Floating photovoltaic electrical connection wiring method and system

Abstract

The invention discloses a floating photovoltaic electrical connection wiring method and system, and relates to the technical field of photovoltaic power generation system design, and the method comprises the steps: analyzing the power generation influence factors of a floating photovoltaic power station, and predicting the power generation amounts of different time periods or different regions according to the power generation influence factors; according to the floating photovoltaic power station and the generating capacity of the different areas, path planning is carried out, and constraint conditions are set; and determining a trunk line and a connection point according to the path planning result and the generating capacity, and completing electrical connection wiring. The improved A * algorithm is used for path planning, a multi-objective optimization method is adopted, multiple objectives such as the path length, the electric energy loss and the construction difficulty are balanced, constraint conditions such as the maximum bearing current and the voltage drop range of the cable are considered, and system operation safety is ensured. The achievement of the invention is supported by national key research and development plan projects, and the project name is offshore floating photovoltaic power generation key technology and core component research and development and engineering demonstration (project number: 2022YFB4200700).

Description

[0001] The results of this invention are supported by the National Key R&D Program Project, and the project name is: R&D and Engineering Demonstration of Key Technologies and Core Components for Offshore Floating Photovoltaic Power Generation (Project No.: 2022YFB4200700). Technical Field

[0002] The invention relates to the technical field of photovoltaic power generation system design, and in particular to a floating photovoltaic electrical connection wiring method and system. Background Art

[0003] As an emerging renewable energy utilization method, floating photovoltaic power generation has received widespread attention in recent years. By installing photovoltaic modules on the water surface, this technology not only solves the problem of traditional ground photovoltaic power stations occupying a large amount of land resources, but also effectively utilizes the cooling effect of water to improve power generation efficiency. However, the electrical connection and wiring design of floating photovoltaic systems faces many challenges. Traditional photovoltaic power station wiring methods are difficult to apply directly to water environments, because factors such as water surface fluctuations, water flow speed, and water depth changes will significantly affect the stability and efficiency of the system. In addition, the layout of floating photovoltaic systems is more complex, and special factors such as floating structures and anchoring systems need to be considered, which makes the optimization of electrical connection wiring particularly important.

[0004] Existing floating photovoltaic electrical connection wiring methods usually adopt simplified models and ignore many influencing factors, resulting in a large deviation between the design results and the actual situation. For example, most methods fail to fully consider the dynamic impact of the water surface environment on power generation efficiency, and fail to effectively integrate meteorological data and hydrological characteristics. In terms of path planning, existing technologies often only consider the shortest distance principle, ignoring multi-objective optimization requirements such as power loss and construction difficulty. In addition, when determining the trunk lines and connection points, the existing methods lack in-depth analysis of the overall power generation distribution of the system, making it difficult to achieve global optimization. These deficiencies have led to inefficient electrical connection wiring of floating photovoltaic systems, increased system construction and maintenance costs, and reduced overall power generation efficiency. Summary of the invention

[0005] In view of the problems existing in the existing floating photovoltaic electrical connection wiring method, the present invention is proposed.

[0006] Therefore, the problem to be solved by the present invention is that the existing wiring method ignores many influencing factors, resulting in a large deviation between the design result and the actual situation.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] In a first aspect, an embodiment of the present invention provides a floating photovoltaic electrical connection wiring method, which comprises:

[0009] Analyze the factors that affect power generation of the floating photovoltaic power station, and predict the power generation in different time periods or different regions based on the factors that affect power generation;

[0010] Perform path planning and set constraint conditions according to the floating photovoltaic power station layout data and the power generation of the different areas;

[0011] According to the path planning results and power generation, the trunk lines and connection points are determined, and the electrical connection wiring is completed.

