Water surface photovoltaic power station current collection system power generation unit layout and current collection cable collaborative optimization design method

Abstract

The invention relates to a water surface photovoltaic power station current collection system power generation unit layout and current collection cable collaborative optimization design method. Compared with the prior art, the problem that reasonable layout of water surface photovoltaic power station power generation units and reasonable laying of current collection cables are difficult to achieve is solved. The method comprises the following steps: acquiring the water area condition of a water surface photovoltaic power station and the condition of a photovoltaic device; optimizing the layout of power generation units of the water surface photovoltaic power station; optimizing a current collection cable of the water surface photovoltaic power station; carrying out collaborative optimization on the layout of power generation units of the water surface photovoltaic power station and a current collection cable; and layout of power generation units of the water surface photovoltaic power station and acquisition of a current collection cable laying result. The invention provides layout optimization of power generation units of a water surface photovoltaic power station current collection system based on a minimum power generation unit, and current collection cable optimization integrating fuzzy C-means clustering, a DM-MSTP algorithm and current collection cable automatic type selection. And performing water surface photovoltaic power station power generation unit layout and current collection cable collaborative optimization by using a particle swarm algorithm and taking the total investment cost of the water surface photovoltaic power station as a target, thereby achieving the purpose of water surface photovoltaic power station current collection system power generation unit layout and current collection cable collaborative optimization design.

Description

Technical Field

[0001] The present invention relates to the technical field of water surface photovoltaic power stations, and in particular to a collaborative optimization design method for the layout of power generation units and collection cables of a water surface photovoltaic power station collection system. Background Art

[0002] The cost of the power collection system of a water-surface photovoltaic power station accounts for a non-negligible proportion of the investment in a water-surface photovoltaic power station. The optimization of the power collection system includes two parts: optimization of the layout of photovoltaic power generation units and optimization of the power collection cables.

[0003] The optimization of photovoltaic power generation unit layout not only affects the AC side capacity configuration and AC / DC cable engineering of the photovoltaic power generation system, but also affects the overall efficiency of the photovoltaic power generation system. Compared with the optimization of ground photovoltaic power generation unit layout, the optimization of water surface photovoltaic power generation unit layout is more complicated. It is not only limited by the shape of the water surface, but also by the operation and maintenance channels. The operation and maintenance channels have their own requirements and affect the installed capacity, capacity ratio, power generation unit shape, cable path, etc. of the photovoltaic power generation unit.

[0004] The existing research results of water surface photovoltaic power stations are aimed at the design of mooring systems of water surface photovoltaic power stations. There are few studies on the design and optimization of the collection system of water surface photovoltaic power stations. Since both water surface photovoltaic power stations and offshore wind farms involve the optimization of the collection system, we refer to the research reports on the optimization of the collection system of offshore wind farms. In the optimization of the collection system of offshore wind farms, heuristic algorithms and graph theory-based methods are often used to optimize the length of the collection cable, and sequential optimization, combination optimization, double-layer optimization and other methods are used to coordinate the optimization of the micro-site selection of offshore wind farms and the collection cables. As for the layout of the power generation units and the laying of the collection cables of the collection system of water surface photovoltaic power stations, they are still based on manual design or BIM software design, with the disadvantages of low automation, poor economy and time-consuming design.

[0005] Therefore, the coordinated optimization design of the layout of power generation units and the laying of collector cables in the water surface photovoltaic power station collection system has become a key technical problem that needs to be urgently solved in the field of water surface photovoltaic power station technology. Summary of the invention

[0006] The purpose of the present invention is to solve the defect that it is difficult to achieve the reasonable layout of power generation units and the reasonable laying of collector cables in the prior art of water surface photovoltaic power stations, and to provide a collaborative optimization design method for the layout of power generation units and collector cables of the collector system of a water surface photovoltaic power station to solve the above problems.

[0007] In order to achieve the above object, the technical solution of the present invention is as follows:

[0008] A method for collaborative optimization design of power generation unit layout and power collection cables of a power collection system of a water surface photovoltaic power station comprises the following steps:

[0009] 11) Obtaining water conditions and photovoltaic device conditions: Obtaining basic data on the water area for site selection of water surface photovoltaic power stations and photovoltaic devices of water surface photovoltaic power stations. Photovoltaic devices of water surface photovoltaic power stations include inverters, photovoltaic panels and box-type substations. Pre-calculating the basic data, obtaining the number of photovoltaic modules in the minimum power generation unit and the length and width of the photovoltaic modules;

[0010] 12) Optimization of the layout of power generation units of water surface photovoltaic power stations: The minimum number of power generation units N in the water surface photovoltaic power generation unit p.unit The length-to-width ratio K=L / W is used as the optimization variable, the investment cost of the power generation unit of the water surface photovoltaic power station is used as the objective function, the water conditions, power generation capacity, and operation and maintenance channel constraints are used as constraints, and the layout of the power generation unit of the water surface photovoltaic power station is optimized based on the minimum power generation unit and the particle swarm algorithm is used to obtain the layout of the power generation unit of the water surface photovoltaic power station; the box-type substation is set to be arranged in the middle of the power generation unit of the water surface photovoltaic power station, and the coordinates of the box-type substation are obtained according to the layout of the power generation unit of the water surface photovoltaic power station;

[0011] 13) Optimization of collector cables for water-surface photovoltaic power stations: Based on the coordinates of box-type substations, the improved fuzzy C clustering, DM-MSTP and automatic selection method of collector cables are integrated to optimize the cables between box-type substations in water-surface photovoltaic power stations, and the laying method of collector cables for water-surface photovoltaic power stations is obtained;

[0012] 14) Co-optimization of the layout of power generation units and power collection cables of the water surface photovoltaic power station collection system: Calculate the total investment cost of the water surface photovoltaic power station collection system, and use the particle swarm algorithm to iteratively optimize until the convergence conditions are met to determine the minimum number of power generation units N in the water surface photovoltaic power generation unit p.unit and the length-to-width ratio K=L / W, the optimal total investment cost of the water surface photovoltaic power station collection system, the layout of the water surface photovoltaic power station power generation units, and the general plan for the laying of the collection cables are obtained.

[0013] The layout optimization of the power generation unit of the water surface photovoltaic power station comprises the following steps:

[0014] 21) Determine the capacity of the water surface photovoltaic power generation unit based on the definition of the minimum power generation unit:

[0015] The photovoltaic power generation unit consisting of an inverter and n photovoltaic modules is defined as the minimum power generation unit. Based on the PVsyst software, the geographical parameters of the water surface photovoltaic power station, the photovoltaic panel model, and the inverter model are input. The number of photovoltaic modules in parallel and the number of inverters obtained are divided, and the quotient is the number of photovoltaic modules in the minimum power generation unit, n.

