Reactive power optimization configuration method and system for offshore wind plant

Abstract

The invention relates to the technical field of offshore wind power monitoring, and discloses an offshore wind power plant reactive power optimization configuration method and system.The method comprises the steps that the maximum capacity value of a reactive power compensation device is determined based on a constructed first constraint condition, a constructed second constraint condition and a target function, and the minimum internal network loss of a wind power plant serves as the target function; and the reactive power of the fan and the capacity of the compensation device are used as optimization variables. Multiple targets of reducing network loss, reducing investment of reactive compensation equipment, improving voltage stability and system operation reliability and the like can be effectively achieved.

Description

Technical Field

[0001] This invention relates to the field of offshore wind power monitoring technology, and in particular to a method and system for optimizing reactive power configuration in offshore wind farms. Background Technology

[0002] Offshore wind farm power transmission methods can generally be categorized into: high-voltage AC transmission, flexible DC transmission, and low-frequency AC transmission. In high-voltage AC transmission, the charging power of submarine cables can raise the system voltage, thus affecting system stability. Current technologies typically treat the wind farm as a PQ node with a power factor of 1, using reactive power compensation devices to ensure system voltage stability. However, this approach neglects the reactive power regulation capabilities of the wind turbines, making it difficult to reduce the capacity of the reactive power compensation devices and thus failing to meet reactive power compensation requirements. Therefore, there is an urgent need for a method that can determine the capacity of the reactive power compensation devices while optimizing the reactive power output of wind turbines at different locations. Summary of the Invention

[0003] This invention provides a method and system for optimizing reactive power configuration in offshore wind farms, which solves the problem in the prior art that does not consider the reactive power regulation capability of wind turbines, thus making it difficult to reduce the capacity of reactive power compensation devices and meet reactive power compensation requirements.

[0004] Firstly, this application provides a method for optimizing reactive power allocation in offshore wind farms, including: S1: Obtain the main parameters of the offshore wind power AC grid-connected system, and based on the equivalence principle, convert the offshore wind farm system into a PQ node with equivalent impedance through parallel calculation; S2: Take the initial value of the active power output of the wind turbine as 0, and the initial value of the reactive power compensation device capacity on the side of the submarine cable near the offshore wind farm as 0. Construct the first set of constraints and objective function required for optimization calculation. S3: Based on the first set of constraints and the objective function, use the optimization algorithm to calculate the reactive power output of each wind turbine: If all constraints in the first set of constraints are met, calculate the active power output of the wind turbine, the capacity of the reactive power compensation device, and the reactive power output of each wind turbine obtained by the optimization algorithm, and execute S4; otherwise, increase the capacity of the reactive power compensation device by ΔS and recalculate the reactive power output of each wind turbine using the optimization algorithm. S4: If the active power output of the fan is greater than or equal to the fan capacity, then execute S5; otherwise, increase the active power output of the fan by ΔP and then execute S3 again. S5: Calculate the improvement efficiency k of the reactive power compensation device based on the active power output of the wind turbine, the capacity of the reactive power compensation device, and the reactive power output of each wind turbine. Find the minimum k value that is not less than the preset threshold. Take the active power output of the wind farm corresponding to the minimum k value as the optimized value of the maximum active power output of the wind farm. Set the capacity of the reactive power compensation device corresponding to the optimized value of the maximum active power output of the wind farm as the optimized value of the capacity of the reactive power compensation device. S6: Construct a second set of constraints based on the first set of constraints; S7: Input the actual active power output of the wind turbine. Based on the second set of constraints, the objective function, and the reactive power compensation device capacity corresponding to the maximum active power output optimization value of the wind farm, use the optimization algorithm to calculate the reactive power output of each wind turbine and the reactive power compensation device as the grid connection optimization result.

[0005] Optionally, the main parameters of the offshore wind power AC grid-connected system include: wind turbine capacity, submarine cable length, line impedance, onshore AC grid voltage level, submarine cable charging power, and transformer no-load loss.