[0012] As a preferred solution of the floating photovoltaic electrical connection wiring method of the present invention, the factors affecting power generation need to be solved to predict the power generation, as shown in the following formula:

[0013]

[0014] Among them, E t is the expected power generation in time period t (kWh), n is the number of solar panels, A i is the area of ​​the i-th solar panel, η i is the efficiency of the i-th solar panel, H t is the solar radiation in time period t, θ i is the angle between the sun's rays and the surface of the i-th solar panel, T t is the average ambient temperature during the time period t, T STC is the temperature under standard test conditions, D t is the dust deposition index in time period t, S i is the shadow factor of the i-th solar panel, m is the number of loss factors, L j is the jth loss factor, k is the time adjustment factor, t is the current time, t 0 is the reference time point.

[0015] As a preferred solution of the floating photovoltaic electrical connection wiring method of the present invention, wherein: the path planning takes path length, heuristic estimation, power loss and construction difficulty as targets to generate non-dominated solutions;

[0016] The objective function of the path planning is shown in the following formula:

[0017] f(n)=a·g(n)+β·h(n)+γ·e(n)+δ·c(n)

[0018] Among them, f(n) is the total evaluation function of node n, g(n) is the actual cost from the starting point to node n, h(n) is the estimated cost from node n to the target, e(n) is the energy loss evaluation function, c(n) is the construction difficulty evaluation function, and α, β, γ, δ are the weight coefficients of path length, heuristic estimation, energy loss and construction difficulty, respectively.

[0019] As a preferred solution of the floating photovoltaic electrical connection wiring method of the present invention, the path planning further includes dynamically adjusting the weight coefficient, as shown in the following formula:

[0020]

[0021] Among them, σ j Represents the importance score of each target, which is dynamically updated by the following formula:

[0022]

[0023] Where η is the learning rate, is the partial derivative of target j with respect to the total evaluation function, and the horizontal line represents the average value.

[0024] As a preferred solution of the floating photovoltaic electrical connection wiring method of the present invention, the constraint conditions include a maximum cable carrying current constraint, a voltage drop range constraint and a budget constraint.

[0025] As a preferred solution of the floating photovoltaic electrical connection wiring method of the present invention, wherein: the determination of the trunk line includes:

[0026] defining a hierarchical structure, and setting local power generation and cumulative power generation for nodes in each level of the hierarchical structure;

[0027] According to the hierarchical structure and the accumulated power generation, a hierarchical node structure is obtained by using a recursive function;

[0028] The recursive function includes,

[0029] The function checks whether the cumulative power generation of the current node is less than the threshold E of this level. threshold (level), if it is less than the threshold, the function returns directly and no longer processes the node and its child nodes; if it passes the threshold check, the current node is added to the set L of the corresponding level level In the process, the child nodes are further processed by traversing all the child nodes of the current node. For each child node, the ratio of its cumulative power generation to the cumulative power generation of the current node is calculated. If this ratio is greater than the set threshold r threshold , then recursively call this function on this child node and increase the level by 1.

[0030] As a preferred solution of the floating photovoltaic electrical connection wiring method of the present invention, the determination of the connection point includes:

[0031] defining a connection cost function for each node in the hierarchical node structure;

[0032] Determine the cost of each node connecting directly to the main line and the cost of connecting to a child node and then connecting to the main line through the child node;

[0033] Compare the costs of the two approaches, choose the smaller one, and proceed from the bottom up.

[0034] In a second aspect, an embodiment of the present invention provides a floating photovoltaic electrical connection wiring system, comprising:

[0035] A power generation determination module is used to analyze factors affecting power generation of a floating photovoltaic power station, and predict power generation in different time periods or in different regions based on the factors affecting power generation;

[0036] A path planning module, used for performing path planning according to the floating photovoltaic power station and the power generation of the different areas, and setting constraint conditions;

[0037] The main line and connection point determination module is used to determine the main line and connection point according to the path planning results and power generation, and complete the electrical connection wiring.

[0038] In a third aspect, an embodiment of the present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, wherein: when the processor executes the computer program, any step of the above-mentioned floating photovoltaic electrical connection wiring method is implemented.

[0039] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, any step of the above-mentioned floating photovoltaic electrical connection wiring method is implemented.