[0016] The minimum generating unit capacity is expressed as:

[0017] P min =P INV ×λ (1)

[0018] Where: P min is the minimum generating unit capacity, P INV is the rated power of the inverter, λ is the capacity ratio, and its value is calculated based on the PVsyst software;

[0019] The power generation capacity of the water surface photovoltaic power generation unit is expressed as:

[0020] P=P min ×N p.unit (2)

[0021] Where: P is the power generation capacity of the water surface photovoltaic power generation unit, N p.unit is the minimum number of power generation units;

[0022] 22) Define the aspect ratio of the water surface photovoltaic power generation unit based on the arrangement of photovoltaic modules:

[0023] The photovoltaic modules of the power generation unit of the water surface photovoltaic power station are arranged into a rows and b columns. Suppose there are K b PV panels, each with K a PV panels, then:

[0024] K a ×K b =n×N p.unit (3)

[0025] The length and width of the power generation unit of the water surface photovoltaic power station are defined as:

[0026] L=L unit ×K b (4)

[0027] W=W unit ×K a (5)

[0028] Where: L and W represent the length and width of the water surface photovoltaic power generation unit respectively, L unit , W unit Respectively represent the length and width of each photovoltaic module, and its value is determined by the selected photovoltaic panel model, photovoltaic inclination angle, and the spacing between panels;

[0029] 23) Establish an optimization model for the layout of power generation units of a water surface photovoltaic power station as follows:

[0030] The minimum number of generating units N p.unit The aspect ratio K = L / W of the water surface photovoltaic power generation unit is set as the optimization variable, and the minimum investment cost of the water surface photovoltaic power station power generation unit is set as the optimization target. The objective function is expressed as:

[0031] min C unit (6)

[0032] C unit =C p.unit ×N p.unit ×N unit (7)

[0033] Where: C unit is the investment cost of the power generation unit, C p.unit is the minimum power generation unit cost, N unit is the number of power generation units of the water surface photovoltaic power station;

[0034] Considering that the total capacity of the power generation units of the water surface photovoltaic power station must meet the constraints of the power generation capacity, and all the power generation units of the water surface photovoltaic power station cannot exceed the water boundary, there is no intersection and overlap between the power generation units, and the width reserved for the operation and maintenance channel should meet the national standard requirements; therefore, the constraints that need to be met by the layout optimization of the power generation units of the water surface photovoltaic power station are:

[0035]

[0036] Where: P total is the power generation capacity, x i,v ,y i,v are the horizontal and vertical coordinates of each vertex of the water surface photovoltaic power generation unit, where i = 1, 2…m, represents the serial number of the water surface photovoltaic power generation unit, v = 1, 2, 3, 4 represents the vertex number of the water surface photovoltaic power generation unit, and x min 、x max ,y min ,y max Represent the boundary coordinates of the water area, L space is the width of the operation and maintenance channel;

[0037] 24) In steps 21)-23), the particle swarm algorithm is used to optimize the layout of the power generation units of the water surface photovoltaic power station, and the initial version of the layout of the power generation units of the water surface photovoltaic power station is obtained. The box-type substation is arranged in the middle of the power generation units of the water surface photovoltaic power station, and the coordinates of the box-type substation are obtained according to the layout of the power generation units of the water surface photovoltaic power station.

[0038] The optimization of the collector cable of the water surface photovoltaic power station comprises the following steps:

[0039] 31) Calculation of the carrying capacity of a single collector cable:

[0040] The maximum number of box-type substations supported by a single collector cable is expressed as:

[0041]

[0042] Where: N max is the maximum number of box-type substations that a single collector cable can withstand, U is the collector system voltage, I maxis the maximum current carrying capacity of the collector cable, cosθ is the power factor, P N is the power generation power of the power generation unit;

[0043] 32) The improved fuzzy C clustering algorithm is used to partition the box-type substation. The improved fuzzy C clustering algorithm is as follows:

[0044] 321) The improved fuzzy C clustering mathematical model is established as follows:

[0045]

[0046] Constraints:

[0047]

[0048] In the formula, u ij represents the membership of the ith box-type substation to the jth cluster. The box-type substation serial number is consistent with the water surface photovoltaic power generation unit serial number. g is the membership factor, and p i is the coordinate of the ith box-type substation, c j is the coordinate of the jth cluster center, m is the number of box-type substations, and c is the number of cluster centers;

[0049] 322) Randomly generate the membership degree u according to the constraints of formula (11) ij ;

[0050] 323) Iterate and loop and update the cluster center;

[0051] 324) Calculate the radial distance: The coordinates of the box-type substation are represented in the form of a universal formula, and the coordinate vector of the box-type substation is recorded as:

[0052]

[0053] The coordinate vector of the cluster center is recorded as:

[0054]

[0055] Calculate the angle between the box-type substation and the cluster center, and we have:

[0056]

[0057] Determine whether the angle θ is greater than 90°. If it is greater than 90°, set the distance d from the box-type substation to the cluster center vector to infinity. Otherwise, update the distance according to formula (15):

[0058]

[0059] 325) Update membership:

[0060]

[0061] 326) Determine the termination condition and jump out of the loop:

[0062] |u ij (t)-u ij (t-1)|≤σ (17)

[0063] σ is the set termination condition judgment value, and the membership degree u of the current iteration ij If the numerical error of the value of the previous iteration does not exceed the termination judgment value, the iteration ends, otherwise it enters the next iteration;

[0064] 327) Determine the minimum number of partitions and partition:

[0065] Based on the improved fuzzy C clustering algorithm, the initial number of partitions is set to 1, and it is gradually increased until it meets equation (9) and stops. At this time, it is the minimum number of partitions that meets the current carrying capacity constraint. This number is recorded as N, and the box-type substation is partitioned with N as the number of partitions.

[0066] 33) Constructing distance matrix: After dividing the box-type substation into zones with the onshore booster station as the radiation center, calculate the distances between the box-type substations in each zone and between the box-type substation and the onshore booster station to construct the distance matrix;

[0067] The distance calculation formula is expressed as:

[0068]

[0069] Where: L d is the element in the distance matrix of the dth partition; are the horizontal and vertical coordinates of the box-type substation in the dth zone, respectively, where d = 1, 2...N, i = 1, 2...m;

[0070] 34) Use the DM-MSTP algorithm to optimize the cable length of each partition: The DM-MSTP algorithm collects data through the adjacency matrix, where the Min-Columns list is used to collect column minimum values, and the MST-Path list is used to archive the minimum generation path;

[0071] 341) Find the minimum element of each column and record it in the Min-Columns list, select the maximum element, and then save the connection method corresponding to the maximum element in the adjacency matrix into the MST-path;

[0072] 342) Delete the connected elements in the adjacency matrix, mark the rows and columns of the connected elements, find the minimum element of each column in the marked elements and record it in the Min-Columns list, select the minimum value, and then save the connection method into the MST-path;

[0073] 343) If all elements are connected, go to 344), otherwise return to 342);

[0074] 344) Generate a minimum spanning tree according to the connection mode saved in the MST-path;

[0075] 35) Optimize the selection of collector cables for water photovoltaic power stations based on the automatic selection algorithm of collector cables:

[0076] 351) The investment cost function of the collector cable is established:

[0077] The established collector cable investment cost function is:

[0078]