[0006] Optionally, the equivalence principle satisfies the following relationship: (1) In the formula, , The equivalent active power of the i-th wind turbine and the impedance of the wind turbine step-up transformer; , , The values ​​are: number of parallel branches, active power of wind turbines, and impedance of wind turbine step-up transformers in a real wind farm. 4. The reactive power optimization configuration method for offshore wind farms according to claim 1, characterized in that step S2 includes: Given that the active power output of the wind turbine is 0, and the reactive power compensation device capacity on the side of the submarine cable closest to the offshore wind farm is 0, the first set of constraints is established as follows: (2) The objective function is to minimize the internal network loss of the offshore wind farm, as follows: (3) (4) In the formula, These are the weighting coefficients. This is the penalty coefficient; For internal grid losses in wind farms; , These are the voltages at each node and the system's rated voltage, respectively. , These represent the minimum and maximum active power output of the fan at different locations; , These represent the minimum and maximum reactive power output of the fan at different locations; The power factor of the fan; Rated capacity; , These represent the capacity of the compensation device and the maximum capacity of the compensation device, respectively. It contributes power to the wind turbines in different locations. The minimum voltage at each node. The maximum voltage at each node. To provide reactive power output for wind turbines in different locations, This represents the value indicating whether the voltage at each node exceeds the limit.

[0007] Optionally, S3 includes: Input wind farm system parameters and particle swarm optimization parameters, including the number of particles N, maximum number of iterations, inertia weight w, and acceleration coefficient. , Minimum particle velocity Maximum particle velocity ; Assuming the active power output of the wind turbines is the same at different locations, To increase from 0 to Based on the power factor requirements and the requirement that the fan power does not exceed its rated capacity, the minimum reactive power output of the fan at different locations is obtained. Maximum value ; Initialize particle positions and velocities, and randomly generate an N*R random matrix; N represents the number of particles, and each particle has R dimensions, corresponding to the reactive power output of R wind turbines. , … N feasible solutions are obtained; the system power flow is solved to obtain N objective function values. Update the particle velocity and position. If the particle velocity and position do not exceed the limits, calculate the updated fitness value of the particle and find the optimal solution. If the particle velocity and position exceed the limits, set the current particle velocity and position as extreme values. If the number of particle iterations is exceeded, stop the calculation and obtain the reactive power output of the wind turbine at different positions. Solve for system power flow: Given the active power and reactive power of node m in the system as follows: , The voltage at node n is The active power and reactive power of node n are respectively , The impedance between the two nodes is The susceptance is b. Calculate the power loss between nodes m and n to charge the submarine cable. as follows: (5) In the formula, U n This refers to the voltage at the beginning of the submarine cable. During steady-state operation of an offshore wind farm, the voltages at the two nodes are assumed to be the same. , ... Among them, the impedance between the two nodes = ; Power flowing into node n , They are respectively: (6) In the formula, , Let be the complex powers of nodes n and m, respectively. The power loss between nodes m and n; in, = + j ; The voltage at node m is calculated as follows: (7) In the formula, This represents the longitudinal component of the voltage drop between nodes m and n.

[0008] Optionally, increasing the active power output of the wind turbine by ΔP includes: Increase the reactive power compensation capacity from 0, increasing it by 0.1 each time. , Power to charge the submarine cable; Assuming the capacity is d, if the system voltage meets the requirements, take d / 2; if the voltage meets the constraints, take d / 4; if the system voltage does not meet the requirements, take 3d / 4 of the capacity. Repeat this process until the compensation capacity is x*. At that time, the system voltage satisfies the constraint, and the compensation capacity is (x-0.01)*. When the system voltage does not meet the constraint, x* It is considered as the capacity of the reactive power compensation device.

