Multi-objective optimization design method and system for single-sided photovoltaic module temperature control system

Abstract

The invention discloses a multi-objective optimization design method and system for a single-sided photovoltaic module temperature control system, and the method comprises the following steps: obtaining annual simulation data for a target region, the annual simulation data comprising the power generation amount and cost data of the temperature control system under different experiment schemes; based on the annual simulation data, fitting an annual energy production increase amount response model and a cost increase amount response model of the target region; obtaining a Pareto optimal boundary by combining a genetic algorithm according to the annual energy output increase amount response model and the cost increase amount response model, and obtaining a series of optimal parameter combinations; according to each optimal parameter combination, the income of the temperature control system in the life cycle is calculated, and when the income is the maximum, the corresponding parameter combination is the optimal design parameter. According to the method, two-stage optimization is carried out on the basis of the generating capacity numerical simulation data, the costs and the electricity prices of the target region, and the optimal design parameters meeting the field generating capacity and cost requirements can be obtained.

Description

Technical Field

[0001] The present invention belongs to the technical field of solar power generation, and in particular relates to a multi-objective optimization design method and system for a temperature control system of a single-sided photovoltaic module. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] Crystalline silicon cells are currently the mainstream of solar cell power generation. When other conditions remain unchanged, temperature is one of the factors that cause the attenuation of power generation efficiency. Therefore, controlling the temperature of solar cell modules is of great significance to improving their working efficiency.

[0004] At the back panel of the single-sided solar cell module, the method of combining phase change materials with heat pipes is used to increase the heat transfer path of the photovoltaic panel. By combining phase change heat storage with heat pipe heat dissipation, the purpose of temporarily storing and removing the heat generated by the photovoltaic panel to the greatest extent is achieved; at the same time, when there is no solar radiation at night, the heat pipe will accelerate the rate at which the phase change material dissipates the heat stored during the day into the air, which helps to ensure the performance of the phase change material in the next heat storage cycle, so that the entire device can continue to operate efficiently. Compared with the method of temperature control using only phase change materials, the above method has a better effect of temperature control and efficiency enhancement.

[0005] Obviously, the key parameters such as the materials of phase change materials and the number of heat pipes required are important factors affecting the temperature control and efficiency enhancement effect. In different regions, the meteorological conditions are different, especially when the solar radiation level varies greatly, the key parameters of the phase change material / heat pipe coupled temperature control device need to be personalized to ensure the optimal temperature control effect. Summary of the invention

[0006] In order to overcome the deficiencies of the above-mentioned prior art, the present invention provides a multi-objective optimization design method and system for a temperature control system of a single-sided photovoltaic module, in particular, a multi-objective optimization design of a phase change material / heat pipe coupled temperature control system, which can obtain optimal design parameters that meet local power generation and cost requirements for different target areas.

[0007] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions:

[0008] A multi-objective optimization design method for a single-sided photovoltaic module temperature control system includes the following steps:

[0009] Acquire full-year simulation data for a target area, wherein the full-year simulation data includes power generation and cost data of a temperature control system under different experimental schemes;

[0010] Based on the full-year simulation data, fitting an annual power generation increase response model and a cost increase response model for the target region;

[0011] According to the annual power generation increase response model and the cost increase response model, a Pareto optimal boundary is obtained by combining a genetic algorithm to obtain a series of optimal parameter combinations;

[0012] The benefit of the temperature control system during its life cycle is calculated based on each optimal parameter combination, and the parameter combination corresponding to the maximum benefit is the optimal design parameter of the temperature control system in the target area.

[0013] In some embodiments, the different experimental schemes are combinations of multiple design parameters and factor levels thereof; the design parameters include heat pipe area ratio, phase change temperature of phase change material and thickness of phase change material.

[0014] In some embodiments, the annual power generation increase response model fitting method is: performing numerical simulation of the heat transfer process under different experimental schemes, and fitting the annual power generation increase response model of the target area according to the numerical simulation results.

[0015] In some embodiments, the cost increase response model fitting method is: according to the cost of phase change materials, heat pipes and packaging, the cost increase response model can be obtained by fitting.

