CN117876030A  Coordination planning method for offshore wind farm units and power collecting network  Google Patents
Coordination planning method for offshore wind farm units and power collecting network Download PDFInfo
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Abstract
The invention discloses a coordination planning method for an offshore wind farm unit and a power collecting network, which comprises the following steps: according to the actual topological connection condition of the existing offshore wind farm, setting a plurality of wind turbine generator set tobeselected nodes and an offshore boosting platform node, and constructing a coordinated planning model of the offshore wind farm generator set and a power collecting network by considering the wake effect of the multiwind direction scene; and solving the coordination planning model of the offshore wind farm unit and the power collecting network by adopting a broken line processing intersection avoidance algorithm to obtain a coordination planning result. The invention provides wake loss factors in the model to describe multiwinddirection scenes, so that the wake model is more fit with the actual situation; and the traditional intersection avoidance constraint is replaced by adopting an algorithm for processing the intersection avoidance of the cable by using the broken line in the model, so that the solving efficiency of the model is improved.
Description
Technical Field
The invention relates to an optimization planning technology, in particular to a coordinated planning method for offshore wind farm units and a power collecting network.
Background
At present, the existing method for optimizing and planning the offshore wind farm units and the collector network mainly researches the topological connection of the offshore wind farm units and the collector network cable as two independent problems. For site selection optimization of the wind turbine, the main method at present comprises mathematical optimization technologies such as mixed integer programming, nonlinear programming, sequence convex programming and the like, and heuristic optimization technologies such as genetic algorithm, random search algorithm and the like; for optimization planning of the collecting network, the main mathematical planning methods at present comprise integer quadratic programming, mixed integer linear programming and sequential optimization, and heuristic algorithms comprise particle swarm algorithm, genetic algorithm, monte Carlo method and the like. In addition, wake models commonly used at present for wake loss calculation of the offshore wind turbine generator comprise a Jensen model, an Ainslie model, a G.C.Larsen model and the like.
The existing optimization planning method for the offshore wind farm units and the collection network mainly has the following technical defects:
(1) In most cases, the offshore wind farm is divided into two problems of wind turbine group site selection and power collection network cable topological connection to conduct optimization planning respectively, the mutual correlation and influence of the two problems are not considered, and the finally obtained optimization result is not an optimal solution.
(2) For calculation of wake effects among offshore wind turbines, most of current researches only consider single wind direction scenes, and do not consider multiwind direction scenes which are closer to actual environments.
(3) In solving the topological connection model of the current collecting network cable, the cable intersection is usually limited by adopting intersection avoidance constraint, but the constraint condition has higher complexity, and when the scale of the offshore wind power plant is continuously increased, the time required for solving the optimization model is longer
Disclosure of Invention
In order to solve at least one technical problem existing in the background technology, the invention provides a coordinated planning method for an offshore wind farm unit and a collector network.
In order to achieve the above purpose, the technical scheme of the invention is as follows:
a coordinated planning method for offshore wind farm units and a centralized network, the method comprising:
according to the actual topological connection condition of the existing offshore wind farm, setting a plurality of wind turbine generator set tobeselected nodes and an offshore boosting platform node, and constructing a coordinated planning model of the offshore wind farm generator set and a power collecting network by considering the wake effect of the multiwind direction scene;
and solving the coordination planning model of the offshore wind farm unit and the power collecting network by adopting a broken line processing intersection avoidance algorithm to obtain a coordination planning result.
Compared with the prior art, the invention has the beneficial effects that:
according to the coordination optimization planning model of the offshore wind turbine and the power collecting network, a plurality of wind turbine tobeselected nodes and an offshore boosting platform node are set according to the actual topological connection condition of the existing offshore wind turbine, and the site selection combination of the plurality of wind turbines in the offshore wind turbine, the radial submarine cable topological connection of the power collecting system and the transformer combination in the offshore boosting platform are optimized under the consideration of the wake effect of the multiwinddirection scene, so that annual equivalent income of the offshore wind turbine is maximum. The wake loss factors are put forward in the model to describe multiwinddirection scenes, so that the wake model is more fit with the actual situation; and the traditional intersection avoidance constraint is replaced by adopting an algorithm for processing the intersection avoidance of the cable by using the broken line in the model, so that the solving efficiency of the model is improved.