[0009] Optionally, the step of calculating the improvement benefit k of the reactive power compensation device based on the active power output of the wind turbine, the capacity of the reactive power compensation device, and the reactive power output of each wind turbine includes: The ratio of the increase in active power to reactive power compensation capacity in a wind farm is used as the efficiency improvement k. The increase in active power in a wind farm is the sum of the active power output of R wind turbines when the reactive power compensation device capacity is fixed, minus the sum of the active power output of R wind turbines when the reactive power compensation device capacity is zero.

[0010] Optionally, the second set of constraints is as follows: (8) In the formula, This indicates the minimum capacity of the compensation device.

[0011] Secondly, this application provides a reactive power optimization configuration system for offshore wind farms, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the method described in the first aspect above.

[0012] The present invention has the following beneficial effects: The reactive power optimization configuration method for offshore wind farms in this application determines the maximum capacity of the reactive power compensation device based on the constructed first constraint, second constraint, and objective function. The objective function is to minimize the internal grid loss of the wind farm, with wind turbine reactive power and compensation device capacity as optimization variables. This method can effectively achieve multiple objectives, including reducing grid losses, reducing investment in reactive power compensation equipment, and improving voltage stability and system operational reliability.

[0013] In addition to the objectives, features and advantages described above, the present invention has other objectives, features and advantages.

[0014] The present invention will now be described in further detail with reference to the figures. Attached Figure Description

[0015] The accompanying drawings, which form part of this application, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings: Figure 1 This is a flowchart of a preferred embodiment of the reactive power optimization configuration method for offshore wind farms according to the present invention; Figure 2 This is a structural diagram of an offshore wind farm system according to a preferred embodiment of the present invention; Figure 3 This is the equivalent circuit of the offshore wind farm system in a preferred embodiment of the present invention; Figure 4 This is a graph showing the change in reactive power output of the fan at different locations as a function of active power output, according to a preferred embodiment of the present invention. Figure 5 This is a schematic diagram showing the change in the capacity of the reactive power compensation device with the active power output of the wind farm before and after optimizing the reactive power output of the wind farm according to a preferred embodiment of the present invention. Figure 6This is a schematic diagram illustrating the change of system voltage with the active power output of a wind farm according to a preferred embodiment of the present invention. Detailed Implementation

[0016] The technical solution of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Similarly, the terms "an" or "a," and similar terms, do not indicate a quantity limitation, but rather indicate the presence of at least one.

[0018] Please see Figure 1 This application provides a method for optimizing reactive power allocation in offshore wind farms, including: S1: Obtain the main parameters of the offshore wind power AC grid-connected system, and based on the equivalence principle, convert the offshore wind farm system into a PQ node with equivalent impedance through parallel calculation; S2: Take the initial value of the active power output of the wind turbine as 0, and the initial value of the reactive power compensation device capacity on the side of the submarine cable near the offshore wind farm as 0. Construct the first set of constraints and objective function required for optimization calculation. S3: Based on the first set of constraints and the objective function, use the optimization algorithm to calculate the reactive power output of each wind turbine: If all constraints in the first set of constraints are met, calculate the active power output of the wind turbine, the capacity of the reactive power compensation device, and the reactive power output of each wind turbine obtained by the optimization algorithm, and execute S4; otherwise, increase the capacity of the reactive power compensation device by ΔS and recalculate the reactive power output of each wind turbine using the optimization algorithm. S4: If the active power output of the fan is greater than or equal to the fan capacity, then execute S5; otherwise, increase the active power output of the fan by ΔP and then execute S3 again. S5: Calculate the improvement efficiency k of the reactive power compensation device based on the active power output of the wind turbine, the capacity of the reactive power compensation device, and the reactive power output of each wind turbine. Find the minimum k value that is not less than the preset threshold. Take the active power output of the wind farm corresponding to the minimum k value as the optimized value of the maximum active power output of the wind farm. Set the capacity of the reactive power compensation device corresponding to the optimized value of the maximum active power output of the wind farm as the optimized value of the capacity of the reactive power compensation device. S6: Construct a second set of constraints based on the first set of constraints; S7: Input the actual active power output of the wind turbine. Based on the second set of constraints, the objective function, and the reactive power compensation device capacity corresponding to the maximum active power output optimization value of the wind farm, use the optimization algorithm to calculate the reactive power output of each wind turbine and the reactive power compensation device as the grid connection optimization result.