[0079] Where: C cable is the investment cost of the collector cable, N is the number of partitions of the fuzzy C clustering, m is the number of box-type substations in each partition, L C.q is the length of the qth collector cable, C C.q (φ) is the cost per kilometer of the qth collector cable, and φ is the cross-sectional area of ​​the collector cable;

[0080] The automatic selection of the collector cable must meet its capacity restriction condition, that is, the maximum carrying capacity of the selected collector cable model must be greater than or equal to the sum of the capacities of the box-type substations downstream. The constraints that the automatic selection of the collector cable needs to meet are:

[0081]

[0082] In the formula, Q is the number of collector cables in the collector system, S q·max represents the maximum apparent power in the qth collector cable, and F represents the number of box-type substations in the qth collector cable;

[0083]

[0084] Where, I represents the current carrying capacity of the collector cable; P N is the rated power of the water surface photovoltaic power generation unit; U is the voltage level of the collection system; Power factor; when the current carrying capacity of a box-type substation carried by a collector cable exceeds its limit, it will automatically change to other collector cables of larger models;

[0085] 352) Based on the optimization result of the collector cable length, a collector cable connection table is generated for each partition, in which the first row represents the starting node, the second row represents the ending node, and the third row represents the distance between the corresponding starting node and the ending node;

[0086] 353) Determine whether the number of node appearances is less than or equal to 2. If the number of node appearances is less than or equal to 2, the program automatically determines that the topology is a chain connection, and then performs power flow calculation according to equations (9), (20), and (21), selects the collector cable, and jumps out of the step. Otherwise, enter 354);

[0087] 354) If it is determined to be a non-chain connection topology, select a node other than the booster station on the road with a number of occurrences of 1;

[0088] In the collector cable connection table, find the connection mode of the node with the number of occurrences of 1, record it as col, and record the corresponding position in the table as s. Let r = s-1. If Link(1, s) = Link(2, r), where Link(1, s) represents the element in the first row and s column of the table, and Link(2, r) represents the element in the second row and r column, it means a series connection mode, then s-1, r-1; otherwise r-1, continue to judge Link(1, s) = Link(2, r-1) and select according to the constraints of equations (9), (20), and (21);

[0089] Traverse forward until the sequence number is 1, end the traversal process, record the number of box-type substations on each tree branch, and save the branch node sequence number connected to the tree branch respectively, and go to step 355);

[0090] 355) Select a node with a number of occurrences greater than or equal to 3, indicating that a branch appears at this point; find a node with a number of occurrences greater than or equal to 3 in the collector cable connection table, record the position in the corresponding table as u, traverse from back to front, calculate the number of downstream box-type substations loaded by the node, add the node itself, and then the number of box-type substations loaded by its upstream collector line is determined; the selection rule of the trunk is the same as 353), if it is in the form of series connection, the number of box-type substations loaded recorded is increased, and so on, traverse forward until the sequence number is 1;

[0091] 356) Calculate C based on the selection results and the price of the collector cable cable , and obtain the laying method of collector cables for water surface photovoltaic power stations.

[0092] The collaborative optimization of the layout of power generation units and the power collection cables of the power collection system of the water surface photovoltaic power station comprises the following steps:

[0093] 41) Based on the available water area, restricted water area, and operation and maintenance channel requirements, obtain the area where the power generation units of the water surface photovoltaic power station can be laid; based on the photovoltaic panel model, inverter model, and cable model, use PVsyst software to calculate the number of series components, the number of parallel strings, and the capacity ratio parameters;

[0094] 42) Taking the minimum investment cost of the power generation unit of the water surface photovoltaic power station as the optimization goal, the minimum number of power generation units N p.unit and the aspect ratio of the power generation unit K are the optimization variables, where the initial value of the minimum number of power generation units is set to 1, and the initial value of the aspect ratio of the power generation unit is set to K a =1, in order to satisfy the constraint condition of formula (8), the particle swarm algorithm is used to implement optimization and determine whether the total capacity of the power generation unit meets the power generation capacity requirement. If it does, the plane layout of the power generation unit is generated, and then the box-type substation is arranged at the center of the power generation unit to generate the coordinates of the box-type substation; if it does not meet the requirement, N p.unit =N p.unit +1, K=K+1 and repeat 42);

[0095] 43) Based on the current carrying capacity constraint of the collector cable and the partition principle of the minimum number of partitions, the improved fuzzy C clustering algorithm is first used to partition the box-type substation with the road booster station as the base point, and then the DM-MSTP algorithm is used to optimize the length of the collector cable in each partition. Then, the cable automatic selection algorithm is used to automatically select the chain and tree topologies to achieve the optimization of the collector cable selection;

[0096] 44) Calculate the total investment cost C of the water surface photovoltaic power station collection system, C = C unit +C cable , and use the particle swarm algorithm to iterate and optimize. When the fitness value reaches the convergence condition within the preset number of iterations, that is, the total investment cost of the water surface photovoltaic power station collection system is no longer significantly reduced, the general layout diagram of the water surface photovoltaic power station collection system and the optimal total investment cost of the collection system are output; if not, then N p.unit =N p.unit +1, K=K+1 and repeat 42)-44) until the convergence condition is met.

[0097] Beneficial Effects

[0098] As for the layout of power generation units and the laying of collector cables in the power collection system of water surface photovoltaic power stations, the existing design based on manual design or BIM software has the disadvantages of low automation, poor economy and time-consuming design. Therefore, the problem of collaborative optimization design of power generation unit layout and collector cable laying in water surface photovoltaic power stations has become a key technical problem that needs to be solved urgently in the field of water surface photovoltaic power station technology. In order to achieve the collaborative optimization of photovoltaic power generation unit layout and collector cable that meets the constraints of water surface shape and operation and maintenance channel, the optimization of power generation unit layout of water surface photovoltaic power station power collection system based on minimum power generation unit and collector cable optimization integrating fuzzy C-means clustering, DM-MSTP algorithm and automatic selection of collector cable are proposed. Then, the particle swarm algorithm is used to coordinate the optimization of power generation unit layout and collector cable of water surface photovoltaic power station with the total investment cost of water surface photovoltaic power station as the target, so as to achieve the purpose of collaborative optimization design of power generation unit layout and collector cable of water surface photovoltaic power station power collection system.

[0099] The present invention does not require manual layout of power generation units. While ensuring smooth operation and maintenance channels and meeting the total power generation conditions, it can adaptively respond to different complex water conditions, make full use of the water space, and achieve the optimal economic goal. Aiming at the optimization problem of collector cables in water surface photovoltaic power stations, the present invention proposes an integrated improved fuzzy C clustering, DM-MSTP algorithm and automatic selection method for collector cables. Compared with manual wiring and manual selection, which are time-consuming, labor-intensive and do not guarantee economic optimization, automatic wiring and selection of collector cables are achieved while ensuring that the collector cables do not cross and do not exceed the current carrying capacity limit of the collector cables, which greatly improves the design efficiency and effectively saves the investment cost of the collector cables.