Drawings
FIG. 1 is a flow chart of a coordinated planning method for offshore wind farm units and a centralized network provided by an embodiment of the invention;
FIG. 2 is a schematic illustration of a Jensen wake model;
FIG. 3 is a schematic diagram of a multiwind wake region;
FIG. 4 is a schematic diagram of a connected branchtype polyline;
FIG. 5 is a schematic view of leaf node polylines;
FIG. 6 is a graph of actual node distribution of an offshore wind farm;
FIG. 7 is a plot of the distribution of candidate mounting points for an optimization model;
FIG. 8 is an actual topology of an offshore wind farm;
FIG. 9 is a topology diagram of a conventional optimization result;
FIG. 10 is a topology diagram of an optimization result using a polyline processing intersection avoidance algorithm.
Detailed Description
Examples:
the technical scheme of the invention is further described below with reference to the accompanying drawings and examples.
Referring to fig. 1, the coordinated planning method for the offshore wind farm unit and the collector network provided by the embodiment mainly includes the following steps:
according to the actual topological connection condition of the existing offshore wind farm, setting a plurality of wind turbine generator set tobeselected nodes and an offshore boosting platform node, and constructing a coordinated planning model of the offshore wind farm generator set and a power collecting network by considering the wake effect of the multiwind direction scene;
and solving the coordination planning model of the offshore wind farm unit and the power collecting network by adopting a broken line processing intersection avoidance algorithm to obtain a coordination planning result.
Therefore, the coordination optimization planning model of the offshore wind turbine and the collector network established by the method is used for setting a plurality of nodes to be selected of the wind turbine and a node of an offshore boosting platform according to the actual topological connection condition of the existing offshore wind farm, and optimizing to obtain the site selection combination of the plurality of types of wind turbines in the offshore wind farm, the topological connection of the radial submarine cable of the collector system and the transformer combination in the offshore boosting platform under the consideration of the wake effect of the multiwinddirection scene, so that the annual equivalent income of the offshore wind farm is maximum. The wake loss factors are put forward in the model to describe multiwinddirection scenes, so that the wake model is more fit with the actual situation; and the traditional intersection avoidance constraint is replaced by adopting an algorithm for processing the intersection avoidance of the cable by using the broken line in the model, so that the solving efficiency of the model is improved.
In a specific embodiment, the wake effect considering the multiwind scenario includes:
when wind energy passes through the offshore wind turbine, a part of kinetic energy is transferred from wind to a rotor of the wind turbine to be converted into electric energy, meanwhile, blades of the fan have a certain blocking effect on wind speed, so that the emitted power of the wind turbine in a downstream area is reduced, and a Jensen model is used for describing wake effect:
wherein: lambda (lambda) _{i,j,t} The wake attenuation coefficient is used for representing the wake influence degree of a tmodel fan i on a fan j; d (D) _{t} The diameter of the blade of the fan with the model t is; r is the radial distance between two fans along the wind direction; c _{T} Is a thrust coefficient; alpha is the wake angle of the fan; t is the axial thrust; ρ is the air density; v _{i} Is the wind speed at fan i; a is the area swept by the wind turbine blade; h is the height of the wind turbine; z _{o} Is the surface roughness. A schematic diagram of the Jensen wake model is shown in FIG. 2.
In practice, the wind direction distribution has various scenarios, dividing the possible wind direction into n sector areas, each sector area corresponding to an arc angle μ=2pi/n. Assuming that any particular wind direction is within the same sectorThe wind direction d is defined as the statistically expected wind direction in the sector and is the direction in which the bisector of the sector is located. For a particular point in the area, there is a series of wind direction angles in the sector, the wake area of which includes the point, the ratio of angle of the series of wind direction angles to μ is defined as the wind interference factor of node i to node j, using ψ _{i,j} Representation of ψ _{i,j} The range of (2) is 0 to 1, and the value of (2) depends on the geometric relationship between fans, as shown in fig. 3.
