CN112487659B - Optimal design method and system for offshore wind farm current collection system - Google Patents
Optimal design method and system for offshore wind farm current collection system Download PDFInfo
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Abstract
The invention discloses an optimization design method and an optimization design system for an offshore wind farm power collection system, wherein the method respectively adopts a centralized offshore booster station optimization mode and an offshore light booster station optimization mode, topology optimization is carried out on the power collection system according to voltage grades, topology optimization results corresponding to the voltage grades in the optimization modes are obtained and serve as an alternative scheme, multi-party game evaluation optimization is carried out on the alternative scheme, and optimization results are output.
Description
The technical field is as follows:
the invention relates to the field of optimization of a current collection system of a marine step-up transformer substation, in particular to an optimization design method and system of a current collection system of an offshore wind farm.
Background art:
with the development of offshore wind power generation in recent years, the development of offshore wind power is gradually developing to large capacity and long distance from the current situation of global offshore wind power development planning, so that the optimization of an offshore wind farm electrical system is more important. In an electrical system of an offshore wind farm, an offshore boost substation (offset substation) is used as a connection hub of an offshore wind farm and an onshore power grid, bears a voltage conversion task with optimal efficiency, and is an important component of offshore wind power development.
The electrical system of an offshore wind farm is used to collect the power of the wind farm and to deliver it to a land-based network. Currently, some expert scholars have studied the electrical system of offshore wind farms. Hou P et al published on Wind Energy, entitled over Optimization for offset Wind Farm electric System, and used a fuzzy C-means algorithm (FCM algorithm) to partition a large Offshore Wind Farm, and then selected the clustering center of each partition as the installation position of the Offshore substation. Chou C-J et al published a comprehensive Evaluation of the HVDC and HVAC Links Integrated in a Large offset Wind Farm-An Actual Case Study in Taiwan power transmission systems from Offshore Wind power to the Penghumu transformer substation to Taiwan land transformer substations in IEEE Transactions on Industry Applications, and considered factors such as charging current, overload, overvoltage, etc. Joke et al used FCM-based particle swarm optimization for substation site selection in the reactive power planning of urban medium-voltage distribution networks, and overcome the problem that initial clusters in the FCM have a large influence on the clustering center.
However, in the above studies, the electrical design of offshore wind farms was based on centralized offshore substations. Centralized substations have the same functionality as onshore substations, but are more costly to use in offshore wind farms. With the increase of the scale of an offshore wind farm and the distance from the sea, the capacity, the volume and the weight of a transformer substation are continuously increased, the hoisting difficulty is further improved and far exceeds the bearing weight of a single crane ship, and great challenges are brought to installation and construction.
The invention content is as follows:
in order to solve the problems in the prior art, the invention provides an optimal design method and an optimal design system for an offshore wind farm power collection system.
The technical scheme of the invention is as follows:
an optimal design method for an offshore wind farm power collection system comprises the following specific steps:
1) acquiring initial data of an offshore wind farm; the initial data comprises offshore wind turbine coordinates, onshore booster station coordinates, submarine cables and transformer data;
2) respectively adopting a centralized offshore booster station optimization mode and an offshore light booster station optimization mode, carrying out topology optimization on the current collection system according to the initial data and the voltage grades, and obtaining topology optimization results corresponding to the voltage grades in the optimization modes as alternative schemes;
3) and carrying out multi-party game evaluation optimization on the alternative scheme, and outputting an optimization result.
Preferably, the voltage class comprises 35kV, 66 kV.
Preferably, the multiparty gambling evaluation optimization comprises:
based on Nash's theorem, the total life cycle cost of the current collection system is used as an economic evaluation index, the whole radiation influence range of the wind power plant is used as a first-class environment evaluation index, the submarine resource area occupied by laying the submarine cable is used as a second-class environment rating index, and the available capacity of the wind power plant is used as a reliability evaluation index, an optimization system is formed, a current collection system combined game optimization model is solved, a payment function and the weight occupied by each evaluation index are determined, the alternative scheme is evaluated, and the optimal scheme is obtained.