[0019] In this embodiment, Figure 2 This is a structural diagram of an offshore wind farm system according to a preferred embodiment of the present invention; the equivalent circuit of the offshore wind farm system is obtained from the structural diagram as follows: Figure 3 As shown, in the equivalent circuit obtained from the offshore wind farm system structure diagram: b 4,5 b 5,4 This represents the susceptance of the submarine cable between nodes 4 and 5 (the susceptance between different nodes is represented by the node values); P t0 Q t0 The impedances between nodes 1 and 2, 2 and 3, 3 and 4, 4 and 5, and 5 and 6 represent the equivalent impedances of the AC power grid, the equivalent impedance of the onshore overhead line, the equivalent impedance of the 220 kV AC submarine cable, the equivalent impedance of the transformer, and the equivalent impedance of the collector line, respectively. Nodes 6 to 17 represent the equivalent offshore wind farm.

[0020] The aforementioned reactive power optimization configuration method for offshore wind farms determines the maximum capacity of the reactive power compensation device based on the constructed first constraint, second constraint, and objective function. The objective function is to minimize grid losses within the wind farm, with wind turbine reactive power and compensation device capacity as optimization variables. This method can effectively achieve multiple objectives, including reducing grid losses, minimizing investment in reactive power compensation equipment, and improving voltage stability and system operational reliability.

[0021] In this application, the main parameters of the offshore wind power AC grid-connected system include: wind turbine capacity, submarine cable length, line impedance, onshore AC grid voltage level, submarine cable charging power, and transformer no-load loss.

[0022] The equivalence principle satisfies the following relationship: (1) In the formula, , The equivalent active power of the i-th wind turbine and the impedance of the wind turbine step-up transformer; , , This represents the number of parallel branches, the active power of the wind turbines, and the impedance of the wind turbine step-up transformer in a real wind farm.

[0023] Optionally, S2 includes: Given that the active power output of the wind turbine is 0, and the reactive power compensation device capacity on the side of the submarine cable closest to the offshore wind farm is 0, the first set of constraints is established as follows: (2) The objective function is to minimize the internal network loss of the offshore wind farm, as follows: (3) (4) In the formula, These are the weighting coefficients. This is the penalty coefficient; For internal grid losses in wind farms; , These are the voltages at each node and the system's rated voltage, respectively. , These represent the minimum and maximum active power output of the fan at different locations; , These represent the minimum and maximum reactive power output of the fan at different locations; The power factor of the fan; Rated capacity; , These represent the capacity of the compensation device and the maximum capacity of the compensation device, respectively. It contributes power to the wind turbines in different locations. The minimum voltage at each node. The maximum voltage at each node. To provide reactive power output for wind turbines in different locations, This represents the value indicating whether the voltage at each node exceeds the limit.