[0040] The beneficial effect of the present invention is to optimize the layout, inclination and orientation of solar panels through 3D modeling and simulation, maximize power generation efficiency, consider factors such as shadow effect, temperature, dust deposition, and more accurately estimate power generation. Use the improved A* algorithm for path planning, adopt a multi-objective optimization method, balance multiple objectives such as path length, power loss and construction difficulty, and consider constraints such as the maximum cable carrying current and voltage drop range to ensure the safe operation of the system. By optimizing the wiring path, the required cable length can be reduced, the material cost can be reduced, and the Pareto optimization method is used to generate multiple non-dominated solutions to provide decision makers with more options. Dynamically adjust the algorithm weights so that the solution can adapt to different project needs and preferences. Through the hierarchical structure design of the trunk and branch lines, reasonably allocate power transmission, determine the optimal connection point location, and further optimize the system structure. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. Among them:

[0042] Figure 1 Flowchart of method for wiring floating photovoltaic electrical connections. DETAILED DESCRIPTION

[0043] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0044] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0045] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0046] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0047] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0048] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0049] Example 1

[0050] Reference Figure 1 , which is the first embodiment of the present invention, provides a floating photovoltaic electrical connection wiring method, comprising:

[0051] Use professional 3D modeling software to build a virtual model of the system, accurately draw the floating structure, solar panel array and anchoring system, add water characteristics such as water depth, water flow direction and speed, simulate the sun's trajectory in different seasons, calculate the angle of sunlight incidence, and integrate meteorological data such as wind speed, rainfall and other environmental factors.

[0052] Consider the inclination, orientation and spacing of solar panels, optimize the layout to maximize power generation efficiency, analyze the shadow effect between arrays, minimize mutual shading, consider the impact of factors such as temperature and dust deposition on power generation efficiency, and estimate the expected power generation in different time periods (hours, days, months, years).

[0053] Furthermore, according to the basic solar power generation formula, it is summed, that is, in actual power generation applications, there are multiple solar panels, and the cosine function is used to simulate the clamping of sunlight and the panel, removing its effect on the actual amount of radiation received, as follows:

[0054]

[0055] Furthermore, temperature has a significant impact on the efficiency of solar panels. A nonlinear function is used to simulate the temperature increase, thereby describing the decrease in the heating efficiency of solar panels. In addition, solar panels are exposed to the air, and there will be more or less dust accumulation on the surface. Moreover, dust accumulation will reduce the efficiency of solar panels, so the decline rate is further described:

[0056]

[0057] Similarly, if the solar panels are arranged in parallel, the shadow of the front solar panel will cause the input of the rear solar panel, and there will be some loss during transmission. By adding the shadow factor and the loss, the influence is eliminated, and finally the time change factor is added to estimate the power consumption in different time periods to obtain the final estimation formula:

[0058]

[0059] Among them, E t is the expected power generation in time period t (kWh), n is the number of solar panels, A i is the area of ​​the i-th solar panel (m 2 ), η i is the efficiency of the i-th solar panel, H t is the solar radiation in time period t (kWh / m 2 ), θ i is the angle between the sun's rays and the surface of the i-th solar panel, T t is the average ambient temperature in the time period t (℃), T STC is the temperature under standard test conditions (usually 25°C), D t is the dust deposition index in time period t, S i is the shadow factor of the i-th solar panel (a value between 0 and 1, 1 means no shadow), m is the number of loss factors, L j is the jth loss factor (such as line loss, inverter loss, etc.), k is the time adjustment factor, t is the current time, t 0 is the reference time point.

[0060] Furthermore, the layout and capacity design of the trunk lines can be determined based on the power generation forecasts of different regions, and the series and parallel connection schemes of solar panels can also be optimized based on the power generation forecasts.

[0061] Furthermore, the layout of the power generation panels is collected, the power generation distribution is obtained according to the power estimation formula, the water surface topography and other related data are established, and a digital map is established, including information such as obstacles, water depth, flow rate, etc. The improved A* algorithm is used for preliminary path planning.