Preferably, the objective function of the current collection system combined game optimization model is as follows:
minC＝(C o +C M +C F )×P V.sum +C I +C D ×P V
the constraint conditions are as follows:
s.t.I sfc.max ≤min{K sfc I sfc·o }
wherein C is the total life cycle cost of the current collection system; v is the overall radiation influence range of the current collection system and adopts the volume; c o The operation loss of the submarine cable and the transformer; c M For maintenance costs; c F Loss due to power failure; p V.sum The current value and the conversion coefficient of annual investment charge; p is V Is a discount coefficient; c I Initial investment cost; c D For recovery costs; s, f and c respectively refer to the distances of the submarine cable on an x axis, a y axis and a z axis on a space coordinate system; n is a radical of s 、N sf 、N sfc The distance from the cut-off on the x axis, the y axis and the z axis of the space coordinate system to the magnetic induction intensity of less than 100 mu T; s sfc For the purpose of exceeding the control limit of 100 μ T in the influence range of the magnetic induction of the cable section under the condition of maximum continuous load currentCross-sectional area; l is sfc The length of the section of submarine cable; i is sfc.max For the maximum continuous load current flowing through the section of sea cable, I sfc.0 For long-term current-carrying capacity, K, of the sea cable sfc The integral correction coefficient of the current-carrying capacity is allowed for the section of submarine cable for a long time; s sfc.min Minimum cross-section allowed for the section of submarine cable to meet short-circuit thermal stability criteria, I sfc.∞ Is steady-state short-circuit current t when the sea cable is short-circuited sfc Is the length of short-circuit fault of the submarine cable in the section C sfc.r The thermal stability factor of the section of sea cable is obtained.
Preferably, the objective function for evaluating the alternatives is:
in the formula: x is the number of l Is an effective strategy set Z based on alternative l l 1, 2, where m is the number of alternatives; a is l Is the coefficient corresponding to alternative l.
Preferably, the optimization process of the offshore light booster station optimization mode in the step 2) comprises the following steps:
2.1) determining the fan coordinate of the light booster station by adopting a k-medoids clustering algorithm according to the following method:
2.1.1) determining the number k of light booster stations and the coordinates of fans to be clustered;
2.1.2) determining k initial clustering centers by adopting a random selection method, wherein the k initial clustering centers are used as the fan coordinates of the light booster station;
2.1.3) clustering according to a nearest principle, sequentially calculating the distance from each fan to be clustered to k light booster stations, respectively calculating the distances from the fans to be clustered except the light booster stations to all the light booster stations according to the principle that the fan is closest to the k light booster stations, selecting the fan with the smallest distance to the light booster stations, classifying the fan into one class, and then selecting the fan with the smallest distance to the light booster stationsCalculating the total distance from all the fans to be clustered to each light booster station, wherein the total distance D corresponding to the ith light booster station Ti Comprises the following steps:
D Ti ＝k 1 D Hi +k 2 D Mi
wherein D is Ti The total distance is the sum of the total distance from the ith light booster station to the onshore booster station and the total distance between the ith light booster station and the jth fan to be clustered; k is a radical of 1 、k 2 The price coefficients of the medium-pressure submarine cable and the high-pressure submarine cable are respectively; d Hi The total distance from the ith light booster station to the onshore booster station; d Mi The total distance between the ith light booster station and the jth fan to be clustered is calculated; d i s2land The distance between the ith light booster station and the onshore booster station is defined, and k is the number of the light booster stations; d ij WT2s The distance from the jth fan to be clustered in the ith cluster to the ith light booster station coordinate is calculated; j is 1, 2, and p is the total number of fans to be clustered in the ith cluster;
2.1.4) re-determining k clustering centers;
2.1.5) repeating 2.1.3) -2.1.4), comparing the total distance corresponding to each light booster station fan, and determining the cluster center coordinate at the minimum value as the light booster station fan coordinate;
2.2) based on the light booster station fan coordinate, solving the topological structure of the current collection system by using a single parent genetic algorithm, wherein the objective function and the constraint condition of the single parent genetic algorithm are respectively as follows:
an objective function:
constraint conditions are as follows:
x ij 0 or 1, j 0,1 i
Wherein x is ij Is the on-off coefficient, x, between the ith light booster station and the jth fan in the ith cluster ij When 1, x ij Indicating that the ith light booster station and the jth fan in the ith cluster are connected in series, x ij When 0, x ij Indicating that the ith light booster station and the jth fan in the ith cluster are not connected in series d ij The distance between the ith light booster station and j fans in the ith cluster is calculated; and z is the length of a single loop cable, and when z reaches the minimum, the topological graph of the current collection system is obtained.
Preferably, the number k of the light booster stations in step 2.1) is obtained by an enumeration method.
An offshore wind farm power collection system optimal design system, comprising:
the data acquisition module is used for acquiring initial data of the offshore wind farm; the initial data comprises offshore wind turbine coordinates, onshore booster station coordinates, submarine cables and transformer data;
the alternative scheme module is used for performing topology optimization on the current collection system according to the voltage grades according to the initial data by adopting a centralized offshore booster station optimization mode and an offshore light booster station optimization mode respectively, acquiring topology optimization results corresponding to the voltage grades in the optimization modes, and taking the topology optimization results as alternative schemes;
and the game evaluation optimization module is used for carrying out multi-party game evaluation optimization on the alternative schemes and outputting an optimization result.