[0016] In some embodiments, based on the annual power generation increase response model and the cost increase response model, a non-dominated sorting genetic algorithm with an elite strategy is combined to optimize with the goal of maximizing the annual power generation increase and minimizing the cost increase to obtain the Pareto optimal boundary.

[0017] In some embodiments, the method for calculating the profit of the temperature control system during its life cycle is: calculate the income from electricity sales during the life cycle of the temperature control system due to the increase in power generation, minus the increase in cost, which is the profit during the life cycle.

[0018] A second aspect of the present invention provides a multi-objective optimization design system for a single-sided photovoltaic module temperature control system, comprising:

[0019] A simulation data acquisition module is configured to acquire full-year simulation data for a target area, wherein the full-year simulation data includes power generation and cost data of a temperature control system under different experimental schemes;

[0020] A response model fitting module is configured to fit the annual power generation increase response model and the cost increase response model of the target area based on the annual simulation data;

[0021] A parameter combination optimization module is configured to obtain a series of optimal parameter combinations by combining a genetic algorithm to obtain a Pareto optimal boundary based on the annual power generation increase response model and the cost increase response model;

[0022] The parameter combination determination module is configured to calculate the benefit of the temperature control system during its life cycle based on each optimal parameter combination. The parameter combination corresponding to the maximum benefit is the optimal design parameter of the temperature control system in the target area.

[0023] A third aspect of the present invention provides an electronic device, comprising a processor and a memory, wherein the memory stores computer instructions, and when the computer instructions are executed by the processor, the electronic device executes the method described.

[0024] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the program implements the method described when executed by a processor.

[0025] A fifth aspect of the present invention provides a computer program product, the computer program product comprising a computer program, and when the computer program is executed by a processor, the method described is implemented.

[0026] One or more of the above technical solutions are first based on the numerical simulation data of power generation in the target area and the various costs of the temperature control system, and multi-objective optimization is performed based on response surface and genetic algorithm to obtain a series of optimal parameter combinations; then, combined with the local electricity price, the optimal design parameters are determined from the optimal parameter combination with the goal of maximizing the profit of the temperature control system during its life cycle. That is, a two-stage optimization is carried out, which can fully consider the local actual situation and obtain the optimal design parameters that meet the actual power generation and cost requirements, providing a personalized solution for optimizing design schemes in different regions. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0028] Figure 1 This is a flow chart of a multi-objective optimization design method for a temperature control system of a single-sided photovoltaic module in an embodiment of the present invention;

[0029] Figure 2 This is a Pareto frontier diagram of power generation increase-cost increase in Lanzhou, Gansu;

[0030] Figure 3 It is a schematic diagram of the relationship between the revenue and cost increase during the life cycle of the temperature control system. DETAILED DESCRIPTION

[0031] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0032] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0033] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0034] One or more embodiments of the present invention are a design parameter optimization scheme for a phase change material / heat pipe coupled temperature control system of a single-sided photovoltaic module, wherein the phase change material / heat pipe coupled temperature control system of the single-sided photovoltaic module includes a phase change material and a heat pipe arranged on the back of the single-sided photovoltaic module. The heat pipe is used to extract heat from the photovoltaic module and the phase change material. The phase change material can undergo phase change within a certain temperature range and still maintain a solid form. It can store heat that the heat pipe cannot discharge in time, improve the temperature uniformity of the photovoltaic module, and couple the phase change material with the heat pipe to form complementary advantages and achieve better temperature control effect. As a specific implementation method, the heat pipe is a U-shaped tube, including two horizontal parts and a curved part. The phase change material is arranged between the two horizontal parts, and one of the horizontal parts is embedded in the upper surface of the phase change material. By attaching the upper surface of the photovoltaic module to the back plate of the photovoltaic module, the photovoltaic module is in contact with both the heat pipe and the phase change material. For specific packaging methods, please refer to patent document CN218939705U.

