A method for selecting offshore booster stations considering wind turbine-wind farm coordinated optimization

Abstract

The present invention discloses a method for selecting an offshore substation site considering the coordinated optimization of wind turbines and wind farms, comprising obtaining wind turbine capacity, wind turbine coordinates and output data inside the wind farm, wind farm capacity, coordinates and output data, power system transmission equipment information, target area transmission price and abandoned power compensation price, and a candidate set for offshore substation site selection; generating an initial population of wind turbines through a topology optimization model of wind turbines inside the wind farm according to the wind turbine capacity, wind turbine coordinates and wind turbine output data, and obtaining the best individual in the current population; generating an initial population of wind farms through a topology optimization model of wind turbines between wind farms according to the wind farm coordinates and the best individual, obtaining the best individual in the offspring population of the wind farm, and determining the optimal topology of a two-layer system of wind turbines and wind farms under the current offshore substation site selection; calculating the optimal topology of the two-layer system of wind turbines and wind farms for each candidate offshore substation site selection in the candidate set, and selecting the offshore substation site selection as the best site selection.

Description

Technical Field

[0001] The present invention relates to the technical field of topological optimization of wind power collection systems, and in particular to an offshore booster station site selection method that takes into account wind turbine-wind farm coordinated optimization. Background Art

[0002] As the most dynamic renewable clean energy generation method in the 21st century, wind power generation has made great contributions to building a low-carbon society, promoting the transformation of new and old kinetic energy, and promoting sustainable economic development. Compared with inland wind resources, offshore wind resources are more stable, have better wind energy quality, higher power generation efficiency, and less direct impact on human life [1]. Therefore, in recent years, wind power has developed rapidly in countries around the world. As of the end of 2020, the cumulative total installed capacity of offshore wind power has reached 32.5GW, and the global installed capacity of offshore wind power is still growing year by year. Large-scale offshore wind power grid connection in the far sea is gradually becoming one of the main development directions of renewable energy.

[0003] my country's offshore wind farms are mainly built in the eastern and southern coastal areas, close to the load center, and can provide a large amount of electricity resources for inland areas. However, in recent years, the development of offshore wind power has encountered problems such as low utilization of wind resources, imbalance between wind power and other power resources, and wind abandonment and grid disconnection caused by incoordination with the load side of the power system. The fundamental way to solve the problem of offshore wind power consumption is to reasonably plan the wind farm topology structure that couples the random characteristics of wind power, optimize the unit output of cluster wind farms by using the smoothing effect of large wind farms, design economical and reliable grid-connected transmission solutions, and build a collection and transmission system that adapts to the coordinated control of large-scale offshore wind farms and onshore power grids.

[0004] The site selection of offshore substations is also an important influencing factor, so it is very necessary to design an offshore substation site selection strategy that considers the coordinated optimization of wind turbines and wind farms. Summary of the invention

[0005] The purpose of the present invention is to overcome the shortcomings of the prior art and provide a method for selecting an offshore booster station site considering wind turbine-wind farm coordinated optimization, comprising the following steps:

[0006] Step 1: Obtain wind turbine capacity, wind turbine coordinates and output data inside the wind farm, wind farm capacity, coordinates and output data, power system transmission equipment information, target area transmission price and abandoned power compensation price, and offshore booster station site selection candidate set;

[0007] Step 2: Generate the initial population of wind turbines through the internal wind turbine topology optimization model of the wind farm according to the wind turbine capacity, wind turbine coordinates and wind turbine output data, and calculate the net profit of each wind turbine. If the net profit of the wind turbine does not meet the termination criterion, generate a sub-population, perform crossover and mutation on the sub-population, and then calculate the net profit of each wind turbine. If the net profit of the wind turbine meets the termination criterion, obtain the optimal individual in the current population.

