Data-center-based improved photovoltaic / thermal cogeneration method and system

Abstract

The present invention relates to the technical field of photovoltaic / thermal cogeneration. Disclosed are a data-center-based improved photovoltaic / thermal cogeneration method and system. The method comprises: on the basis of a data center, acquiring the total solar irradiance energy received by a photovoltaic power station over the years, and calculating the average annual total solar irradiance energy received; on the basis of the average annual total solar irradiance energy received and the average annual electric energy fed into a power grid by the photovoltaic power station, calculating waste thermal energy and waste electric energy; and on the basis of the waste thermal energy, obtaining waste thermal energy generated on photovoltaic panels, grading the waste thermal energy generated on the photovoltaic panels, and designing a multi-layer thermal conduction structure for each grade. By means of an intelligent control system and multi-layer thermal conduction structures, the present invention effectively manages waste thermal energy generated by photovoltaic panels. By means of setting thermal-energy grades and corresponding multi-layer structures, the system can provide optimal thermal management solutions for different thermal loads, such that thermal energy losses can be reduced, and the photovoltaic panels can be maintained at an optimal operating temperature, thereby improving the efficiency of electric-energy conversion.

Description

Photovoltaic cogeneration method and system based on data center improvement TECHNICAL FIELD

[0001] The present application relates to the field of photovoltaic cogeneration technology, and particularly relates to a photovoltaic cogeneration method and system based on data center improvement. BACKGROUND

[0002] With the growth of global energy demand and the increasing awareness of environmental protection, 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 electricity, most of the energy is lost in the form of heat, which leads to low efficiency of photovoltaic panels and high operating temperature that may shorten the service life. In order to improve energy utilization efficiency, photovoltaic cogeneration (PV / T) systems have emerged, which not only generate electricity but also recover and utilize heat energy for heating, hot water or other industrial processes, thereby achieving comprehensive utilization of energy and maximizing efficiency.

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

[0004] Insufficient heat management design: Existing photovoltaic cogeneration systems have deficiencies in heat management, common problems include low heat recovery efficiency and uneven heat distribution. This leads to high temperature of photovoltaic panels, affecting their power output efficiency and possibly shortening the service life of the equipment.

[0005] Insufficient control and optimization technology: The control system in many existing photovoltaic cogeneration systems often lacks precision, unable to adjust the system in real time in response to environmental changes such as temperature fluctuations and changes in sunlight. In addition, the lack of advanced data analysis capabilities makes it impossible for the system to optimize based on historical and real-time data, affecting the overall performance and response speed of the system.

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

[0007] The system uses advanced intelligent control systems and data analysis technology to automatically adjust cooling and heat management strategies by monitoring environmental and system parameters in real time. SUMMARY

[0008] In view of the above problems, the present application is proposed.

[0009] Therefore, the present application aims to solve the problem that the existing photovoltaic cogeneration system is insufficient in heat management design and control and optimization technology.

[0010] To solve the above technical problems, the present application provides the following technical solutions: a photovoltaic cogeneration method based on data center improvement, comprising: obtaining total light energy received by a photovoltaic power station in each year based on a data center, calculating average total light energy received per year; obtaining electric energy that should be produced per year according to the average total light energy received per year and parameters of a photovoltaic panel, obtaining electric energy that is connected to a power grid by the photovoltaic power station based on the data center, calculating waste heat energy and waste electric energy; obtaining waste heat energy generated on the photovoltaic panel based on the waste heat energy, grading the waste heat energy generated on the photovoltaic panel, and designing a multilayer heat conduction structure for each grade; the multilayer heat conduction structure is connected with a circulating system, and the circulating flow rate is controlled by the data center; a fan with adaptive power is arranged in the photovoltaic panel based on the waste electric energy, and the fan is controlled to be turned on or turned off by the data center.

