Photovoltaic power generation system parameter optimization method, device and equipment and readable storage medium

Abstract

The application discloses a photovoltaic power generation system parameter optimization method, device and equipment and a computer readable storage medium. The method comprises the following steps: acquiring various system parameters of a photovoltaic power generation system and photovoltaic power generation system characteristics of the photovoltaic power generation system under the various system parameters, wherein the system parameters are adjustable system parameters of the photovoltaic power generation system; determining target activation values of the various system parameters according to the various photovoltaic power generation system characteristics and at least one characteristic constraint; and selecting target system parameters from the various system parameters according to the target activation values and the various photovoltaic power generation system characteristics. The application realizes a scheme for optimizing the parameters of the photovoltaic power generation system by using the target activation values determined according to the photovoltaic power generation system characteristics and the characteristic constraint, and improves the parameter optimization effect of the photovoltaic power generation system.

Description

Technical Field

[0001] This invention relates to the field of photovoltaic power generation system technology, and in particular to a method, apparatus, equipment and computer-readable storage medium for optimizing parameters of a photovoltaic power generation system. Background Technology

[0002] A photovoltaic (PV) power generation system is a complex system in which numerous system parameters are coupled together, affecting the system's target values ​​(e.g., power generation, economic benefits). There is no explicit mathematical expression to represent the relationship between the target values ​​and the system parameters; in other words, it is a black box system.

[0003] In the past, business requirements only needed to optimize a single objective. Typically, the optimal combination of target parameter values ​​was selected from various system parameter combinations based on the target values ​​corresponding to each parameter combination and the constraints of that single objective. However, with increasing market competition, new challenges have arisen for the algorithms and results of photovoltaic (PV) power generation system parameter optimization. Today, PV power generation system optimization tasks involve multiple objectives with shared constraints. If the above method is still used, the large number of parameter value combinations in a PV power generation system leads to lengthy selection times when choosing system parameter combinations based on the constraints of each objective, resulting in low optimization efficiency. Summary of the Invention

[0004] The main objective of this invention is to provide a method, apparatus, device, and computer-readable storage medium for optimizing photovoltaic power generation system parameters. The aim is to provide a scheme for optimizing photovoltaic power generation system parameters by adjusting the target value of the optimization target obtained by combining the parameter values ​​of the photovoltaic power generation system with the target value of the limiting target corresponding to the constraint condition, thereby improving the optimization efficiency of photovoltaic power generation system parameters.

[0005] To achieve the above objectives, the present invention provides a method for optimizing photovoltaic power generation system parameters, the method comprising the following steps:

[0006] Obtain at least one combination of system parameters of a photovoltaic power generation system and a target value corresponding to each combination of system parameters, wherein the target value includes a target value for an optimization target and a target value for a constraint target;

[0007] When the target value of the constraint target corresponding to the parameter value combination meets the constraint condition corresponding to the constraint target, the target value of the optimization target corresponding to the parameter value combination is adjusted according to the preset first value in the optimization direction of the optimization target to update the target value of the optimization target;

[0008] When the target value of the constraint target corresponding to the parameter value combination does not meet the constraint condition corresponding to the constraint target, the target value of the optimization target corresponding to the parameter value combination is adjusted according to the preset second value in the optimization direction of the optimization target to update the target value of the optimization target, wherein the preset first value is greater than the preset second value;

[0009] Based on the optimization direction of the optimization objective, select the target parameter value combination that corresponds to the target objective in each parameter value combination as the optimal target value.

[0010] Optionally, before the step of obtaining at least one combination of system parameters of the photovoltaic power generation system and the target value corresponding to each combination of parameter values, the method further includes:

[0011] Iterate through the combinations of system parameter values ​​of the photovoltaic power generation system to generate at least one combination of parameter values ​​for the current cycle;

[0012] After the step of selecting the target parameter value combination with the target value corresponding to the target of the optimization objective as the optimal target value from each of the parameter value combinations according to the optimization direction of the optimization objective, the method further includes:

[0013] Update the global optimal parameter value combination based on the target parameter value combination and the optimization direction;

[0014] Determine if the traversal has ended;

[0015] If not, return to the step of iterating through the system parameter value combinations of the photovoltaic power generation system to generate at least one parameter value combination for the current cycle.

[0016] Optionally, before the step of selecting the target parameter value combination with the target value of the optimization objective as the optimal target value from each of the parameter value combinations according to the optimization direction of the optimization objective, the method further includes:

[0017] If the target value of the constraint target corresponding to each parameter value combination in the current round does not meet the constraint condition corresponding to the constraint target, then return to the step of traversing the parameter value combinations of the system parameters of the photovoltaic power generation system to generate at least one parameter value combination in the current round.

[0018] Optionally, after the step of returning to the combination of parameter values ​​of the system parameters traversed in the photovoltaic power generation system to generate at least one combination of parameter values ​​for the current cycle, the method further includes:

[0019] If the target value of the constraint target corresponding to each parameter value combination in all rounds does not meet the constraint condition corresponding to the constraint target, then the constraint condition corresponding to the constraint target is adjusted, and / or the parameter value combination of the system parameters of the photovoltaic power generation system is adjusted, and the process returns to the step of traversing the parameter value combination of the system parameters of the photovoltaic power generation system to generate at least one parameter value combination for the current round.

[0020] Optionally, the step of obtaining the target value corresponding to each of the parameter value combinations includes:

[0021] The target value corresponding to each combination of parameter values ​​is calculated by substituting each of the parameter value combinations into the objective function.

[0022] Optionally, the system parameters include at least one of the following: component installation angle, bracket spacing distance, component azimuth angle, system capacity ratio, and bracket height.

[0023] Optionally, the limiting target includes at least one of revenue value, gross profit margin, and cost per kilowatt-hour, and the optimization target is a target other than the limiting target.