[0008] Step 3: According to the wind farm coordinates and the optimal individual, the initial population of wind farms is generated through the wind turbine topology optimization model between wind farms, and the net income of each wind farm is calculated. If the net income of the wind farm does not meet the termination criterion, a sub-generation population of wind farms is generated, and the sub-generation population of wind farms is crossovered and mutated, and then the net income of each wind farm is calculated. If the net income of the wind farm meets the termination criterion, the optimal individual in the sub-generation population of wind farms after crossover and mutation is obtained, and the optimal topology of the wind turbine-wind farm double-layer system under the current offshore booster station site selection is determined;

[0009] Step 4: Calculate the optimal topology of the wind turbine-wind farm double-layer system for each candidate offshore substation site in the candidate set, and select the topology with the largest net benefit. The corresponding offshore substation site is the optimal site.

[0010] Furthermore, the candidate set for offshore wind farm site selection is generated based on a grid map, and the area between two given coordinates is gridded to obtain the candidate set.

[0011] Furthermore, the wind turbine-wind farm double-layer system includes wind turbine topology within the wind farm and topology between wind farms.

[0012] Furthermore, the wind farm internal wind turbine topology optimization model is built based on the wind farm internal wind turbine coordinates, capacity and output data; the inter-wind farm topology optimization model is obtained based on the wind farm coordinates, capacity and output data; the collaborative optimization model is obtained based on the wind farm internal wind turbine information and wind farm information.

[0013] Furthermore, the wind turbine topology optimization model between wind farms is established based on a genetic algorithm, combined with wind turbine topology optimization results within the wind farm and wind power smoothing effect.

[0014] An offshore booster station site selection system that applies an offshore booster station site selection method that considers wind turbine-wind farm collaborative optimization includes: wind turbine topology within a wind farm and topology between wind farms; wherein the wind turbine topology within a wind farm includes wind turbines and transmission lines, and the wind turbines are connected to wind turbines or wind farms through transmission lines; the topology between wind farms includes wind farms, transmission lines, and offshore booster stations, and the wind farms are connected to wind turbines, wind farms, and offshore booster stations through transmission lines.

[0015] The beneficial effects of the present invention are: 1. An innovative point of the present invention is that, taking into account the wind power smoothing effect, a topology optimization model of the wind turbines inside the wind farm is obtained through the coordinates, capacity and output data of the wind turbines inside the wind farm, and a genetic algorithm is used to optimize the topology of the wind turbines inside the wind farm. According to the optimal topology of the wind turbines inside the wind farm, a wind farm topology optimization model is established through the wind farm coordinates to obtain the optimal topology of the wind turbine-wind farm double-layer system for the current offshore substation site selection.

[0016] 2. On the basis of the above, according to the candidate set of offshore substation site selection, the optimal wind turbine-wind farm two-layer system topology is obtained, which corresponds to the optimal offshore substation site selection. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 is a system diagram of the collaborative optimization model of the present invention;

[0018] Figure 2 A schematic diagram of an offshore wind farm cluster access system of the present invention;

[0019] Figure 3 This is a wind farm cluster output curve in a certain area of ​​Jiangsu in an embodiment of the present invention;

[0020] Figure 4 is a continuous output curve of a wind farm in an embodiment of the present invention;

[0021] Figure 5 is one of the three wind turbine topology diagrams inside the wind farm in the embodiment of the present invention;

[0022] Figure 6 This is the second of the three wind turbine topology diagrams inside the wind farm in the embodiment of the present invention;

[0023] Figure 7 This is the third of the three wind turbine topology diagrams in the wind farm according to the embodiment of the present invention;

[0024] Figure 8 Schematic diagram of optimization result of wind turbine topology 1 inside a wind farm according to an embodiment of the present invention;

[0025] Fig. 9 Schematic diagram of optimization result of wind turbine topology 2 inside a wind farm in an embodiment of the present invention;

[0026] Fig.10 It is the topology optimization result of the offshore wind power integrated system in the embodiment of the present invention. DETAILED DESCRIPTION

[0027] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings, but the protection scope of the present invention is not limited to the following.

[0028] like Figure 1As shown, a method for selecting an offshore booster station site considering wind turbine-wind farm coordinated optimization includes the following steps;

[0029] Step 1: Obtain wind turbine capacity, wind turbine coordinates and output data inside the wind farm, wind farm capacity, coordinates and output data, power system transmission equipment information, target area transmission price and abandoned power compensation price, and offshore booster station site selection candidate set;

[0030] Step 2: Generate the initial population of wind turbines through the internal wind turbine topology optimization model of the wind farm according to the wind turbine capacity, wind turbine coordinates and wind turbine output data, and calculate the net profit of each wind turbine. If the net profit of the wind turbine does not meet the termination criterion, generate a sub-population, perform crossover and mutation on the sub-population, and then calculate the net profit of each wind turbine. If the net profit of the wind turbine meets the termination criterion, obtain the optimal individual in the current population.