[0011] As a preferred scheme of the photovoltaic cogeneration method based on data center improvement, the calculation of the average total light energy received per year comprises: determining light energy E sun (t) at any time t as,

[0012] E sun (t) = I local (t) * A PV

[0013] wherein I local (t) represents solar radiation intensity of a region corresponding to the photovoltaic power station at time t, A PV represents total receiving solar energy surface area of the photovoltaic power station; and total light energy in one year is accumulated and represented as,

[0014] wherein T represents total hours of a year; for each year y, annual total light energy E year (y) is represented as,

[0015] total light energy from year y start to y end is calculated, E year (y) of each year is summed up, and is represented as,

[0016] and finally average annual light total energy E avg_year is represented as,

[0017] As a preferred solution of the improved photovoltaic cogeneration method based on data center, wherein: the annual expected electricity production includes, based on the average annual total energy E avg_year and the parameters of the photovoltaic panel to calculate the expected output power E prod , expressed as,

[0018] E prod = E avg_year × η × A × F eff (θ, β, T avg )

[0019] Wherein, η represents the average energy conversion efficiency of the photovoltaic panel, A represents the total receiving area of the photovoltaic panel, F eff (θ, β, T avg ) represents the adjustment factor function, θ represents the average incident angle of sunlight, β represents the installation angle of the photovoltaic panel, T avg represents the average working temperature of the photovoltaic panel, T opt represents the optimal working temperature, and ΔT represents the rate constant of temperature deviation efficiency reduction; the waste heat energy includes, subtracting the expected output power from the average annual total energy to obtain the waste heat energy Q waste , expressed as,

[0020] Q waste = E avg_year -E prod

[0021] The waste electricity includes, subtracting the electricity into the power grid from the expected output power to obtain the waste electricity, expressed as,

[0022] E waste = E prod -E grid

[0023] Wherein, E grid represents the average annual electricity of the photovoltaic power station into the power grid.

[0024] As a preferred solution of the improved photovoltaic cogeneration method based on data center, wherein: the waste heat energy generated on the photovoltaic panel includes, defining the proportion of the photovoltaic panel in the total area of the photovoltaic power station R is expressed as,

[0025] Based on the proportion R, the waste heat energy is divided into two parts including the waste heat energy Q waste_panel irradiated on the photovoltaic panel and the waste heat energy Q waste_ground irradiated on the ground, expressed as,

[0026] Q waste_panel = (E avg_year -E prod ) x R

[0027] Q waste_ground = (E avg_year -E prod ) x (1-R).

[0028] As a preferred scheme of the improved photovoltaic cogeneration method based on data center, wherein: the multi-layer heat conduction structure designed for each level includes, the waste heat energy Q waste_panel is compared with the threshold value to determine the heat dissipation level; when Q waste_panel ≤500kWh / m 2 , it is determined as low-grade heat dissipation; when 500kWh / m 2 <Q waste_panel ≤1000kWh / m 2 , it is determined as medium-grade heat dissipation; when Q waste_panel >1000kWh / m 2 , it is determined as high-grade heat dissipation; when it is determined as low-grade heat dissipation or medium-grade heat dissipation, the multi-layer heat conduction structure is a two-layer structure; when it is determined as high-grade heat dissipation, the multi-layer heat conduction structure is a three-layer structure; when it is the two-layer structure, the first layer is a contact layer, and the second layer is an environmental interface layer; when it is the three-layer structure, the first layer is a contact layer, the second layer is a thermal insulation layer, and the third layer is an environmental interface layer; the contact layer adopts a material with high thermal conductivity; the thermal insulation 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.

[0029] As a preferred scheme of the improved photovoltaic cogeneration method based on data center, wherein: the circulating system is provided with a heat sensor at each connection with the photovoltaic panel heat conduction structure, the heat sensor collects the photovoltaic panel temperature and sends it to the data center, the data center controls the power of the fluid pump according to the photovoltaic panel temperature, and further controls the circulating flow rate.

[0030] As a preferred scheme of the improved photovoltaic cogeneration method based on data center, wherein: the fan with adaptive power includes, based on the waste electric energy, a fan with adaptive waste electric energy power is provided for the photovoltaic panel, when the temperature data collected by the data center is greater than the optimal working temperature threshold value, the data center controls the fan to open, and the fan is powered by the electric energy converted by the photovoltaic panel.

[0031] Another object of the present application is to provide an improved photovoltaic cogeneration system based on a data center, which can control the photovoltaic cogeneration system.