[0024] To achieve the above objectives, the present invention also provides a photovoltaic power generation system parameter optimization device, the photovoltaic power generation system parameter optimization device comprising:

[0025] The acquisition module is used to acquire at least one combination of system parameters of the photovoltaic power generation system and a target value corresponding to each combination of system parameters, wherein the target value includes the target value of the optimization target and the target value of the constraint target;

[0026] The first adjustment module is used to adjust the target value of the optimization target corresponding to the parameter value combination according to a preset first value in the optimization direction of the optimization target when the target value of the constraint target corresponding to the parameter value combination meets the constraint condition corresponding to the constraint target, so as to update the target value of the optimization target.

[0027] The second adjustment module is used to adjust the target value of the optimization target corresponding to the parameter value combination according to a preset second value in the optimization direction of the optimization target to update the target value of the optimization target when the target value of the constraint target corresponding to the parameter value combination does not meet the constraint conditions corresponding to the constraint target. The preset first value is greater than the preset second value.

[0028] The selection module is used to select the target parameter value combination with the target value of the optimization target as the optimal target value from each of the parameter value combinations, based on the optimization direction of the optimization target.

[0029] Optionally, before the step of obtaining at least one combination of system parameters of the photovoltaic power generation system and the target value corresponding to each combination of parameter values, the photovoltaic power generation system parameter optimization device is further configured to:

[0030] Iterate through the combinations of system parameter values ​​of the photovoltaic power generation system to generate at least one combination of parameter values ​​for the current cycle;

[0031] After the step of selecting the target parameter value combination with the target value of the optimization objective as the optimal target value from each of the parameter value combinations according to the optimization direction of the optimization objective, the photovoltaic power generation system parameter optimization device is further configured to:

[0032] Update the global optimal parameter value combination based on the target parameter value combination and the optimization direction;

[0033] Determine if the traversal has ended;

[0034] If not, return to the step of iterating through the system parameter value combinations of the photovoltaic power generation system to generate at least one parameter value combination for the current cycle.

[0035] Optionally, before the step of selecting the target parameter value combination with the target value of the optimization objective as the optimal target value from each of the parameter value combinations according to the optimization direction of the optimization objective, the photovoltaic power generation system parameter optimization device is further configured to:

[0036] If the target value of the constraint target corresponding to each parameter value combination in the current round does not meet the constraint condition corresponding to the constraint target, then return to the step of traversing the parameter value combinations of the system parameters of the photovoltaic power generation system to generate at least one parameter value combination in the current round.

[0037] Optionally, after the step of returning to the parameter value combinations that iterate through the system parameters of the photovoltaic power generation system to generate at least one parameter value combination for the current round, the photovoltaic power generation system parameter optimization device is further configured to:

[0038] If the target value of the constraint target corresponding to each parameter value combination in all rounds does not meet the constraint condition corresponding to the constraint target, then the constraint condition corresponding to the constraint target is adjusted, and / or the parameter value combination of the system parameters of the photovoltaic power generation system is adjusted, and the process returns to the step of traversing the parameter value combination of the system parameters of the photovoltaic power generation system to generate at least one parameter value combination for the current round.

[0039] Optionally, the acquisition module is further configured to:

[0040] The target value corresponding to each combination of parameter values ​​is calculated by substituting each of the parameter value combinations into the objective function.

[0041] Optionally, the system parameters include at least one of the following: component installation angle, bracket spacing distance, component azimuth angle, system capacity ratio, and bracket height.

[0042] Optionally, the limiting target includes at least one of revenue value, gross profit margin, and cost per kilowatt-hour, and the optimization target is a target other than the limiting target.

[0043] To achieve the above objectives, the present invention also provides a photovoltaic power generation system parameter optimization device, the photovoltaic power generation system parameter optimization device comprising: a memory, a processor, and a photovoltaic power generation system parameter optimization program stored in the memory and executable on the processor, wherein when the photovoltaic power generation system parameter optimization program is executed by the processor, it implements the steps of the photovoltaic power generation system parameter optimization method as described above.

[0044] Furthermore, to achieve the above objectives, the present invention also proposes a computer-readable storage medium storing a photovoltaic power generation system parameter optimization program, wherein the photovoltaic power generation system parameter optimization program, when executed by a processor, implements the steps of the photovoltaic power generation system parameter optimization method as described above.

[0045] In this invention, at least one combination of system parameters of a photovoltaic power generation system and a target value corresponding to each of the parameter value combinations are obtained. The target value includes a target value for an optimization target and a target value for a constraint target. When the target value of the constraint target corresponding to the parameter value combination meets the constraint condition corresponding to the constraint target, the target value of the optimization target corresponding to the parameter value combination is adjusted in the optimization direction of the optimization target according to a preset first value to update the target value of the optimization target. When the target value of the constraint target corresponding to the parameter value combination does not meet the constraint condition corresponding to the constraint target, the target value of the constraint target corresponding to the parameter value combination is adjusted in the optimization direction of the optimization target according to a preset second value. The target value of the optimization target is adjusted to update the target value of the optimization target, wherein the preset first value is greater than the preset second value; according to the optimization direction of the optimization target, the target parameter value combination with the corresponding target value of the optimization target as the optimal target value is selected from each of the parameter value combinations; by adjusting and reconstructing the target value of the optimization target according to the target value of the limiting target of each parameter value combination, and then performing target optimization of parameter value combination according to the adjusted target value of the optimization target, the parameter value combination optimization of system parameters with multiple limiting targets is realized, without the need to select system parameter combinations according to the limiting conditions of each limiting target one by one, thereby improving the optimization efficiency of photovoltaic power generation system parameters. Attached Figure Description

[0046] Figure 1 This is a schematic diagram of the hardware operating environment involved in the embodiments of the present invention;

[0047] Figure 2 This is a flowchart illustrating the first embodiment of the photovoltaic power generation system parameter optimization method of the present invention;

[0048] Figure 3 This is a schematic diagram of an update table of target values ​​for an optimization objective according to an embodiment of the present invention;

[0049] Figure 4 This is a schematic diagram of the functional modules of a preferred embodiment of the photovoltaic power generation system parameter optimization device of the present invention.

[0050] The objectives, features, and advantages of this invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0051] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0052] like Figure 1 As shown, Figure 1 This is a schematic diagram of the device structure of the hardware operating environment involved in the embodiments of the present invention.