[0062] For example, in a feasible embodiment, the A* algorithm is improved as follows:

[0063] It should be noted that the basic A* algorithm implementation first defines the node structure, including the position, g value (the actual cost from the starting point to the current node) and h value (the estimated cost from the current node to the target), implements the open list and closed list to manage the nodes to be explored and explored, and designs the heuristic function, considering the straight-line distance and obstacle density.

[0064] Improve the basic A* algorithm, introduce dynamic weight adjustment, dynamically adjust the weights of g and h according to the characteristics of the current path, use finer grids for complex areas, further add path smoothing, and reduce unnecessary jagged paths. Consider the characteristics of floating photovoltaic systems, incorporate water flow speed and direction into the cost function, optimize the layout of cables in the water, consider water depth changes, avoid deep water or unstable areas, add obstacle avoidance logic, and bypass floating bodies and other fixed facilities.

[0065] Furthermore, considering multiple objectives such as path length, power loss, and construction difficulty at the same time, the Pareto optimization method is used to generate a series of non-dominated solutions. The multi-objective A* algorithm can be expressed as follows:

[0066] f(n)=a·g(n)+β·h(n)+γ·e(n)+δ·c(n)

[0067] Among them, f(n) is the total evaluation function of node n, g(n) is the actual cost from the starting point to node n, h(n) is the estimated cost from node n to the target, e(n) is the energy loss evaluation function, c(n) is the construction difficulty evaluation function, and α, β, γ, δ are the weight coefficients of path length, heuristic estimation, energy loss and construction difficulty, respectively.

[0068] Specifically, the actual cost g(n) from the starting point to node n introduces a time-varying factor to simulate the impact of sleep fluctuations on the path length, as follows:

[0069]

[0070] Among them, x n ,y n is the coordinate of node n, parent(n) is the parent node of node n, λ is the amplitude coefficient of the influence of water surface fluctuation on path length, w is the frequency of water surface fluctuation, and t is the current time.

[0071] The heuristic function h(n) considers the impact of water depth on cabling difficulty and cost, encouraging the algorithm to choose shallow water areas when possible. Adding the water depth factor helps avoid deep water areas and reduce the difficulty of installation and maintenance:

[0072]

[0073] Where D is the scaling factor of the distance estimate, x goal ,y goal is the coordinate of the target point, μ is the water depth influence coefficient, depth(n): is the water depth at node n, max depth is the maximum water depth in area S.

[0074] In the calculation of power loss target, considering that temperature has a significant impact on resistance, which in turn affects power loss, and water flow velocity causes changes in cable heat dissipation effect, which indirectly affects resistance, the improvements of temperature and water flow are added:

[0075]

[0076] Among them, R is the resistivity of the cable, I is the current, and L is nis the cable length from the starting point to node n, A is the cross-sectional area of the cable, θ is the influence coefficient of temperature on resistance, T n is the temperature at node n, T ref is the reference temperature (usually the standard temperature), is the influence coefficient of water flow velocity on power loss, v n is the water flow velocity at node n.

[0077] In the construction difficulty assessment objective, the influences of water depth, obstacle density, and water flow velocity are combined using a non-linear function, simultaneously reflecting the non-linear growth of water depth on construction difficulty, the progressive influence of obstacle density on construction difficulty, and the rapid growth influence of water flow velocity on construction safety, as follows:

[0078]

[0079] Among them, W 1 , W 2 , W 3 are the weights of the influences of water depth, obstacle density, and water flow velocity, d 0 is the reference depth of the influence of water depth, k is the steepness coefficient of the influence of obstacle density, o n is the obstacle density at node n, o 0 is the reference value of the obstacle density, s n is the water flow velocity at node n, s max is the maximum water flow velocity.

[0080] Furthermore, dynamically adjust the weights of each part:

[0081]

[0082] Among them, σ j represents the importance score of each objective, and is dynamically updated through the following formula:

[0083]

[0084] Among them, η is the learning rate, is the partial derivative of objective j with respect to the total evaluation function, and the horizontal line represents the average value.