[0032] To solve the above technical problems, the present application provides the following technical solutions: a photovoltaic cogeneration method based on an improved 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 energy of light received by the photovoltaic power station over the years and the average annual electric energy of the photovoltaic power station connected to the power grid based on the data center; the waste energy calculation module calculates the average annual total energy of light received by the photovoltaic power station based on the total energy of light received by the photovoltaic power station over the years, obtains the electric energy that should be produced annually according to the average annual total energy of light received and the parameters of the photovoltaic panel, and calculates the waste heat energy and the waste electric energy based on the average annual electric energy of the photovoltaic power station connected to the power grid; the structural design module obtains the waste heat energy generated on the photovoltaic panel based on the waste heat energy, and divides the waste heat energy generated on the photovoltaic panel into several grades, each grade being designed with a multi-layer heat conduction structure.

[0033] The control module controls the circulation flow rate of the circulation system and the on-off of the fan in the photovoltaic panel through the data center.

[0034] A computer device comprising a memory and a processor, the memory storing a computer program, and the processor implementing the steps of the photovoltaic cogeneration method based on an improved data center when executing the computer program.

[0035] A computer readable storage medium having a computer program stored thereon, the computer program being executed by a processor to implement the steps of the photovoltaic cogeneration method based on an improved data center.

[0036] The present application has the following advantages: the present application effectively manages the waste heat energy generated by the photovoltaic panel through the intelligent control system and the multi-layer heat conduction structure. By setting the heat energy grades and the corresponding multi-layer structure, the system can provide the best thermal management solution for different heat loads, reduce heat energy loss, maintain the photovoltaic panel at the best working temperature, and thus improve the electric energy conversion efficiency.

[0037] Using the computing power of the data center, the present application realizes real-time monitoring and performance optimization of the photovoltaic cogeneration system. The system can real-time collect environmental changes, dynamically adjust the circulation rate and fan cooling, optimize the output of the photovoltaic panel and the utilization of heat energy, and improve the system response efficiency and operation flexibility. BRIEF DESCRIPTION OF DRAWINGS

[0038] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments will be briefly introduced as follows. Obviously, the drawings in the following description only constitute some embodiments of the present application, and for those skilled in the art, other drawings can be obtained based on these drawings without any creative effort. Among them:

[0039] Fig. 1 is a flow chart of a photovoltaic cogeneration method based on data center improvement in embodiment 1.

[0040] Fig. 2 is a module structure diagram of a photovoltaic cogeneration system based on data center improvement in embodiment 3. DETAILED DESCRIPTION

[0041] In order to make the above-mentioned purposes, features and advantages of the present application more apparent and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the drawings.

[0042] In the following description, many specific details are set forth in order to provide a thorough understanding of the present application, but the present application can also be implemented in other ways different from those described herein, and those skilled in the art can make similar generalizations without departing from the concept of the present application, therefore the present application is not limited to the specific embodiments disclosed below.

[0043] Embodiment 1, referring to Fig. 1, is the first embodiment of the present application, which provides a photovoltaic cogeneration method based on data center improvement, including, as shown in Fig. 1:

[0044] Step 1: Based on the data center, the total light energy received by the photovoltaic power station in the past years is obtained, and the average total light energy received per year is calculated.

[0045] According to the historical data collected by the data center, the light energy E sun (t) is determined at any time t.

[0046] E sun (t) = I local (t) × A PV

[0047] Wherein, I local (t) represents the solar radiation intensity of the corresponding area of the photovoltaic power station at time t, and A PV represents the total receiving solar energy surface area of the photovoltaic power station.

[0048] The total light energy accumulated in one year is represented as,

[0049] Wherein, T represents the total number of hours in a year.

[0050] E (y) represents the total light energy of each year y year (y) represents the total light energy of each year y

[0051] The total light energy from year y start to y end is calculated, and E year (y) of each year is summed up, represented as

[0052] The total light energy of each year is finally obtained, represented as avg_year

[0053] Step 2: Based on the total light energy of each year and the parameters of the photovoltaic panel, the electric energy that should be produced each year is obtained, and based on the data center, the electric energy of the photovoltaic power station integrated into the power grid is obtained, and the waste heat energy and the waste electric energy are calculated.