Compared with the prior art, the invention has the following beneficial effects
The invention provides an optimization design method and an optimization design system for an offshore wind farm power collection system, wherein the method respectively adopts a centralized offshore booster station optimization mode and an offshore light booster station optimization mode, topology optimization is carried out on the power collection system according to voltage grades, topology optimization results corresponding to the voltage grades in the optimization modes are obtained and serve as an alternative scheme, multi-party game evaluation optimization is carried out on the alternative scheme, and optimization results are output.
Description of the drawings:
FIG. 1 is a flow chart of the calculation of the k-medoids algorithm;
FIG. 2 is a flow chart of the current collection system joint game optimization;
FIG. 3 is a schematic diagram of the wind turbine of the offshore wind farm and the location of a onshore grid connection point in the embodiment;
fig. 4 is an optimization result of the current collection system in the optimization mode of the conventional centralized offshore booster station; wherein, (a) is a schematic diagram of a ring topology structure of 66kV submarine cable connection, and (b) is a schematic diagram of a ring topology structure of 35kV submarine cable connection;
FIG. 5 shows the optimized result of the current collection system in the optimized mode of the offshore light booster station; wherein, (a) is a schematic diagram of a ring topology structure of 66kV submarine cable connection, and (b) is a schematic diagram of a ring topology structure of 35kV submarine cable connection.
The specific implementation mode is as follows:
the invention is further described with reference to specific embodiments and corresponding figures.
The first embodiment is as follows:
an optimal design method for an offshore wind farm power collection system is shown in fig. 1 and 2, and comprises the following specific steps:
1) acquiring initial data of an offshore wind farm; the initial data comprises offshore wind turbine coordinates, onshore booster station coordinates, submarine cables and transformer data; the submarine cable and transformer data specifically comprise the purchase and laying cost of a submarine cable, the purchase and installation cost of a transformer and the purchase and laying cost of a spare submarine cable interconnected between light booster stations, the reconstruction cost of a fan foundation occupied by the light booster stations, the maintenance cost and the like, the power failure loss, the operation loss of the submarine cable and the transformer, the capacity of the offshore booster stations, the total installed capacity of a wind power plant, the maximum continuous load current and the long-term current carrying capacity flowing through the submarine cable, the overall correction coefficient of the current carrying capacity allowed by the submarine cable for a long time, the minimum section allowed by the submarine cable meeting the short-circuit thermal stability standard, the stable short-circuit current and short-circuit fault of the submarine cable are long, and the thermal stability coefficient of the submarine cable.
2) Respectively adopting an optimization mode of a centralized offshore booster station and an optimization mode of a light offshore booster station, carrying out topology optimization on the current collection system according to the initial data and the voltage grades of 35kV and 66kV, obtaining topology optimization results corresponding to the voltage grades of 35kV and 66kV in each optimization mode, and using the topology optimization results as alternative schemes;
the optimization process of the optimization mode of the offshore light booster station comprises the following steps:
2.1) determining the fan coordinate of the light booster station by adopting a k-medoids clustering algorithm according to the following method:
2.1.1) determining the number k of light booster stations and the coordinates of fans to be clustered; in this example, the number k of the light booster stations is obtained by an enumeration method.