In FIG. 3, the wake interference region can be divided into four different regions, and the ψ of the different regions is required to be determined _{i,j} And (3) performing calculation:
or>
Wherein:
wherein: r is (r) _{ij} And theta _{ij} Polar coordinates of the coordinates j relative to the coordinates i; r is (r) _{c} Length of line segment OC; θ _{ij} ^{c} The angle of the coordinate j relative to the point C; k (k) _{ij} ^{up} And k _{ij} ^{lo} The slope of the connection line between the upper and lower end points of the coordinate j and the coordinate i is respectively shown.
For wake effects of multiwinddirection scenes, wake loss factors are proposed to describe the comprehensive wake effect of a tmodel fan i on a fan j, and the expression is as follows:
wherein: p is p ^{d} _{i,j,t} Is a wake loss factor; p is p ^{k} Is the probability of occurrence of the wind scenario k.
In a specific embodiment, the coordinated planning model of the offshore wind farm set and the collection network considering the multiwind wake effect aims at maximizing expected annual benefits of the offshore wind farm, and performs coordinated optimization on the wind farm set, the collection cable and the offshore boosting platform. Under the condition of considering a plurality of wind speed and direction scenes and wake effects, the expected electricity generating quantity gain and fan cost, the current collecting cable cost, the offshore boosting platform construction cost and the current collecting network loss cost of the total fan of the wind turbine are optimized, and the comprehensive optimal wind turbine site selection coordinates and model, the current collecting network cable topological connection and the offshore boosting station configuration are obtained. The fan combination variable, the cable combination variable and the transformer combination variable are denoted by x, y and z, respectively. The objective function of the model is as in equations (12) and (13):
wherein: c (C) _{rev} Expected revenue for a wind farm year; r is the discount rate, and 5% is taken; t is the project period of the offshore wind farm, and is generally 25 years; delta T is a unit period, taking 1 hour; c (C) _{wt} And C _{cb} Investment cost of the fan and the power collecting network cable is respectively; c (C) _{loss} To collect annual loss cost of the system; c (C) _{st} The investment cost for the offshore boosting platform is realized. c _{e} For the online electricity price, 0.5 yuan/kWh is taken; p is p _{i} ^{wt} Generating power for the wind turbine generator at the node i; m is m _{i,t} ^{wt} Selecting an address and type selection variable for the wind turbine, taking '1' to represent that a t type No. 1 fan is built at a node i, otherwise taking '0'; p (P) _{t} ^{N} The rated power of a fan of the t model is represented; u (u) _{t} ^{wt} The manufacturing cost of the unit capacity of the tmodel fan; m is m _{i,j,c} ^{cb} Selecting a variable for submarine cable connection, wherein '1' is used for indicating that ctype submarine cable connection is adopted between a node i and a node j, otherwise '0' is adopted; d, d _{i,j} Distance from node i to node j; u (u) _{c} ^{cb} The manufacturing cost of the unit length of the submarine cable of the model c is set; omega shape _{wt} 、Ω _{st} And omega _{owf} Respectively collecting fan nodes, offshore booster station nodes and offshore wind power stations with nodes; omega shape _{W} 、Ω _{C} And omega _{T} Respectively a fan type set, a submarine cable type set and a transformer type set; i _{i,j} U, which is the current flowing from node i to node j _{j} The current, the voltage and the resistance in the node j are all per unit value; p (P) _{b} Is the workA reference value of the rate; z _{s} The number of the stype transformers; u (u) _{s} ^{st} The manufacturing cost of the transformer is s type; c (C) _{p} Is the construction cost of the offshore boosting platform.