[0054] Based on the total light energy of each year E avg_year and the parameters of the photovoltaic panel, the expected output electric energy E prod is calculated, represented as

[0055] E prod = E avg_year × η × A × F eff (θ, β, T avg )

[0056] Wherein, η represents the average energy conversion efficiency of the photovoltaic panel, A represents the total receiving area of the photovoltaic panel, F eff (θ, β, T avg ) represents the adjustment factor function, θ represents the average incident angle of sunlight, β represents the installation inclination angle of the photovoltaic panel, T avg represents the average working temperature of the photovoltaic panel, T opt represents the optimal working temperature, and ΔT represents the rate constant of temperature deviation efficiency reduction.

[0057] The calculation method of the waste heat energy includes subtracting the expected output electric energy from the total light energy of each year to obtain the waste heat energy Q waste , represented as

[0058] Q waste = E avg_year -E prod

[0059] The calculation method of the waste electric energy includes subtracting the electric energy integrated into the power grid from the expected output electric energy to obtain the waste electric energy, represented as

[0060] E waste ​= E prod - E grid

[0061] where E grid represents the average annual electrical energy that is incorporated into the grid by the photovoltaic power station.

[0062] The proportion R of the total area of the photovoltaic power station occupied by the photovoltaic panel is defined as,

[0063] Based on the proportion R, the waste heat energy is divided into two parts, including the waste heat energy Q waste_panel that is irradiated on the photovoltaic panel and the waste heat energy Q waste_ground that is irradiated on the ground, which is expressed by the formula,

[0064] Q waste_panel = (E avg_year -E prod ) × R

[0065] Q waste_ground = (E avg_year -E prod ) × (1-R).

[0066] Step 3: Based on the waste heat energy, the waste heat energy generated on the photovoltaic panel is classified, and a multi-layer heat conduction structure is designed for each classification.

[0067] The waste heat energy Q waste_panel irradiated on the photovoltaic panel is compared with the threshold value to determine the heat dissipation classification;

[0068] When Q waste_panel ≤ 500 kWh / m 2 , it is determined to be low-grade heat dissipation; when 500 kWh / m 2 < Q waste_panel ≤ 1000 kWh / m 2 , it is determined to be medium-grade heat dissipation; and when Q waste_panel > 1000 kWh / m 2 , it is determined to be high-grade heat dissipation.

[0069] The conversion efficiency of photovoltaic panels is usually between 15% and 20%, which means that about 80% to 85% of the received solar energy is converted into heat energy and not utilized for electricity.

[0070] According to this efficiency, it can be estimated that under typical sunlight conditions, a photovoltaic panel will receive about 1000 to 1500 kWh of solar energy per square meter per year. Therefore, the waste heat energy (the part that is not converted into electrical energy) will account for a large part of this total energy.

[0071] These threshold values for determining the gear are based on general experience and typical data settings, but also need to be adapted to different geographical and climatic conditions. For example, in areas with stronger sunlight, a high heat energy threshold may be more common, while in areas with weaker sunlight, a low heat energy threshold may be more suitable. The thresholds of the present invention are based on an average value of existing approximate solar energy data, and the specific environment can set the threshold value according to the data collected by the actual photovoltaic power plant.

[0072] By setting the thresholds in this way, it can help system designers and operators to choose appropriate thermal management strategies according to different heat energy levels, taking into account both the system's operating efficiency and optimizing cost and implementation complexity. The setting of these thresholds provides a standardized reference for the thermal energy management of photovoltaic systems, which helps to make more informed decisions in the design and evaluation process.

[0073] 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.

[0074] When it is a two-layer structure, the first layer is a contact layer, and the second layer is an environmental interface layer.

[0075] 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.

[0076] The contact layer uses a material with high thermal conductivity; the thermal isolation layer uses a material with high thermal insulation performance and structural stability; the environmental interface layer uses a material with high heat dissipation efficiency performance.

[0077] For example, low heat energy level - two-layer structure:

[0078] First layer (contacting photovoltaic panel): aluminum-based alloy, preferably with high thermal conductivity to quickly conduct heat.

[0079] Second layer (environmental interface): graphene coating, used to improve heat dissipation efficiency while providing lighter weight and higher environmental stability.