[0100] A collaborative optimization design method for the layout of power generation units and collector cables of a water surface photovoltaic power station collection system proposed in the present invention, compared with the traditional design method of first arranging the power generation units of the water surface photovoltaic power station and then optimizing the length of the collector cables and manually selecting the collector cables, the proposed method first optimizes the layout of power generation units of the water surface photovoltaic power station collection system based on the minimum power generation unit, and then integrates fuzzy C-means clustering, DM-MSTP algorithm and automatic selection of collector cables to automatically optimize the length and selection of collector cables at the same time, and finally uses a particle swarm algorithm to coordinately optimize the layout of power generation units and collector cables of the water surface photovoltaic power station collection system with the total investment cost of the water surface photovoltaic power station as the target, which not only overcomes the low degree of automation, poor economy and time-consuming design of the existing collection system design of the water surface photovoltaic power station, but also can effectively avoid falling into the local optimal solution, effectively saving economic costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0101] Figure 1 is a method sequence diagram of the present invention;

[0102] Figure 2It is a flow chart of the layout of power generation units and the collaborative optimization scheme of power collection cables of the power collection system of the water surface photovoltaic power station of the present invention;

[0103] Figure 3 The optimized diagram of the length of the collector cables of the water surface photovoltaic power station generated by the embodiment of the present invention;

[0104] Figure 4 The optimized diagram of the power generation unit layout and power collection cables of the power collection system of the water surface photovoltaic power station generated by the embodiment of the present invention. DETAILED DESCRIPTION

[0105] In order to have a further understanding and recognition of the structural features and the effects achieved by the present invention, a preferred embodiment and accompanying drawings are used for detailed description as follows:

[0106] like Figure 1 As shown, the method for collaborative optimization design of power generation unit layout and power collection cable of a water surface photovoltaic power station power collection system of the present invention comprises the following steps:

[0107] The first step is to obtain the water conditions and photovoltaic device conditions: obtain the basic data of the site selection water area and photovoltaic devices of the water surface photovoltaic power station. The photovoltaic devices of the water surface photovoltaic power station include inverters, photovoltaic panels and box-type substations. Pre-calculate the basic data to obtain the number of photovoltaic modules in the minimum power generation unit and the length and width of the photovoltaic modules.

[0108] The second step is to optimize the layout of the power generation units of the water surface photovoltaic power station: the minimum number of power generation units N in the water surface photovoltaic power generation unit p.unit The optimization variables are the investment cost of the power generation unit of the water surface photovoltaic power station and the aspect ratio K = L / W. The water conditions, power generation capacity, and operation and maintenance channel constraints are the constraints. The capacity of the water surface photovoltaic power generation unit is determined based on the definition of the minimum power generation unit. The layout of the power generation unit of the water surface photovoltaic power station is optimized using the particle swarm algorithm to obtain the layout of the power generation unit of the water surface photovoltaic power station. The box-type substation is set to be arranged in the middle of the power generation unit of the water surface photovoltaic power station, and the coordinates of the box-type substation are obtained according to the layout of the power generation unit of the water surface photovoltaic power station. Compared with the layout of the manual power generation unit of the water surface photovoltaic power station, the optimal power generation unit capacity and aspect ratio can be automatically determined, making full use of the water space, reducing the design time, and saving economic costs.

[0109] (1) Determine the capacity of the water surface photovoltaic power generation unit based on the definition of the minimum power generation unit:

[0110] The photovoltaic power generation unit consisting of an inverter and n photovoltaic modules is defined as the minimum photovoltaic power generation unit. Based on the PVsyst software, the geographical parameters of the water surface photovoltaic power station, the photovoltaic panel model, and the inverter model are input. The number of photovoltaic modules in parallel and the number of inverters obtained are divided, and the quotient is the number of photovoltaic modules in the minimum power generation unit, n.

[0111] The minimum generating unit capacity is expressed as:

[0112] P min =P INV ×λ (1)

[0113] Where: P min is the minimum generating unit capacity, P INV is the rated power of the inverter, λ is the capacity ratio, and its value is calculated based on the PVsyst software;

[0114] The power generation capacity of the water surface photovoltaic power generation unit is expressed as:

[0115] P=P min ×N p.unit (2)

[0116] Where: P is the power generation capacity of the water surface photovoltaic power generation unit, N p.unit is the minimum number of generating units.

[0117] (2) Define the aspect ratio of the water surface photovoltaic power generation unit based on the photovoltaic group arrangement method:

[0118] The photovoltaic modules of the power generation unit of the water surface photovoltaic power station are arranged into a rows and b columns. Suppose there are K b PV panels, each with K a PV panels, then:

[0119] K a ×K b =n×N p.unit (3)

[0120] The length and width of the power generation unit of the water surface photovoltaic power station are defined as:

[0121] L=L unit ×K b (4)

[0122] W=W unit ×K a (5)

[0123] Where: L and W represent the length and width of the water surface photovoltaic power generation unit respectively, L unit , W unit Respectively represent the length and width of each photovoltaic module, and their values ​​are determined by the selected photovoltaic panel model, photovoltaic inclination angle, and spacing between panels.

[0124] (3) Establish an optimization model for the layout of power generation units of a water surface photovoltaic power station, as shown below:

[0125] The minimum number of generating units N p.unitThe aspect ratio K = L / W of the water surface photovoltaic power generation unit is set as the optimization variable, and the minimum investment cost of the water surface photovoltaic power station power generation unit is set as the optimization target. The objective function is expressed as:

[0126] min C unit (6)

[0127] C unit =C p.unit ×N p.unit ×N unit (7)

[0128] Where: C unit is the investment cost of the power generation unit, C p.unit is the minimum power generation unit cost, N unit is the number of power generation units of the water surface photovoltaic power station;

[0129] Considering that the total capacity of the power generation units of the water surface photovoltaic power station meets the constraints of the power generation capacity, and all the power generation units of the water surface photovoltaic power station cannot exceed the water boundary, there is no intersection and overlap between the power generation units, and the width reserved for the operation and maintenance channel should meet the national standard requirements; therefore, the constraints satisfied by the layout optimization of the power generation units of the water surface photovoltaic power station are:

[0130]

[0131] Where: P total is the power generation capacity, x i,v ,y i,v are the horizontal and vertical coordinates of each vertex of the water surface photovoltaic power generation unit, where i = 1, 2…m, represents the serial number of the water surface photovoltaic power generation unit, v = 1, 2, 3, 4 represents the vertex number of the water surface photovoltaic power generation unit, and x min 、x max ,y min ,y max Represent the boundary coordinates of the water area, L space is the width of the operation and maintenance channel;

[0132] (4) In steps (1)-(3), the particle swarm algorithm is used to optimize the layout of the power generation units of the water surface photovoltaic power station, and the initial version of the layout of the power generation units of the water surface photovoltaic power station is obtained. The box-type substation is arranged in the middle of the power generation units of the water surface photovoltaic power station, and the coordinates of the box-type substation are obtained according to the layout of the power generation units of the water surface photovoltaic power station.