[0053] It should be noted that the photovoltaic power generation system parameter optimization device in this embodiment of the invention can be a smartphone, personal computer, server, or other device, and no specific limitation is made here.

[0054] like Figure 1 As shown, the photovoltaic power generation system parameter optimization device may include: a processor 1001, such as a CPU; a network interface 1004; a user interface 1003; a memory 1005; and a communication bus 1002. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display screen and an input unit such as a keyboard; optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface). The memory 1005 may be a high-speed RAM or a stable, non-volatile memory, such as a disk storage device. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0055] Those skilled in the art will understand that Figure 1The equipment structure shown does not constitute a limitation on the equipment for optimizing photovoltaic power generation system parameters. It may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0056] like Figure 1 As shown, the memory 1005, serving as a computer storage medium, may include an operating system, a network communication module, a user interface module, and a photovoltaic power generation system parameter optimization program. The operating system is a program that manages and controls the hardware and software resources of the device, supporting the operation of the photovoltaic power generation system parameter optimization program and other software or programs. Figure 1 In the device shown, the user interface 1003 is mainly used for data communication with the client; the network interface 1004 is mainly used for establishing a communication connection with the server; and the processor 1001 can be used to call the photovoltaic power generation system parameter optimization program stored in the memory 1005 and perform the following operations:

[0057] Obtain at least one combination of system parameters of a photovoltaic power generation system and a target value corresponding to each combination of system parameters, wherein the target value includes a target value for an optimization target and a target value for a constraint target;

[0058] When the target value of the constraint target corresponding to the parameter value combination meets the constraint condition corresponding to the constraint target, the target value of the optimization target corresponding to the parameter value combination is adjusted according to the preset first value in the optimization direction of the optimization target to update the target value of the optimization target;

[0059] When the target value of the constraint target corresponding to the parameter value combination does not meet the constraint condition corresponding to the constraint target, the target value of the optimization target corresponding to the parameter value combination is adjusted according to the preset second value in the optimization direction of the optimization target to update the target value of the optimization target, wherein the preset first value is greater than the preset second value;

[0060] Based on the optimization direction of the optimization objective, select the target parameter value combination that corresponds to the target objective in each parameter value combination as the optimal target value.

[0061] Furthermore, before obtaining at least one combination of system parameters of the photovoltaic power generation system and the target value corresponding to each combination of parameter values, the processor 1001 can also call the photovoltaic power generation system parameter optimization program stored in the memory 1005 to perform the following operations:

[0062] Iterate through the combinations of system parameter values ​​of the photovoltaic power generation system to generate at least one combination of parameter values ​​for the current cycle;

[0063] After the operation of selecting the target parameter value combination with the target value of the optimization objective as the optimal target value from each of the parameter value combinations according to the optimization direction of the optimization objective, the processor 1001 can also be used to call the photovoltaic power generation system parameter optimization program stored in the memory 1005 to perform the following operations:

[0064] Update the global optimal parameter value combination based on the target parameter value combination and the optimization direction;

[0065] Determine if the traversal has ended;

[0066] If not, return to the step of iterating through the system parameter value combinations of the photovoltaic power generation system to generate at least one parameter value combination for the current cycle.

[0067] Furthermore, before selecting the target parameter value combination whose target value is the optimal target value from each of the parameter value combinations according to the optimization direction of the optimization target, the processor 1001 can also call the photovoltaic power generation system parameter optimization program stored in the memory 1005 to perform the following operations:

[0068] If the target value of the constraint target corresponding to each parameter value combination in the current round does not meet the constraint condition corresponding to the constraint target, then return to the step of traversing the parameter value combinations of the system parameters of the photovoltaic power generation system to generate at least one parameter value combination in the current round.

[0069] Furthermore, after the operation of returning to the parameter value combinations of the system parameters traversed in the photovoltaic power generation system to generate at least one parameter value combination for the current round, the processor 1001 can also be used to call the photovoltaic power generation system parameter optimization program stored in the memory 1005 to perform the following operations:

[0070] If the target value of the constraint target corresponding to each parameter value combination in all rounds does not meet the constraint condition corresponding to the constraint target, then the constraint condition corresponding to the constraint target is adjusted, and / or the parameter value combination of the system parameters of the photovoltaic power generation system is adjusted, and the process returns to the step of traversing the parameter value combination of the system parameters of the photovoltaic power generation system to generate at least one parameter value combination for the current round.

[0071] Further, the operation of obtaining the target value corresponding to each combination of parameter values ​​based on each activation value includes:

[0072] The target value corresponding to each combination of parameter values ​​is calculated by substituting each of the parameter value combinations into the objective function.

[0073] Furthermore, the system parameters include at least one of the following: component installation angle, bracket spacing distance, component azimuth angle, system capacity ratio, and bracket height.

[0074] Furthermore, the limiting target includes at least one of revenue value, gross profit margin, and cost per kilowatt-hour, and the optimization target is a target other than the limiting target.

[0075] Based on the above structure, various embodiments of the photovoltaic power generation system parameter optimization method are proposed.

[0076] Reference Figure 2 , Figure 2 This is a flowchart illustrating the first embodiment of the photovoltaic power generation system parameter optimization method of the present invention.

