Methods, devices and storage media for AC / DC networking of offshore wind power clusters

Abstract

This invention relates to a method, apparatus, and storage medium for AC / DC networking of offshore wind power clusters. The method includes: Step S1: Obtaining the topology of the wind power cluster, as well as the location and capacity of the offshore booster station; Step S2: Defining four sets of binary decision variables to describe the topology of the transmission system; Step S3: Considering the costs of offshore converter stations, onshore converter stations, onshore substations, and high-voltage transmission lines, establishing a total investment model for the transmission system based on the defined binary decision variables; Step S4: Linearizing the stepped costs based on disjunctive inequalities, and optimizing the transmission methods of each electric field in the offshore wind power cluster, the number, location, and capacity of converter stations, the division of wind farm groups, and the selection of onshore common connection points according to the obtained mixed-integer linearized model, to obtain the networking result. Compared with the prior art, this invention has the advantages of taking into account the overall economic efficiency of the wind farm cluster.

Description

Technical Field

[0001] This invention relates to the field of AC / DC networking planning for offshore wind power clusters, and in particular to a method, apparatus and storage medium for AC / DC networking of offshore wind power clusters. Background Technology

[0002] Offshore wind power boasts advantages such as high wind energy density, high utilization hours, no land occupation, and proximity to load centers for easy local consumption. In recent years, the development of offshore wind power has been characterized by large-scale, multi-level, and deep-sea deployments. According to a report released by GWEC, the global newly added grid-connected offshore wind power capacity reached 21.1 GW in 2021, with China accounting for 80% of the global increase, making China surpass the UK to become the country with the largest cumulative installed offshore wind power capacity globally. The two key components of an offshore wind farm are the wind turbine and the electrical system, accounting for approximately 50% and 30% of the total investment, respectively. Due to the high cost of building offshore wind farms, even minor improvements to the turbine wiring layout or electrical system topology design can result in significant budget savings.

[0003] In recent years, experts and scholars both domestically and internationally have conducted extensive and in-depth research on the grid connection of large-scale offshore wind farm clusters. This research primarily focuses on the analysis and study of offshore wind farm cluster grid connection systems employing pure AC / pure DC transmission methods, with less consideration given to the simultaneous use of both high-voltage AC and high-voltage DC transmission methods. Most research on hybrid AC / DC transmission concentrates on the cost differences between AC and DC transmission systems, yielding equivalent transmission distances for high-voltage AC and high-voltage DC systems under different transmission capacities, but without considering AC / DC transmission methods as optimization variables in planning models.

[0004] However, the grid connection planning of offshore wind farm clusters faces the following two new challenges:

[0005] 1) When the planned offshore wind farm cluster spans a wide sea area, using a single AC or DC power transmission method cannot optimize the total investment cost of the offshore wind farm cluster plan.

[0006] 2) For offshore wind farms with different installed capacities, the optimal transmission distance for high-voltage AC and high-voltage DC transmission varies within a wide range. Therefore, for offshore wind farms with a certain distance from shore and a certain installed capacity, the selection of high-voltage AC and high-voltage DC transmission methods is somewhat ambiguous due to the different division of wind farm clusters. Inappropriate selection will, on the one hand, lead to a huge waste of investment in offshore electrical systems, which is not conducive to the investment recovery of offshore wind power, especially grid-parity offshore wind farms. On the other hand, it will also limit the application of high-voltage DC in large-scale offshore wind power grid connection, which is not conducive to giving full play to the flexible control advantages of DC transmission. Summary of the Invention

[0007] The purpose of this invention is to provide a method, apparatus and storage medium for AC / DC networking of offshore wind power clusters.

[0008] The objective of this invention can be achieved through the following technical solutions:

[0009] A method for AC / DC networking of offshore wind power clusters based on multidimensional binary decision variables includes:

[0010] Step S1: Obtain the topology of the wind power cluster, as well as the location and capacity of the offshore substation;

[0011] Step S2: Define four sets of binary decision variables to describe the topology of the power transmission system;

[0012] Step S3: Considering the costs of offshore converter stations, onshore converter stations, onshore substations, and high-voltage transmission lines, establish a total investment model for the power transmission system based on the defined binary decision variables;

[0013] Step S4: Linearize the stepped cost based on the disjunctive inequality. Optimize the power transmission mode, number, location and capacity of converter stations, division of wind farm groups, and selection of onshore common connection points for each electric field in the offshore wind cluster according to the obtained mixed integer linearization model, and obtain the network configuration results.

