Improved photovoltaic combined heat and power generation method and system based on data center

Abstract

The invention discloses an improved photovoltaic combined heat and power generation method and system based on a data center, and relates to the technical field of photovoltaic combined heat and power generation, and the method comprises the steps: obtaining the total illumination energy received by a photovoltaic power station over the years based on the data center, and calculating the average total illumination energy received every year; calculating waste heat energy and waste electric energy according to the average annual received total illumination energy and the average annual electric energy merged into the power grid by the photovoltaic power station; waste heat energy generated on a photovoltaic panel is obtained based on the waste heat energy, the waste heat energy generated on the photovoltaic panel is graded, and a multi-layer heat conduction structure is designed for each grade. Waste heat energy generated by the photovoltaic panel is effectively managed through the intelligent control system and the multi-layer heat conduction structure. By setting a heat energy grade and a corresponding multi-layer structure, the system can provide an optimal heat management solution for different heat loads, the heat energy loss is reduced, and the photovoltaic panel is kept at the optimal working temperature, so that the electric energy conversion efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of photovoltaic cogeneration, and in particular to an improved photovoltaic cogeneration method and system based on a data center. Background Art

[0002] With the growth of global energy demand and the improvement of environmental awareness, the use of renewable energy has become the focus of energy policy and technology development. Among the many renewable energy technologies, photovoltaic power generation has attracted much attention due to its clean and sustainable characteristics. However, in the process of converting solar energy into electrical energy, most of the energy in the photovoltaic power generation system is lost in the form of heat, which leads to low efficiency of photovoltaic panels and excessively high operating temperatures, which may shorten the service life. In order to improve energy efficiency, photovoltaic combined heat and power (PV / T) systems have emerged. The system can not only generate electricity, but also recycle and utilize heat energy for heating, hot water or other industrial processes, thereby realizing the comprehensive utilization of energy and maximizing efficiency.

[0003] Although photovoltaic cogeneration systems have the potential to improve energy efficiency, they still face technical challenges in practical applications:

[0004] Inadequate thermal management design: Existing PV cogeneration systems have deficiencies in thermal management, with common problems including low heat recovery efficiency and uneven heat distribution. This causes the temperature of the PV panels to be too high, affecting their power output efficiency and potentially shortening the life of the equipment.

[0005] Inadequacies in control and optimization technology: Control systems in many existing PV cogeneration systems often lack precision and are unable to adjust the system in real time to respond to environmental changes, such as temperature fluctuations and changes in sunlight. In addition, the lack of advanced data analysis capabilities prevents the system from being optimized based on historical and real-time data, affecting the overall efficiency and response speed of the system.

[0006] In response to the above technical challenges, the present invention proposes a photovoltaic cogeneration method and system based on data center improvements. The specific innovations and improvements are as follows: Based on the historical data of the data center, the present invention sets up heat dissipation demand gears for photovoltaic power stations. According to different gears, the advanced multi-layer heat conduction structure is integrated to effectively improve the efficiency of heat transfer from photovoltaic panels to heat exchangers. This structure uses high thermal conductivity materials and optimizes the heat flow path to evenly distribute heat and reduce local overheating.

[0007] This system uses advanced intelligent control systems and data analysis technology to automatically adjust cooling and thermal management strategies by real-time monitoring of environmental and system parameters. Summary of the invention

[0008] In view of the above-mentioned problems, the present invention is proposed.

[0009] Therefore, the problem to be solved by the present invention is that the existing photovoltaic cogeneration system has deficiencies in thermal management design, and deficiencies in control and optimization technology.

[0010] In order to solve the above technical problems, the present invention provides the following technical solutions: an improved photovoltaic cogeneration method based on a data center, comprising: obtaining the total light energy received by the photovoltaic power station in previous years based on the data center, and calculating the average total light energy received each year; obtaining the electric energy that should be produced each year based on the average total light energy received each year and various parameters of the photovoltaic panel, and obtaining the average electric energy connected to the power grid by the photovoltaic power station each year based on the data center, and calculating the waste heat energy and the waste electric energy; obtaining the waste heat energy generated on the photovoltaic panel based on the waste heat energy, classifying the waste heat energy generated on the photovoltaic panel, and designing a multi-layer heat conduction structure for each grade; the multi-layer heat conduction structure is externally connected to a circulation system, and the circulation flow rate is controlled by the data center; and a fan with an adaptive power is set in the photovoltaic panel based on the waste electric energy, and the fan is controlled to be turned on and off by the data center.