[0024] Optionally, S3 includes: Input wind farm system parameters and particle swarm optimization parameters, including the number of particles N, maximum number of iterations, inertia weight w, and acceleration coefficient. , Minimum particle velocity Maximum particle velocity ; Assuming the active power output of the wind turbines is the same at different locations, To increase from 0 to Based on the power factor requirements and the requirement that the fan power does not exceed its rated capacity, the minimum reactive power output of the fan at different locations is obtained. Maximum value ; Initialize particle positions and velocities, and randomly generate an N*R random matrix; N represents the number of particles, and each particle has R dimensions, corresponding to the reactive power output of R wind turbines. , … N feasible solutions are obtained; the system power flow is solved to obtain N objective function values. Update the particle velocity and position. If the particle velocity and position do not exceed the limits, calculate the updated fitness value of the particle and find the optimal solution. If the particle velocity and position exceed the limits, set the current particle velocity and position as extreme values. If the number of particle iterations is exceeded, stop the calculation and obtain the reactive power output of the wind turbine at different positions. Solve for system power flow: Given the active power and reactive power of node m in the system as follows: , The voltage at node n is The active power and reactive power of node n are respectively , The impedance between the two nodes is The susceptance is b. Calculate the power loss between nodes m and n to charge the submarine cable. as follows: (5) In the formula, U n This refers to the voltage at the beginning of the submarine cable. During steady-state operation of an offshore wind farm, the voltages at the two nodes are assumed to be the same. , ... Among them, the impedance between the two nodes = ; Power flowing into node n , They are respectively: (6) In the formula, , Let be the complex powers of nodes n and m, respectively. The power loss between nodes m and n; in, = + j ; Ignoring the transverse component of the voltage drop, the voltage at node m is calculated as follows: (7) In the formula, This represents the longitudinal component of the voltage drop between nodes m and n.

[0025] Next, initialize the particle position and velocity, and randomly generate an N*R random matrix; N represents the number of particles, and each particle has R dimensions, corresponding to R reactive power variables Qg1, Qg2...QgR respectively; obtain N feasible solutions and N objective function values ​​(i.e. fitness values).

[0026] Next, update the particle velocity and position. If the particle velocity and position do not exceed the limits, calculate the updated fitness value of the particle and find the optimal solution; if the particle velocity and position exceed the limits, set the particle velocity and position to extreme values ​​at this time.

[0027] Finally, if the number of particle iterations is exceeded, the calculation stops, and the reactive power output of the wind turbine at different locations is obtained.

[0028] Optionally, increasing the active power output of the wind turbine by ΔP includes: Increase the reactive power compensation capacity from 0, increasing it by 0.1 each time. , Power to charge the submarine cable; Assuming the capacity is d, if the system voltage meets the requirements, take d / 2; if the voltage meets the constraints, take d / 4; if the system voltage does not meet the requirements, take 3d / 4 of the capacity. Repeat this process until the compensation capacity is x*. At that time, the system voltage satisfies the constraint, and the compensation capacity is (x-0.01)*. When the system voltage does not meet the constraint, x* It is considered as the capacity of the reactive power compensation device.

[0029] Optionally, the step of calculating the improvement benefit k of the reactive power compensation device based on the active power output of the wind turbine, the capacity of the reactive power compensation device, and the reactive power output of each wind turbine includes: The ratio of the increase in active power to reactive power compensation capacity in a wind farm is used as the efficiency improvement k. The increase in active power in a wind farm is the sum of the active power output of R wind turbines when the reactive power compensation device capacity is fixed, minus the sum of the active power output of R wind turbines when the reactive power compensation device capacity is zero.

[0030] Specifically, when the capacity of the reactive power compensation device is fixed, it means that Sb takes a certain fixed value based on the range of Sb in the second set of constraints.

[0031] Optionally, the second set of constraints is as follows: (8) In the formula, This represents the minimum capacity of the compensation device. The remaining variables are the same as described above and will not be repeated here.

[0032] The objective function is the same as described above, and will not be repeated here.

[0033] In this application, the reactive power output of each wind turbine and the reactive power compensation device are calculated using an optimization algorithm as follows: Based on the above steps, determine the maximum capacity of the reactive power compensation device. With the goal of minimizing the internal grid loss of the wind farm, use the reactive power of the wind turbine and the capacity of the compensation device as optimization variables to reduce the internal grid loss of the wind farm.