[0080] Medium heat energy level - two-layer structure:

[0081] First layer (contacting photovoltaic panel): copper, due to its excellent heat conduction performance, suitable for medium heat load.

[0082] Second layer (environmental interface): phase change material (PCM) layer, used to absorb and store excess heat, and release heat energy when the temperature decreases.

[0083] High heat energy level - three-layer structure, for high heat energy, a three-layer structure is used to maximize the management and utilization of heat energy:

[0084] First layer (contact photovoltaic panel): silver-based alloy, providing the highest level of thermal conductivity performance.

[0085] Second layer: aluminum oxide (Al203) ceramic, as a thermal isolation layer, reducing heat loss to the external environment while maintaining the mechanical strength of the structure.

[0086] Third layer (environmental interface): high thermal conductivity graphene composite material, for effective heat dissipation while taking advantage of the high thermal conductivity and mechanical stability of graphene.

[0087] The material design of each layer can be designed according to specific environmental factors and economic considerations.

[0088] Step 4: The multi-layer thermal conduction structure is connected to a circulation system, and the circulation flow rate is controlled by the data center.

[0089] The circulation system is provided with a thermal sensor at each connection with the photovoltaic panel thermal conduction structure, which collects the photovoltaic panel temperature and sends it to the data center, which controls the power of the fluid pump and thus controls the circulation flow rate.

[0090] Step 5: Based on the waste electrical energy, a fan is set up in the photovoltaic panel that adapts to the power, and the fan is controlled by the data center.

[0091] Based on the waste electrical energy, a fan is set up in the photovoltaic panel that adapts to the power of the waste electrical energy (selecting a fan that can drive the corresponding power according to the waste electrical energy), when the temperature data collected by the data center is greater than the optimal working temperature threshold, the data center controls the fan to open, and the fan is powered by the electrical energy converted by the photovoltaic panel (generally, when the temperature is high, it is the moment when the light intensity is sufficient, and the amount of electrical energy conversion is large, so there will be no power supply shortage).

[0092] Example 2, the second embodiment of the invention, which is different from the first embodiment: a photovoltaic cogeneration method and system based on data center improvement, further comprising, in order to verify the technical effects used in this method, this embodiment compares the test results of the traditional technical solution and the method of the invention by scientific demonstration means, in order to verify the real effect of the method.

[0093] The method of the invention and the traditional method are loaded into a simulation model for testing. (The simulation model simulates the working condition of a photovoltaic power station for one year)

[0094] The obtained data is summarized and a test comparison table is drawn, as shown in Table 1:

[0095] Table 1: Test data comparison table

[0096] Energy utilization efficiency: The present application effectively improves the transfer efficiency of thermal energy from photovoltaic panels to heat exchangers through the integration of advanced multi-layer heat conduction structures according to different gears. The use of advanced intelligent control systems and data analysis techniques, through real-time monitoring of environmental and system parameters, automatically adjusts cooling and thermal management strategies, significantly improving the overall utilization efficiency of energy. As can be seen from the table, the efficiency has increased from 15% to 25%, which is achieved through more efficient energy capture and conversion mechanisms.

[0097] Electricity and heat production: Compared with traditional photovoltaic systems, the system based on data centers not only improves electricity production, but also realizes effective recovery of heat energy. This proves that in the data center environment, solar energy can be more fully utilized.

[0098] Environmental impact (CO2 emission reduction): Due to the improvement of energy utilization efficiency and the reduction of dependence on fossil energy, CO2 emissions are significantly reduced, and the environmental impact is reduced.

[0099] Example 3, referring to Figure 2, is the third embodiment of the present application, which is different from the first two embodiments: a system for improved photovoltaic cogeneration based on data centers, including a data acquisition module, a waste energy calculation module, a structural design module and a control module; The data acquisition module obtains the total energy received by the photovoltaic power station from the data center over the years, and the average annual electricity energy incorporated into the grid by the photovoltaic power station; The waste energy calculation module calculates the total energy received by the photovoltaic power station over the years, and calculates the total energy received by the photovoltaic power station over the years. According to the average annual total energy received by the photovoltaic power station and the parameters of the photovoltaic panel, the annual electricity energy should be produced, and based on the average annual electricity energy incorporated into the grid by the photovoltaic power station, the waste heat energy and the waste electricity energy are calculated; The structural design module obtains the waste heat energy generated by the photovoltaic panel based on the waste heat energy, and divides the waste heat energy generated by the photovoltaic panel into several 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.