2.1.2) determining k initial clustering centers by adopting a random selection method, wherein the k initial clustering centers are used as the fan coordinates of the light booster station;
2.1.3) clustering according to a nearest principle, sequentially calculating the distance from each fan to be clustered to k light booster stations, respectively calculating the distances from the fans to be clustered except the light booster stations to all the light booster stations according to the principle that the fan is closest to the k light booster stations, selecting the fan to be clustered to have the smallest distance to the light booster stations, classifying the fan to be clustered into one class, and calculating the total distance from all the fans to be clustered to each light booster station, wherein the total distance D corresponding to the ith light booster station is the total distance D corresponding to the ith light booster station Ti Comprises the following steps:
D Ti ＝k 1 D Hi +k 2 D Mi
wherein D is Ti The total distance is the sum of the total distance from the ith light booster station to the onshore booster station and the total distance between the ith light booster station and the jth fan to be clustered; k is a radical of 1 、k 2 The price coefficients of the medium-pressure submarine cable and the high-pressure submarine cable are respectively; d Hi The total distance from the ith light booster station to the onshore booster station (the cable used for the distance is a high-voltage cable); d Mi The total distance between the ith light booster station and the jth fan to be clustered (the cable used in the distance is a medium-voltage cable); d i s2land The distance between the ith light booster station and the onshore booster station is defined, and k is the number of the light booster stations; d ij WT2s The distance from the jth fan to be clustered in the ith cluster to the ith light booster station coordinate is calculated; j is 1, 2, and p is the total number of fans to be clustered in the ith cluster;
2.1.4) re-determining k clustering centers;
2.1.5) repeating 2.1.3) -2.1.4), comparing the total distance corresponding to each light booster station fan, and determining the cluster center coordinate at the minimum value as the light booster station fan coordinate;
2.2) based on the light booster station fan coordinate, solving the topological structure of the current collection system by using a single parent genetic algorithm, wherein the objective function and the constraint condition of the single parent genetic algorithm are respectively as follows:
an objective function:
constraint conditions are as follows:
x ij 0 or 1, j 0,1 i
Wherein x is ij Is the on-off coefficient, x, between the ith light booster station and the jth fan in the ith cluster ij When 1, x ij Indicating that the ith light booster station and the jth fan in the ith cluster are connected in series, x ij When 0, x ij Indicating that the ith light booster station and the jth fan in the ith cluster are not connected in series d ij The distance between the ith light booster station and j fans in the ith cluster is calculated; and z is the length of a single loop cable, and when z reaches the minimum, the topological graph of the current collection system is obtained.
3) And carrying out multi-party game evaluation optimization on the alternative scheme, and outputting an optimization result. Wherein the multi-party game evaluation optimization comprises the following steps:
based on Nash's theorem, the total life cycle cost of the current collection system is used as an economic evaluation index, the whole radiation influence range of the wind power plant is used as a first-class environment evaluation index, the submarine resource area occupied by laying the submarine cable is used as a second-class environment rating index, and the available capacity of the wind power plant is used as a reliability evaluation index, an optimization system is formed, a current collection system combined game optimization model is solved, a payment function and the weight occupied by each evaluation index are determined, the alternative scheme is evaluated, and the optimal scheme is obtained.
The objective function of the current collection system combined game optimization model is as follows:
minC＝(C o +C M +C F )×P V.sum +C I +C D ×P V
the constraint conditions are as follows:
s.t.I sfc.max ≤min{K sfc I sfc·o }
wherein C is the total life cycle cost of the current collection system; v is the overall radiation influence range of the current collection system and adopts the volume; c o The running loss of the submarine cable and the transformer; c M For maintenance costs; c F Loss due to power failure; p V.sum The current value and the conversion coefficient of annual investment charge; p V Is a discount coefficient; c I Initial investment cost; c D For recovery costs; s, f and c respectively refer to the distances of the submarine cable on an x axis, a y axis and a z axis on a space coordinate system; n is a radical of s 、N sf 、N sfc The distance from the cut-off on the x axis, the y axis and the z axis of the space coordinate system to the magnetic induction intensity of less than 100 mu T; s sfc The cross-sectional area of the influence range of the magnetic induction intensity of the section of the cable exceeding the control limit value of 100 mu T under the condition of the maximum continuous load current; l is sfc The length of the section of submarine cable; i is sfc.max For the maximum continuous load current flowing through the section of sea cable, I sfc.0 Is the long-term current-carrying capacity, K, of the submarine cable of the section sfc The integral correction coefficient of the current-carrying capacity is allowed for the section of submarine cable for a long time; s sfc.min Minimum cross-section allowed for the section of submarine cable to meet short-circuit thermal stability criteria, I sfc.∞ Is steady-state short-circuit current t when the sea cable is short-circuited sfc Is the length of short-circuit fault of the submarine cable in the section C sfc.r The thermal stability factor of the section of sea cable is obtained.
The objective function for evaluating the alternatives is as follows:
in the formula: x is the number of l Set of effective policies Z based on alternative l l 1, 2, where m is the number of alternatives; a is l As the coefficient corresponding to alternative l.
Example two:
an offshore wind farm power collection system optimal design system, comprising:
the data acquisition module is used for acquiring initial data of the offshore wind farm; the initial data comprises offshore wind turbine coordinates, onshore booster station coordinates, submarine cables and transformer data;
the alternative scheme module is used for performing topology optimization on the current collection system according to the voltage grades according to the initial data by adopting a centralized offshore booster station optimization mode and an offshore light booster station optimization mode respectively, acquiring topology optimization results corresponding to the voltage grades in the optimization modes, and taking the topology optimization results as alternative schemes;
and the game evaluation optimization module is used for carrying out multi-party game evaluation optimization on the alternative schemes and outputting an optimization result.