[0077] This invention provides an embodiment of a photovoltaic power generation system parameter optimization method. It should be noted that although the logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order. In this embodiment, the executing entity of the photovoltaic power generation system parameter optimization method can be a personal computer, smartphone, server, or other device; no limitation is made in this embodiment. For ease of description, the execution entity is omitted from the following description of each embodiment. In this embodiment, the photovoltaic power generation system parameter optimization method includes:

[0078] Step S10: Obtain at least one combination of system parameters of the photovoltaic power generation system and the target value corresponding to each combination of parameter values, wherein the target value includes the target value of the optimization target and the target value of the constraint target;

[0079] In this embodiment, it should be noted that the photovoltaic power generation system is a system coupled with various system parameters. These system parameters include system variables and system fixed parameters. The system fixed parameters are the non-adjustable system parameters of the photovoltaic power generation system. The system variables include at least one of the following: component installation angle, support spacing distance, component azimuth angle, system capacity ratio, and support height. The component installation angle is the installation tilt angle of the component in the photovoltaic power generation system, and the component installation angle is adjusted within a preset angle range, which can be from 0° to 60°. The support spacing distance is the distance between two adjacent supports in the photovoltaic power generation system; the support spacing distance is adjusted within a preset distance range, which can be greater than 5. The component azimuth angle is the azimuth angle of the component relative to the sun in the photovoltaic power generation system, and the component azimuth angle is adjusted within a preset azimuth angle range, which can be from -30° to 30°. The capacity ratio is adjusted within a preset capacity ratio range, which can be from 1 to 2. The support height is the height of the support above the ground in the photovoltaic power generation system. The target value is the target value under the combined coupling of parameter values ​​of the photovoltaic power generation system. The number of targets can be one or more. When there are multiple targets, the targets include optimization targets and constraint targets. The number of constraint targets can be one or more. The optimization target is unique. The constraint targets include at least one of revenue value, gross profit margin and cost per kilowatt-hour.

[0080] In one feasible implementation, the limiting target is revenue value, and the optimization target is gross profit margin or cost per kilowatt-hour; or, the limiting target is gross profit margin, and the optimization target is revenue value or cost per kilowatt-hour; or, the limiting target is cost per kilowatt-hour, and the optimization target is revenue value or gross profit margin.

[0081] In another feasible embodiment, the limiting target is revenue value and gross profit margin, and the optimization target is cost per kilowatt-hour; or, the limiting target is revenue value and cost per kilowatt-hour, and the optimization target is gross profit margin; the limiting target is gross profit margin and cost per kilowatt-hour, and the optimization target is revenue value.

[0082] Step S10 includes:

[0083] Step S11: Substitute each of the parameter value combinations into the objective function to calculate the target value corresponding to each parameter value combination.

[0084] Step S20: When the target value of the constraint target corresponding to the parameter value combination meets the constraint condition corresponding to the constraint target, the target value of the optimization target corresponding to the parameter value combination is adjusted according to the preset first value in the optimization direction of the optimization target to update the target value of the optimization target;

[0085] In this embodiment, it should be noted that the limiting condition is a constraint condition for the limiting target, which can be a function constraint, such as a range constraint. The preset first value is an adjustment value of the target value of the optimization target corresponding to the parameter value combination when the target value of the limiting target corresponding to the pre-set judgment parameter value combination meets the limiting condition of the limiting target. The preset first value can be a positive value, a negative value, or 0. The optimization direction can be the direction of the maximum value or the direction of the minimum value.

[0086] For example, it is determined whether the target value of the constraint target corresponding to the parameter value combination meets the constraint condition corresponding to the constraint target. When the target value of the constraint target corresponding to the parameter value combination meets the constraint condition corresponding to the constraint target, the optimization direction and preset first value of the optimization target are obtained. According to the preset first value, the target value of the optimization target corresponding to the parameter value combination is adjusted in the optimization direction to update the target value of the optimization target.

[0087] Step S30: When the target value of the constraint target corresponding to the parameter value combination does not meet the constraint condition corresponding to the constraint target, the target value of the optimization target corresponding to the parameter value combination is adjusted according to the preset second value in the optimization direction of the optimization target to update the target value of the optimization target, wherein the preset first value is greater than the preset second value;

[0088] In this embodiment, it should be noted that the preset second value is the adjustment value of the target value of the optimization target corresponding to the parameter value combination when the target value of the constraint target corresponding to the preset judgment parameter value combination does not meet the constraint condition corresponding to the constraint target. The preset second value can be a positive value, a negative value, or 0.

[0089] For example, when the target value of the constraint target corresponding to the parameter value combination does not meet the constraint condition corresponding to the constraint target, a preset second value is obtained, and the target value of the optimization target corresponding to the parameter value combination is adjusted in the optimization direction according to the preset second value to update the target value of the optimization target.

[0090] In one feasible embodiment, the preset first value is 0 and the preset second value is negative; or, the preset first value is negative and the preset second value is negative; or, the preset first value is positive and the preset second value is positive; or, the preset first value is positive and the preset second value is 0; or, the preset first value is positive and the preset second value is negative.

[0091] In one feasible implementation, a filtering function corresponding to the restriction condition is obtained, wherein the filtering function is constructed from the restriction range of the target value of the restriction target, and the target value of the restriction target corresponding to the parameter value combination is determined according to the filtering function to whether it meets the restriction condition corresponding to the restriction target.

[0092] Optionally, the filtering function may specifically include:

[0093] F=a≥R

[0094] Where F is the filtering function, a is the target value of the restricted target, and R is the lower limit of the restricted target value range.

[0095] F=a≤R

[0096] Where F is the filtering function, a is the target value of the restricted target, and R is the upper limit of the restricted target value range.

[0097] F = R1 ≤ a ≤ R2

[0098] Where F is the filtering function, a is the target value of the restricted target, R1 is the lower limit of the restricted target value range, and R2 is the upper limit of the restricted target value range.

[0099] In another feasible embodiment, the ratio of the target value of the restricted target corresponding to each parameter value combination to the restriction value in the restriction conditions of the restricted target is obtained; according to the restriction range in the restriction conditions, a ratio threshold corresponding to the ratio is determined; according to the restriction range and the ratio threshold, it is determined whether the target value of the restricted target corresponding to the parameter value combination meets the restriction conditions corresponding to the restricted target; if the ratio is greater than or equal to the ratio threshold, a preset first value is selected to adjust the target value of the optimization target corresponding to the parameter value combination; if the ratio is less than the ratio threshold, a preset second value is selected to adjust the target value of the optimization target corresponding to the parameter value combination.

[0100] Optionally, the step of obtaining the ratio of the target value of the constraint target corresponding to each of the parameter value combinations to the constraint value in the constraint conditions of the constraint target may specifically include:

[0101] V i =S i (x,y,z) / R i

[0102] Among them, V i S is the ratio of the target value of the constrained target i corresponding to the parameter value combination to the constraint value in the constraint condition of the constrained target i. i (x,y,z) represents the target value of target i, and Rii The constraint value in the constraint conditions for limiting target i.