[0011] As a preferred solution of the photovoltaic cogeneration method based on data center improvement described in the present invention, wherein: the calculation of the average annual total light energy received includes determining the light energy E at any time t sun (t) is expressed as,

[0012] E sun (t) = I local (t)×A PV

[0013] Among them, I local (t) represents the solar radiation intensity of the area corresponding to the photovoltaic power station at time t, A PV It is expressed as the total solar energy receiving surface area of ​​the photovoltaic power station; the total solar energy accumulated in one year is expressed as,

[0014]

[0015] Where T represents the total number of hours in a year; for each year y, the annual total sunlight energy E year (y) is expressed as,

[0016]

[0017] Calculate from year y start to y end The total sunlight energy during the period is E year (y) is summed and expressed as,

[0018]

[0019] Finally, the average annual total light energy E avg_year It is expressed as,

[0020]

[0021] As a preferred solution of the photovoltaic cogeneration method based on the data center improvement described in the present invention, wherein: the electric energy that should be produced each year includes the average annual total sunlight energy E avg_year The expected output electric energy E is calculated based on the parameters of the photovoltaic panels prod , expressed as,

[0022] E prod =E avg_year ×η×A×F eff (θ,β,T avg )

[0023]

[0024] Where η represents the average energy conversion efficiency of the photovoltaic panel, A represents the total receiving area of ​​the photovoltaic panel, and F eff (θ,β,T avg ) is expressed as the adjustment factor function, θ is the average incident angle of sunlight, β is the installation inclination angle of the photovoltaic panel, T avg Expressed as the average operating temperature of the photovoltaic panel, T opt It is represented as the optimal operating temperature, ΔT is represented as the rate constant of temperature deviation efficiency reduction; the waste heat energy includes the waste heat energy Q obtained by subtracting the expected output electricity from the average annual total sunlight energy waste , expressed as,

[0025] Q waste =E avg_year -E prod

[0026] The wasted electric energy includes the wasted electric energy obtained by subtracting the electric energy fed into the power grid from the expected output electric energy, expressed as:

[0027] E waste =E prod -E grid

[0028] Among them, E grid It is expressed as the average annual electrical energy connected to the grid by photovoltaic power stations.

[0029] As a preferred solution of the photovoltaic cogeneration method based on the improvement of the data center described in the present invention, wherein: the waste heat energy generated on the photovoltaic panels includes defining the ratio R of the photovoltaic panels to the total area of ​​the photovoltaic power station as:

[0030]

[0031] Based on the ratio R, the waste heat energy is divided into two parts, including the waste heat energy Q irradiated on the photovoltaic panel waste_panel and the waste heat energy Q radiated to the ground waste_ground , the formula is expressed as,

[0032] Q waste_panel =(E avg_year -E prod )×R

[0033] Q waste_ground =(E avg_year -E prod )×(1-R).

[0034] As a preferred solution of the photovoltaic cogeneration method based on the data center improvement described in the present invention, wherein: the multi-layer heat conduction structure designed for each level includes: the waste heat energy Q irradiated on the photovoltaic panel waste_panel Compare with the threshold to determine the cooling level; when

[0035] Q waste_panel ≤500kWh / m 2 When 500kWh / m 2 <Q waste_panel ≤1000kWh / m 2 When Q waste_panel >1000kWh / m 2 When it is determined to be high-end heat dissipation; when it is determined to be low-end heat dissipation or mid-end heat dissipation, the multi-layer heat conduction structure is a two-layer structure; when it is determined to be high-end heat dissipation, the multi-layer heat conduction structure is a three-layer structure; when it is the two-layer structure, the first layer is the contact layer, and the second layer is the environmental interface layer; when it is the three-layer structure, the first layer is the contact layer, the second layer is the thermal isolation layer, and the third layer is the environmental interface layer; the contact layer adopts a material with high thermal conductivity; the thermal isolation layer adopts a material with high thermal insulation performance and stable structure; the environmental interface layer adopts a material with high heat dissipation efficiency performance.