[0014] In step S1, the topology of the wind power cluster, as well as the location and capacity of the offshore booster, are generated using fuzzy clustering (FCM), minimum spanning tree, and genetic algorithm.

[0015] The binary decision variables in step S2 are Z. v,m Z w,v Z w,p Z v,p ,in:

[0016] Location matrix Z of offshore converter station v,m The converter station v is located at a grid position formed by the gridding of the empty sea area between the offshore wind farm cluster and the coastline, and is an N-type grid. v ×N m The matrix, matrix element Z v,m (v,m)=1 indicates that the offshore converter station v is located at grid m. When the matrix is ​​empty, it means that there is no offshore converter station.

[0017] Adjacency matrix Z w,v : Represents the connection relationship between the wind farm booster station w and the offshore converter station v, matrix element Z w,v(w,v)=1 indicates that the wind farm booster station w is connected to the offshore converter station v. When this matrix is ​​empty, it means that all the wind farm booster stations are directly connected to the onshore common connection point, which is a pure AC planning scheme.

[0018] Adjacency matrix Z w,p : Represents the connection relationship between the wind farm booster station w and the onshore common junction point p, matrix element Z w,p (w,p)=1 indicates that the wind farm booster station w is connected to the onshore common connection point p. When this matrix is ​​empty, it means that all wind farm booster stations are connected to the offshore converter station, which is a pure DC planning scheme.

[0019] Adjacency matrix: Represents the connection relationship between an offshore converter station v and an onshore common connection point p, with matrix elements Z. v,p (v,p)=1 indicates that the offshore converter station v is connected to the onshore common connection point p.

[0020] The total investment model for the power transmission system is as follows:

[0021]

[0022] Where: v, k, g, w, and p are the indices for offshore converter station, onshore converter station, onshore substation, offshore booster station, and onshore common connection point, respectively; Cost of offshore converter stations; Cost of onshore converter stations; Cost of onshore substations; The construction cost of the 220kV AC submarine cable from the wind farm (w) to the offshore converter station (v) The construction cost of the 220kV AC submarine cable from the wind farm w to the onshore common connection point p; Cost of ±320kV DC submarine cable from offshore converter station v to onshore common connection point p, For the line The cost of reactive power compensation.

[0023] The total investment model for the power transmission system also includes:

[0024]

[0025]

[0026]

[0027]

[0028]

[0029]

[0030]

[0031]

[0032] Where: R f The cost required to build a new offshore converter platform; This refers to the length of the submarine cable from the wind farm to the offshore converter station. The length of the submarine cable from the wind farm to the onshore public connection point; The length of the submarine cable from the offshore converter station to the onshore public connection point; Cost per unit capacity of converters for offshore converter stations; Cost per unit capacity of converter in onshore converter stations; Cost per unit capacity of transformers in onshore substations; This represents the rated capacity of the v-th offshore converter station; Let be the rated capacity of the k-th onshore converter station; Let g be the rated capacity of the g-th onshore substation; These are the unit construction cost functions for the high-voltage AC output lines of wind farms and the high-voltage DC grid-connected lines of offshore converter stations, respectively.

[0033] The constraints of the total investment model for the power transmission system include integer constraints, converter station location constraints, and cable substation and converter station capacity constraints.

[0034] The capacity constraints of the cable substations and converter stations include:

[0035]

[0036] in: Capacity of each string of medium-voltage AC cables; Capacity of high-voltage AC cable; This refers to the capacity of the high-voltage DC cable; Capacity of offshore substations; Capacity of offshore converter stations.

[0037] The feasible site selection region R of the offshore converter station is rasterized, discretizing the continuous site selection space into N. c ×N r A square grid, the coordinates of the center of each grid (x) m ,y m All of these are candidate coordinates for offshore converter stations.

[0038] An AC / DC grid connection device for offshore wind power clusters based on multidimensional binary decision variables includes a memory, a processor, and a program stored in the memory. When the processor executes the program, it implements the method described above.

[0039] A storage medium having a program stored thereon, which, when executed, implements the method described above.