[0035] In order to optimize the design parameters under meteorological conditions in different regions, the patent document CN116108658A, based on the typical daily meteorological parameters of the target area throughout the year, infers the phase change parameter configuration and heat pipe parameter configuration required to achieve the target photovoltaic module backplane temperature based on the energy conservation relationship. However, this document only takes the temperature control effect as the goal, and does not comprehensively consider the improvement of power generation and cost control. In the patent document CN116248044A, the phase change temperature, the amount of phase change material and the number of heat pipes are used as dependent variables, and the power generation of the solar cell module under different dependent variable values ​​is dynamically simulated and calculated throughout the year, and the total power generation of the set time period under different dependent variable values ​​is obtained. With the total power generation as the horizontal coordinate and the cost increment as the vertical coordinate, a Pareto diagram is drawn in the form of a two-dimensional scatter plot to obtain the frontier of the Pareto diagram. However, this document only obtains a series of optimal value combinations, and cannot clarify a set of optimal design parameters, and cannot guide the final design of the control system.

[0036] In order to balance the increase in power generation and cost control, one or more embodiments of the present invention disclose a multi-objective optimization design method for a phase change material / heat pipe coupled temperature control system for a single-sided photovoltaic module, with the annual power generation increase and cost increase of the system as the dual objectives, and three parameters, namely, the heat pipe area ratio, the phase change temperature of the phase change material, and the thickness of the phase change material, are selected as decision variables, and a multi-objective optimization algorithm combining the response surface method and the non-dominated sorting multi-objective genetic algorithm with an elite strategy is used for optimization. The method specifically includes the following steps:

[0037] Step 1: Obtaining full-year simulation data for the target area, wherein the full-year simulation data includes power generation and cost data of the temperature control system under different experimental schemes;

[0038] Step 2: Based on the full-year simulation data, fitting the annual power generation increase response model and the cost increase response model of the target area;

[0039] Step 3: Based on the annual power generation increase response model and the cost increase response model, a Pareto optimal boundary is obtained by combining a genetic algorithm to obtain a series of optimal parameter combinations;

[0040] Step 4: Calculate the benefits of the temperature control system during its life cycle based on each optimal parameter combination. The parameter combination corresponding to the maximum benefit is the optimal design parameter of the temperature control system in the target area.

[0041] In step 1, meteorological conditions in different regions are different. In order to apply the single-sided photovoltaic module temperature control system in the target area, it is necessary to obtain the full-year simulation data of the target area. The method for obtaining the full-year simulation data is: select the hourly dry-bulb temperature and solar radiation emphasis data of a typical year; under different experimental schemes, simulate the power generation and cost data of the temperature control system.

[0042] The different experimental schemes are combinations of multiple design parameters and their factor levels. The design parameters include heat pipe area ratio, phase change material phase change temperature and phase change material thickness.

[0043] As an example, when designing the experimental scheme, the three design parameters of heat pipe area ratio, phase change material phase change temperature and phase change material thickness were divided into three experimental factor levels, represented by -1, 0, and +1 respectively. On this basis, an experimental design scheme was established with a total of 15 design experimental points. For different regions, the annual numerical simulation of the PV-PCM / HP system was carried out in turn according to the experimental scheme.

[0044] Table 1 Experimental influencing factors and factor levels

[0045]

[0046] Table 2 Box-Behnken design experimental plan

[0047]

[0048]

[0049] In step 2, following the experimental plan, after numerical simulation of the heat transfer process under different levels of influencing factors, a response model of the annual power generation increase in the target area is fitted according to the numerical simulation results. The response model is a second-order polynomial equation, and each response model contains a constant term, a linear term, an interaction term, and a square term.

[0050] Taking Lanzhou, Gansu as an example, the power generation increase response function y1 is:

[0051] y1=-3.5892+25.473X1+0.1934X2+0.311X3+0.0398X 12 -0.1261X 13 -0.0067X 23 -21.2856X1 2 -0.0031X2 2 +0.0036X3 2

[0052] According to the phase change material, heat pipe and packaging costs, the response model y2 of the cost increase can be obtained by fitting.

[0053] Taking the following table addition as an example, we can get y2=0.4013+88.8889X1+1.081X3

[0054] Table 3 Example of unit price of phase change materials, heat pipes and packaging

[0055] Paraffin wax PW (yuan / t) Expanded graphite EG (yuan / t) <![CDATA[Acrylic (yuan / m 3 )]]> <![CDATA[Heat pipe (yuan / m 2 )]]> unit price 6500 3600 20.0 1250

[0056] In step 3, on the basis of determining the response model of each climate zone, based on the non-dominated sorting genetic algorithm with elite strategy, the Pareto frontier distribution of the power increase-cost increase of the PV-PCM / HP system in each region is obtained under conflicting objectives.