[0085] Use the Pareto optimization method to generate a series of non-dominated solutions:

[0086] Define the dominance relationship: If for all objectives i, f_i(x) ≤ f_i(y), and there is at least one objective j such that f_j(x) < f_j(y), then solution x is said to dominate solution y.

[0087] Maintain a Pareto optimal solution set P, for each newly generated solution x:

[0088] If no solution in P dominates x, add x to P;

[0089] Remove all solutions from P that are dominated by x.

[0090] Finally, the algorithm outputs the Pareto optimal solution set P.

[0091] It provides a series of non-dominated solutions instead of a single "optimal" solution, allowing decision makers to make trade-offs and choices among multiple objectives, better handling conflicts between objectives in multi-objective optimization problems, increasing decision-making flexibility, and adapting to different project needs and preferences.

[0092] Furthermore, in order to obtain the wiring plan for the multi-objective A* algorithm, some constraints are also needed, including the maximum cable carrying current constraint, the voltage drop range constraint, and the budget constraint.

[0093] For example, in a feasible constraint setting, the cable maximum carrying current constraint can be set as follows:

[0094]

[0095] Among them, I i is the actual current of cable i, I max is the maximum allowable current of the cable under standard conditions, μ is the influence coefficient of temperature on current carrying capacity, T i is the actual temperature of cable i, T ref is the reference temperature (usually the standard ambient temperature), T max The maximum operating temperature allowed for the cable.

[0096] In this feasible constraint setting, the influence of cable temperature rise on the maximum carrying current during transportation is considered;

[0097] For example, in a feasible constraint setting, the voltage drop range constraint can be set as follows:

[0098]

[0099] Among them, V min is the minimum allowable voltage, V max is the maximum allowable voltage, V 0 is the initial voltage of the system, R is the resistivity of the cable material, I i is the current in cable i, L i is the length of cable i, A i is the cross-sectional area of ​​cable i, α is the influence coefficient of temperature on resistance, T i is the temperature of cable i, T ref is the reference temperature.

[0100] For example, in a feasible constraint setting, the budget constraint can be set as follows:

[0101]

[0102] Among them, c i is the unit length cost of cable i, L i is the length of cable i, η is the coefficient of influence of water depth on cost, d i is the water depth at the location of cable i, d max is the maximum water depth in the system and B is the total budget.

[0103] Furthermore, the wiring scheme based on the A* algorithm is combined with the local power generation to design the trunk and branch line structures and determine the optimal connection point location.

[0104] For example, in a feasible embodiment, the trunk and branch structures are as follows:

[0105] Based on the preliminary routing results of the A* algorithm, we first define a hierarchical structure L = (L 1 ,L 2 ,…,L k ) where L i Represents the line of the i-th level, L1 is the main line, and Lk is the thinnest branch line; for each node n, its local power generation E(n) and cumulative power generation EA(n) are defined as: EA(n) = E(n) + ∑ c∈children(n) EA(c) further constructs a hierarchical structure based on recursive functions:

[0106] First, the function checks whether the cumulative power generation of the current node EA(node) is less than the threshold E of the level. threshold (level), if it is less than the threshold, the function returns directly and no longer processes the node and its child nodes; if it passes the threshold check, the current node is added to the set L of the corresponding level level In the process, the child nodes are further processed by traversing all the child nodes of the current node. For each child node, the ratio of its cumulative power generation to the cumulative power generation of the current node is calculated. If this ratio is greater than the set threshold r threshold , then recursively call this function on this child node and increase the level by 1.

[0107] The recursion terminates when the cumulative power generation of the node is less than the threshold of the level or when the node has no child nodes, or the power generation ratio of all child nodes is lower than the threshold.

[0108] A hierarchical node structure is obtained through a recursive function. Specifically, L1 contains the highest level nodes, usually corresponding to the trunk line, L2 contains the second highest level nodes, corresponding to the main branch line, and so on. Lk contains the lowest level nodes, corresponding to a single or small group of photovoltaic panel units.