[0036] As a preferred solution of the photovoltaic cogeneration method based on data center improvement described in the present invention, the circulation system is provided with a thermal sensor at each connection with the heat conduction structure of the photovoltaic panel, the thermal sensor collects the temperature of the photovoltaic panel and sends it to the data center, and the data center controls the power of the fluid pump according to the temperature of the photovoltaic panel, thereby controlling the circulation flow rate.

[0037] As a preferred solution of the improved photovoltaic cogeneration method based on a data center described in the present invention, the fan with adaptive power includes setting a fan that adapts to the power of waste electric energy for the photovoltaic panel based on the waste electric energy, and when the temperature data collected by the data center is greater than the optimal operating temperature threshold, the data center controls the fan to turn on, and the fan is powered by the electric energy converted by the photovoltaic panel.

[0038] Another object of the present invention is to provide an improved photovoltaic cogeneration system based on a data center, which can control the photovoltaic cogeneration system.

[0039] In order to solve the above technical problems, the present invention provides the following technical solutions: a system based on an improved photovoltaic cogeneration method of a data center, comprising: a data acquisition module, a waste energy calculation module, a structural design module and a control module; the data acquisition module obtains the total light energy received by the photovoltaic power station in previous years and the average annual electric energy connected to the power grid by the photovoltaic power station based on the data center; the waste energy calculation module calculates the average annual total light energy received by the photovoltaic power station through the total light energy received by the photovoltaic power station in previous years, obtains the electric energy that should be produced each year based on the average annual total light energy received and various parameters of the photovoltaic panel, and then calculates the waste heat energy and the waste electric energy based on the average annual electric energy connected to the power grid by the photovoltaic power station; the structural design module obtains the waste heat energy generated on the photovoltaic panel based on the waste heat energy, grades the waste heat energy generated on the photovoltaic panel, and designs a multi-layer heat conduction structure for each grade;

[0040] The control module controls the circulation flow rate of the circulation system and the opening and closing of the fan in the photovoltaic panel through the data center.

[0041] A computer device includes a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the photovoltaic cogeneration method based on data center improvement are implemented.

[0042] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the photovoltaic cogeneration method based on data center improvement as described above.

[0043] The beneficial effects of the present invention are as follows: the present invention effectively manages the waste heat energy generated by the photovoltaic panel through an intelligent control system and a multi-layer heat conduction structure. By setting the heat energy level and the corresponding multi-layer structure, the system can provide the best thermal management solution for different heat loads, reduce heat energy loss, keep the photovoltaic panel at the best operating temperature, and thus improve the power conversion efficiency.

[0044] By utilizing the computing power of the data center, the present invention realizes real-time monitoring and performance optimization of the photovoltaic cogeneration system. The system can collect environmental changes in real time, dynamically adjust the cycle rate and fan cooling, optimize the output of photovoltaic panels and the use of thermal energy, and improve the system response efficiency and operational flexibility. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0046] Figure 1 This is a flow chart of an improved photovoltaic cogeneration method based on a data center in Example 1.

[0047] Figure 2 This is a module structure diagram of an improved photovoltaic cogeneration system based on a data center in Example 3. DETAILED DESCRIPTION

[0048] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0049] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0050] Example 1, reference Figure 1 , which is the first embodiment of the present invention, and which provides a photovoltaic cogeneration method based on data center improvement, including: Figure 1 As shown:

[0051] Step 1: Based on the data center, obtain the total amount of light energy received by the photovoltaic power station over the years and calculate the average total amount of light energy received each year.

[0052] According to the historical data collected by the data center, the light energy E at any time t is determined sun (t) is expressed as,

[0053] E sun (t) = I local (t)×A PV

[0054] Among them, I local(t) represents the solar radiation intensity of the area corresponding to the photovoltaic power station at time t, A PV It is expressed as the total surface area of ​​the photovoltaic power station that receives solar energy.