[0031] Step 3: According to the wind farm coordinates and the optimal individual, the initial population of wind farms is generated through the wind turbine topology optimization model between wind farms, and the net income of each wind farm is calculated. If the net income of the wind farm does not meet the termination criterion, a sub-generation population of wind farms is generated, and the sub-generation population of wind farms is crossovered and mutated, and then the net income of each wind farm is calculated. If the net income of the wind farm meets the termination criterion, the optimal individual in the sub-generation population of wind farms after crossover and mutation is obtained, and the optimal topology of the wind turbine-wind farm double-layer system under the current offshore booster station site selection is determined;

[0032] Step 4: Calculate the optimal topology of the wind turbine-wind farm double-layer system for each candidate offshore substation site in the candidate set, and select the topology with the largest net benefit. The corresponding offshore substation site is the optimal site.

[0033] The candidate set for offshore wind farm site selection is generated based on the grid map. The area between two given coordinates is gridded to obtain the candidate set.

[0034] The wind turbine-wind farm two-layer system includes the wind turbine topology within the wind farm and the topology between wind farms.

[0035] The wind turbine topology optimization model inside the wind farm is built based on the wind turbine coordinates, capacity and output data inside the wind farm; the topology optimization model between wind farms is obtained based on the wind farm coordinates, capacity and output data; the collaborative optimization model is obtained based on the wind turbine information inside the wind farm and the wind farm information.

[0036] The wind turbine topology optimization model between wind farms is established based on genetic algorithm, combined with the wind turbine topology optimization results within the wind farm and the wind power smoothing effect.

[0037] An offshore booster station site selection system that applies an offshore booster station site selection method that considers wind turbine-wind farm collaborative optimization includes: wind turbine topology within a wind farm and topology between wind farms; wherein the wind turbine topology within a wind farm includes wind turbines and transmission lines, and the wind turbines are connected to wind turbines or wind farms through transmission lines; the topology between wind farms includes wind farms, transmission lines, and offshore booster stations, and the wind farms are connected to wind turbines, wind farms, and offshore booster stations through transmission lines.

[0038] A method for selecting an offshore booster station site considering wind turbine-wind farm coordinated optimization comprises the following steps:

[0039] S1, obtain the wind turbine capacity, coordinates and output data inside the wind farm, the wind farm capacity, coordinates and output data, power system transmission equipment information, target area transmission price and abandoned power compensation price, and offshore booster station site selection candidate set;

[0040] S2, input the capacity, coordinates and output data of wind turbines inside the wind farm into the established collaborative optimization model, and use the genetic algorithm to solve the model. First, generate the initial population and calculate the net profit of each wind turbine. If the termination criterion is not met, generate a child population, and then calculate the net profit of each wind turbine after crossover and mutation. If the termination criterion is met, the optimal individual in the current population is obtained; input the wind farm coordinates into the established collaborative optimization model, and according to the optimal individual obtained by the topology optimization of the wind turbines inside the wind farm, first generate the initial population and calculate the net profit of each wind farm. If the termination criterion is not met, generate a child population, and then calculate the net profit of each wind farm after crossover and mutation. If the termination criterion is met, the optimal individual in the current population is obtained, and the optimal topology of the wind turbine-wind farm double-layer system under the current offshore booster station site selection is determined.

[0041] S3, for each candidate offshore substation site in the candidate set, the optimal topology of the wind turbine-wind farm double-layer system is calculated, and the topology with the largest net benefit is selected, and the corresponding offshore substation site is the optimal site.