Constraints of the model include:
wind turbine generator set combination constraint
Under the condition that constraint conditions are met, selecting a wind turbine with a proper model to be installed on a node to be selected of a fan, wherein the constraint comprises wind farm capacity constraint and turbine wake loss constraint. The total loader capacity of an offshore wind farm is typically a known value, and the actual capacity of an offshore wind farm can be described as:
(1k)p _{g} ≤p _{sum} ≤(1+k)p _{g} (15)
wherein: p is p _{sum} Is the actual installed capacity of the offshore wind farm; p is p _{g} Target installed capacity for an offshore wind farm; k is the capacity coefficient, taking 3%.
The wake loss of the wind turbine, namely the power loss of the fan caused by wake effect among wind turbine, adopts a large M method to describe the power emitted by the wind turbine under uncertainty, and is as follows:
wherein: a, a _{j} The power loss ratio of the fan j; p (P) _{t} ^{v} The initial power of the tmodel fan is generated; binary variable n _{i} ^{wt} Indicating whether the node i is provided with a fan or not; m is a very large positive number.
Current collecting network cable combination constraint
For the current collecting system of the offshore wind farm, a typical alternating current collecting network and a radial current collecting topological structure are adopted, power generated by the wind turbine is transmitted to an offshore booster station through an alternating current submarine cable, and the cable is connected into a radial structure. The collector network cable assembly constraints can be divided into cable connection constraints and collector network loss cost constraints. Regarding the coordinates of a wind turbine generator and an offshore booster station in a current collection system as a directed graph, wherein a connecting line between two nodes in the graph is a directed arc, the offshore booster station node is a tree root node of a radial structure, and then the current collection network cable connection constraint can be expressed as follows:
wherein: binary variable n _{i,j} ^{cb} Indicating whether node i and node j are connected to a cable; MS is the maximum number of cable strings that can be connected to the offshore booster station; f (f) _{i,j} ^{cb} Is the maximum power that can be circulated between node i and node j; u (U) _{N} 、I _{N,c} The rated voltage class and the current carrying capacity of the ctype cable, respectively.
In a current collection system of an offshore wind farm, a cable resistance can cause certain electric quantity loss when power flows through a cable, and a grid loss cost constraint of a current collection network can be expressed as follows:
wherein: p (P) _{i} Power is sent out for the fan i; r is R _{c} Is the resistance of a type c cable. U (U) _{i} For electricity at node iPressing; for the nonconvex nonlinear equation constraint (28), it is linearized using the mccomick envelope method, which translates into a convex constraint, as shown in equation (33):
offshore boosting platform transformer assembly contract bundle
The power generated by the offshore wind farm is firstly collected to the offshore boosting platform, converted into a higher voltage level through the boosting transformer and then transmitted to the land gridconnected point, and the total capacity of a transformer group of the offshore boosting platform is not smaller than the actual capacity of the offshore wind farm, namely:
wherein: s is S _{TN,s} Is the rated capacity of an stype transformer.
Determination of initial active output of unit in wind power plant
The maximum obtainable active force of a single fan g may be expressed as:
wherein C is _{pg} The wind energy utilization coefficient of the fan g; p (P) _{rated} The rated power of the fan g; ρ represents the air density; r is the rotor radius of the fan; v _{g} The inflow wind speed of the fan g; v _{ci} ,v _{rated} And v _{co} The cutin, rated, and cutout wind speeds of the fan g are shown, respectively.
For the topological structure of the offshore wind farm collection network, the condition of cable crossing needs to use an expensive bridge structure in actual construction, and the structure can reduce the cable capacity and greatly reduce the reliability of the cable. Therefore, constraints need to be added to the model to avoid cable intersections, and constraints of equation (36) are typically employed to avoid cable intersections.
Wherein: s is the set of all directed arcs (i, j) and arcs (h, l) intersecting.