[0055] The total sunlight energy accumulated in one year is expressed as,

[0056]

[0057] Where T represents the total number of hours in a year.

[0058] For each year y, the annual total sunlight energy E year (y) is expressed as,

[0059]

[0060] Calculate from year y start to y end The total sunlight energy during the period is E year (y) is summed and expressed as,

[0061]

[0062] Finally, the average annual total light energy E avg_year It is expressed as,

[0063]

[0064] Step 2: Based on the average total annual sunlight energy received and the various parameters of the photovoltaic panels, the electricity that should be produced each year is obtained. Based on the data center, the average annual electricity that the photovoltaic power station feeds into the grid is obtained, and the waste heat energy and waste electricity are calculated.

[0065] Based on the average annual total sunlight energy E avg_year The expected output electric energy E is calculated based on the parameters of the photovoltaic panels prod , expressed as,

[0066] E prod =E avg_year ×η×A×F eff (θ,β,T avg )

[0067]

[0068] Where η represents the average energy conversion efficiency of the photovoltaic panel, A represents the total receiving area of ​​the photovoltaic panel, and F eff (θ,β,T avg ) is expressed as the adjustment factor function, θ is the average incident angle of sunlight, β is the installation inclination angle of the photovoltaic panel, T avgExpressed as the average operating temperature of the photovoltaic panel, T opt It is represented as the optimum operating temperature, and ΔT is represented as the rate constant of efficiency reduction due to temperature deviation.

[0069] The calculation method of waste heat energy includes subtracting the expected output electricity from the average annual total solar energy to obtain the waste heat energy Q waste , expressed as,

[0070] Q waste =E avg_year -E prod

[0071] The calculation method of the wasted electric energy includes subtracting the electric energy fed into the grid from the expected output electric energy to obtain the wasted electric energy, expressed as,

[0072] E waste =E prod -E grid

[0073] Among them, E grid It is expressed as the average annual electrical energy connected to the grid by photovoltaic power stations.

[0074] The ratio of photovoltaic panels to the total area of ​​photovoltaic power stations is defined as R,

[0075]

[0076] Based on the ratio R, the waste heat energy is divided into two parts, including the waste heat energy Q irradiated on the photovoltaic panel waste_panel and the waste heat energy Q radiated to the ground waste_ground , the formula is expressed as,

[0077] Q waste_panel =(E avg_year -E prod )×R

[0078] Q waste_ground =(E avg_year -E prod )×(1-R).

[0079] Step 3: Based on the waste heat energy, the waste heat energy generated on the photovoltaic panels is obtained, the waste heat energy generated on the photovoltaic panels is graded, and a multi-layer heat conduction structure is designed for each grade.

[0080] The waste heat energy Q waste_panel Compare with the threshold to determine the heat dissipation level;

[0081] When Q waste_panel ≤500kWh / m 2 When 500kWh / m2 <Q waste_panel ≤1000kWh / m 2 When Q waste_panel >1000kWh / m 2 When , it is judged as high-end cooling.

[0082] Photovoltaic panels typically have a conversion efficiency of between 15% and 20%, meaning that approximately 80% to 85% of the received solar energy is converted into heat and not used as electricity.

[0083] Based on this efficiency, it can be estimated that under typical sunlight conditions, photovoltaic panels receive about 1000 to 1500 kWh of solar energy per square meter per year. Therefore, waste heat (the part that is not converted into electricity) accounts for a large part of this total energy.

[0084] Although these thresholds for determining gear positions are set based on general experience and typical data, they also need to adapt to different geographical and climatic conditions. For example, in areas with stronger sunlight, high thermal energy thresholds may be more common, while in areas with weaker sunlight, low thermal energy thresholds may be more applicable. The threshold of the present invention is an average value based on existing approximate light energy data, and the threshold can be set for a specific environment based on data collected by an actual photovoltaic power plant.

[0085] Setting thresholds in this way can help system designers and operators select appropriate thermal management strategies based on different thermal energy levels, taking into account both the system's operating efficiency and optimizing costs and implementation complexity. The setting of these thresholds provides a standardized reference for thermal management of photovoltaic systems, helping to make more informed decisions during the design and evaluation process.