[0109] Need to explain, E threshold (level) can be calculated by the following formula:

[0110] E threshold (level)=E total ·a level-1

[0111] Among them, E total is the total power generation of the entire system, and level is the desired number of levels.

[0112] r threshold By calculating the power generation ratio of all child nodes to the parent node, drawing a ratio distribution histogram, and selecting an appropriate percentile as r threshold Initial value.

[0113] Further, determine the best connection point location:

[0114] For example, in one feasible embodiment, as follows:

[0115] For each node in the system, a connection cost function C(n) is defined, taking into account three main factors: Distance factor L(n), which represents the distance from node n to the main line. The longer the distance, the higher the connection cost because longer cables are required. Power generation factor 1 / EA(n): EA(n) is the cumulative power generation of the node. The inverse of this term means that the greater the power generation, the lower the connection cost. Location factor R(n), which reflects the location of the node. Finally, the optimal connection point is found through a dynamic programming algorithm.

[0116] For example, in one feasible embodiment, as follows:

[0117] For each node, there are two options:

[0118] Connect the node directly to the main line at a cost of C(n);

[0119] Connect the node to one of its child nodes, and then connect to the main line through the child node.

[0120] By comparing the costs of the two options, the smaller one is selected. This process is carried out from bottom to top, and finally the optimal connection solution for the entire system is obtained.

[0121] Furthermore, this embodiment also provides a floating photovoltaic electrical connection wiring system, including:

[0122] A power generation determination module is used to analyze factors affecting power generation of a floating photovoltaic power station, and predict power generation in different time periods or in different regions based on the factors affecting power generation;

[0123] A path planning module, used for performing path planning according to the floating photovoltaic power station and the power generation of the different areas, and setting constraint conditions;

[0124] The main line and connection point determination module is used to determine the main line and connection point according to the path planning results and power generation, and complete the electrical connection wiring

[0125] This embodiment also provides a computer device, which is applicable to the floating photovoltaic electrical connection wiring method, including a memory and a processor; the memory is used to store computer executable instructions, and the processor is used to execute the computer executable instructions to implement the floating photovoltaic electrical connection wiring method proposed in the above embodiment.

[0126] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected via a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covering the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0127] This embodiment further provides a storage medium on which a computer program is stored. When the program is executed by a processor, the floating photovoltaic electrical connection wiring method proposed in the above embodiment is implemented.

[0128] The storage medium proposed in this embodiment and the data storage method proposed in the above embodiment belong to the same inventive concept. The technical details not fully described in this embodiment can be found in the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0129] Example 2

[0130] This is the second embodiment of the present invention. This embodiment provides a floating photovoltaic electrical connection wiring method. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through economic benefit calculation and simulation experiments.

[0131] In order to verify the effectiveness of the floating photovoltaic electrical connection wiring method of the present invention, an experiment was conducted in a large reservoir. First, a virtual model of a floating photovoltaic system containing 500 solar panels was built using the professional 3D modeling software SolidWorks. The model accurately depicts the floating structure, solar panel array and anchoring system. By integrating the water depth data provided by the local hydrological bureau, water body features with a water depth range of 5-30 meters were added to the model. At the same time, using the historical data of the meteorological station for one year, the sun's trajectory in different seasons was simulated, the angle of sunlight incidence was calculated, and environmental factors such as wind speed and rainfall were integrated.

[0132] In the layout optimization stage, considering the latitude and seasonal changes in the area, the inclination angle of the solar panels was set to 15°-30°, facing due south, and the distance between panels was 1.5 times the length of the panel. The shadow analysis algorithm was implemented using MATLAB programming, and the optimal spacing to minimize mutual shading was calculated by simulating the changes in the position of the sun throughout the year. Taking into account the local high temperature in summer and dust deposition in winter, the temperature correction coefficient and dust influence factor were introduced in the power generation efficiency estimation. Based on the improved power generation estimation formula, the expected power generation at different time scales (hours, days, months, and years) was calculated.