[0040] Compared with existing technologies, this invention has the following advantages: It proposes a unified planning scheme for large-scale offshore wind farm cluster grid-connected systems that considers a hybrid AC / DC transmission method, offering greater economic advantages compared to pure DC / pure AC transmission methods. Compared to traditional schemes that directly determine the transmission method for each wind farm based on the equivalent distance of AC / DC transmission, this invention uses the transmission method as a decision variable to construct a cost model for the transmission system, better considering the overall economic efficiency of the wind farm cluster. Attached Figure Description

[0041] Figure 1 This is a structural diagram of a hybrid AC / DC access system for a large offshore wind farm.

[0042] Figure 2 This is the algorithm flowchart.

[0043] Figure 3 To facilitate the cluster layout of offshore wind farms.

[0044] Figure 4 This is the optimized result of the offshore wind farm access system of the present invention.

[0045] Figure 5 This represents the optimized results of the traditional offshore wind farm access system. Detailed Implementation

[0046] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. These embodiments are based on the technical solution of the present invention and provide detailed implementation methods and specific operating procedures. However, the scope of protection of the present invention is not limited to the following embodiments.

[0047] A method for AC / DC network planning of offshore wind power clusters based on multidimensional binary decision variables, such as Figure 2 As shown, it includes the following steps:

[0048] 1) The offshore wind farm cluster grid-connected system is divided into four layers. First, the internal topology of the wind turbine layer is optimized and planned. The minimum spanning tree, FCM clustering algorithm, and genetic algorithm are used to optimize the planning of the medium-voltage power collection system, so as to obtain the topology optimization results of a single wind farm and the location and capacity of the offshore booster station.

[0049] 2) Utilize the locations and capacities of offshore substations for each wind farm obtained in step 1) to plan the power transmission system. Optimize the offshore converter station layer by gridding the feasible locations of offshore converter stations, with the grid center representing the candidate locations. Based on the obtained offshore substation locations and capacities, candidate offshore converter station locations, and candidate onshore common junctions (CCJ), define four sets of binary decision variables to describe the power transmission system topology, thereby determining the location of offshore converter stations and the connection relationships between offshore substations, between offshore substations and onshore CCJs, and between offshore converter stations and onshore CCJs.

[0050] 3) Considering the costs of offshore converter stations, onshore converter stations, onshore substations, and high-voltage transmission lines, a total investment model for the power transmission system is established using the proposed binary decision variables;

[0051] 4) Based on the disjunctive inequality, the stepped cost is linearized, and the resulting mixed integer linearized model is used to optimize the best power transmission mode for each electric field in the offshore wind cluster, the optimal number, location and capacity of converter stations, the division of wind farm groups, and the selection of onshore common connection points.

[0052] In step 1), the topology of the hierarchical optimization model for offshore wind farm clusters is as follows: Figure 1 As shown.

[0053] The wind turbine layer to the offshore substation layer is the power collection system. By using fuzzy clustering (FCM), minimum spanning tree, and genetic algorithm to optimize the planning of the power collection system, the topology of each wind farm and the location and capacity of the offshore substation can be obtained.

[0054] The offshore wind farm power collection system consists of two parts: an offshore substation and a medium-voltage submarine cable network. The total investment cost model for the offshore wind farm power collection system can be expressed as follows:

[0055]

[0056] stSb ranc h≤S max

[0057] In the formula: represents the total investment cost of the electrical connections for the wind farm's power collection system; w represents the number of wind farms. Investment cost for offshore substations; C MV,cable Cost of medium-voltage submarine cables; S branch The apparent power transmitted on each line of the electrical wiring; S max This represents the maximum apparent power that each branch can transmit.

[0058] In step 2), the topology connection relationship variables are defined: the topology of the power transmission system consists of four binary matrices (Z... v,m Z w,v Z w,p Z v,p These matrices represent the binary decision variables in the planning model, as defined below:

[0059] ①Location matrix of offshore converter station Z v,m The converter station v is located at a grid position formed by the gridding of the empty sea area between the offshore wind farm cluster and the coastline, and is an N-type grid. v ×N m The matrix. Matrix element Z v,m (v,m) = 1 indicates that the offshore converter station v is located at grid m. An empty matrix indicates that there is no offshore converter station.

[0060] ②Adjacency matrix Z w,v : Represents the connection between the wind farm booster station w and the offshore converter station v, matrix element Z w,v (w,v) = 1 indicates that the wind farm's booster station w is connected to the offshore converter station v. When this matrix is ​​empty, it means that all the wind farm's booster stations are directly connected to the onshore common junction point.