[0086] When it is determined to be low-grade heat dissipation or medium-grade heat dissipation, the multi-layer heat conduction structure is a two-layer structure; when it is determined to be high-grade heat dissipation, the multi-layer heat conduction structure is a three-layer structure.

[0087] When it is a two-layer structure, the first layer is the contact layer and the second layer is the environmental interface layer.

[0088] When it is a three-layer structure, the first layer is the contact layer, the second layer is the thermal isolation layer, and the third layer is the environmental interface layer.

[0089] The contact layer is made of materials with high thermal conductivity; the thermal isolation layer is made of materials with high thermal insulation performance and stable structure; and the environmental interface layer is made of materials with high heat dissipation efficiency.

[0090] For example, low thermal energy level - double layer structure:

[0091] First layer (contacting the photovoltaic panel): Aluminum-based alloy, preferably with high thermal conductivity to conduct heat quickly.

[0092] Second layer (environmental interface): graphene coating to improve heat dissipation efficiency while providing light weight and high environmental stability.

[0093] Medium thermal energy level-double layer structure:

[0094] First layer (contacting the PV panel): Copper, suitable for medium heat loads due to its excellent thermal conductivity.

[0095] Second layer (environmental interface): Phase change material (PCM) layer, which absorbs and stores excess heat and is able to release thermal energy when the temperature drops.

[0096] High thermal energy level - three-layer structure, for high thermal energy, use a three-layer structure to maximize the management and utilization of thermal energy:

[0097] First layer (contacting the photovoltaic panel): Silver-based alloy, providing the highest level of thermal conductivity.

[0098] Second layer: Alumina (Al2O3) ceramic, acts as a thermal insulation layer, reducing heat loss to the external environment while maintaining the mechanical strength of the structure.

[0099] Third layer (environmental interface): high thermal conductivity graphene composite material for efficient heat dissipation while taking advantage of graphene’s high thermal conductivity and mechanical stability.

[0100] The material design of each layer can be tailored based on specific environmental factors and economic considerations.

[0101] Step 4: The multi-layer heat conduction structure is connected to an external circulation system to control the circulation flow rate through the data center.

[0102] The circulation system is equipped with a thermal sensor at each connection point with the heat conduction structure of the photovoltaic panel. The thermal sensor collects the temperature of the photovoltaic panel and sends it to the data center. The data center controls the power of the fluid pump according to the temperature of the photovoltaic panel, thereby controlling the circulation flow rate.

[0103] Step 5: A fan with adaptive power is set in the photovoltaic panel based on the waste electricity, and the fan is controlled by the data center.

[0104] Based on the waste electricity, fans that adapt to the waste electricity power are set for the photovoltaic panels (fans that can drive the corresponding power are selected according to the waste electricity). When the temperature data collected by the data center is greater than the optimal operating temperature threshold, the data center controls the fans to turn on, and the fans are powered by the electricity converted by the photovoltaic panels (generally, when the temperature is high, the light intensity is sufficient, the amount of electricity converted is large, and there will be no power shortage).

[0105] Embodiment 2, the second embodiment of the present invention, is different from the first embodiment in that: an improved photovoltaic cogeneration method and system based on a data center also includes: in order to verify and illustrate the technical effects adopted in this method, this embodiment adopts a traditional technical solution and the method of the present invention for comparative testing, and compares the test results by means of scientific demonstration to verify the real effect of this method.

[0106] The method of the present invention and the traditional method were loaded into the simulation model for testing. (The simulation model simulates the working conditions of a photovoltaic power station for one year)

[0107] The obtained data are summarized and a test comparison table is drawn, as shown in Table 1:

[0108] Table 1: Test data comparison table

[0109]

[0110] Energy efficiency: The present invention integrates advanced multi-layer heat conduction structures according to different gears to effectively improve the efficiency of heat transfer from photovoltaic panels to heat exchangers. It adopts advanced intelligent control systems and data analysis technologies, and automatically adjusts cooling and thermal management strategies by real-time monitoring of environmental and system parameters, greatly improving the comprehensive efficiency of energy utilization. As can be seen from the table, the efficiency has increased from 15% to 25%, which is achieved through a more efficient energy capture and conversion mechanism.