[0042] A brief description of how this solution works:

[0043] In the process of gathering and transmitting "wind turbines-wind farms-offshore substations-transmission systems-onshore power grids", the active output of offshore wind power is complementary in space. By gathering offshore wind power from different regions, it is helpful to reduce output fluctuations and make the output characteristic curve of wind turbine groups smoother, which is also called the smoothing effect or convergence effect of wind power output. The historical data of a cluster composed of several offshore wind farms in a certain area of ​​Jiangsu Province are statistically analyzed, and the following are obtained: Figure 2 The wind farm cluster output curve is shown.

[0044] Figure 3The thick red line is the overall output of the wind farm cluster, and the thin blue triangle lines represent the output of each wind farm. The statistical results show that when several wind farms are connected at the same time, the output of each wind farm shows a certain complementarity, which reduces the per-unit maximum value of the overall output of the wind farm, verifying the smoothing effect of the wind farm cluster.

[0045] For the transmission lines of wind farms or wind farm clusters, if they are configured according to installed capacity, the transmission lines will often be lightly loaded and the asset utilization rate will be low; if the transmission line capacity is too low, a large amount of wind power will be abandoned. Therefore, it is necessary to establish an economic comprehensive optimization model to coordinate the construction capacity of the transmission line and the loss of wind power abandonment. The comprehensive benefits of the transmission line are divided into costs and benefits, which are given by the net present value.

[0046]

[0047] Where: B total is the annual income; C L is the annual cost; r is the interest rate; N is the operating life.

[0048] The electricity sent by the wind farm is the source of revenue for the line. The wind abandonment caused by transmission capacity limitations, that is, the electricity not sent, should also be included in the line revenue as a penalty. Ignoring the price difference of electricity sent by the wind farm at different times, the annual revenue of the wind farm is B total Mainly affected by wind power income B TE and the cost of compensation for curtailed power generation C cur Decide, where B TE Mainly determined by the annual power generation of the wind power station, C cur Mainly determined by the annual wind power curtailment caused by transmission capacity limitations

[0049] C cur =[(1+r) N -1] / [r(1+r) N ]p b E cur

[0050] B TE =[(1+r) N -1] / [r(1+r) N ]p o E

[0051] Where: B TE is the wind power electricity income; C cur Compensation cost for power curtailment; p o 、p b is the price parameter; E cur is the annual power abandonment of the wind farm; E is the annual power generation of the wind farm.

[0052] Based on the annual continuous output curve that characterizes the output characteristics of wind power generation, the annual power abandonment and annual power generation of the wind farm are calculated. Figure 4 The annual continuous output curve of a wind farm is depicted as a function of the cumulative duration t. dur (t). The active power limit of the wind farm’s export line is P LL , so the theoretical output of the wind farm is greater than P LL When the power exceeds the line power constraint, the power will be abandoned. LL The wind farm output is not less than P LL The area enclosed by the annual continuous output curve and the coordinate axis is the theoretical annual power generation capacity of the wind farm E 0 , is the annual abandoned electricity in the shaded area E cur The sum of the annual power generation E of the blank area.

[0053] According to the above definition, the annual abandoned electricity of the wind farm is E cur The annual power generation E can be calculated by the following formula

[0054]

[0055]

[0056] Where P dur,max is the annual maximum output of the wind farm. According to the relationship between the annual power generation, annual power generation and annual power abandonment of the wind farm, the above formula is equivalent to:

[0057]

[0058] The constraints for the topology optimization of the power collection system mainly include the submarine cable transmission capacity constraint, the submarine cable current carrying capacity constraint, the submarine cable support wind turbine number constraint and the submarine cable crossing avoidance constraint.

[0059] When selecting a submarine cable, it should be ensured that the capacity of all wind turbines connected to the submarine cable does not exceed the limited capacity of the submarine cable, which is expressed as follows:

[0060]

[0061] Where S ij represents the capacity of wind turbine j connected to submarine cable i, n i represents the number of wind turbines connected to submarine cable i, S imax represents the maximum transmission capacity of submarine cable i, and N represents the number of submarine cables.

[0062] The current carrying capacity constraints of submarine cables include the current carrying capacity constraints of single wind turbine submarine cables and the current carrying capacity constraints of aggregation submarine cables, and their expressions are as follows:

[0063]

[0064] Among them I ij represents the current carrying capacity of cable i connected to fan j, P wj represents the rated output of fan j, U ij represents the rated voltage of the submarine cable ij, represents the power factor of fan j, I i Indicates that n is connected i Current carrying capacity of cable i of wind turbine, U i Indicates the rated voltage of the gathering submarine cable i.