[0061] ③Adjacency matrix Z w,p : Represents the connection relationship between the wind farm booster station w and the onshore common junction point p, matrix element Z w,p (w,p) = 1 indicates that the wind farm's booster station w is connected to the onshore common junction point p. When this matrix is ​​empty, it means that all the wind farm's booster stations are connected to the offshore converter station.

[0062] ④ Adjacency matrix: Represents the connection relationship between the offshore converter station v and the onshore common connection point p, with matrix elements Z v,p (v,p)=1 indicates that the offshore converter station v is connected to the onshore common connection point p.

[0063] In step 3), considering the costs of offshore converter stations, onshore converter stations, onshore substations, high-voltage transmission lines, and reactive power compensation costs of the AC system, a total investment model for the transmission system is established using the proposed binary decision variables:

[0064]

[0065] In the formula, v, k, g, w, and p are the indices of offshore converter station, onshore converter station, onshore substation, offshore booster station, and onshore common connection point, respectively. Cost of offshore converter stations; Cost of onshore converter stations; Cost of onshore substations; The construction cost of the 220kV AC submarine cable from the wind farm (w) to the offshore converter station (v) The construction cost of the 220kV AC submarine cable from the wind farm w to the onshore common connection point p; Cost of ±320kV DC submarine cable from offshore converter station v to onshore common connection point p, For the line The cost of reactive power compensation;

[0066] The above costs can be further described as follows:

[0067]

[0068]

[0069]

[0070]

[0071]

[0072]

[0073]

[0074]

[0075] In the formula, v represents the number of offshore converter stations; R f The cost required to build a new offshore converter platform; This refers to the length of the submarine cable from the wind farm to the offshore converter station. This refers to the length of the submarine cable connecting the wind farm to the onshore substation. This refers to the length of the submarine cable connecting the offshore converter station to the onshore converter station. Cost per unit capacity of converters for offshore converter stations; Cost per unit capacity of converter in onshore converter stations; Cost per unit capacity of transformers in onshore substations; This represents the rated capacity of the v-th offshore converter station; Let be the rated capacity of the k-th onshore converter station; Let g be the rated capacity of the g-th onshore substation; These are the unit construction cost functions for high-voltage AC output lines of wind farms and high-voltage DC grid-connected lines of offshore converter stations, respectively. Considering that the selection of submarine cables at the same voltage level mainly depends on the transmission capacity S, this paper expresses the cost of high-voltage AC and DC submarine cables as a step function of transmission capacity. c The reactive power generated by the charging current of directly grid-connected high-voltage AC lines; Q off Qon These are the reactive power compensation capacities for offshore and onshore applications, respectively. Construction cost per unit capacity for reactive power compensation at sea; For the construction cost per unit capacity of reactive power compensation on land; V ac This refers to the rated voltage of the high-voltage AC submarine cable; f n The system's rated frequency; C i The capacitance per unit length of the selected cable.

[0076] ① To ensure that each offshore wind farm has a connection to the onshore power grid, the following constraints must be met:

[0077]

[0078] ② To ensure that each offshore converter station can be successfully connected to the onshore power grid, the following constraints must be met:

[0079]

[0080] ③ Constraints on the number of offshore converter stations: For a certain scale of offshore wind farm, the number of offshore converter stations is limited and generally will not exceed the number of wind farms.

[0081] 0≤n vsc ≤n sub

[0082] ④ Converter station site selection constraints

[0083] The converter station must be located between the wind farm and the grid connection point; therefore, the feasible site selection area R of the converter station is constrained as follows:

[0084]

[0085] ⑤ Capacity constraints of cables, substations, and converter stations

[0086] The capacity of the medium-voltage AC collection cable is equal to the output of the same string of offshore wind turbines; the capacity of the offshore converter station is not less than the sum of the capacities of all AC submarine cables collected at that station; cable current carrying capacity constraints:

[0087]

[0088] In the formula Capacity of high-voltage AC cable; This refers to the capacity of the high-voltage DC cable; Capacity of offshore substations; Capacity of offshore converter stations;

[0089] In step 4), the linearized step cost model is used. The choice of high-voltage submarine cable type is mainly determined by transmission capacity. Therefore, the investment cost of high-voltage submarine cable can be regarded as a step function of transmission capacity, such as the construction cost function of AC cable, which has a general form:

[0090]

[0091]

[0092] In the formula, For high-voltage AC cables in the nth interval The investment cost is denoted by ; the subscript n is the segmented interval index of the step function for the investment cost of high-voltage AC submarine cables. Its equivalent linearized model is:

[0093]

[0094] In the formula, the binary variable matrix Used to determine whether the AC cable capacity falls within the range. If it belongs to... The value is 1 if the sum is less than 1, and 0 otherwise; similarly, we can deduce that K is a sufficiently large positive number. The equivalent linearized model is:

[0095]

[0096] In the formula, the subscript q is the segmented interval index of the ladder function of the investment cost of the DC line connecting the converter station to the grid.

[0097] Substituting the above formula into the cost of cables for direct AC grid connection of wind farms, we get:

[0098]

[0099] The product of the two binary variables in the equation makes the expression nonlinear, and its equivalent linearized model is:

[0100]

[0101] In the formula, Z w,p,n (w,p,n) represents Z w,p (w,p) and The product of.

[0102] This invention rasterizes the feasible site selection region R of offshore converter stations, discretizing the continuous site selection space into N. c ×N r A square grid. The coordinates of the center of each grid (x, y) m ,y m All coordinates are candidate coordinates for offshore converter stations. The distance L between the candidate coordinates and each wind farm is... w,mand its distance L from each land public contact point m,p Known parameters can be calculated as the basis for selecting the location of offshore converter stations.

[0103] Introducing the binary decision variable matrix Z v,m This determines whether grid m is selected as the planning site for the offshore converter station v. If selected, then Z... v,m The value of (v,m) is 1; otherwise, it is 0.

[0104] 0≤Σ v Σ m Z v,m ≤n sub

[0105] The lengths of the 220kV AC collection line from the planned wind farm to the offshore converter station, and the line from the offshore converter station to the onshore converter station, can be expressed as:

[0106]

[0107]

[0108] Substituting the above formula into the AC submarine cable cost model, we can obtain...

[0109]

[0110] The product of the three binary variable matrices in the formula makes the expression still nonlinear, and its equivalent linearized model is:

[0111]

[0112] In the formula, Z w,v,m For Z w,v and Z v,m The product of Z and Z, when its value is 1, represents the connection of wind farm w to offshore converter station v located in grid m; w,v,m,n For Z w,v,m and The product of.

[0113] Similarly, an equivalent linearized model for the cost of DC submarine cables can be obtained.

[0114]

[0115] In the formula, Z v,m,p For Z v,m and Z v,p The product of Z and Z, when its value is 1, represents the connection of the offshore converter station v with a location of grid m to the onshore grid connection point p; v,m,p,q For Z v,m,p and The product of.

[0116] In addition, the discretized location of the collecting converter station must avoid the situation where a collecting converter station has multiple locations.

[0117]

[0118] This formula allows for the offshore converter station v to be left unsited, meaning that the planned scheme does not include the construction of the offshore converter station.

[0119] Multiple offshore converter stations must also avoid choosing the same site.

[0120]

[0121] Each wind farm must be connected to a sited offshore converter station or directly connected to an onshore substation.

[0122]

[0123] The following is an illustration using a specific case:

[0124] (1) Parameter settings

[0125] The case study in this article selects an offshore wind farm cluster comprising 18 offshore wind farms located 70–140 km offshore, all of which are planned and under construction concurrently. The installed capacity of each offshore wind farm is shown in Table 1. The total installed capacity is 4500 MW.

[0126] Table 1 Installed capacity of each offshore wind farm

[0127]

[0128] The coordinates and installed capacity of the offshore wind turbines have been determined, and the distribution of the 18 offshore wind farms is as follows: Figure 3 As shown. The coordinates of the 7 candidate land PCC points are known: PCC1 (10.6, 132.4), PCC2 (8.2, 98.5), PCC3 (4.3, 62.7), PCC4 (3.6, 32.1), PCC5 (5.3, -10.9), PCC6 (7.3, -43.2), PCC7 (10.4, -108.7).

[0129] The power collection system is connected by submarine medium-voltage cables with a voltage level of 35kV; the offshore power transmission system is connected by submarine 220kV high-voltage AC cables and submarine ±320kV high-voltage DC cables; the typical cost of the power transmission projects involved is shown in Tables 2 and 3.