[0111] Electrical and thermal energy output: Compared with traditional photovoltaic systems, the data center-based system not only improves electrical energy output, but also achieves effective thermal energy recovery. This proves that solar energy can be more fully utilized in the data center environment.

[0112] Environmental impact (CO2 emission reduction): Due to the improvement of energy efficiency and the reduction of dependence on fossil energy, CO2 emissions have been significantly reduced and the environmental impact has been alleviated.

[0113] Example 3, reference Figure 2, which is the third embodiment of the present invention, and is different from the previous two embodiments in that: a system of photovoltaic cogeneration method based on data center improvement, including a data acquisition module, a waste energy calculation module, a structure design module and a control module; the data acquisition module obtains the total light energy received by the photovoltaic power station in previous years and the average annual electric energy connected to the power grid by the photovoltaic power station based on the data center; the waste energy calculation module calculates the average annual total light energy received by the photovoltaic power station through the total light energy received by the photovoltaic power station in previous years, obtains the electric energy that should be produced each year based on the average annual total light energy received and various parameters of the photovoltaic panel, and then calculates the waste heat energy and the waste electric energy based on the average annual electric energy connected to the power grid by the photovoltaic power station; the structure design module obtains the waste heat energy generated on the photovoltaic panel based on the waste heat energy, grades the waste heat energy generated on the photovoltaic panel, and designs a multi-layer heat conduction structure for each grade; the control module controls the circulation flow rate of the circulation system and the opening and closing of the fan in the photovoltaic panel through the data center.

[0114] If the functions are implemented in the form of 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 part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0115] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in conjunction with such instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in conjunction with such instruction execution systems, devices or apparatuses.

[0116] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0117] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0118] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A photovoltaic cogeneration method based on data center improvement, characterized by: include, Based on the data center, the total amount of sunlight received by the photovoltaic power station over the years is obtained, and the average total amount of sunlight received per year is calculated; The electricity that should be produced each year is obtained based on the average total amount of sunlight received each year and the various parameters of the photovoltaic panels. The average amount of electricity that the photovoltaic power station feeds into the power grid each year is obtained based on the data center, and the waste heat and waste electricity are calculated. Based on the waste heat energy, the waste heat energy generated on the photovoltaic panel is obtained, the waste heat energy generated on the photovoltaic panel is graded, and a multi-layer heat conduction structure is designed for each grade; The multi-layer heat conduction structure is connected to an external circulation system, and the circulation flow rate is controlled by the data center; Based on the waste electricity, power-adaptive fans are set in the photovoltaic panels, and the data center controls the fans to start and stop.

2. The photovoltaic cogeneration method based on data center improvement according to claim 1, characterized in that: The calculation of the average annual total light energy received includes determining the light energy E at any time t. sun (t) is expressed as, E sun (t)=I local (t)×A PV Among them, I local (t) represents the solar radiation intensity of the area corresponding to the photovoltaic power station at time t, A PV It is expressed as the total surface area of ​​PV power station receiving solar energy; The total sunlight energy accumulated in one year is expressed as, Where T represents the total number of hours in a year; For each year y, the annual total sunlight energy E year (y) is expressed as, Calculate from year y start to y end The total sunlight energy during the period is E year (y) is summed and expressed as, Finally, the average annual total light energy E avg_year It is expressed as, 3. The photovoltaic cogeneration method based on data center improvement according to claim 2, characterized in that: The electrical energy that should be produced each year includes the average annual total sunlight energy E avg_year The expected output electric energy E is calculated based on the parameters of the photovoltaic panels prod , expressed as, E prod =E avg_year ×η×A×F eff (θ,β,T avg ) Where η represents the average energy conversion efficiency of the photovoltaic panel, A represents the total receiving area of ​​the photovoltaic panel, and F eff (θ,β,T avg ) is expressed as the adjustment factor function, θ is the average incident angle of sunlight, β is the installation inclination angle of the photovoltaic panel, T avg Expressed as the average operating temperature of the photovoltaic panel, T opt It is represented as the optimal operating temperature, and ΔT is represented as the rate constant of the decrease in efficiency due to temperature deviation; The waste heat energy includes the waste heat energy Q obtained by subtracting the estimated output electricity from the average annual total solar energy. waste , expressed as, Q waste =And avg_year -AND prod The wasted electric energy includes the wasted electric energy obtained by subtracting the electric energy fed into the power grid from the expected output electric energy, expressed as: AND waste =And prod -AND grid Among them, E grid It is expressed as the average annual electrical energy connected to the grid by photovoltaic power stations.