[0065] Due to the limited current carrying capacity of submarine cables, the number of wind turbines that can be connected to each submarine cable is n. i is finite, and its expression is as follows:

[0066]

[0067] Among them I maxi Indicates the maximum current carrying capacity of the collection cable i, represents the power factor of the submarine cable i, P w Represents the average rated output of the wind turbines connected to the collecting submarine cable i.

[0068] The offshore wind power collection cables are usually installed by blowing and burying. Considering the actual engineering requirements, the collection cables are not allowed to cross each other. The input information of the model is the wind turbine location coordinates, so it is necessary to use the node coordinate information to determine whether the cables cross. The cable crossing constraint is

[0069]

[0070] Among them, P1P2 and Q1Q2 represent two line segments that cannot intersect. and · represent cross product and dot product calculations.

[0071] The grid-connected operation of offshore wind farms needs to be collected at the offshore booster station before transmission. The capacity of the offshore booster station should not be less than the capacity of each collection cable. The expression is as follows:

[0072]

[0073] Where S i Indicates the cable capacity, N i Indicates the number of cables collected at the booster station, S asc Indicates the capacity of the offshore booster station.

[0074] In the present invention, the model is optimized based on the genetic algorithm according to the optimization model. The site selection range of the offshore booster station is gridded and processed into discrete square grid units, and the location of the center of each grid unit on the map is used as the candidate address of the offshore booster station.

[0075] This embodiment Figure 1 The offshore wind farm cluster access system performs optimized site selection, inputs wind farm internal wind turbine information and output data into the established collaborative optimization model, and completes wind farm internal wind turbine topology optimization; inputs wind farm information and output data into the established collaborative optimization model, establishes a wind turbine-wind farm double-layer model, comprehensively considers large-scale wind power output characteristics, wind power smoothing effect, transmission project construction cost, wind power abandonment cost, wind power transmission income and other factors, and selects the optimal topology structure under the current offshore substation site selection; finds the optimal offshore substation site selection considering wind turbine-wind farm collaborative optimization through addressing strategy.

[0076] 1. Offshore wind turbine topology optimization

[0077] The capacity, coordinates and output data of wind turbines inside the wind farm are input into the established collaborative optimization model, and the genetic algorithm is used to solve the model. First, the initial population is generated and the net profit of each wind turbine is calculated. If the termination criterion is not met, a child population is generated, and then after crossover and mutation, the net profit of each wind turbine is calculated. If the termination criterion is met, the optimal individual in the current population is obtained, that is, the optimal topology of wind turbines inside the wind farm.

[0078] Take three wind farm topologies being planned in a certain area of ​​Jiangsu as an example. Figure 5 The cost of the power collection submarine cable and the number of mounted wind turbines are shown in Table 1.

[0079] Table 1 Economic and technical parameters of power collection submarine cables

[0080] <![CDATA[Submarine cable cross-sectional area / mm 2 > Submarine cable price / (10,000 yuan / km) Number of mounted fans 70 77.8 2 120 91.16 3 185 106.76 4 240 117.23 5 400 155.29 6

[0081] The three wind farm topologies are optimized. The optimization results are shown in Tables 2 and 3. The optimized topologies are shown in Tables 2 and 3. Figure 6 The optimization results show that the structure of topology 3 has not changed, and the optimization results of topology 1 and topology 2 are different from the planned ones, and the costs can be reduced by 2.06 million and 450,000 yuan respectively, which shows that the method proposed in this paper can effectively optimize the wind farm wind turbine topology and reduce the cost.

[0082] Table 2 Cost comparison before and after topology optimization

[0083] Topology Recommended topology cost / (100 million yuan) Cost after optimization / (100 million yuan) Topology 1 2.3804 2.3598 Topology 2 3.1988 3.1943 Topology 3 3.6369 3.6369

[0084] Table 3 Comparison of lengths of various types of submarine cables before and after topology optimization

[0085]

[0086]

[0087] 2. Wind power cluster topology optimization

[0088] Topology optimization was carried out on seven offshore wind farms in a certain area of ​​Jiangsu Province. The parameters of the collector submarine cables are shown in Table 4.

