rate of photovoltaic power generation but also reduces energy storage costs through intelligent control, thereby achieving efficient energy utilization and cost optimization.

[0211] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application is shown.

[0212] It should be noted that the computer system of the electronic device in this embodiment is only an example and should not impose any limitations on the function and scope of use of the embodiments of this application.

[0213] In this embodiment, the computer system includes a central processing unit 401, which can perform various appropriate actions and processes based on a program stored in a read-only memory 402 or a program loaded from a storage section 408 into a random access memory 403. For example, it can execute the integrated photovoltaic-storage collaborative optimization method for photovoltaic-storage-flexible buildings described in the above embodiment. The random access memory 403 also stores various programs and data required for system operation. The central processing unit 401, the read-only memory 402, and the random access memory 403 are interconnected via a bus 404. An input / output interface 405 is also connected to the bus 404.

[0214] The following components are connected to the input / output interface 405: an input section 406 including a keyboard, mouse, etc.; an output section 407 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 408 including a hard disk, etc.; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card, modem, etc. 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. A removable medium 411, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 410 as needed so that computer programs read from it can be installed into the storage section 408 as needed.

[0215] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program including a computer program for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 409, and / or installed from removable medium 411. When the computer program is executed by central processing unit 401, it performs various functions defined in the system of this application.

[0216] If the aforementioned 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 this invention, or the part that contributes to the prior art, or a part 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 to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0217] 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 these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A light storage integrated collaborative optimization method applied to a light storage direct flexible building, characterized in that, The method comprises the following steps: obtaining construction information of a target building, and constructing a three-dimensional network based on the construction information; obtaining cloud data through satellite meteorology, and predicting 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 a high-irradiance area and a low-irradiance area according to the irradiance distribution and a set threshold, and arranging corresponding photovoltaic components and power controllers in the high-irradiance area and the low-irradiance area respectively; determining a net benefit function in the power generation and energy storage process based on the equipment parameters of the photovoltaic components, and determining the working power of the photovoltaic components according to the net benefit function; controlling the photovoltaic components to work through the power controllers based on the working power of the photovoltaic components; The obtaining of the construction information of the target building and the construction of the three-dimensional network based on the construction information specifically comprises: obtaining the construction information of the target building, wherein the construction information comprises position and orientation information and surface parameters of the target building; determining a local curvature of the target building at each position based on the surface parameters , the formula is: wherein, represents coordinate information of the architectural surface, represents the corresponding surface parameters at the extracted interest point in the architectural surface, represents the coordinates of the interest point, represents the local curvature of the target building at ; According to the position orientation information, a solar direction vector corresponding to each time is determined , based on the solar direction vector and the local curvature , a cosine value corresponding to an included angle between a solar ray and a normal vector of the curved surface is determined as a light angle parameter : in, The illumination angle parameter represents the angle between the sunlight and the target building. The surface normal vector at time t t The cosine of the angle between them; This represents the partial derivative operation. express t The solar direction vector corresponding to the sun's position at any given time. t Indicates time, The magnitude of the solar direction vector; said local curvature in combination with the illumination angle parameter a grid-based modeling algorithm is employed to generate a three-dimensional network model containing both architectural geometry and dynamic lighting features, obtaining a three-dimensional network.

2. The method of claim 1, wherein the method is applied to a building with integrated photovoltaic and energy storage systems. The method comprises the following steps of: determining a sun direction vector corresponding to each time according to position orientation information , and specifically comprises: obtaining the position and orientation information of the target building, including the latitude B and the longitude L of the target building; calculating the solar time based on the longitude L: wherein, is solar time, is the local time of the target building, is the standard longitude, is the equation of time; Based on solar time Calculating the solar hour angle The formula for which is Based on the latitude B and the solar hour angle Calculate the solar altitude angle h(t) and solar azimuth angle. The calculation formula is as follows: wherein denotes the solar declination angle at the time t , , denotes the solar altitude angle and the solar azimuth angle at the time t , respectively; based on the solar elevation angle with the solar azimuth angle , a solar direction vector is constructed : wherein represents t the sun direction vector corresponding to the sun position at the time instant.

3. The integrated synergistic optimization method for photovoltaic-storage integrated building systems according to claim 1, characterized in that, The obtaining of the cloud data through satellite meteorology and the prediction of the irradiance distribution on the surface of the target building within a preset time based on the cloud data and the three-dimensional network specifically comprises: acquiring satellite meteorological data comprising a reference value of the irradiance in cloud-free conditions , the absorption and transmission coefficients of the cloud layer to the solar radiation, including the absorption coefficient , the transmission coefficient and the scattering coefficient ; based on the irradiance reference value , the attribute coefficient and the three-dimensional network model of the target building construction, combined with the local curvature at each position and the illumination angle parameter , the irradiance model of the building surface is constructed, and the irradiance at any moment t at any position of the target building surface is determined : wherein, represents the irradiance at the target building surface at time t , , represents the exponential operation of the natural constant, , respectively represent the roof height of the target building and the height of the cloud top, , respectively represent the cloud absorption coefficient and the transmission coefficient at the height , represents the scattering coefficient of atmospheric molecules, represents the local curvature of the target building at , is a lighting angle parameter, representing the cosine value of the angle between the sunlight and the normal vector of the curved surface of the target building at at time t ; determining the irradiance corresponding to each position of the target building at each time point based on an irradiance model to form the irradiance distribution on the surface of the target building within the preset time.