[0057] Table 4 Genetic algorithm parameter settings

[0058]

[0059]

[0060] In step 4, after obtaining a series of optimal parameter combinations, the optimal design parameters are determined from the optimal parameter combinations with the goal of maximizing the benefits of the temperature control system during its life cycle. Specifically, Figure 3 As shown, the relationship between the benefit and the cost increase during the life cycle of the temperature control system is calculated under each optimal parameter combination. The point with the maximum successful benefit during the life cycle corresponds to the optimal design parameters of the phase change material / heat pipe coupled temperature control system in this area.

[0061] The method for calculating the life cycle profit is: based on the local coal-fired power generation benchmark price, calculate the income from the sale of electricity during the life cycle due to the increase in power generation, minus the increase in cost, which is the life cycle profit.

[0062] One or more of the above embodiments take the increase in annual power generation and the increase in cost of the system as the dual objectives, select the three parameters of heat pipe area ratio, phase change material phase change temperature and phase change material thickness as decision variables, and use a multi-objective optimization algorithm combining the response surface method and the genetic algorithm with elite strategy non-dominated sorting to optimize and obtain a series of optimization solutions. On this basis, the optimal design and decision variable values ​​are obtained based on the maximum benefit within the life cycle. It is possible to optimize the number of heat pipes, phase change material temperature, and phase change material usage according to the meteorological conditions in different regions, solve the parameterization and object-oriented design problems of the temperature control module, improve the stability and reliability of phase change passive temperature control, and solve the balance problem between cost increase and power generation increase.

[0063] One or more of the above embodiments take the annual power generation increase and cost increase of the system as the dual objectives, select key design parameters as decision variables, and use a multi-objective optimization algorithm that combines the response surface method and the genetic algorithm with non-dominated sorting with an elite strategy for optimization. Finally, the maximum benefit within the life cycle is used as the decision goal. This can solve the parameterization and object-oriented design problems of the temperature control module, improve the stability and reliability of phase change passive temperature control, and solve the balance problem between cost increase and power generation increase.

[0064] One or more embodiments of the present invention further provide a multi-objective optimization design system for a single-sided photovoltaic module temperature control system, comprising:

[0065] A simulation data acquisition module is configured to acquire full-year simulation data for a target area, wherein the full-year simulation data includes power generation and cost data of a temperature control system under different experimental schemes;

[0066] A response model fitting module is configured to fit the annual power generation increase response model and the cost increase response model of the target area based on the annual simulation data;

[0067] A parameter combination optimization module is configured to obtain a series of optimal parameter combinations by combining a genetic algorithm to obtain a Pareto optimal boundary based on the annual power generation increase response model and the cost increase response model;

[0068] The parameter combination determination module is configured to calculate the benefit of the temperature control system during its life cycle based on each optimal parameter combination. The parameter combination corresponding to the maximum benefit is the optimal design parameter of the temperature control system in the target area.

[0069] One or more embodiments of the present invention also provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the multi-objective optimization design method for the phase change material / heat pipe coupled temperature control system of a single-sided photovoltaic module is implemented.

[0070] The memory may include one or more non-volatile memories and one or more volatile memories. Examples of non-volatile memories include, but are not limited to, at least one of the following: read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, hard disk, compact disc (CD), digital video disc (DVD) or other magnetic storage and / or optical storage. Examples of volatile memories include, but are not limited to, at least one of the following: random access memory (RAM), or other volatile memories that do not last during the power-off duration. The computer program may be stored in the ROM. The above method is implemented when the processor executes the computer program.

[0071] In some embodiments, the program may be tangibly contained in a computer-readable medium, which may be included in the device (such as in a memory) or other storage device accessible by the device. The program can be loaded from the computer-readable medium to the RAM for execution. The computer-readable medium may include any type of tangible non-volatile memory, such as ROM, EPROM, flash memory, hard disk, the computer-readable storage medium stores a computer program, and the computer program implements the above method when executed by the processor.