Since the calculation complexity of the equation (36) is O (n) ^{3} ) As the offshore wind farm increases in size, i.e., the number of fans increases, the time required for computation increases substantially. For this reason, the present embodiment proposes a cable intersection avoidance algorithm employing a broken line process. To eliminate the intersection phenomenon, it is considered to add a broken line portion to the topological connection. In reality, the coverage of the offshore wind farm is huge, the diameter size of a cable line is negligible compared with that of a fan, so that the fan coordinate can be approximately used as a possible turning point, the submarine cable changes direction at the fan to form a broken line, the intersection phenomenon is eliminated, the required submarine cable length is increased due to broken line connection, and the total cost of the cable is increased, as shown in the formula (37):
wherein: Δz is the cable cost delta, representing the cable cost added by the cable (i, j) becoming the polyline (i, k, j).
The broken line processed cable intersection avoidance algorithm. The specific calculation steps of (a) are as follows:
1. initializing: given intersecting cable setsAnd obtaining a set S according to the node coordinates of the wind turbine to be selected, wherein deltaz=0.
2. Solving a coordinated optimization planning model of the offshore wind farm units and the collecting network with the constraint (36) of cable intersection in the avoiding occurrence set G to obtain a cable connection set N ^{*} Find intersecting cable set g=n ^{*} ∩S。
2. And (3) checking a communication branch: if it isAnd>At this time, the cable (i, j) and the cable (h, l) intersect and the node j is communicated with the node l, as shown in fig. 3, the node closest to the cable intersection point is selected as a turning node k, a broken line (i, k, j) is obtained, the cable (i, j) and the cable (h, l) are removed from the set G, and Δz is calculated _{1} ，Δz＝Δz+Δz _{1} 。
3. Leaf node inspection: if it isAnd>At this time, leaf nodes of the collecting network exist in the nodes of the intersecting cables, as shown in fig. 4, the leaf node closest to the cable intersecting point is selected as a turning node k to obtain a broken line (i, k, j), cables (i, j) and cables (h, l) are removed from a set G, and Δz is calculated _{2} ，Δz＝Δz+Δz _{2} 。
4. Intersection test: judging intersecting cable set after broken line processingIf yes, outputting a result, otherwise adding an intersection constraint +.>Returning to the step 2.
The method is further illustrated in the following in connection with an application scenario example:
taking a certain practical offshore wind farm in China as an example, the correctness and the effectiveness of the proposed optimization planning model and solving algorithm are verified. The test system hardware environment is Intel (R) i712700F CPU@2.10GHz,32G memory, the operating system is Win11, and the test system is programmed in GAMS Studio 42 software.
The actual capacity of the offshore wind farm is 400MW, the rated voltage of an alternating current bus at the lowvoltage side of a wind farm booster station is 35kV, 50 wind turbines are installed in the wind farm, the rated power of a single wind turbine is 8MW, and the cutin wind speed, the rated wind speed and the cutout wind speed are 3m/s, 10m/s and 25m/s respectively. The actual distribution of fans and booster stations of the offshore wind power plant and the calculation result distribution of an optimization model are respectively shown in fig. 6 and 7, 91 wind turbine set tobeselected mounting points are arranged in the optimization model, offshore booster station nodes are actual coordinates, 3 types of wind turbine sets are set, rated powers of the wind turbine sets are respectively 6.45MW, 8MW and 11MW, and the cutin wind speed, the rated wind speed and the cutout wind speed of each type of fan are the same; there are 7 types of 35kV alternating current sea cable and 5 types of 35/220kV transformers, and specific parameters thereof are shown in tables 1 and 2. The historical wind measurement data are counted, and the wind speed is divided into 5 sections according to the output characteristics of the fan, wherein the sections are respectively [0,3 ], [3, 5], [5,7 ], [7,10 ], [10,25]; and the wind direction is divided into 8 wind direction sections of north, northeast, east, southeast, south, southwest, west and northwest. And the optimization model adopts a GUROBI solver to finish solving.