[0089] Table 4 Cost and capacity parameters of power collection submarine cables

[0090] Capacity / MW 150 200 300 350 400 Price / (10,000 yuan / km) 550 734 887 1200 1500

[0091] The longitude and latitude of the seven wind farms are converted to obtain the geographical location information of the wind farms. The onshore booster station is located at (100,100), as shown in Table 5.

[0092] Table 5 Wind farm location information

[0093] serial number X / km Y / km Installed capacity / MW 1 -53.09 51.11 10 2 -48.16 51.39 20 3 -33.27 -24.20 30 4 -17.11 -22.55 20 5 -13.16 51.29 30 6 -19.80 -45.94 10 7 100.49 -31.29 20

[0094] The output information of the wind farm is intercepted using the historical output data of the wind farm as the annual output data of the scenario year, which also reflects the correlation information within the wind farm cluster. At the same time, the transmission price and investment information are given: the transmission price is 0.08 yuan / (Kw*h), the compensation price for wind farm power abandonment due to transmission active power limitation is 0.32 yuan / (Kw*h), the service life of the collection system is 20 years, and the base discount rate is 0.08.

[0095] The genetic algorithm in this paper is used to solve the problem and perform 50 iterations. The final topology optimization result is as follows: Figure 7 As shown in the figure. The location of the offshore booster station is (0,35). The hollow circles in the figure are wind farms, and the black squares are offshore booster stations and onshore booster stations.

[0096] The connection method of connecting each wind farm directly to the offshore booster station (default coordinates: (0, 0)) and then connecting to the onshore booster station through the offshore booster station is compared with the result optimized in this paper. The comparison results are shown in Table 6.

[0097] Table 6 Comparison of topology optimization results

[0098] Topology Type Line length / km Line cost / 100 million yuan Revenue / 100 million yuan Before optimization 563.21 40.17 1.18 After optimization 416.24 30.65 10.63

[0099] Using the improved genetic algorithm proposed in this paper, the cost of the power collection system was reduced from 4.017 billion yuan to 3.065 billion yuan, a cost reduction of 23.6%. The revenue of the power collection system was increased from 118 million yuan to 1.063 billion yuan, and the overall revenue was increased by 945 million yuan.

[0100] Furthermore, the collaborative optimization includes topology optimization of wind turbines within a wind farm and topology optimization between wind farms.

[0101] Furthermore, the wind farm information and wind turbine information inside the wind farm should include the following data: equipment coordinates, equipment output data, and equipment capacity.

[0102] Furthermore, for the current offshore booster station site selection, based on the collaborative optimization model, the wind turbine topology structure inside the wind farm and the topology structure between wind farms are comprehensively considered, and the model is optimized using a genetic algorithm to obtain the optimal topology of wind turbines inside the wind farm and the optimal topology between wind farms under the current offshore booster station site selection.

[0103] Furthermore, the wind turbine topology optimization models within the wind farm and between wind farms are established based on genetic algorithms and take into account the wind power smoothing effect.

[0104] Furthermore, the candidate set for offshore wind farm site selection is generated based on the grid map, and the area between two given coordinates is gridded to obtain the candidate set.

[0105] Furthermore, the location of the offshore substation is established based on the optimal topology of wind turbines within the wind farm and the optimal topology between wind farms.

[0106] Furthermore, the wind farm internal wind turbine topology optimization model is built based on the wind farm internal wind turbine coordinates, capacity and output data; the inter-wind farm topology optimization model is built based on the wind farm coordinates, capacity and output data; the collaborative optimization model is built based on the wind farm internal wind turbine information and wind farm information.

[0107] A computer-readable storage medium, characterized in that the computer-readable storage medium stores one or more computer programs, which, when executed by one or more processors, implement the offshore substation site selection strategy considering wind turbine-wind farm collaborative optimization as described in any one of the above.