[0100] If the functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application or the parts of the technical solutions that essentially contribute to the prior art or the parts of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0101] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a list of executable instructions for implementing logic functions, which can be embodied in any computer-readable medium for use by or in connection with an instruction execution system, apparatus or device, such as a computer-based system, a system including a processor or other system that can fetch the instructions from the instruction execution system, apparatus or device and execute the instructions, or in conjunction with these instructions execution systems, apparatus or devices. For the purpose of this specification, the "computer-readable medium" can be any device that can contain, store, communicate, propagate or transport programs for use by or in connection with an instruction execution system, apparatus or device, or in conjunction with these instruction execution systems, apparatus or devices.

[0102] More specific examples (a non-exhaustive list) of the computer-readable medium include the following: an electrical connection having one or more wires (electrical devices), a portable computer diskette (magnetic devices), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). In addition, the computer-readable medium can even be paper or other suitable medium on which the program can be printed, because the program can be electronically obtained, for example, by optical scanning of the paper or other medium, followed by editing, interpreting or otherwise processing, if necessary, in other suitable ways, to be electronically obtained and then stored in the computer memory.

[0103] It should be understood that portions of the present application can be implemented in hardware, software, firmware, or combinations thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, implementation can be with any or a combination of the following technologies, which are all well known in the art: a discrete logic circuit having logic gates for implementing logic functions upon an application of data signals, an application specific integrated circuit having appropriate combinational logic gates, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0104] It should be noted that the above examples are only used to illustrate the technical solutions of the present application but not limit the present application. Although the present application is described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced equivalently without departing from the spirit and scope of the present application, and all should be covered in the scope of the claims of the present application.

Claims

1. A method for improved photovoltaic cogeneration based on data center, characterized in that: The method comprises the following steps: Based on the data center, the total energy of the light received by the photovoltaic power station in the past years is obtained, and the average total energy of the light received per year is calculated; According to the average total energy of the light received per year and the parameters of the photovoltaic panel, the electric energy that should be produced per year is obtained, and based on the data center, the average electric energy of the photovoltaic power station connected to the power grid per year is obtained, the waste heat energy and the waste electric energy are calculated; Based on the waste heat energy, the waste heat energy generated on the photovoltaic panel is obtained, and 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 with a circulating system, and the circulating flow rate is controlled by the data center; Based on the waste electric energy, a fan with adaptive power is arranged in the photovoltaic panel, and the opening and closing of the fan is controlled by the data center.

2. A method for improved photovoltaic cogeneration based on data centers as claimed in claim 1, wherein: The calculating the average total energy of light received per year comprises determining the light energy E sun (t) is represented as, E sun (t) = I local (t) x A PV where I local (t) denotes the solar radiation intensity at time t for the area corresponding to the photovoltaic power plant, A PV denotes the total receiving solar energy surface area of the photovoltaic power plant; The total light energy accumulated in one year is expressed as, T represents the total number of hours in a year; For each year y, the annual total light energy E year (y) is expressed as, The total light energy during the years from y start to y end is calculated, summing E year (y) for each year, expressed as, Finally, the total energy E of the light per year is obtained as an average avg_year is represented as, 3. A data center based improved combined PV-thermal power generation method as claimed in claim 2, wherein: The expected annual production of electrical energy E is calculated based on the average annual total energy of the light E avg_year and the parameters of the photovoltaic panel prod , expressed as E prod = E avg_year × η × A × F eff (θ, β, T avg ) wherein η denotes the average energy conversion efficiency of the photovoltaic panel, A denotes the total receiving area of the photovoltaic panel, F eff (θ, β, T avg ) denotes the adjustment factor function, θ denotes the average incidence angle of the sunlight, β denotes the installation inclination angle of the photovoltaic panel, T avg denotes the average operating temperature of the photovoltaic panel, T opt denotes the optimal operating temperature, and ΔT denotes the rate constant of the temperature deviation efficiency reduction. The waste heat energy includes, subtracting the expected output electric energy from the total energy of the average annual illumination to obtain the waste heat energy Q waste , is expressed as, Q waste = E avg_year - E prod The waste electric energy includes the expected output electric energy minus the electric energy connected to the power grid, and is represented as E waste = E prod - E grid where E grid represents the average annual electrical energy fed into the grid by the photovoltaic power plant.