Table 1 submarine cable parameters
Table 2 transformer parameters
And respectively carrying out conventional optimization calculation directly added with all cable intersection constraints and optimization calculation for cable intersection by applying the proposed broken line processing method on the built offshore wind farm unit and integrated network coordinated optimization planning model, comparing the optimization calculation result with various indexes of an actual offshore wind farm, wherein the offshore wind farm topology with 3 conditions is shown in a table 3, 3 types of wind turbines are configured in topological connection of the two optimization results, and 3 parts of the optimization topology of the proposed algorithm are subjected to broken line processing, as shown by blue broken lines. As can be seen from Table 3, the expected annual energy generation of the blower with the optimized result of the algorithm is maximum, the cable network loss is minimum, the cable investment cost and the blower investment cost are both superior to those of the actual situation, and the offshore booster stations with 3 situations are configured by adopting 2X 200MW transformers, so that the investment cost of the booster stations is the same. On the annual equivalent income, the optimization result of the proposed algorithm is improved by 3.24% compared with the actual topological connection of the offshore wind farm, and is improved by 2.12% compared with the topological connection of the conventional optimization result; in solving time, the model solving efficiency is obviously superior to that of conventional optimization because the proposed algorithm optimization reduces a large number of unnecessary constraints.
Table 3 comparison of optimized results
In summary, compared with the prior art, the coordination planning method for the offshore wind farm units and the collector network provided by the embodiment has the following technical advantages:
(1) Wake loss factors that take into account the wake effects of multiwinddirection scenarios are presented. And calculating wake attenuation coefficients of different types of fans on wake area coordinates by adopting a Jensen wake model, and jointly describing wind strong interference factors of multiple wind directions to obtain wake loss factors of all types of fans, so that wake loss power of the wind turbine generator under uncertainty can be calculated.
(2) The coordination optimization planning model of the offshore wind farm units and the centralized network is established, the factors such as annual expected income of the offshore wind farm units, investment cost of the wind farm units, investment cost of submarine cables, network loss cost and the like can be comprehensively considered, comprehensive optimization is carried out on site selection and combination of the multitype wind farm units in the offshore wind farm, cable topological connection of the radial shape and transformer combination configuration of the offshore booster station, and the optimization model is converted into a mixed integer linear planning model so as to reduce complexity of model solving.
(3) The algorithm for processing the intersection avoidance of the cables through the broken lines is provided, the broken lines can be formed at the nodes of the fans when the sea cables are connected by combining the actual sizes of the fans and the cables in the offshore wind farm, and the broken lines are processed on the intersection cables obtained by the optimization model, so that the traditional intersection avoidance constraint is avoided, the scale of the solved optimization model is reduced, and the calculation efficiency is improved.
The above embodiments are only for illustrating the technical concept and features of the present invention, and are intended to enable those skilled in the art to understand the content of the present invention and implement the same, and are not intended to limit the scope of the present invention. All equivalent changes or modifications made in accordance with the essence of the present invention are intended to be included within the scope of the present invention.
Claims (9)
1. The coordination planning method for the offshore wind farm units and the collection network is characterized by comprising the following steps of:
according to the actual topological connection condition of the existing offshore wind farm, setting a plurality of wind turbine generator set tobeselected nodes and an offshore boosting platform node, and constructing a coordinated planning model of the offshore wind farm generator set and a power collecting network by considering the wake effect of the multiwind direction scene;
and solving the coordination planning model of the offshore wind farm unit and the power collecting network by adopting a broken line processing intersection avoidance algorithm to obtain a coordination planning result.