[0072] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented by software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a server or terminal, the process or function described in the embodiment of the present application is generated in whole or in part. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a server or terminal or a data storage device such as a server or data center that includes one or more available media integrated. The available medium can be a magnetic medium (such as a floppy disk, a hard disk and a tape, etc.), an optical medium (such as a digital video disk (digital video disk, DVD), etc.), or a semiconductor medium (such as a solid-state hard disk, etc.).

[0073] In addition, although each operation is described in a specific order, this should be understood as requiring such operation to be performed in the specific order shown or in a sequential order, or requiring that all illustrated operations should be performed to obtain desired results. Under certain circumstances, multitasking and parallel processing may be advantageous. Similarly, although some specific implementation details are included in the above discussion, these should not be interpreted as limiting the scope of the application. Some features described in the context of a separate embodiment can also be implemented in a single implementation in combination. On the contrary, the various features described in the context of a single implementation can also be implemented in multiple implementations individually or in any suitable sub-combination mode.

[0074] Although the subject matter has been described in language specific to structural features and / or methodological logical actions, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. On the contrary, the specific features and actions described above are merely example forms of implementing the claims.

Claims

1. A multi-objective optimization design method for a single-sided photovoltaic module temperature control system, characterized in that: The following steps are involved: Acquire full-year simulation data for a target area, wherein the full-year simulation data includes power generation and cost data of a temperature control system under different experimental schemes; Based on the full-year simulation data, fitting an annual power generation increase response model and a cost increase response model for the target region; According to the annual power generation increase response model and the cost increase response model, a Pareto optimal boundary is obtained by combining a genetic algorithm to obtain a series of optimal parameter combinations; The benefit of the temperature control system during its life cycle is calculated based on each optimal parameter combination, and the parameter combination corresponding to the maximum benefit is the optimal design parameter of the temperature control system in the target area.

2. The multi-objective optimization design method for the temperature control system of a single-sided photovoltaic module according to claim 1, characterized in that: The different experimental schemes are combinations of multiple design parameters and their factor levels; the design parameters include heat pipe area ratio, phase change temperature of phase change material and thickness of phase change material.

3. The multi-objective optimization design method for the temperature control system of a single-sided photovoltaic module according to claim 2, characterized in that: The annual power generation increase response model fitting method is: perform numerical simulation of the heat transfer process under different experimental schemes, and fit the annual power generation increase response model of the target area according to the numerical simulation results.

4. The multi-objective optimization design method for the temperature control system of a single-sided photovoltaic module according to claim 2, characterized in that: The cost increase response model fitting method is: according to the cost of phase change materials, heat pipes and packaging, the cost increase response model can be obtained by fitting.

5. The multi-objective optimization design method for the temperature control system of a single-sided photovoltaic module according to claim 1, characterized in that: According to the response model of annual power generation increase and the response model of cost increase, combined with a non-dominated sorting genetic algorithm with an elite strategy, an optimization is performed with the goal of maximizing annual power generation increase and minimizing cost increase to obtain the Pareto optimal frontier.

6. The multi-objective optimization design method for a single-sided photovoltaic module temperature control system according to claim 1, characterized in that: The method for calculating the profit of the temperature control system during its life cycle is as follows: calculate the income from electricity sales during the life cycle of the temperature control system due to the increase in power generation, and subtract the increase in cost to obtain the profit during the life cycle.

7. A multi-objective optimization design system for a single-sided photovoltaic module temperature control system, characterized in that: include: A simulation data acquisition module is configured to acquire full-year simulation data for a target area, wherein the full-year simulation data includes power generation and cost data of a temperature control system under different experimental schemes; A response model fitting module is configured to fit the annual power generation increase response model and the cost increase response model of the target area based on the annual simulation data; A parameter combination optimization module is configured to obtain a series of optimal parameter combinations by combining a genetic algorithm to obtain a Pareto optimal boundary based on the annual power generation increase response model and the cost increase response model; The parameter combination determination module is configured to calculate the benefit of the temperature control system during its life cycle based on each optimal parameter combination. The parameter combination corresponding to the maximum benefit is the optimal design parameter of the temperature control system in the target area.

8. An electronic device, characterized in that: The electronic device comprises a processor and a memory, wherein the memory stores computer instructions, and when the computer instructions are executed by the processor, the electronic device executes the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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