[0103] Optionally, the step of determining whether the target value of the constraint target corresponding to the parameter value combination meets the constraint conditions corresponding to the constraint target based on the constraint range and the ratio threshold may specifically include:

[0104]

[0105] Among them, F i (x,y,z) represents the determination result of the target value of target i, k1 is the preset first value, k2 is the preset second value, and V i The ratio of the target value of the constraint target i corresponding to the parameter value combination to the constraint value in the constraint condition of the constraint target i, where r is the ratio threshold.

[0106] Optionally, the step of adjusting the target value of the optimization target corresponding to the parameter value combination in the optimization direction of the optimization target to update the target value of the optimization target may specifically include:

[0107]

[0108] Among them, F new (x,y,z) represents the updated target value of the optimization objective, F org (x,y,z) represents the target value of the optimization objective, F i (x,y,z) represents the determination result of the target value of the restricted target i, and K represents the number of each restricted target. The sign of ± is determined by the optimization direction of the optimization target. When the optimization direction is the direction of the maximum value, the sign of ± is +, and when the optimization direction is the direction of the minimum value, the sign of ± is -.

[0109] In another feasible implementation, refer to Figure 3 , Figure 3 This is a schematic diagram of an update table for the target value of an optimization objective according to an embodiment of the present invention. Figure 3 This includes parameter value combinations (parameter combinations shown in the figure), the target value of the optimization target (F org shown in the figure), the target value of the constraint target (S1 shown in the figure), the updated target value of the optimization target (F new1, F new2, F new3 shown in the figure), and the constraint value in the constraint conditions (R shown in the figure). The adjustment amount of the target value of the optimization target that meets the constraint conditions corresponding to the parameter value combination (that is, the preset first value) is 1, and the adjustment amount of the target value of the optimization target that does not meet the constraint conditions corresponding to the parameter value combination (that is, the preset second value) is 0.

[0110] Step S40: Based on the optimization direction of the optimization target, select the target parameter value combination with the target value of the corresponding optimization target as the optimal target value from each of the parameter value combinations.

[0111] In this embodiment, it should be noted that the combination of target parameter values ​​can be a single value or multiple values.

[0112] In one feasible embodiment, if the optimization direction is the maximum value direction, then the target parameter value combination with the largest target value of the optimization target is selected from each of the parameter value combinations; if the optimization direction is the minimum value direction, then the target parameter value combination with the smallest target value of the optimization target is selected from each of the parameter value combinations.

[0113] In another feasible embodiment, before the step of adjusting the target value of the optimization target corresponding to the parameter value combination according to a preset first value in the optimization direction of the optimization target to update the target value of the optimization target when the target value of the constraint target corresponding to the parameter value combination meets the constraint condition corresponding to the constraint target, the method further includes:

[0114] Obtain the range of target values ​​for each combination of parameter values ​​corresponding to the optimization target, and determine a preset first value and a preset second value based on the range.

[0115] It is understandable that when the preset first and second values ​​have a small adjustment effect on the target value of the optimization objective, it is easy to select the wrong combination of target parameter values ​​(for example, the target value of the optimization objective of parameter value combination A is 1, the target value of the optimization objective of parameter value combination B is 1.1, the target value of the optimization objective of parameter value combination C is 1, the target value of the optimization objective of parameter value combination B is 1.2, the target values ​​of the limiting objectives corresponding to parameter value combination A and parameter value combination B meet the limiting conditions corresponding to the limiting objectives, the target value of the limiting objective corresponding to parameter value combination C does not meet the limiting conditions corresponding to the limiting objectives, the preset first value is 0.1, the preset second value is 0, and the optimization direction is the maximum value direction, then the target value of the optimization objective of parameter value combination A is updated to 1.1, the target value of the optimization objective of parameter value combination B is updated to 1.2, the target value of the optimization objective of parameter value combination C is updated to 1.2, and the selected target parameter value combination is parameter value combination B and parameter value combination C), thus resulting in low optimization accuracy of photovoltaic power generation system parameters.

[0116] To address the aforementioned shortcomings, a preset first value and a preset second value are determined based on the range of target values ​​corresponding to the optimization targets of each parameter value combination. This ensures that the target values ​​of the optimization targets corresponding to the constraint conditions of the constraint targets in each parameter value combination are as close as possible to the optimization direction. Consequently, the target values ​​of the optimization targets that meet the constraint conditions of the constraint targets are more clearly defined, thus balancing the optimization accuracy and efficiency of the photovoltaic power generation system parameters.

[0117] In this invention, at least one combination of system parameters of a photovoltaic power generation system and a target value corresponding to each of the parameter value combinations are obtained. The target value includes a target value for an optimization target and a target value for a constraint target. When the target value of the constraint target corresponding to the parameter value combination meets the constraint condition corresponding to the constraint target, the target value of the optimization target corresponding to the parameter value combination is adjusted in the optimization direction of the optimization target according to a preset first value to update the target value of the optimization target. When the target value of the constraint target corresponding to the parameter value combination does not meet the constraint condition corresponding to the constraint target, the target value of the constraint target corresponding to the parameter value combination is adjusted in the optimization direction of the optimization target according to a preset second value. The target value of the optimization target is adjusted to update the target value of the optimization target, wherein the preset first value is greater than the preset second value; according to the optimization direction of the optimization target, the target parameter value combination with the corresponding target value of the optimization target as the optimal target value is selected from each of the parameter value combinations; by adjusting and reconstructing the target value of the optimization target according to the target value of the limiting target of each parameter value combination, and then performing target optimization of parameter value combination according to the adjusted target value of the optimization target, the parameter value combination optimization of system parameters with multiple limiting targets is realized, without the need to select system parameter combinations according to the limiting conditions of each limiting target one by one, thereby improving the optimization efficiency of photovoltaic power generation system parameters.