[0133] The third step is to optimize the collector cables of the water photovoltaic power station: Based on the coordinates of the box-type substation, the improved fuzzy C clustering, DM-MSTP and automatic selection method of the collector cables are integrated to optimize the collector cables between the box-type substations in the water photovoltaic power station, ensuring that the collector cables do not cross and do not exceed the current carrying capacity of the cables to obtain the laying method of the collector cables of the water photovoltaic power station. The automatic laying of the collector cables of the water photovoltaic power station is realized, saving time and economic costs.

[0134] (1) Calculation of the load-bearing capacity of a single collector cable:

[0135] The maximum number of box-type substations supported by a single collector cable is expressed as:

[0136]

[0137] Where: N max is the maximum number of box-type substations that a single collector cable can withstand, U is the collector system voltage, I max is the maximum current carrying capacity of the collector cable, cosθ is the power factor, P N is the power generation capacity of the power generation unit.

[0138] (2) The improved fuzzy C clustering algorithm is used to partition the box-type substation. The improved fuzzy C clustering algorithm is as follows:

[0139] A1) The improved fuzzy C clustering mathematical model is established as follows:

[0140]

[0141] Constraints:

[0142]

[0143] In the formula, u ij represents the membership of the i-th box-type substation to the j-th cluster. The box-type substation serial number is consistent with the water surface photovoltaic power generation unit serial number. g is the membership factor, and p i is the coordinate of the ith box-type substation, c j is the coordinate of the jth cluster center, m is the number of box-type substations, and c is the number of cluster centers;

[0144] A2) Randomly generate the membership degree u according to the constraint condition of formula (11) ij ;

[0145] A3) Iterate and update the cluster center;

[0146] A4) Calculate the radial distance: The coordinates of the box-type substation are represented in the form of a universal formula. The coordinate vector of the box-type substation is recorded as:

[0147]

[0148] The coordinate vector of the cluster center is recorded as:

[0149]

[0150] Calculate the angle between the box-type substation and the cluster center, and we have:

[0151]

[0152] Determine whether the angle θ is greater than 90°. If it is greater than 90°, set the distance d from the box-type substation to the cluster center vector to infinity. Otherwise, update the distance according to formula (15):

[0153]

[0154] A5) Update membership:

[0155]

[0156] A6) Determine the termination condition and jump out of the loop:

[0157] |u ij (t)-u ij (t-1)|≤σ (17)

[0158] σ is the set termination condition judgment value, and the membership degree u of the current iteration ij If the numerical error of the value of the previous iteration does not exceed the termination judgment value, the iteration ends, otherwise it enters the next iteration;

[0159] A7) Determine the minimum number of partitions and partition them:

[0160] Based on the improved fuzzy C clustering algorithm, the initial number of partitions is set to 1, and it is gradually increased until it meets equation (9). At this time, it is the minimum number of partitions that meets the current carrying capacity constraint. This number is recorded as N, and the box-type substation is partitioned with N as the number of partitions.

[0161] (3) Constructing the distance matrix: After dividing the box-type substation into zones with the onshore booster station as the radial center, calculate the distances between the box-type substations in each zone and between the box-type substation and the onshore booster station to construct the distance matrix;

[0162] The distance calculation formula is expressed as:

[0163]

[0164] Where: L d is the element in the distance matrix of the dth partition; They are the horizontal and vertical coordinates of the box-type substation in the dth zone, where d=1,2...N, i=1,2...m.

[0165] (4) Use the DM-MSTP algorithm to optimize the cable length of each partition: The DM-MSTP algorithm collects data through the adjacency matrix, where the Min-Columns list is used to collect column minimum values, and the MST-Path list is used to archive the minimum generation path;

[0166] B1) Find the minimum element of each column and record it in the Min-Columns list, select the maximum element, and then save the connection method corresponding to the maximum element in the adjacency matrix into the MST-path;

[0167] B2) Delete the connected elements in the adjacency matrix, mark the rows and columns of the connected elements, find the minimum element of each column in the marked elements and record it in the Min-Columns list, select the minimum value, and then save the connection method into the MST-path;

[0168] B3) If all elements are connected, go to 344), otherwise return to 342);

[0169] B4) Generate a minimum spanning tree according to the connection mode saved in the MST-path.

[0170] (5) Automatic selection of collector cables to optimize the selection of collector cables for water-surface photovoltaic power stations:

[0171] C1) Establishment of the investment cost function of the collector cable:

[0172] The established collector cable investment cost function is:

[0173]

[0174] Where: C cable is the investment cost of the collector cable, N is the number of partitions of the fuzzy C clustering, m is the number of box-type substations in each partition, L C.q is the length of the qth collector cable, C C.q (φ) is the cost per kilometer of the qth collector cable, and φ is the cross-sectional area of ​​the collector cable;

[0175] The automatic selection of the collector cable must meet its capacity restriction condition, that is, the maximum carrying capacity of the selected collector cable model must be greater than or equal to the sum of the capacities of the box-type substations downstream. The constraints that the automatic selection of the collector cable needs to meet are:

[0176]

[0177] In the formula, Q is the number of collector cables in the collector system, S q·max represents the maximum apparent power in the qth collector cable, and F represents the number of box-type substations in the qth collector cable;

[0178]

[0179] Where, I represents the current carrying capacity of the collector cable; P N is the rated power of the water surface photovoltaic power generation unit; U is the voltage level of the collection system; Power factor; when the current carrying capacity of a box-type substation carried by a collector cable exceeds its limit, it will automatically change to other collector cables of larger models;

[0180] C2) Based on the optimization result of the collector cable length, a collector cable connection table is generated for each partition, in which the first row represents the starting node, the second row represents the ending node, and the third row represents the distance between the corresponding starting node and the ending node;

[0181] C3) Determine whether the number of node appearances is less than or equal to 2. If the number of node appearances is less than or equal to 2, the program automatically determines that the topology is a chain connection, and then performs power flow calculation according to equations (9), (20), and (21), selects the collector cable, and jumps out of the step. Otherwise, it goes to C4);

[0182] C4) If it is determined to be a non-chain connection topology, select a node other than the booster station on the road with a number of occurrences of 1;

[0183] In the collector cable connection table, find the connection mode of the node with the number of occurrences of 1, record it as col, and record the corresponding position in the table as s. Let r = s-1. If Link(1, s) = Link(2, r), where Link(1, s) represents the element in the first row and s column of the table, and Link(2, r) represents the element in the second row and r column, it means a series connection mode, then s-1, r-1; otherwise r-1, continue to judge Link(1, s) = Link(2, r-1) and select according to the constraints of equations (9), (20), and (21);

[0184] Traverse forward until the sequence number is 1, end the traversal process, record the number of box-type substations on each tree branch, and save the branch node sequence number connected to the tree branch respectively, and go to step C5);

[0185] C5) Select nodes with a number of occurrences greater than or equal to 3, indicating that a branch appears at this point; Find nodes with a number of occurrences greater than or equal to 3 in the collector cable connection table, record the position in the corresponding table as u, traverse from back to front, calculate the number of downstream box-type substations carried by the node, add the node itself, and then the number of box-type substations carried by its upstream collector line is determined; The selection rule of the trunk is the same as C3). If it is in the form of series connection, the number of box-type substations carried by the record is increased, and so on, traversing forward until the sequence number is 1;

[0186] C6) Calculate C based on the selection results and the price of the collector cable cable , and obtain the laying method of collector cables for water surface photovoltaic power stations.