Example three:
in this example, taking a certain offshore wind farm with a capacity of 360MW in a certain sea area as an example, the optimal design method of the invention is adopted to optimally design the current collection system, and meanwhile, the voltage class optimization and the booster station type optimization are combined, and the influence of the light booster station and the traditional centralized booster station on the environment is contrastively analyzed. The wind power plant has 100 3.6MW wind driven generators, each coordinate and a land grid-connected point are shown in figure 3, a pentagram is the position of the land grid-connected point, and the distance from the land grid-connected point to the center of the wind power plant is about 50 km. The distance between the fans is about 900 meters. The medium-voltage submarine cable is divided into 35kV and 66kV in voltage class, and the high-voltage submarine cable is 220kV in voltage class. The failure rate of the submarine cable is 0.03 times/(km.a), and the repair time of the submarine cable is 1000 hours; the repair time of the submarine cable is 1000 hours. The failure rate of a main transformer of the offshore booster station is 0.01, the maintenance cost is about 80 ten thousand yuan, and the repair time is 200 h. The service life of the offshore wind farm is 25 years, and the average power of the offshore wind farm is 1.07 MW.
For ease of understanding, the centralized-based offshore booster station optimization mode is referred to herein as a legacy station mode; the marine-based light booster station optimization mode is referred to as a light station mode. The following schemes are adopted in the current collection system optimization considering the environmental influence: different voltage level optimizations (including 35kV and 66kV) were performed in the legacy station mode and in the lightweight station mode, respectively. The optimized topological structures of the specific schemes are respectively shown in fig. 4 and 5:
in order to more intuitively show the optimization results of various different schemes, the optimization results of the environment-friendly current collection system under different booster station modes and different voltage levels are summarized as shown in table 1:
table 1 summary of optimization results of environment-friendly power collection system in different booster station forms
The results of the different voltage class related optimizations in the light station mode are shown in tables 2 and 3:
TABLE 2 switching device number and cost at different voltage classes
| Submarine cable voltage class (kV) | Current collection network structure | Number of switch devices (table) | Cost (Wanyuan) |
| 35 | Ring shape | 32 | 1504 |
| 66 | Ring shape | 20 | 1240 |
TABLE 3 cost of the power collection system under different voltage classes (Wanyuan)
| Submarine cable voltage class (kV) | Initial investment cost | Cost of breakdown maintenance | Loss of power failure | Loss of network |
| 35 | 20856.19 | 12967.16 | 276.49 | 1015.56 |
| 66 | 18525.84 | 10041 | 399.2 | 2265.76 |
After the primary optimization of the current collection system of the offshore wind farm, the game theory based on Nash equilibrium is adopted to comprehensively evaluate 4 schemes to be selected, wherein the first scheme and the second scheme are respectively the conditions of selecting 35KV and 66KV voltage levels in the traditional station mode, and the third scheme and the fourth scheme are the conditions of selecting 35KV and 66KV voltage levels in the light station mode.
The strategy set of the game analysis is the above 4 alternatives. The main influence factors of the topological planning of the collecting system form a payment function U relative to the influence weight of the alternative scheme, the payment function U is used as a quantitative analysis entrance of game evaluation, the value ratio of the payment function U inherits the principle of respecting the actual engineering, and the payment function U can be adjusted according to the national policy and the weight required by the owner. In order to respond to the global strategy of sustainable development of ocean productivity, the future development of offshore wind power in China must fully consider the non-intermittent supply capacity of ocean resources, ensure the long-term bearing capacity of ecological environment, pay attention to the coordination of economy and environment, stand in the perspective of irreversible ecological destruction, mainly consider the balance requirement of ocean electromagnetic ecological environment, consider the economic cost and the reliability requirement of an owner side at the same time, comprehensively consider the weight ratio of setting economy, environment affinity and reliability to be 3:4:3, electromagnetic environment factors and seabed resource occupation factors in the environment affinity respectively account for two components, and each payment function takes the following values: the payment function value of the analysis system is 100, the sum of the payment function values corresponding to the economic factor N1 is 30, and the payment function of each alternative scheme is inversely related to the economic cost based on the economic cost minimum principle; the sum of the payment function values corresponding to the electromagnetic environment factor N2 is 20, and the payment function of each scheme is inversely related to the radiation range on the basis of the minimum principle of the radiation range; the sum of the corresponding payment function values of the submarine resource occupation factor N3 is 20, and based on the minimum submarine resource occupation principle, the payment functions of all the schemes are negatively related to the total length of the submarine cable; the sum of the payment function values corresponding to the reliability factor N4 is 30, and the payment function of each scheme is positively correlated with the average annual available capacity based on the highest reliability principle.