[0130] Table 2 AC Submarine Cable Parameters

[0131]

[0132] Table 3 Parameters of DC Submarine Cables

[0133]

[0134]

[0135] (2) Analysis of the optimization results of the AC / DC hybrid access system for offshore wind farm clusters in this invention

[0136] Figure 3 The optimized results of the offshore wind farm grid connection system of this invention are shown in Table 4. Blue circles represent wind turbines, black boxes represent offshore substations, red boxes represent offshore converter stations, solid blue lines represent high-voltage AC collection lines within the wind farm cluster, dashed blue lines represent 220kV high-voltage AC grid-connected submarine cables, red lines represent ±320kV high-voltage DC submarine cables, and red circles represent onshore common grid connection points. Different wind turbine colors indicate the division of the wind farm cluster. The optimized line configuration results are shown in Table 4.

[0137] Table 4 Optimization results of the transmission cable of the present invention

[0138]

[0139]

[0140] The AC / DC hybrid unified planning model proposed in this invention does not directly specify the power transmission mode of the wind farm based on distance, but rather uses a given binary decision variable z. w,v z w,p To determine the power transmission method of each wind farm. For example... Figure 3 As shown, wind farms 1, 2, 3, and 11 use AC power transmission, while wind farms 4, 5, 6, 7, 8, 9, 10, 12, 13, 14, 15, 16, 17, and 18 use DC power transmission.

[0141] (3) Analysis of the optimization results of the AC / DC hybrid access system for offshore wind farm clusters using traditional methods

[0142] Traditional AC / DC hybrid planning arbitrarily assigns transmission methods to each wind farm based on the equivalent distance of AC / DC transmission. For example... Figure 4As shown, since the capacity of each planned wind farm is less than 600MW, previous studies indicate that the equivalent AC / DC distance is approximately 100km. Therefore, wind farms 1, 2, 3, 4, 5, 6, 11, 14, and 15 will be directly connected to the nearest onshore public grid connection point via AC transmission. Wind farms 7, 8, 9, 10, 12, 13, 16, 17, and 18 will first be connected to an offshore converter station to convert DC power before being connected to the onshore public grid connection point. This scheme selects the cluster center as the location of the offshore converter station and obtains the optimal number of offshore converter stations through enumeration. The results of the traditional method's line optimization configuration are shown in Table 5.

[0143] Table 5 Optimization results of traditional transmission cable methods

[0144]

[0145]

[0146] Compared with the optimized results of this invention, wind farms 4, 5, 6, 14, and 15 in the traditional AC / DC hybrid planning scheme adopt AC transmission. The reasons for this are mainly as follows: 1) Due to economies of scale, while individual wind farms may achieve the lowest cost, the overall economic efficiency is not necessarily optimal. 2) The equivalent transmission distance varies considerably with capacity. Due to the aggregation effect of the wind farm cluster, wind farms that were originally optimally suited for AC transmission may now use DC transmission. 3) The choice of transmission method for individual wind farms is coupled with the division of the wind farm cluster and cannot be considered separately.

[0147] (4) Cost comparison analysis of different planning schemes

[0148] Table 6 shows the optimized costs of different AC / DC planning methods. As can be seen from Table 6, the DC unified planning method proposed in this invention reduces the cost by 8.51% compared to the traditional AC / DC hybrid planning method. Although the method proposed in this invention adds one more converter station than the traditional AC / DC planning method, the cost increase for this part is lower than the cost of building five more AC transmission lines in the traditional scheme.

[0149] Table 6 Optimization Costs of Different AC / DC Planning Methods

[0150]

[0151]

[0152] This case demonstrates that the method proposed in this patent is effective and feasible. It can select the transmission mode for different wind farms based on minimizing the objective function, automatically delineate wind farm groups, and determine the location of offshore converter stations. Moreover, compared to the traditional method of manually selecting the transmission mode based on the offshore distance and capacity of each wind farm, the AC / DC unified planning method proposed in this paper can better consider the overall economic efficiency of the cluster.