[0187] Step 4: Co-optimization of the layout of the power generation units and the collection cables of the water surface photovoltaic power station: Calculate the total investment cost of the collection system of the water surface photovoltaic power station, and use the particle swarm algorithm to iteratively optimize until the convergence conditions are met to determine the minimum number of power generation units N in the water surface photovoltaic power generation unit p.unit and the length-to-width ratio K = L / W, the optimal total investment cost of the power generation unit and the collector cable of the water surface photovoltaic power station, the layout of the power generation unit of the water surface photovoltaic power station, and the general layout of the collector cable are obtained. The implementation flow chart of the proposed scheme is shown in Figure 2 shown.

[0188] (1) Based on the available water area, restricted water area, and operation and maintenance channel requirements, the area where the power generation units of the water surface photovoltaic power station can be laid is obtained; based on the photovoltaic panel model, inverter model, and cable model, the PVsyst software is used to calculate the number of series components, the number of parallel strings, and the capacity ratio parameters;

[0189] (2) Taking the minimum investment cost of the power generation unit of the water surface photovoltaic power station as the optimization goal, the minimum number of power generation units N p.unit and the aspect ratio K of the power generation unit are the optimization variables, where the initial value of the minimum number of power generation units is set to 1, and the initial value of the aspect ratio of the power generation unit is set to K a =1, in order to satisfy the constraint condition of formula (8), the particle swarm algorithm is used to implement optimization and determine whether the total capacity of the power generation unit meets the power generation capacity requirement. If it does, the plane layout of the power generation unit is generated, and then the box-type substation is arranged at the center of the power generation unit to generate the coordinates of the box-type substation; if it does not meet the requirement, N p.unit =N p.unit +1, K=K+1 and repeat (2);

[0190] (3) Based on the current carrying capacity constraint of the collector cable and the partition principle of the minimum number of partitions, the improved fuzzy C clustering algorithm is first used to partition the box-type substation with the road booster station as the base point. Then, the DM-MSTP algorithm is used to optimize the length of the collector cable in each partition. Then, the automatic cable selection algorithm is used to automatically select the chain and tree topologies to achieve the optimization of the collector cable selection.

[0191] (4) Calculate the total investment cost C of the water surface photovoltaic power station collection system, C = C unit +C cable , and use the particle swarm algorithm to iterate and optimize. When the fitness value reaches the convergence condition within the preset number of iterations, that is, the total investment cost of the water surface photovoltaic power station collection system is no longer significantly reduced, the general layout diagram of the water surface photovoltaic power station collection system and the optimal total investment cost of the collection system are output; if not, then N p.unit =N p.unit +1, K=K+1 and repeat (2)-(4) until the convergence condition is met.

[0192] In order to further illustrate the accuracy and reliability of the method of the present invention, a case analysis is conducted on the layout of power generation units and laying of power collection cables of a water surface photovoltaic power station collection system by taking a water surface photovoltaic power station as an example. The models and parameters of the relevant equipment of the water surface photovoltaic power station are shown in Table 1:

[0193] Table 1 Models and parameters of relevant equipment in water surface photovoltaic power station

[0194]

[0195]

[0196] Through the optimization of the layout of the power generation units of the water surface photovoltaic power station, it can be obtained that there are 70 power generation units in the water area, each of which contains 7 minimum power generation units, with an aspect ratio of 30:17. The box-type substation is set to be located in the center of the power generation unit, and the coordinates of the box-type substation are extracted, where coordinate 1 is the location of the road booster station. The 70 box-type substations are partitioned using the improved fuzzy C clustering, and the 70 box-type transformers are divided into 5 zones. Figure 3 The five-pointed star in the figure represents the cluster center. The cable connection based on the DM-MSTP algorithm results in the following results: Figure 3 shown.

[0197] The specifications of the collector cables used in the water surface photovoltaic power station are shown in Table 2.

[0198] Table 2 Collector cable model parameters

[0199]

[0200] When the combination of 7 minimum power generation units is corresponding, the automatic selection table of the collector cable is shown in Table 3.

[0201] Table 3 Automatic selection table for collector cables

[0202]

[0203]

[0204] The water surface photovoltaic power station collection system studied is optimized through the layout of power generation units and collection cables. The optimization results are as follows: Figure 4 shown.

[0205] Table 4 Comparison of cable length and total investment of different methods

[0206]

[0207] Table 4 shows a comparison of cable length and total investment for different methods of the collection system of a water surface photovoltaic power station. Compared with the manual design method, the sequential optimization method and the proposed method achieved a reduction of 3.4% and 24.2% in the length of the collection cable, a reduction of 13.4% and 17.1% in the investment in the collection cable, and a reduction of 0.7% and 0.91% in the total investment, respectively. The proposed method for collaborative optimization design of the layout of power generation units and collection cables of the collection system of a water surface photovoltaic power station is significantly superior to the manual design method and the sequential optimization method, and can reduce the investment cost for investors in the construction of water surface photovoltaic power stations.

[0208] Aiming at the design problem of the power collection system of a water surface photovoltaic power station, the present invention proposes a collaborative optimization design method for the layout of power generation units and collector cables of the power collection system of a water surface photovoltaic power station, which integrates the minimum power generation unit, improved fuzzy C clustering, DM-MSTP algorithm, automatic selection algorithm for collector cables, and particle swarm algorithm. Under the condition of ensuring smooth operation and maintenance channels and meeting the total power generation amount, it can adaptively respond to different complex water conditions, make full use of the water space, and achieve the optimal economic goal; it can realize automatic optimization of the collector cables while ensuring that the collector cables do not cross and do not exceed the current carrying capacity limit of the collector cables, and realize automatic laying of the collector cables while ensuring that the collector cables do not cross and do not exceed the current carrying capacity limit of the collector cables; it can significantly reduce the design time of the power collection system of a water surface photovoltaic power station, and effectively avoid falling into the local optimal solution, effectively saving economic costs.