[0133] Subsequently, the improved A* algorithm was used for path planning. The algorithm added water flow speed and direction as new variables in the cost function to optimize the layout of cables in water. By setting the water depth threshold, areas with a water depth of more than 25 meters were successfully avoided. In the construction difficulty assessment, the nonlinear effects of water depth, obstacle density and water flow speed were considered. A series of non-dominated solutions were generated using the Pareto optimization method, providing multiple wiring schemes for decision-making.

[0134] In the constraint setting, considering the high temperature in summer in the region, the temperature influence coefficient μ in the cable maximum carrying current constraint is set to 0.005 / ℃, and Tmax is set to 90℃. In the voltage drop range constraint, considering the system scale, the maximum allowable voltage drop is set to 5%. In the budget constraint, based on the total project investment, the cable budget cap is set to 8% of the total investment.

[0135] Finally, based on the wiring results of the A* algorithm, the trunk and branch structure were designed in combination with the local power generation. A 4-layer hierarchical structure was constructed through a recursive function, where L1 is the trunk, L2-L3 are branches, and L4 corresponds to a single or small group of photovoltaic panel units. When determining the optimal connection point location, the dynamic programming algorithm was used to compare the costs of the two options of directly connecting to the trunk and connecting to the trunk through a subnode, and finally the optimal connection solution for the entire system was obtained.

[0136] Compared with other existing technologies, the advantages of our solution are as follows:

[0137] Table 1 Comparison of existing technologies

[0138] Optimization Project Traditional methods Method of the present invention Improvement unit Average annual electricity generation 876.5 968.2 10.46％ MWh System efficiency 15.8 17.5 10.76％ ％ Total wiring length 15.6 13.8 -11.54％ km Power loss rate 3.2 2.7 -15.63％ ％ Maximum water depth adaptability 20 25 25.00％ m Construction Difficulty Index 72 65 -9.72％ Dimensionless System reliability score 85 92 8.24％ point

[0139] By comparing the data in the table, it can be clearly seen that the method of the present invention shows significant advantages in multiple key indicators. First, the average annual power generation increased from 876.5MWh to 968.2MWh, an increase of 10.46%. This significant increase is mainly due to the fact that the method of the present invention takes into account more influencing factors, such as accurate shadow analysis, temperature correction and dust effects, which makes the layout of solar panels more optimized and makes full use of available space and light resources.

[0140] The improvement in system efficiency is more obvious, increasing from 15.8% to 17.5%, a relative improvement of 10.76%. This improvement fully demonstrates the advantages of the method of the present invention in overall system optimization. By considering special factors such as water flow and water depth, and using the improved A* algorithm for path planning, the various components of the system have achieved better coordination.

[0141] In terms of total wiring length, the method of the present invention achieved a 11.54% reduction, from 15.6 km to 13.8 km. This not only directly reduces material costs, but also indirectly reduces the power loss of the system. The reduction in power loss rate from 3.2% to 2.7% is a relative improvement of 15.63%, which further improves the overall efficiency of the system.

[0142] The maximum water depth adaptability is increased from 20m to 25m, an increase of 25%, which shows the adaptability of the method of the present invention in complex hydrological environments. This improvement allows the system to be applied in a wider range of waters, greatly increasing the flexibility of site selection.

[0143] The reduction of the construction difficulty index (from 72 to 65, an improvement of 9.72%) shows that the method of the present invention has higher feasibility in practical application. By considering the nonlinear effects of water depth, obstacle density and water flow velocity, the construction plan is optimized and the implementation difficulty is reduced.

[0144] In general, the method of the present invention has significant advantages in improving power generation efficiency, optimizing wiring design, enhancing environmental adaptability and improving system reliability. These improvements not only improve the technical indicators of the system, but also bring substantial benefits in terms of economy and sustainability.

[0145] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A floating photovoltaic electrical connection wiring method, characterized in that: include, Analyze the factors that affect power generation of the floating photovoltaic power station, and predict the power generation in different time periods or different regions based on the factors that affect power generation; Perform path planning and set constraint conditions according to the floating photovoltaic power station layout data and the power generation of the different areas; According to the path planning results and power generation, the trunk lines and connection points are determined, and the electrical connection wiring is completed.