[0108] A strategy for offshore booster station site selection considering wind turbine-wind farm collaborative optimization, characterized in that it includes: wind turbine topology within the wind farm and topology between wind farms; wherein the wind turbine topology within the wind farm includes wind turbines and transmission lines, and the wind turbines are connected to the wind turbines or wind farms through the transmission lines; the topology between wind farms includes wind farms, transmission lines and offshore booster stations, and the wind farms are connected to the wind turbines, wind farms and offshore booster stations through transmission lines. When one or more of the computer programs are executed by one or more processors, the offshore booster station site selection method considering wind turbine-wind farm collaborative optimization as described in any one of the above items is implemented.

[0109] The above is only a preferred embodiment of the present invention. It should be understood that the present invention is not limited to the form disclosed herein, and should not be regarded as excluding other embodiments, but can be used in various other combinations, modifications and environments, and can be modified within the scope of the concept described herein through the above teachings or the technology or knowledge of the relevant field. The changes and modifications made by those skilled in the art shall not deviate from the spirit and scope of the present invention, and shall be within the scope of protection of the claims attached to the present invention.

Claims

1. A method for selecting an offshore substation site considering wind turbine-wind farm coordinated optimization, characterized in that: The steps include: Step 1: Obtain wind turbine capacity, wind turbine coordinates and output data inside the wind farm, wind farm capacity, coordinates and output data, power system transmission equipment information, target area transmission price and abandoned power compensation price, and offshore booster station site selection candidate set; Step 2: Generate the initial population of wind turbines based on the wind turbine capacity, wind turbine coordinates and wind turbine output data through the wind farm internal wind turbine topology optimization model, and calculate the net profit of each wind turbine. If the net profit of the wind turbine does not meet the termination criterion, generate a sub-population, perform crossover and mutation on the sub-population, and then calculate the net profit of each wind turbine. If the net profit of the wind turbine meets the termination criterion, obtain the optimal individual in the current population. Step 3: According to the wind farm coordinates and the optimal individual, the initial population of wind farms is generated through the wind turbine topology optimization model between wind farms, and the net income of each wind farm is calculated. If the net income of the wind farm does not meet the termination criterion, a sub-generation population of wind farms is generated, and the sub-generation population of wind farms is crossovered and mutated, and then the net income of each wind farm is calculated. If the net income of the wind farm meets the termination criterion, the optimal individual in the sub-generation population of wind farms after crossover and mutation is obtained, and the optimal topology of the wind turbine-wind farm double-layer system under the current offshore booster station site selection is determined; Step 4: For each candidate offshore substation site in the candidate set, the optimal topology of the wind turbine-wind farm double-layer system is calculated, and the topology with the largest net benefit is selected. The corresponding offshore substation site is the optimal site; The wind turbine topology optimization model between wind farms is established based on a genetic algorithm and combined with wind turbine topology optimization results within the wind farm and wind power smoothing effect.

2. The method for selecting an offshore substation site considering wind turbine-wind farm coordinated optimization according to claim 1, characterized in that: The candidate set for offshore booster station site selection is generated based on a grid map, and two regions with given coordinates are gridded to obtain a candidate set.

3. The method for selecting an offshore booster station site considering wind turbine-wind farm coordinated optimization according to claim 1, characterized in that: The wind turbine-wind farm double-layer system includes wind turbine topology inside the wind farm and topology between wind farms.

4. The method for selecting an offshore booster station site considering wind turbine-wind farm coordinated optimization according to claim 2, characterized in that: The wind farm internal wind turbine topology optimization model is built based on the wind farm internal wind turbine coordinates, wind turbine capacity and output data; the inter-wind farm topology optimization model is obtained based on the wind farm coordinates, wind farm capacity and output data.

5. An offshore booster station site selection system using an offshore booster station site selection method considering wind turbine-wind farm coordinated optimization as described in any one of claims 1 to 4, characterized in that: include: Wind farm internal wind turbine topology and inter-wind farm topology; The internal wind turbine topology of the wind farm includes wind turbines and transmission lines, and the wind turbines are connected to the wind turbines or wind farms through transmission lines; the inter-wind farm topology includes wind farms, transmission lines and offshore substations, and the wind farms are connected to wind turbines, wind farms and offshore substations through transmission lines.

Images