2. The coordinated planning method for the offshore wind farm units and the collection network according to claim 1, wherein the consideration of the wake effect of the multiwind scenario comprises the following steps of adopting a Jensen model to describe the wake effect:
wherein: lambda (lambda) _{i,j,t} The wake attenuation coefficient is used for representing the wake influence degree of a tmodel fan i on a fan j; d (D) _{t} The diameter of the blade of the fan with the model t is; r is the radial distance between two fans along the wind direction; c _{T} Is a thrust coefficient; alpha is the wake angle of the fan; t is the axial thrust; ρ is the air density; v _{i} Is the wind speed at fan i; a is the area swept by the wind turbine blade; h is the height of the wind turbine; z _{o} Is the surface roughness;
for wake effects of multiwinddirection scenes, wake loss factors are provided to describe the comprehensive wake effect of a fan at a tmodel node i on a fan at a node j, and the expression is as follows:
wherein: p is p ^{d} _{i,j,t} Is a wake loss factor; p is p ^{k} Probability of occurrence for wind scenario k; psi ^{k} _{i,j} And the wind power interference factor of the node i to the node j in the scene k is obtained.
3. The coordination planning method for the offshore wind farm units and the power collecting network according to claim 2, wherein an objective function of a coordination planning model for the offshore wind farm units and the power collecting network is as follows:
wherein: x, y and z are fan combination variables, cable combination variables and transformer combination variables respectively; c (C) _{rev} Expected revenue for a wind farm year; r is the discount rate; t is the project period of the offshore wind farm; Δt is a unit period; c (C) _{wt} And C _{cb} Investment cost of the fan and the power collecting network cable is respectively; c (C) _{loss} To collect annual loss cost of the system; c (C) _{st} Investment cost for the offshore boosting platform; c _{e} The online electricity price is obtained; p is p _{i} ^{wt} Generating power for the wind turbine generator at the node i; m is m _{i,t} ^{wt} Selecting an address and type selection variable for the wind turbine, taking '1' to represent that a t type No. 1 fan is built at a node i, otherwise taking '0'; p (P) _{t} ^{N} The rated power of a fan of the t model is represented; u (u) _{t} ^{wt} The manufacturing cost of the unit capacity of the tmodel fan; m is m _{i,j,c} ^{cb} Selecting a variable for submarine cable connection, wherein '1' is used for indicating that ctype submarine cable connection is adopted between a node i and a node j, otherwise '0' is adopted; d, d _{i,j} Distance from node i to node j; u (u) _{c} ^{cb} The manufacturing cost of the unit length of the submarine cable of the model c is set; omega shape _{wt} 、Ω _{st} And omega _{owf} Respectively collecting fan nodes, offshore booster station nodes and offshore wind power stations with nodes; omega shape _{W} 、Ω _{C} And omega _{T} Respectively a fan type set, a submarine cable type set and a transformer type set; i _{i,j} U, which is the current flowing from node i to node j _{j} A node voltage that is node j; p (P) _{b} Is a reference value of power; z _{s} The number of the stype transformers; u (u) _{s} ^{st} The manufacturing cost of the transformer is s type; c (C) _{p} Is the construction cost of the offshore boosting platform.
4. A method for coordinated planning of offshore wind farm units and a collection network according to claim 3, wherein the constraint condition of the objective function comprises a wind farm unit combination constraint, the wind farm unit combination means that a wind farm unit with a proper model is selected to be installed on a node to be selected of a fan under the condition that the constraint condition is met, and the constraint comprises a wind farm capacity constraint and a unit wake loss constraint; the total loader capacity of an offshore wind farm is typically a known value, and the actual capacity of an offshore wind farm is described as:
(1k)p _{g} ≤p _{sum} ≤(1+k)p _{g} (15)
wherein: p is p _{sum} Is the actual installed capacity of the offshore wind farm; p is p _{g} Target installed capacity for an offshore wind farm; k is a capacity coefficient;
the wake loss of the wind turbine, namely the power loss of the fan caused by wake effect among wind turbine, adopts a large M method to describe the power emitted by the wind turbine under uncertainty, and is as follows:
wherein: a, a _{j} The power loss ratio of the fan j; p (P) _{t} ^{v} The initial power of the tmodel fan is generated; binary variable n _{i} ^{wt} Indicating whether or not the node i installs windA machine; m is a positive number.