[0118] Furthermore, based on the first embodiment described above, a second embodiment of the photovoltaic power generation system parameter optimization algorithm of the present invention is proposed. In this embodiment, before step S10, the algorithm further includes:

[0119] Step A10: Iterate through the parameter value combinations of the system parameters of the photovoltaic power generation system to generate at least one parameter value combination for the current round;

[0120] In one feasible embodiment, the parameter value combinations of the system parameters of the photovoltaic power generation system are divided into at least one round, and the parameter value combinations of the system parameters of the photovoltaic power generation system in a single round are traversed to generate at least one parameter value combination for the current round.

[0121] In another feasible implementation, all parameter value combinations of the system parameters of the photovoltaic power generation system are traversed to generate at least one parameter value combination for the current cycle.

[0122] After step S40, the method further includes:

[0123] Step S50: Update the global optimal parameter value combination according to the target parameter value combination and the optimization direction;

[0124] In one feasible implementation, if the optimization direction is the maximum value direction, the target parameter value combination of the previous round is obtained as the historical parameter value combination. If the target value of the optimization target corresponding to the historical parameter value combination is greater than the target value of the optimization target corresponding to the target parameter value combination, the global optimal parameter value combination is kept unchanged. If the target value of the optimization target corresponding to the historical parameter value combination is equal to the target value of the optimization target corresponding to the target parameter value combination, the target parameter value combination is added to the global optimal parameter value combination. If the target value of the optimization target corresponding to the historical parameter value combination is less than the target value of the optimization target corresponding to the target parameter value combination, the global optimal parameter value combination is updated to the historical parameter value combination.

[0125] In another feasible implementation, if the optimization direction is the minimum direction, the target parameter value combination of the previous round is obtained as the historical parameter value combination. If the target value of the optimization target corresponding to the historical parameter value combination is less than the target value of the optimization target corresponding to the target parameter value combination, the global optimal parameter value combination is kept unchanged. If the target value of the optimization target corresponding to the historical parameter value combination is equal to the target value of the optimization target corresponding to the target parameter value combination, the target parameter value combination is added to the global optimal parameter value combination. If the target value of the optimization target corresponding to the historical parameter value combination is greater than the target value of the optimization target corresponding to the target parameter value combination, the global optimal parameter value combination is updated to the historical parameter value combination.

[0126] Step S60: Determine if the traversal has ended;

[0127] In one feasible implementation, a preset optimization target value threshold is obtained, and each of the parameter value combinations is iterated. Based on the preset optimization target value threshold and the target value of the optimization target corresponding to the global optimal parameter value combination, it is determined whether the traversal has ended.

[0128] In one feasible implementation, when the optimization direction is the maximum value direction, the preset optimization target value threshold includes a preset optimization target value lower limit. If the target value of the optimization target corresponding to the global optimal parameter value combination is greater than or equal to the preset optimization target value lower limit, the traversal is determined to be over; if the target value of the optimization target corresponding to the global optimal parameter value combination is less than the preset optimization target value lower limit, the traversal is determined to be underway.

[0129] In another feasible implementation, when the optimization direction is the minimum value direction, the preset optimization target value threshold includes a preset optimization target value upper limit. If the target value of the optimization target corresponding to the global optimal parameter value combination is less than or equal to the preset optimization target value upper limit, the traversal is determined to be over; if the target value of the optimization target corresponding to the global optimal parameter value combination is greater than the preset optimization target value upper limit, the traversal is determined to be over.

[0130] In another feasible implementation, a preset iteration count threshold is obtained, and each of the parameter value combinations is iterated. The total number of iterations for each of the parameter value combinations is accumulated. If the total number of iterations reaches the preset iteration count threshold, the traversal is determined to be over. If the total number of iterations does not reach the preset iteration count threshold, the traversal is determined to be over.

[0131] In another feasible implementation, if all parameter value combinations in all rounds have been traversed, the traversal is determined to be complete; if there are parameter value combinations in the rounds that have not been traversed, the traversal is determined to be incomplete.

[0132] Step S70: If not, return to the step of traversing the parameter value combinations of the system parameters of the photovoltaic power generation system and generating at least one parameter value combination for the current cycle.

[0133] For example, if the traversal is not finished, the process returns to the step of traversing the parameter value combinations of the system parameters of the photovoltaic power generation system and generating at least one parameter value combination for the current round.

[0134] In this invention, the system parameters of the photovoltaic power generation system are traversed to generate at least one parameter value combination for the current cycle. The globally optimal parameter value combination is updated according to the target parameter value combination and the optimization direction. It is then determined whether the traversal has ended. If not, the process returns to the step of traversing the system parameters of the photovoltaic power generation system and generating at least one parameter value combination for the current cycle. Through iterative traversal, global optimization of the photovoltaic power generation system parameters can be achieved, thereby improving the optimization efficiency of the photovoltaic power generation system parameters.

[0135] Furthermore, based on the first and / or second embodiments described above, a third embodiment of the photovoltaic power generation system parameter optimization algorithm of the present invention is proposed. In this embodiment, before step S30, the algorithm further includes:

[0136] Step B10: If the target value of the constraint target corresponding to each parameter value combination in the current round does not meet the constraint condition corresponding to the constraint target, then return to the step of traversing the parameter value combinations of the system parameters of the photovoltaic power generation system to generate at least one parameter value combination in the current round.

[0137] It is understandable that even if there are many combinations of parameter values ​​for a single cycle of the photovoltaic power generation system, there may still be situations where the target values ​​of the constraint targets corresponding to the various combinations of parameter values ​​in the current cycle do not meet the constraint conditions corresponding to the constraint targets, thus making it impossible to complete the parameter optimization of the photovoltaic power generation system.

[0138] Step B20: If the target value of the constraint target corresponding to each parameter value combination in all rounds does not meet the constraint condition corresponding to the constraint target, then the constraint condition corresponding to the constraint target is adjusted, and / or the parameter value combination of the system parameters of the photovoltaic power generation system is adjusted, and the process returns to the step of traversing the parameter value combination of the system parameters of the photovoltaic power generation system to generate at least one parameter value combination for the current round.