[0153] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

Claims

1. A method for AC / DC networking of offshore wind power clusters based on multidimensional binary decision variables, characterized in that, include: Step S1: Obtain the topology of the wind power cluster, as well as the location and capacity of the offshore substation; Step S2: Define four sets of binary decision variables to describe the topology of the power transmission system; Step S3: Considering the costs of offshore converter stations, onshore converter stations, onshore substations, and high-voltage transmission lines, establish a total investment model for the power transmission system based on the defined binary decision variables; Step S4: Linearize the stepped cost based on the disjunctive inequality. Optimize the power transmission mode, number, location and capacity of converter stations, division of wind farm groups, and selection of onshore common connection points for each electric field in the offshore wind cluster according to the obtained mixed integer linearization model, and obtain the network topology results. The total investment model for the power transmission system is as follows: in: These are indexes for offshore converter stations, onshore converter stations, onshore substations, offshore booster stations, and onshore common connection points, respectively. For offshore converter station v cost; For land-based converter station k cost; For onshore substations g cost; For wind farm To offshore converter station The construction cost of 220kV AC submarine cable For wind farm To land public connection point The construction cost of a 220kV AC submarine cable; For offshore converter station To land public connection point The cost of ±320kV DC submarine cable For the line The cost of reactive power compensation; The total investment model for the power transmission system also includes: in: The cost required to build a new offshore converter platform; This refers to the length of the submarine cable from the wind farm to the offshore converter station. The length of the submarine cable from the wind farm to the onshore public connection point; This refers to the length of the submarine cable from the offshore converter station to the onshore common connection point; Cost per unit capacity of converters for offshore converter stations; Cost per unit capacity of converter in onshore converter stations; Cost per unit capacity of transformers in onshore substations; This represents the rated capacity of the v-th offshore converter station; Let be the rated capacity of the k-th onshore converter station; Let g be the rated capacity of the g-th onshore substation; , These are the unit construction cost functions for high-voltage AC output lines of wind farms and high-voltage DC grid-connected lines of offshore converter stations, respectively. The constraints of the total investment model for the power transmission system include integer constraints, converter station location constraints, and cable substation and converter station capacity constraints. The capacity constraints of the cable substations and converter stations include: in: Capacity of each string of medium-voltage AC cables; Capacity of high-voltage AC cable; Capacity of the high-voltage DC cable; Capacity of offshore substations; Capacity of offshore converter stations.

2. The method for AC / DC networking of offshore wind power clusters based on multidimensional binary decision variables according to claim 1, characterized in that, In step S1, the topology of the wind power cluster, as well as the location and capacity of the offshore booster, are generated using fuzzy clustering (FCM), minimum spanning tree, and genetic algorithm.

3. The method for AC / DC networking of offshore wind power clusters based on multidimensional binary decision variables according to claim 1, characterized in that, The binary decision variables in step S2 are respectively , , , ,in: Location matrix of offshore converter stations The converter station v is located in a grid position formed by the gridding of the empty sea area between the offshore wind farm cluster and the coastline. The matrix, matrix elements , indicating that the offshore converter station v is located at grid m, and the matrix being empty indicates that there is no offshore converter station; Adjacency Matrix : Represents the connection relationship between the wind farm booster station w and the offshore converter station v, matrix elements , indicating that the wind farm booster station w is connected to the offshore converter station v. When this matrix is ​​empty, it means that all wind farm booster stations are directly connected to the onshore public connection point, which is a pure AC planning scheme. Adjacency Matrix : Represents the connection relationship between the wind farm booster station w and the onshore common junction point p, matrix element , indicating that the wind farm booster station w is connected to the onshore common connection point p. When this matrix is ​​empty, it means that all wind farm booster stations are connected to the offshore converter station, which is a pure DC planning scheme. Adjacency matrix: Represents the connection relationship between an offshore converter station v and an onshore common connection point p. Matrix elements This indicates that the offshore converter station v is connected to the onshore common connection point p.

4. The method for AC / DC networking of offshore wind power clusters based on multidimensional binary decision variables according to claim 1, characterized in that, The feasible location region R of the offshore converter station is rasterized, discretizing the continuous location space into... A square grid, with the coordinates of the center of each grid cell. All of these are candidate coordinates for offshore converter stations.

5. A multidimensional binary decision variable-based AC / DC grid connection device for offshore wind power clusters, comprising a memory, a processor, and a program stored in the memory, characterized in that, When the processor executes the program, it implements the method as described in any one of claims 1-4.

6. A storage medium having a program stored thereon, characterized in that, When the program is executed, it implements the method as described in any one of claims 1-4.

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