5. A method of coordinated planning of offshore wind farm units and a collector network according to claim 4, wherein the constraints of the objective function comprise a collector network cable set contract, the network cable connection constraints being expressed as:
wherein: binary variable n _{i,j} ^{cb} Indicating whether node i and node j are connected to a cable; MS is the maximum number of cable strings that can be connected to the offshore booster station; f (f) _{i,j} ^{cb} Is the maximum power that can be circulated between node i and node j; u (U) _{N} 、I _{N,c} The currentcarrying capacity of the rated voltage class and the ctype cable respectively;
in the current collection system of an offshore wind farm, a certain electric quantity loss is caused by cable resistance when power flows through a cable, and the net loss cost constraint of a current collection network is expressed as follows:
wherein: p (P) _{i} Power is sent out for the fan i; r is R _{c} Resistance for type c cable; u (U) _{i} Is the voltage at node i; for the nonconvex nonlinear equation constraint (28), it is linearized using the mccomick envelope method, which translates into a convex constraint, as shown in equation (33):
6. the coordinated planning method for an offshore wind farm unit and a centralized network according to claim 5, wherein the constraint condition of the objective function further comprises a contract bundle of an offshore boost platform transformer group, which is:
the total capacity of the transformer group of the offshore boosting platform should be not less than the actual capacity of the offshore wind farm, namely:
wherein: s is S _{TN,s} Is the rated capacity of an stype transformer.
7. The coordinated planning method of offshore wind farm units and a power collection network according to claim 6, wherein the constraint condition of the objective function further comprises determination of initial active power output of the units in the wind farm, and the maximum available active power output of a single fan g represents:
wherein C is _{pg} The wind energy utilization coefficient of the fan g; p (P) _{rated} The rated power of the fan g; ρ represents the air density; r is the rotor radius of the fan; v _{g} The inflow wind speed of the fan g; v _{ci} ,v _{rated} And v _{co} The cutin, rated, and cutout wind speeds of the fan g are shown, respectively.
8. The coordinated planning method of an offshore wind farm unit and a collection network according to claim 1, wherein the polyline processing intersection avoidance algorithm comprises:
initializing: given intersecting cable setsObtaining a set S according to the node coordinates of the wind turbine to be selected, and enabling deltaz to be 0;
solving: solving a coordinated optimization planning model of the offshore wind farm units and the power collecting network with the constraint of avoiding cable intersection in the collection G to obtain a cable connection collection N ^{*} Find intersecting cable set g=n ^{*} ∩S；
And (3) checking the communication branches: if it isAnd>At the moment, the cable (i, j) is intersected with the cable (h, l) and the node j is communicated with the node l, a node closest to the cable intersection point is selected as a turning node k, a broken line (i, k, j) is obtained, the cable (i, j) and the cable (h, l) are removed from the set G, and deltaz is calculated _{1} ，Δz＝Δz+Δz _{1} ；n _{i,j} ^{cb} Indicating whether node i and node j are connected to a cable, n _{h,l} ^{cb} Indicating whether node h and node l areA connecting cable;
leaf node inspection: if it isAnd>At this time, leaf nodes of the collecting network exist in the nodes of the intersecting cables, the leaf node closest to the cable intersecting point is selected as a turning node k, a broken line (i, k, j) is obtained, the cables (i, j) and the cables (h, l) are removed from the set G, and deltaz is calculated _{2} ，Δz＝Δz+Δz _{2} ；
And an intersection checking step: judging intersecting cable set after broken line processingIf yes, outputting a result, otherwise adding an intersection constraint +.>Returning to the solving step.
9. The coordinated planning method of an offshore wind farm unit and a collector network of claim 8, wherein the cable intersection constraints are:
wherein: s is the set of all directed arcs (i, j) and arcs (h, l) intersecting.
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CN103605912A (en) *  20131210  20140226  武汉大学  Wind power plant power external characteristic modeling method 
CN106599386A (en) *  20161123  20170426  上海电力学院  Model selection and optimization method for fan blade in wind power plant 
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