[0034] The steps of the above-mentioned reactive power optimization configuration method for offshore wind farms are described below with a complete example: Step 1: Equivalently represent the 132 wind turbines in the real wind farm as one feeder and 6 wind turbines. Based on the principle of equivalence, establish an equivalent circuit for a 17-node offshore wind farm system. In equivalent circuits Q c1 , Q c2 This indicates the charging power at both ends of a 220 kV submarine cable; P t0 , Q t0 This indicates the no-load active and reactive power losses of the transformer; Q k1 , Q k2 This indicates the charging power at both ends of a 35 kV submarine cable.

[0035] The principle of equivalence is: (1) In the formula P eq,i This represents the equivalent active power of the i-th wind turbine.

[0036] Step 2: Set the active power output of the wind farm to 0 and the reactive power compensation device capacity on the side of the submarine cable closest to the offshore wind farm to 0, and establish the first set of constraints and objective function required for optimization calculation. Step 3: Based on the first set of constraints and the objective function, use the optimization algorithm to calculate the reactive power output of each wind turbine. If all constraints in the first set of constraints are met, record the active power output of the wind turbine, the capacity of the reactive power compensation device, and the reactive power output of each wind turbine obtained by the optimization algorithm, and jump to step 5; otherwise, continue to step 4. Step 4: Increase the capacity of the reactive power compensation device by ΔS, then proceed to Step 3; Step 5: If the active power output of the wind farm is greater than or equal to the wind farm capacity, proceed to step 6; otherwise, increase the active power output of the wind farm by ΔP and continue to step 3. Step six: Calculate the improvement efficiency of the reactive power compensation device based on the data recorded in step three. k Find the minimum value that is not less than a preset threshold. k value, and the minimum k The value corresponds to the wind farm's active power output, which is the optimized value of the wind farm's maximum active power output. The corresponding reactive power compensation device capacity is equal to the optimized value of the reactive power compensation device capacity. Step 7: Input the actual active power output of the wind farm. Based on the second set of constraints and the objective function, use the optimization algorithm to calculate the reactive power output of each wind turbine and the reactive power compensation device. This result is the reactive power optimization result of the grid-connected system.

[0037] In one example, the main parameters of the offshore wind farm system and the particle swarm optimization algorithm are shown in Tables 1 and 2.

[0038] Table 1 Main parameters of offshore wind farm system

[0039] Table 2 Main parameters of the particle swarm optimization algorithm

[0040] When the submarine cable is 20 km long, all six wind turbines have the same active power output, and each turbine has a rated capacity of 66 MW. Using particle swarm optimization, the curves showing the change in reactive power output as a function of active power output for turbines at different locations are as follows. Figure 4 As shown in Tables 3 and 4, when the active power output of the wind turbines is 10 MW, 30 MW, and 48 MW respectively, the internal grid loss of the wind farm before and after optimizing the reactive power output of the wind turbines at different locations is as follows.

[0041] Table 3. Reactive power output of wind turbines at different locations obtained through optimization algorithm.

[0042] Table 4. Reactive power output of fans at different locations without optimization.

[0043] When the active power output of the wind turbines is 10 MW, the optimization algorithm proposed in this patent can reduce the internal grid loss of the wind farm from 1.78 MW to 1.66 MW, a reduction of 7.2%. When the active power output of the wind turbines is 30 MW and 48 MW, the optimization algorithm proposed in this patent reduces the internal grid loss of the wind farm from 15.54 MW and 38.13 MW to 14.64 MW and 36.77 MW, respectively, a reduction of 6.1% and 3.6%. Comparing Tables 3 and 4, it can be seen that optimizing the reactive power output of wind turbines at different locations can reduce the internal grid loss of the wind farm.

[0044] With everything else remaining unchanged, and the submarine cable length being 50 km, the change in the capacity of the reactive power compensation device with respect to the active power output of the wind farm before and after optimizing the reactive power output is as follows: Figure 5 As shown.

[0045] According to the method described in this patent, the optimized maximum active power output is 372 MW, requiring a reactive power compensation device capacity of 48 Mvar. Comparing this to the case where the wind farm power factor remains at 1, selecting 372 MW as the maximum active power output value results in a reactive power compensation device capacity of 318 Mvar. This demonstrates that fully utilizing the reactive power of the wind farm can reduce the capacity of the compensation device.