[0209] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A collaborative optimization design method for the layout of power generation units and power collection cables of a water surface photovoltaic power station power collection system, characterized in that: The following steps are involved: 11) Obtaining water conditions and photovoltaic device conditions: Obtaining basic data on the water area for site selection of water surface photovoltaic power stations and photovoltaic devices of water surface photovoltaic power stations. Photovoltaic devices of water surface photovoltaic power stations include inverters, photovoltaic panels and box-type substations. Pre-calculating the basic data, obtaining the number of photovoltaic modules in the minimum power generation unit and the length and width of the photovoltaic modules; 12) Optimization of the layout of power generation units of water surface photovoltaic power stations: The minimum number of power generation units N in the water surface photovoltaic power generation unit p.unit The length-to-width ratio K=L / W is used as the optimization variable, the investment cost of the power generation unit of the water surface photovoltaic power station is used as the objective function, the water conditions, power generation capacity, and operation and maintenance channel constraints are used as constraints, and the layout of the power generation unit of the water surface photovoltaic power station is optimized based on the minimum power generation unit and the particle swarm algorithm is used to obtain the layout of the power generation unit of the water surface photovoltaic power station; the box-type substation is set to be arranged in the middle of the power generation unit of the water surface photovoltaic power station, and the coordinates of the box-type substation are obtained according to the layout of the power generation unit of the water surface photovoltaic power station; 13) Optimization of collector cables for water-surface photovoltaic power stations: Based on the coordinates of box-type substations, the improved fuzzy C clustering, DM-MSTP and automatic selection method of collector cables are integrated to optimize the cables between box-type substations in water-surface photovoltaic power stations, and the laying method of collector cables for water-surface photovoltaic power stations is obtained; 14) Co-optimization of the layout of power generation units and power collection cables of the water surface photovoltaic power station collection system: Calculate the total investment cost of the water surface photovoltaic power station collection system, and use the particle swarm algorithm to iteratively optimize until the convergence conditions are met to determine the minimum number of power generation units N in the water surface photovoltaic power generation unit p.unit and the length-to-width ratio K=L / W, the optimal total investment cost of the water surface photovoltaic power station collection system, the layout of the water surface photovoltaic power station power generation units, and the general plan for the laying of the collection cables are obtained.

2. A collaborative optimization design method for the layout of power generation units and power collection cables of a water surface photovoltaic power station power collection system according to claim 1, characterized in that: The layout optimization of the power generation unit of the water surface photovoltaic power station comprises the following steps: 21) Determine the capacity of the water surface photovoltaic power generation unit based on the definition of the minimum power generation unit: The photovoltaic power generation unit consisting of an inverter and n photovoltaic modules is defined as the minimum power generation unit. Based on the PVsyst software, the geographical parameters of the water surface photovoltaic power station, the photovoltaic panel model, and the inverter model are input. The number of photovoltaic modules in parallel and the number of inverters obtained are divided, and the quotient is the number of photovoltaic modules in the minimum power generation unit, n. The minimum generating unit capacity is expressed as: P min =P INV ×λ (1) Where: P min is the minimum generating unit capacity, P INV is the rated power of the inverter, λ is the capacity ratio, and its value is calculated based on the PVsyst software; The power generation capacity of the water surface photovoltaic power generation unit is expressed as: P=P min ×N p.unit (2) Where: P is the power generation capacity of the water surface photovoltaic power generation unit, N p.unit is the minimum number of power generation units; 22) Define the aspect ratio of the water surface photovoltaic power generation unit based on the arrangement of photovoltaic modules: The photovoltaic modules of the power generation unit of the water surface photovoltaic power station are arranged into a rows and b columns. Suppose there are K b PV panels, each with K a PV panels, then: K a ×K b =n×N p.unit (3) The length and width of the power generation unit of the water surface photovoltaic power station are defined as: L=L unit ×K b (4) W=W unit ×K a (5) Where: L and W represent the length and width of the water surface photovoltaic power generation unit respectively, L unit , W unit Respectively represent the length and width of each photovoltaic module, and its value is determined by the selected photovoltaic panel model, photovoltaic inclination angle, and the spacing between panels; 23) Establish an optimization model for the layout of power generation units of a water surface photovoltaic power station as follows: The minimum number of generating units N p.unit The aspect ratio K = L / W of the water surface photovoltaic power generation unit is set as the optimization variable, and the minimum investment cost of the water surface photovoltaic power station power generation unit is set as the optimization target. The objective function is expressed as: my C unit (6) C unit =C p.unit ×N p.unit ×N unit (7) Where: C unit is the investment cost of the power generation unit, C p.unit is the minimum power generation unit cost, N unit is the number of power generation units of the water surface photovoltaic power station; Considering that the total capacity of the power generation units of the water surface photovoltaic power station must meet the constraints of the power generation capacity, and all the power generation units of the water surface photovoltaic power station cannot exceed the water boundary, there is no intersection and overlap between the power generation units, and the width reserved for the operation and maintenance channel should meet the national standard requirements; therefore, the constraints that need to be met by the layout optimization of the power generation units of the water surface photovoltaic power station are: Where: P total is the power generation capacity, x i,v ,y i,v are the horizontal and vertical coordinates of each vertex of the water surface photovoltaic power generation unit, where i = 1, 2…m, represents the serial number of the water surface photovoltaic power generation unit, v = 1, 2, 3, 4 represents the vertex number of the water surface photovoltaic power generation unit, and x min 、x max ,y min ,y max Represent the boundary coordinates of the water area, L space is the width of the operation and maintenance channel; 24) In steps 21)-23), the particle swarm algorithm is used to optimize the layout of the power generation units of the water surface photovoltaic power station, and the initial version of the layout of the power generation units of the water surface photovoltaic power station is obtained. The box-type substation is arranged in the middle of the power generation units of the water surface photovoltaic power station, and the coordinates of the box-type substation are obtained according to the layout of the power generation units of the water surface photovoltaic power station.