In summary, the final model description is shown in table 4:
TABLE 4 topology optimization Game model description of Electrical Collection System
Converting the model into a linear programming problem:
minx 1 +x 2 +x 3 +x 4
solving by a primal-dual path tracking algorithm, wherein the game result is as follows: x is the number of 1 ＝7.5×10 -8 ，x 2 ＝0.0043，x 3 ＝7.3×10 -10 ，x 4 ＝0.1273。
The scheme four with higher probability is the best scheme, and the scheme is the second time. Through the primary optimization and the secondary game analysis considering the electromagnetic environment constraint, the following steps are known:
(1) the current collection system cost in the light station mode is significantly lower than the conventional station mode at the same voltage class in terms of life cycle cost. The economy of the light station mode under the 66kV voltage level is optimal, which is about 85.57 percent of that of the traditional station mode under the 35kV voltage level, and the cost difference is nearly 5264 ten thousand yuan;
(2) in terms of environmental friendliness, the electromagnetic radiation influence range of the light station mode under the 66KV voltage level is the smallest and is only 85.8% of that of the traditional station mode under the same voltage level; in addition, the submarine cable under the 66KV voltage level also occupies less submarine resources, and has remarkable advantages compared with the traditional 35KV cable.
(3) In the aspect of reliability related to the operation period, under the same booster station mode, the average level of the available capacity of the power collection system under the 66KV voltage level is higher than 35KV, and it can be seen that the adoption of 66KV as the standard voltage level of the power collection system has certain reliability advantage. In addition, the average annual available capacity in the light station mode is obviously lower than that in the traditional station mode, which shows that the reliability problem of the light booster station is more prominent, and further research and improvement are needed to improve the operation reliability.
From the comprehensive analysis, the mode and the voltage grade of the booster station are optimized simultaneously, the environment affinity of the current collecting system of the offshore wind farm can be obviously improved, and the life cycle cost is reduced. The environmental impact of the light station versus the concentration station was analyzed as follows:
(1) the total length of the medium-voltage submarine cables required by the topological optimization of the current collection system based on the light station is obviously smaller than that of a traditional station mode, submarine resources occupied by submarine cable laying channels are reduced, damage of a current collection network to the submarine ecological environment is reduced to a certain extent, and the method comprises the aspects of influences of initial ditching laying on inherent animals and plants in the seabed, heating caused by later-stage submarine cable operation, electromagnetic interference and the like.
(2) The power collection system optimization of the light station mode also has certain advantages in the aspect of electromagnetic environment interference, and the overall magnetic interference range has about 15% of advantages compared with the traditional station mode.
(3) As for the self characteristics of different booster stations, the light booster station and the fan share the foundation, so that a huge booster station foundation does not need to be specially built in the construction and construction stage of the offshore wind farm, the construction noise, suspended sediment, transportation and emission pollution and the like are greatly reduced, and the occupation of seabed resources is reduced.
The data result analysis verifies the accuracy and feasibility of the game evaluation method to a certain extent. Therefore, based on the strategic position of sustainable development of marine environment, the scheme of adopting 66kV as the voltage grade of the current collection system in the mode of adopting the light booster station has obvious economic, environmental protection and technical comprehensive benefits compared with other schemes.
Claims (7)
1. An optimal design method for an offshore wind farm current collection system is characterized by comprising the following steps: the method comprises the following specific steps:
1) acquiring initial data of an offshore wind farm; the initial data comprises offshore wind turbine coordinates, onshore booster station coordinates, submarine cables and transformer data;
2) respectively adopting a centralized offshore booster station optimization mode and an offshore light booster station optimization mode, carrying out topology optimization on the current collection system according to the initial data and the voltage grades, and obtaining topology optimization results corresponding to the voltage grades in the optimization modes as alternative schemes;
the optimization process of the offshore light booster station optimization mode comprises the following steps:
2.1) determining the fan coordinate of the light booster station by adopting a k-medoids clustering algorithm according to the following method:
2.1.1) determining the number k of light booster stations and the coordinates of fans to be clustered;
2.1.2) determining k initial clustering centers by adopting a random selection method, wherein the k initial clustering centers are used as the fan coordinates of the light booster station;
2.1.3) clustering according to a nearest principle, sequentially calculating the distance from each fan to be clustered to k light booster stations, respectively calculating the distances from the fans to be clustered except the light booster stations to all the light booster stations according to the principle that the fan is closest to the k light booster stations, selecting the fan to be clustered to have the smallest distance to the light booster stations, classifying the fan to be clustered into one class, and calculating the total distance from all the fans to be clustered to each light booster station, wherein the total distance D corresponding to the ith light booster station is the total distance D corresponding to the ith light booster station Ti Comprises the following steps:
D Ti ＝k 1 D Hi +k 2 D Mi
wherein D is Ti The total distance is the sum of the total distance from the ith light booster station to the onshore booster station and the total distance between the ith light booster station and the jth fan to be clustered; k is a radical of 1 、k 2 The price coefficients of the medium-pressure submarine cable and the high-pressure submarine cable are respectively; d Hi The total distance from the ith light booster station to the onshore booster station; d Mi The total distance between the ith light booster station and the jth fan to be clustered is calculated; d i s2land The distance between the ith light booster station and the onshore booster station is defined, and k is the number of the light booster stations; d ij WT2s The distance from the jth fan to be clustered in the ith cluster to the ith light booster station coordinate is calculated; j is 1, 2, and p is the total number of fans to be clustered in the ith cluster;
2.1.4) re-determining k clustering centers;
2.1.5) repeating 2.1.3) -2.1.4), comparing the total distance corresponding to each light booster station fan, and determining the cluster center coordinate at the minimum value as the light booster station fan coordinate;
2.2) based on the light booster station fan coordinate, solving the topological structure of the current collection system by using a single parent genetic algorithm, wherein the objective function and the constraint condition of the single parent genetic algorithm are respectively as follows:
an objective function:
constraint conditions are as follows:
x ij 0 or 1, j 0,1 i
Wherein x is ij Is the on-off coefficient, x, between the ith light booster station and the jth fan in the ith cluster ij When 1, x ij Indicating that the ith light booster station and the jth fan in the ith cluster are connected in series, x ij When 0, x ij D represents that the ith light booster station and the jth fan in the ith cluster are not connected in series ij The distance between the ith light booster station and j fans in the ith cluster is calculated; z is the length of a single loop cable, and when z reaches the minimum, a topological graph of the current collection system is obtained;
3) and carrying out multi-party game evaluation optimization on the alternative scheme, and outputting an optimization result.
2. The method for optimally designing the current collection system of the offshore wind farm according to claim 1, characterized in that: the voltage class comprises 35kV and 66 kV.
3. The method for optimally designing the current collection system of the offshore wind farm according to claim 1, characterized in that: the multi-party gambling evaluation optimization comprises the following steps:
based on Nash's theorem, the total life cycle cost of the current collection system is used as an economic evaluation index, the whole radiation influence range of the wind power plant is used as a first-class environment evaluation index, the submarine resource area occupied by laying the submarine cable is used as a second-class environment rating index, and the available capacity of the wind power plant is used as a reliability evaluation index, an optimization system is formed, a current collection system combined game optimization model is solved, a payment function and the weight occupied by each evaluation index are determined, the alternative scheme is evaluated, and the optimal scheme is obtained.
4. The method of claim 3, wherein the method comprises: the objective function of the current collection system combined game optimization model is as follows:
minC＝(C o +C M +C F )×P V.sum +C I +C D ×P V
the constraint conditions are as follows:
s.t.I sfc.max ≤min{K sfc I sfc·o }
wherein C is the total life cycle cost of the current collection system; v is the overall radiation influence range of the current collection system and adopts the volume; c o The running loss of the submarine cable and the transformer; c M For maintenance costs; c F Loss due to power failure; p V.sum The current value and the conversion coefficient of annual investment charge; p V Is a discount coefficient; c I Initial investment cost; c D For recovery costs; s, f and c respectively refer to the distances of the submarine cable on an x axis, a y axis and a z axis on a space coordinate system; n is a radical of s 、N sf 、N sfc The distance from the cut-off on the x axis, the y axis and the z axis of the space coordinate system to the magnetic induction intensity of less than 100 mu T; s sfc The cross section area of the influence range of the magnetic induction intensity of the cable exceeding the control limit value of 100 mu T under the condition of the maximum continuous load current; l is sfc Is the length of the sea cable; i is sfc.max Maximum continuous load current for the sea cable to flow, I sfc.0 For long-term current-carrying capacity of submarine cable, K sfc The integral correction coefficient of the current-carrying capacity is allowed for the submarine cable for a long time; s sfc.min Minimum cross-section allowed for submarine cable to meet short-circuit thermal stability criteria, I sfc.∞ Is steady-state short-circuit current t during short-circuit of sea cable sfc Duration of short-circuit fault of submarine cable, C sfc.r The thermal stability factor of the sea cable.
5. The method of claim 3, wherein the method comprises: the objective function for evaluating the alternative is as follows:
x l ≥0,l＝1～m
in the formula: x is the number of l Is an effective strategy set Z based on alternative l l 1, 2, where m is the number of alternatives; a is l Is the coefficient corresponding to alternative l.