2. The floating photovoltaic electrical connection wiring method according to claim 1, characterized in that: To predict the power generation, the factors affecting power generation need to be solved, as shown in the following formula: Among them, E t is the expected power generation in time period t (kWh), n is the number of solar panels, A i is the area of ​​the i-th solar panel, η i is the efficiency of the i-th solar panel, H t is the solar radiation in time period t, θ i is the angle between the sun's rays and the surface of the i-th solar panel, T t is the average ambient temperature during the time period t, T STC is the temperature under standard test conditions, D t is the dust deposition index in time period t, S i is the shadow factor of the i-th solar panel, m is the number of loss factors, L j is the jth loss factor, k is the time adjustment factor, t is the current time, and t0 is the reference time point.

3. The floating photovoltaic electrical connection wiring method according to claim 2, characterized in that: The path planning takes path length, heuristic estimation, power loss and construction difficulty as targets to generate non-dominated solutions; The objective function of the path planning is shown in the following formula: f(n)=a·g(n)+β·h(n)+γ·e(n)+δ·c(n) Among them, f(n) is the total evaluation function of node n, g(n) is the actual cost from the starting point to node n, h(n) is the estimated cost from node n to the target, e(n) is the energy loss evaluation function, c(n) is the construction difficulty evaluation function, and α, β, γ, δ are the weight coefficients of path length, heuristic estimation, energy loss and construction difficulty, respectively.

4. The floating photovoltaic electrical connection wiring method according to claim 3, characterized in that: The path planning also includes dynamically adjusting the weight coefficient, as shown in the following formula: Among them, σ j Represents the importance score of each target, which is dynamically updated by the following formula: Where η is the learning rate, is the partial derivative of target j with respect to the total evaluation function, and the horizontal line represents the average value.

5. The floating photovoltaic electrical connection wiring method according to claim 4, characterized in that: The constraints include a maximum cable carrying current constraint, a voltage drop range constraint, and a budget constraint.

6. The floating photovoltaic electrical connection wiring method according to claim 5, characterized in that: Determining the trunk line includes: defining a hierarchical structure, and setting local power generation and cumulative power generation for nodes in each level of the hierarchical structure; According to the hierarchical structure and the accumulated power generation, a hierarchical node structure is obtained by using a recursive function; The recursive function includes, The function checks whether the cumulative power generation of the current node is less than the threshold E of this level. threshold (level), if it is less than the threshold, the function returns directly and no longer processes the node and its child nodes; If the threshold check is passed, the current node is added to the set L of the corresponding level. level In the process, the child nodes are further processed by traversing all the child nodes of the current node. For each child node, the ratio of its cumulative power generation to the cumulative power generation of the current node is calculated. If this ratio is greater than the set threshold r threshold , then recursively call this function on this child node and increase the level by 1.

7. The floating photovoltaic electrical connection wiring method according to claims 1 and 6, characterized in that: The determination of the connection point includes: defining a connection cost function for each node in the hierarchical node structure; Determine the cost of each node connecting directly to the main line and the cost of connecting to a child node and then connecting to the main line through the child node; Compare the costs of the two approaches, choose the smaller one, and proceed from the bottom up.

8. A floating photovoltaic electrical connection wiring system, based on the floating photovoltaic electrical connection wiring method according to any one of claims 1 to 7, characterized in that: include, A power generation determination module is used to analyze factors affecting power generation of a floating photovoltaic power station, and predict power generation in different time periods or in different regions based on the factors affecting power generation; A path planning module, used for performing path planning according to the floating photovoltaic power station and the power generation of the different areas, and setting constraint conditions; The main line and connection point determination module is used to determine the main line and connection point according to the path planning results and power generation, and complete the electrical connection wiring.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the floating photovoltaic electrical connection wiring method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the floating photovoltaic electrical connection wiring method according to any one of claims 1 to 7 are implemented.

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