3. The method for collaborative optimization design of power generation unit layout and power collection cables of a water surface photovoltaic power station power collection system according to claim 1, characterized in that: The optimization of the collector cable of the water surface photovoltaic power station comprises the following steps: 31) Calculation of the carrying capacity of a single collector cable: The maximum number of box-type substations supported by a single collector cable is expressed as: Where: N max is the maximum number of box-type substations that a single collector cable can withstand, U is the collector system voltage, I max is the maximum current carrying capacity of the collector cable, cosθ is the power factor, P N is the power generation power of the power generation unit; 32) The improved fuzzy C clustering algorithm is used to partition the box-type substation. The improved fuzzy C clustering algorithm is as follows: 321) The improved fuzzy C clustering mathematical model is established as follows: Constraints: In the formula, u ij represents the membership of the i-th box-type substation to the j-th cluster. The box-type substation serial number is consistent with the water surface photovoltaic power generation unit serial number. g is the membership factor, and p i is the coordinate of the ith box-type substation, c j is the coordinate of the jth cluster center, m is the number of box-type substations, and c is the number of cluster centers; 322) Randomly generate the membership u according to the constraints of formula (11) ij ; 323) Iterate and loop and update the cluster center; 324) Calculate the radial distance: The coordinates of the box-type substation are represented in the form of a universal formula, and the coordinate vector of the box-type substation is recorded as: The coordinate vector of the cluster center is recorded as: Calculate the angle between the box-type substation and the cluster center, and we have: Determine whether the angle θ is greater than 90°. If it is greater than 90°, set the distance d from the box-type substation to the cluster center vector to infinity. Otherwise, update the distance according to formula (15): 325) Update membership: 326) Determine the termination condition and jump out of the loop: |u ij (t)-u ij (t-1)|≤σ (17) σ is the set termination condition judgment value, and the membership degree u of the current iteration ij If the numerical error of the value of the previous iteration does not exceed the termination judgment value, the iteration ends, otherwise it enters the next iteration; 327) Determine the minimum number of partitions and partition: Based on the improved fuzzy C clustering algorithm, the initial number of partitions is set to 1, and it is gradually increased until it meets equation (9) and stops. At this time, it is the minimum number of partitions that meets the current carrying capacity constraint. This number is recorded as N, and the box-type substation is partitioned with N as the number of partitions. 33) Constructing distance matrix: After dividing the box-type substation into zones with the onshore booster station as the radiation center, calculate the distances between the box-type substations in each zone and between the box-type substation and the onshore booster station to construct the distance matrix; The distance calculation formula is expressed as: Where: L d is the element in the distance matrix of the dth partition; are the horizontal and vertical coordinates of the box-type substation in the dth zone, respectively, where d = 1, 2...N, i = 1, 2...m; 34) Use the DM-MSTP algorithm to optimize the cable length of each partition: The DM-MSTP algorithm collects data through the adjacency matrix, where the Min-Columns list is used to collect column minimum values, and the MST-Path list is used to archive the minimum generation path; 341) Find the minimum element of each column and record it in the Min-Columns list, select the maximum element, and then save the connection method corresponding to the maximum element in the adjacency matrix into the MST-path; 342) Delete the connected elements in the adjacency matrix, mark the rows and columns of the connected elements, find the minimum element of each column in the marked elements and record it in the Min-Columns list, select the minimum value, and then save the connection method into the MST-path; 343) If all elements are connected, go to 344), otherwise return to 342); 344) Generate a minimum spanning tree according to the connection mode saved in the MST-path; 35) Optimize the selection of collector cables for water photovoltaic power stations based on the automatic selection algorithm of collector cables: 351) The investment cost function of the collector cable is established: The established collector cable investment cost function is: Where: C cable is the investment cost of the collector cable, N is the number of partitions of the fuzzy C clustering, m is the number of box-type substations in each partition, L C.q is the length of the qth collector cable, C C.q (φ) is the cost per kilometer of the qth collector cable, and φ is the cross-sectional area of ​​the collector cable; The automatic selection of the collector cable must meet its capacity restriction condition, that is, the maximum carrying capacity of the selected collector cable model must be greater than or equal to the sum of the capacities of the box-type substations downstream. The constraints that the automatic selection of the collector cable needs to meet are: In the formula, Q is the number of collector cables in the collector system, S q·max represents the maximum apparent power in the qth collector cable, and F represents the number of box-type substations in the qth collector cable; Where, I represents the current carrying capacity of the collector cable; P N is the rated power of the water surface photovoltaic power generation unit; U is the voltage level of the collection system; Power factor; when the current carrying capacity of a box-type substation carried by a collector cable exceeds its limit, it will automatically change to other collector cables of larger models; 352) Based on the optimization result of the collector cable length, a collector cable connection table is generated for each partition, in which the first row represents the starting node, the second row represents the ending node, and the third row represents the distance between the corresponding starting node and the ending node; 353) Determine whether the number of node appearances is less than or equal to 2. If the number of node appearances is less than or equal to 2, the program automatically determines that the topology is a chain connection, and then performs power flow calculation according to equations (9), (20), and (21), selects the collector cable, and jumps out of the step. Otherwise, enter 354); 354) If it is determined to be a non-chain connection topology, select a node other than the booster station on the road with a number of occurrences of 1; In the collector cable connection table, find the connection mode of the node with the number of occurrences of 1, record it as col, and record the corresponding position in the table as s. Let r = s-1. If Link(1, s) = Link(2, r), where Link(1, s) represents the element in the first row and s column of the table, and Link(2, r) represents the element in the second row and r column, it means a series connection mode, then s-1, r-1; otherwise r-1, continue to judge Link(1, s) = Link(2, r-1) and select according to the constraints of equations (9), (20), and (21); Traverse forward until the sequence number is 1, end the traversal process, record the number of box-type substations on each tree branch, and save the branch node sequence number connected to the tree branch respectively, and go to step 355); 355) Select a node with a number of occurrences greater than or equal to 3, indicating that a branch appears at this point; find a node with a number of occurrences greater than or equal to 3 in the collector cable connection table, record the position in the corresponding table as u, traverse from back to front, calculate the number of downstream box-type substations loaded by the node, add the node itself, and then the number of box-type substations loaded by its upstream collector line is determined; the selection rule of the trunk is the same as 353), if it is in the form of series connection, the number of box-type substations loaded recorded is increased, and so on, traverse forward until the sequence number is 1; 356) Calculate C based on the selection results and the price of the collector cable cable , and obtain the laying method of collector cables for water surface photovoltaic power stations.

4. The method for collaborative optimization design of power generation unit layout and power collection cables of a water surface photovoltaic power station power collection system according to claim 1, characterized in that: The collaborative optimization of the layout of power generation units and the power collection cables of the power collection system of the water surface photovoltaic power station comprises the following steps: 41) Based on the available water area, restricted water area, and operation and maintenance channel requirements, obtain the area where the power generation units of the water surface photovoltaic power station can be laid; based on the photovoltaic panel model, inverter model, and cable model, use PVsyst software to calculate the number of series components, the number of parallel strings, and the capacity ratio parameters; 42) Taking the minimum investment cost of the power generation unit of the water surface photovoltaic power station as the optimization goal, the minimum number of power generation units N p.unit and the aspect ratio K of the power generation unit are the optimization variables, where the initial value of the minimum number of power generation units is set to 1, and the initial value of the aspect ratio of the power generation unit is set to K a =1, in order to satisfy the constraint condition of formula (8), the particle swarm algorithm is used to implement optimization and determine whether the total capacity of the power generation unit meets the power generation capacity requirement. If it does, the plane layout of the power generation unit is generated, and then the box-type substation is arranged at the center of the power generation unit to generate the coordinates of the box-type substation; if it does not meet the requirement, N p.unit =N p.unit +1, K=K+1 and repeat 42); 43) Based on the current carrying capacity constraint of the collector cable and the partition principle of the minimum number of partitions, the improved fuzzy C clustering algorithm is first used to partition the box-type substation with the road booster station as the base point, and then the DM-MSTP algorithm is used to optimize the length of the collector cable in each partition. Then, the cable automatic selection algorithm is used to automatically select the chain and tree topologies to achieve the optimization of the collector cable selection; 44) Calculate the total investment cost C of the water surface photovoltaic power station collection system, C = C unit +C cable , and use the particle swarm algorithm to iterate and optimize. When the fitness value reaches the convergence condition within the preset number of iterations, that is, the total investment cost of the water surface photovoltaic power station collection system is no longer significantly reduced, the general layout diagram of the water surface photovoltaic power station collection system and the optimal total investment cost of the collection system are output; if not, then N p.unit =N p.unit +1, K=K+1 and repeat 42)-44) until the convergence condition is met.

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