4. The method of claim 1, wherein the method is applied to a building with integrated photovoltaic and energy storage systems. The dividing of the high-irradiance area and the low-irradiance area according to the irradiance distribution and the set threshold specifically comprises: Obtain the irradiance distribution of each position of the target building surface within a preset time And time-domain average the irradiance to obtain the average irradiance value of each position: wherein, represents the average irradiance of the target building at the position within a preset time period T, is the total duration of the preset time period, represents the corresponding irradiance at the t moment of time on the surface of the target building at the position. Setting an irradiance threshold When the target building is divided into a high irradiance zone; when the target building is divided into a low irradiance zone.

5. The method of claim 1 or 4, applied to a light-storage integrated cooperative optimization method for a light-storage integrated flexible building, characterized in that, The arranging of the corresponding photovoltaic components and power controllers in the high-irradiance area and the low-irradiance area specifically comprises: arranging high-efficiency photovoltaic components according to the area and average irradiance of the high-irradiance area, wherein the high-efficiency photovoltaic components are configured with high-capacity lithium batteries as energy storage units and are equipped with corresponding power controllers; arranging adaptive and low-cost photovoltaic components according to the area and average irradiance of the low-irradiance area, and configuring super capacitors as fast-response energy storage devices and equipping corresponding power controllers. 6.The method for integrated optimization of photovoltaic and energy storage applied to a building with photovoltaic and energy storage according to claim 1, wherein, The determination of the net benefit function in the power generation and energy storage process based on the equipment parameters of the photovoltaic components specifically comprises: determining a power production utility function for the photovoltaic assembly based on the device parameters of the photovoltaic assembly : wherein, i represents an identity of the photovoltaic module, represents a power of the photovoltaic module i , represents a unit power generation benefit coefficient of the photovoltaic module i , represents a power generation marginal cost coefficient of the photovoltaic module i . determining an energy storage cost function for the photovoltaic assembly based on device parameters of the photovoltaic assembly : wherein, represents the energy storage cost coefficient of a photovoltaic module i ; represents the power sensitivity coefficient of a photovoltaic module i ; determining a photovoltaic assembly according to the power generation utility function and the energy storage cost function i a net benefit function at power :​ wherein, is a Lagrange multiplier; n represents the total number of photovoltaic assemblies; represents the total load demand of the building electrical system.

7. The method of claim 1, wherein the method is applied to a light storage integrated cooperative optimization method for a light storage direct flexible building. The determination of the working power of the photovoltaic components according to the net benefit function specifically comprises: Step S401 : initializing the photovoltaic module operating power vector and the Lagrange multiplier where denotes the power of the photovoltaic module i at the 0th iteration. Step S402: Based on the current power vector , according to the current power vector and the device parameters of each photovoltaic module, the net benefit function of each photovoltaic module is calculated by the net benefit function The gradient of the net benefit function of each photovoltaic module is calculated ; Step S403: updating the photovoltaic component working power vector by using an iterative optimization algorithm: wherein, is a preset learning rate, denotes the partial derivative of the net benefit function with respect to power; Step S404: adjusting 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... If the power is less than the preset threshold, stop the iteration, output the optimal power vector, and determine the working power of each photovoltaic module; otherwise, let k=k+1 and return to step S402 to continue the iteration. 8.The method of claim 1, wherein the method is applied to a building with integrated photovoltaic and energy storage systems. The controlling of the photovoltaic components to work through the power controllers based on the working power of the photovoltaic components specifically comprises: generating a configuration instruction based on the working power of the photovoltaic components; sending the configuration instruction to the power controller through a communication interface; The power controller receives and analyzes the configuration instruction to control the photovoltaic components to work.

9. A system for the photovoltaic-storage integrated collaborative optimization method applied to the light storage direct flexible building according to any one of claims 1-8, characterized in that, It comprises: an obtaining unit configured to obtain construction information of a target building, and construct a three-dimensional network based on the construction 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; The layout unit is configured to divide a high irradiance area and a low irradiance area according to the irradiance distribution and a set threshold, and to respectively arrange corresponding photovoltaic modules and power controllers in the high irradiance area and the low irradiance area. The efficiency unit is configured to determine a net benefit function in power generation and energy storage based on device parameters of the photovoltaic modules, and to determine an operating power of the photovoltaic modules according to the net benefit function. The control unit is configured to control the photovoltaic modules to operate through the power controllers based on the operating power of the photovoltaic modules.

Images