4. A method for improved photovoltaic cogeneration based on data centers as claimed in claim 3, wherein: The waste heat energy generated on the photovoltaic panel is obtained by defining the ratio R of the total area of the photovoltaic panel to the total area of the photovoltaic power plant, expressed 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 irradiated on the ground waste_ground , which is expressed by the formula, Q waste_panel = (E avg_year - E prod ) x R Q waste_ground = (E avg_year - E prod ) x (1 - R).

5. A data center based improved combined PV-CHP method as claimed in claim 4, wherein: The designing of a multi-layer heat transfer structure for each level includes obtaining the waste heat energy Q irradiated on the photovoltaic panel waste_panel determining the heat dissipation level by comparing with the threshold value; When Q waste_panel ≤ 500 kWh / m 2 , it is determined as low-grade heat dissipation; when 500 kWh / m 2 < Q waste_panel ≤ 1000 kWh / m 2 , it is determined as medium-grade heat dissipation; when Q waste_panel > 1000 kWh / m 2 , it is determined as high-grade heat dissipation. When it is determined that the low-grade heat dissipation or the middle-grade heat dissipation, the multi-layer heat conduction structure is a two-layer structure; when it is determined that the high-grade heat dissipation, the multi-layer heat conduction structure is a three-layer structure; When the two-layer structure is adopted, the first layer is a contact layer, and the second layer is an environmental interface layer; When the three-layer structure is adopted, the first layer is a contact layer, the second layer is a thermal insulation layer, and the third layer is an environmental interface layer; The contact layer adopts a material with high thermal conductivity; the thermal insulation layer adopts a material with high thermal insulation performance and stable structure; and the environmental interface layer adopts a material with high heat dissipation efficiency.

6. A data center based improved combined PV-CHP method as claimed in claim 5, wherein: The circulating system is provided with a thermal sensor at each connection with the photovoltaic panel heat conduction structure, the photovoltaic panel temperature is collected by the thermal sensor and sent to the data center, the power of the fluid pump is controlled by the data center according to the photovoltaic panel temperature, and the circulating flow rate is controlled.

7. A data center based improved combined PV-CHP method as claimed in claim 6, wherein: The fan with adaptive power includes a fan with adaptive waste electric energy power arranged in the photovoltaic panel based on the waste electric energy, and when the temperature data collected by the data center is greater than the optimal working temperature threshold, the data center controls the fan to open, and the fan is powered by the electric energy converted by the photovoltaic panel.

8. A system employing a data center improved based photovoltaic cogeneration method according to any one of claims 1 to 7, characterized in that: The method comprises a data acquisition module, a waste energy calculation module, a structure design module and a control module; The data acquisition module obtains the total energy of the light received by the photovoltaic power station in the past years based on the data center, and the average electric energy of the photovoltaic power station connected to the power grid per year; The waste energy calculation module calculates the average total energy of the light received per year through the total energy of the light received by the photovoltaic power station in the past years, obtains the electric energy that should be produced per year according to the average total energy of the light received per year and the parameters of the photovoltaic panel, and calculates the waste heat energy and the waste electric energy based on the average electric energy of the photovoltaic power station connected to the power grid per year; The structure design module obtains the waste heat energy generated on the photovoltaic panel based on the waste heat energy, and 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 circulating flow rate of the circulating 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, and the computer device is characterized in that: The processor executes the computer program to realize the steps of the improved photovoltaic cogeneration method based on the data center in any one of claims 1 to 7.

10. A computer readable storage medium having stored thereon a computer program, characterized in that: The computer program, when executed by a processor, implements the steps of the improved photovoltaic cogeneration method based on a data center according to any one of claims 1 to 7.

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