6. The method of claim 5, wherein the method comprises: the number k of the light booster stations in the step 2.1) is obtained by an enumeration method.
7. The utility model provides an offshore wind farm current collection system optimal design system which characterized in that: the method comprises the following steps:
the data acquisition module is used for acquiring initial data of the offshore wind farm; the initial data comprises offshore wind turbine coordinates, onshore booster station coordinates, submarine cables and transformer data;
the alternative scheme determining module is used for performing topology optimization on the current collection system according to the voltage grades according to the initial data by respectively adopting a centralized offshore booster station optimization mode and an offshore light booster station optimization mode, acquiring topology optimization results corresponding to the voltage grades in the optimization modes and taking the topology optimization results as alternative schemes;
the optimization process of the offshore light booster station optimization mode comprises the following steps:
2.1) determining the fan coordinate of the light booster station by adopting a k-medoids clustering algorithm according to the following method:
2.1.1) determining the number k of light booster stations and the coordinates of fans to be clustered;
2.1.2) determining k initial clustering centers by adopting a random selection method, wherein the k initial clustering centers are used as the fan coordinates of the light booster station;
2.1.3) clustering according to a nearest principle, sequentially calculating the distance from each fan to be clustered to k light booster stations, respectively calculating the distances from the fans to be clustered except the light booster stations to all the light booster stations according to the principle that the fan is closest to the k light booster stations, selecting the fan to be clustered to have the smallest distance to the light booster stations, classifying the fan to be clustered into one class, and calculating the total distance from all the fans to be clustered to each light booster station, wherein the total distance D corresponding to the ith light booster station is the total distance D corresponding to the ith light booster station Ti Comprises the following steps:
D Ti ＝k 1 D Hi +k 2 D Mi
wherein D is Ti Is the ith lightThe total distance corresponding to the booster station is the sum of the total distance from the ith light booster station to the onshore booster station and the total distance between the ith light booster station and the jth fan to be clustered; k is a radical of 1 、k 2 The price coefficients of the medium-pressure submarine cable and the high-pressure submarine cable are respectively; d Hi The total distance from the ith light booster station to the onshore booster station; d Mi The total distance between the ith light booster station and the jth fan to be clustered is calculated; d i s2land The distance between the ith light booster station and the onshore booster station is defined, and k is the number of the light booster stations; d is a radical of ij WT2s The distance from the jth fan to be clustered in the ith cluster to the ith light booster station coordinate is calculated; j is 1, 2, p is the total number of the fans to be clustered in the ith cluster;
2.1.4) re-determining k clustering centers;
2.1.5) repeating 2.1.3) -2.1.4), comparing the total distance corresponding to each light booster station fan, and determining the cluster center coordinate at the minimum value as the light booster station fan coordinate;
2.2) based on the light booster station fan coordinate, solving the topological structure of the current collection system by using a single parent genetic algorithm, wherein the objective function and the constraint condition of the single parent genetic algorithm are respectively as follows:
an objective function:
constraint conditions are as follows:
x ij 0 or 1, j 0,1 i
Wherein x is ij Is the on-off coefficient, x, between the ith light booster station and the jth fan in the ith cluster ij When 1, x ij Represents the ithThe light booster station and the jth fan in the ith cluster are connected in series, and x ij When 0, x ij Indicating that the ith light booster station and the jth fan in the ith cluster are not connected in series d ij The distance between the ith light booster station and j fans in the ith cluster is calculated; z is the length of a single loop cable, and when z reaches the minimum, a topological graph of the current collection system is obtained;
and the game evaluation optimization module is used for carrying out multi-party game evaluation optimization on the alternative schemes and outputting an optimization result.
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| CN113408825A (en) * | 2021-07-15 | 2021-09-17 | 西安热工研究院有限公司 | Firefly algorithm based offshore booster station site selection method |
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| CN114186488A (en) | 2021-12-06 | 2022-03-15 | 国网福建省电力有限公司经济技术研究院 | Topological structure optimization method and system for large-scale offshore wind farm current collection system |
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| CN115936319A (en) * | 2022-12-30 | 2023-04-07 | 清华大学深圳国际研究生院 | Reliability evaluation and planning method for offshore wind farm current collection system |
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| CN116976153B (en) * | 2023-09-25 | 2024-03-22 | 电子科技大学中山学院 | Marine wind farm booster station site selection method based on integrated model |
| CN117349999B (en) * | 2023-12-04 | 2024-03-08 | 中国电建集团河北省电力勘测设计研究院有限公司 | Marine wind farm submarine cable comprehensive topological structure optimizing method and storage medium |
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