[0139] It is understandable that even if there are many combinations of parameter values ​​for all rounds of the photovoltaic power generation system, there may still be situations where the target values ​​of the constraint targets corresponding to the various combinations of parameter values ​​in the current round do not meet the constraint conditions corresponding to the constraint targets, thus making it impossible to complete the parameter optimization of the photovoltaic power generation system.

[0140] In one feasible implementation, if the target value of the constraint target corresponding to each parameter value combination in all rounds does not meet the constraint condition corresponding to the constraint target, then the constraint condition corresponding to the constraint target is adjusted, and the process returns to the step of traversing the parameter value combination of the system parameters of the photovoltaic power generation system to generate at least one parameter value combination for the current round.

[0141] In another feasible implementation, if the target value of the constraint target corresponding to each parameter value combination in all rounds does not meet the constraint condition corresponding to the constraint target, then the parameter value combination of the system parameters of the photovoltaic power generation system is adjusted, and the process returns to the step of traversing the parameter value combination of the system parameters of the photovoltaic power generation system to generate at least one parameter value combination for the current round.

[0142] In another feasible implementation, if the target value of the constraint target corresponding to each parameter value combination in all rounds does not meet the constraint condition corresponding to the constraint target, then the parameter value combination of the system parameters of the photovoltaic power generation system and the constraint condition corresponding to the constraint target are adjusted, and the process returns to the step of traversing the parameter value combination of the system parameters of the photovoltaic power generation system to generate at least one parameter value combination for the current round.

[0143] In this invention, if the target values ​​of the constraint targets corresponding to each parameter value combination in the current round do not meet the constraint conditions corresponding to the constraint targets, the process returns to the step of traversing the parameter value combinations of the system parameters of the photovoltaic power generation system to generate at least one parameter value combination for the current round. If the target values ​​of the constraint targets corresponding to each parameter value combination in all rounds do not meet the constraint conditions corresponding to the constraint targets, the constraint conditions corresponding to the constraint targets are adjusted, and / or the parameter value combinations of the system parameters of the photovoltaic power generation system are adjusted, and the process returns to the step of traversing the parameter value combinations of the system parameters of the photovoltaic power generation system to generate at least one parameter value combination for the current round. This achieves timely return to the next round when the target values ​​of the constraint targets corresponding to each parameter value combination in the current round do not meet the constraint conditions corresponding to the constraint targets, and timely adjustment of the constraint conditions and / or parameter value combinations of the constraint targets when the target values ​​of the constraint targets corresponding to each parameter value combination in all rounds do not meet the constraint conditions corresponding to the constraint targets, thereby achieving optimization of the photovoltaic power generation system parameters.

[0144] Furthermore, this invention also proposes a parameter optimization device for a photovoltaic power generation system, referring to... Figure 4 The photovoltaic power generation system parameter optimization device includes:

[0145] The acquisition module 10 is used to acquire at least one combination of parameter values ​​of the system parameters of the photovoltaic power generation system and the target value corresponding to each combination of parameter values, wherein the target value includes the target value of the optimization target and the target value of the constraint target;

[0146] The first adjustment module 20 is used to adjust the target value of the optimization target corresponding to the parameter value combination according to a preset first value in the optimization direction of the optimization target to update the target value of the optimization target when the target value of the constraint target corresponding to the parameter value combination meets the constraint condition corresponding to the constraint target.

[0147] The second adjustment module 30 is used to adjust the target value of the optimization target corresponding to the parameter value combination according to a preset second value in the optimization direction of the optimization target to update the target value of the optimization target when the target value of the constraint target corresponding to the parameter value combination does not meet the constraint conditions corresponding to the constraint target. The preset first value is greater than the preset second value.

[0148] The selection module 40 is used to select the target parameter value combination with the target value of the optimization target as the optimal target value from each of the parameter value combinations, based on the optimization direction of the optimization target.

[0149] Furthermore, before the step of obtaining at least one combination of system parameters of the photovoltaic power generation system and the target value corresponding to each combination of parameter values, the photovoltaic power generation system parameter optimization device is further configured to:

[0150] Iterate through the combinations of system parameter values ​​of the photovoltaic power generation system to generate at least one combination of parameter values ​​for the current cycle;

[0151] After the step of selecting the target parameter value combination with the target value of the optimization objective as the optimal target value from each of the parameter value combinations according to the optimization direction of the optimization objective, the photovoltaic power generation system parameter optimization device is further configured to:

[0152] Update the global optimal parameter value combination based on the target parameter value combination and the optimization direction;

[0153] Determine if the traversal has ended;

[0154] If not, return to the step of iterating through the system parameter value combinations of the photovoltaic power generation system to generate at least one parameter value combination for the current cycle.

[0155] Furthermore, before the step of selecting the target parameter value combination with the target value corresponding to the target of the optimization objective as the optimal target value from each of the parameter value combinations according to the optimization direction of the optimization objective, the photovoltaic power generation system parameter optimization device is also used for:

[0156] If the target value of the constraint target corresponding to each parameter value combination in the current round does not meet the constraint condition corresponding to the constraint target, then return to the step of traversing the parameter value combinations of the system parameters of the photovoltaic power generation system to generate at least one parameter value combination in the current round.

[0157] Furthermore, after the step of returning to the parameter value combinations that iterate through the system parameters of the photovoltaic power generation system to generate at least one parameter value combination for the current round, the photovoltaic power generation system parameter optimization device is further configured to:

[0158] If the target value of the constraint target corresponding to each parameter value combination in all rounds does not meet the constraint condition corresponding to the constraint target, then the constraint condition corresponding to the constraint target is adjusted, and / or the parameter value combination of the system parameters of the photovoltaic power generation system is adjusted, and the process returns to the step of traversing the parameter value combination of the system parameters of the photovoltaic power generation system to generate at least one parameter value combination for the current round.

[0159] Furthermore, the acquisition module 10 is also used for:

[0160] The target value corresponding to each combination of parameter values ​​is calculated by substituting each of the parameter value combinations into the objective function.

[0161] Furthermore, the system parameters include at least one of the following: component installation angle, bracket spacing distance, component azimuth angle, system capacity ratio, and bracket height.