4. The photovoltaic cogeneration method based on data center improvement according to claim 3, characterized in that: The waste heat energy generated by the photovoltaic panels includes defining the ratio R of the photovoltaic panels to the total area of ​​the photovoltaic power station as: Based on the ratio R, the waste heat energy is divided into two parts, including the waste heat energy Q irradiated on the photovoltaic panel waste_panel and the waste heat energy Q radiated to the ground waste_ground , the formula is expressed as, Q waste_panel =(And avg_year -AND prod )×R Q waste_ground =(E avg_year -E prod )×(1-R)。 5. The photovoltaic cogeneration method based on data center improvement according to claim 4, characterized in that: The design of a multi-layer heat conduction structure for each level includes: waste_panel Compare with the threshold to determine the heat dissipation level; When Q waste_panel ≤500kWh / m 2 When 500kWh / m 2 <Q waste_panel ≤1000kWh / m 2 When Q waste_panel >1000kWh / m 2 When , it is judged as high-end cooling; When it is determined to be low-grade heat dissipation or medium-grade heat dissipation, the multi-layer heat conduction structure is a two-layer structure; when it is determined to be high-grade heat dissipation, the multi-layer heat conduction structure is a three-layer structure; When it is a two-layer structure, the first layer is a contact layer, and the second layer is an environmental interface layer; When it is a three-layer structure, the first layer is a contact layer, the second layer is a thermal isolation layer, and the third layer is an environmental interface layer; The contact layer is made of a material with high thermal conductivity; the thermal isolation layer is made of a material with high thermal insulation performance and stable structure; and the environmental interface layer is made of a material with high heat dissipation efficiency.

6. The photovoltaic cogeneration method based on data center improvement according to claim 5, characterized in that: The circulation system is provided with a thermal sensor at each connection with the heat conduction structure of the photovoltaic panel. The thermal sensor collects the temperature of the photovoltaic panel and sends it to the data center. The data center controls the power of the fluid pump according to the temperature of the photovoltaic panel, thereby controlling the circulation flow rate.

7. The photovoltaic cogeneration method based on data center improvement according to claim 6, characterized in that: The method of setting a fan with adaptive power includes setting a fan with adaptive power for the photovoltaic panel based on the waste electric energy. When the temperature data collected by the data center is greater than the optimal operating temperature threshold, the data center controls the fan to turn on. The fan is powered by the electric energy converted by the photovoltaic panel.

8. A system using the photovoltaic cogeneration method based on the data center improvement as claimed in any one of claims 1 to 7, characterized in that: It includes data acquisition module, waste energy calculation module, structure design module and control module; The data acquisition module obtains the total amount of light energy received by the photovoltaic power station over the years and the average amount of electric energy that the photovoltaic power station integrates into the power grid each year based on the data center; The waste energy calculation module calculates the average total amount of light energy received each year through the total amount of light energy received by the photovoltaic power station over the years, obtains the amount of electric energy that should be produced each year based on the average total amount of light energy received each year and various parameters of the photovoltaic panels, and then calculates the waste heat energy and waste electric energy based on the average amount of electric energy that the photovoltaic power station incorporates into the power grid each year; The structural design module obtains the waste heat energy generated on the photovoltaic panel based on the waste heat energy, divides the waste heat energy generated on the photovoltaic panel into grades, and designs a multi-layer heat conduction structure for each grade; The control module controls the circulation flow rate of the circulation system and the opening and closing of the fan in the photovoltaic panel through the data center.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the photovoltaic cogeneration method based on data center improvement described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of a photovoltaic cogeneration method based on data center improvement described in any one of claims 1 to 7 are implemented.

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