[0162] Furthermore, the limiting target includes at least one of revenue value, gross profit margin, and cost per kilowatt-hour, and the optimization target is a target other than the limiting target.

[0163] All embodiments of the photovoltaic power generation system parameter optimization device of the present invention can refer to the various embodiments of the photovoltaic power generation system parameter optimization method of the present invention, and will not be repeated here.

[0164] Furthermore, this embodiment of the invention also proposes a computer-readable storage medium storing a photovoltaic power generation system parameter optimization program, which, when executed by a processor, implements the steps of the photovoltaic power generation system parameter optimization method described below.

[0165] The various embodiments of the photovoltaic power generation system parameter optimization device and computer-readable storage medium of the present invention can all refer to the various embodiments of the photovoltaic power generation system parameter optimization method of the present invention, and will not be repeated here.

[0166] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0167] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0168] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0169] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A photovoltaic power generation system parameter optimization method, characterized in that, The photovoltaic power generation system parameter optimization method comprises the following steps: obtaining at least one parameter value combination of system parameters of a photovoltaic power generation system and corresponding target values of each parameter value combination, wherein the target values include target values of an optimization target and target values of a limiting target; when the target value of the limiting target corresponding to the parameter value combination meets the limiting condition corresponding to the limiting target, adjusting the target value of the optimization target corresponding to the parameter value combination in the optimization direction of the optimization target according to a preset first value to update the target value of the optimization target; when the target value of the limiting target corresponding to the parameter value combination does not meet the limiting condition corresponding to the limiting target, adjusting the target value of the optimization target corresponding to the parameter value combination in the optimization direction of the optimization target according to a preset second value to update the target value of the optimization target, wherein the preset first value is greater than the preset second value; selecting a target parameter value combination corresponding to the target value of the optimization target as an optimal target value from each parameter value combination in the optimization direction of the optimization target.

2. The photovoltaic power system parameter optimization method of claim 1, wherein, Before the step of obtaining at least one parameter value combination of system parameters of a photovoltaic power generation system and corresponding target values of each parameter value combination, the method further comprises: traversing the parameter value combinations of the system parameters of the photovoltaic power generation system to generate at least one parameter value combination of the current round; after the step of selecting a target parameter value combination corresponding to the target value of the optimization target as an optimal target value from each parameter value combination in the optimization direction of the optimization target, the method further comprises: updating a global optimal parameter value combination according to the target parameter value combination and the optimization direction; determining whether the traversal is completed; if not, returning to the step of traversing the parameter value combinations of the system parameters of the photovoltaic power generation system to generate at least one parameter value combination of the current round.

3. The photovoltaic power system parameter optimization method of claim 2, wherein, Before the step of selecting a target parameter value combination corresponding to the target value of the optimization target as an optimal target value from each parameter value combination in the optimization direction of the optimization target, the method further comprises: if the target values of the limiting target corresponding to each parameter value combination of the current round do not meet the limiting condition corresponding to the limiting target, returning to the step of traversing the parameter value combinations of the system parameters of the photovoltaic power generation system to generate at least one parameter value combination of the current round.

4. The photovoltaic power system parameter optimization method of claim 3, wherein, After the step of returning to the step of traversing the parameter value combinations of the system parameters of the photovoltaic power generation system to generate at least one parameter value combination of the current round, the method further comprises: if the target values of the limiting target corresponding to each parameter value combination of all rounds do not meet the limiting condition corresponding to the limiting target, adjusting the limiting condition corresponding to the limiting target and / or adjusting the parameter value combinations of the system parameters of the photovoltaic power generation system, and returning to the step of traversing the parameter value combinations of the system parameters of the photovoltaic power generation system to generate at least one parameter value combination of the current round.

5. The photovoltaic power system parameter optimization method of claim 1, wherein, The step of obtaining the target values corresponding to each parameter value combination comprises: The parameter value combination is substituted into the objective function to obtain a corresponding objective value.

6. The photovoltaic power system parameter optimization method of claim 1, wherein, The system parameters include at least one of a component installation angle, a support interval distance, a component azimuth angle, a system capacity ratio, and a support height.

7. The photovoltaic power system parameter optimization method according to any one of claims 1 to 5, wherein, The limiting objective includes at least one of a revenue value, a gross profit margin, and a degree of electricity cost, and the optimization objective is an objective other than the limiting objective.

8. A photovoltaic power generation system parameter optimization device, characterized by, The photovoltaic power generation system parameter optimization device includes: An acquisition module is configured to acquire at least one parameter value combination of system parameters of a photovoltaic power generation system and corresponding objective values of the parameter value combinations, wherein the objective values include objective values of an optimization objective and objective values of a limiting objective. A first adjustment module is configured to adjust an objective value of the optimization objective corresponding to the parameter value combination in an optimization direction of the optimization objective according to a preset first value to update the objective value of the optimization objective when the objective value of the limiting objective corresponding to the parameter value combination meets a limiting condition corresponding to the limiting objective. A second adjustment module is configured to adjust the objective value of the optimization objective corresponding to the parameter value combination in the optimization direction of the optimization objective according to a preset second value to update the objective value of the optimization objective when the objective value of the limiting objective corresponding to the parameter value combination does not meet the limiting condition corresponding to the limiting objective, wherein the preset first value is greater than the preset second value. A selection module is configured to select, from the parameter value combinations, a target parameter value combination corresponding to an optimal objective value of the objective value of the optimization objective in the optimization direction of the optimization objective.

9. A photovoltaic power generation system parameter optimization device, characterized by, The photovoltaic power generation system parameter optimization device includes a memory, a processor, and a photovoltaic power generation system parameter optimization program stored in the memory and executable on the processor, and the photovoltaic power generation system parameter optimization program, when executed by the processor, implements the steps of the photovoltaic power generation system parameter optimization method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a photovoltaic power generation system parameter optimization program, and the photovoltaic power generation system parameter optimization program, when executed by the processor, implements the steps of the photovoltaic power generation system parameter optimization method according to any one of claims 1 to 7.

Images