[0046] For wind turbines operating with variable power factors, the reactive power compensation device capacity increases by 412 Mvar, while the maximum active power output only increases by 72 MW. The active power output improvement effect brought about by the reactive power compensation device is very poor, which is not economically feasible. This also verifies that the method proposed in this patent can effectively avoid the problem of a significant increase in reactive power compensation device capacity without a significant improvement in active power output.

[0047] When the wind farm power factor is 1 and the compensation device capacity is fixed at 400 Mvar, the system voltage changes with the active power output of the wind farm as follows: Figure 6 As shown, the system voltage may exceed limits (during steady-state operation of an offshore wind farm system, the voltage fluctuation range at the wind turbine grid connection point is 0.97~1.07 pu, and the upper limit of submarine cable voltage is 1.1 pu). For a wind farm with a power factor of 1 and a fixed compensation device capacity of 400 Mvar, when the active power output of the wind farm is 384 MW, the internal network loss is 69.8 MW. For a wind farm with optimized reactive power and reactive power compensation device capacity at different locations, the internal network loss is 64.6 MW. After optimization, the internal network loss is reduced by 7.4%. This verifies that the method proposed in this patent can reasonably allocate the reactive power of the wind farm and the reactive power of the compensation device based on the active power output of the wind farm, avoiding voltage exceeding limits and increased network losses caused by excessive reactive power compensation device capacity.

[0048] This application also provides a reactive power optimization configuration system for offshore wind farms, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the steps of the above-described method. This offshore wind farm reactive power optimization configuration system can implement various embodiments of the above-described offshore wind farm reactive power optimization configuration method and achieve the same beneficial effects; further details are omitted here.

[0049] The above description is merely a specific embodiment of this disclosure, but the scope of protection of this disclosure is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this disclosure should be included within the scope of protection of this disclosure. Therefore, the scope of protection of this disclosure should be determined by the scope of the claims.

Claims

1. A method for optimizing reactive power allocation in offshore wind farms, characterized in that, include: S1: Obtain the main parameters of the offshore wind power AC grid-connected system, and based on the equivalence principle, convert the offshore wind farm system into a PQ node with equivalent impedance through parallel calculation; S2: Take the initial value of the active power output of the wind turbine as 0, and the initial value of the reactive power compensation device capacity on the side of the submarine cable near the offshore wind farm as 0. Construct the first set of constraints and objective function required for optimization calculation. S3: Based on the first set of constraints and the objective function, use the optimization algorithm to calculate the reactive power output of each wind turbine: If all constraints in the first set of constraints are met, calculate the active power output of the wind turbine, the capacity of the reactive power compensation device, and the reactive power output of each wind turbine obtained by the optimization algorithm, and execute S4; otherwise, increase the capacity of the reactive power compensation device by ΔS and recalculate the reactive power output of each wind turbine using the optimization algorithm. S4: If the active power output of the fan is greater than or equal to the fan capacity, then execute S5; otherwise, increase the active power output of the fan by ΔP and then execute S3 again. S5: Calculate the improvement efficiency k of the reactive power compensation device based on the active power output of the wind turbine, the capacity of the reactive power compensation device, and the reactive power output of each wind turbine. Find the minimum k value that is not less than the preset threshold. Take the active power output of the wind farm corresponding to the minimum k value as the optimized value of the maximum active power output of the wind farm. Set the capacity of the reactive power compensation device corresponding to the optimized value of the maximum active power output of the wind farm as the optimized value of the capacity of the reactive power compensation device. S6: Construct a second set of constraints based on the first set of constraints; S7: Input the actual active power output of the wind turbine. Based on the second set of constraints, the objective function, and the reactive power compensation device capacity corresponding to the maximum active power output optimization value of the wind farm, use the optimization algorithm to calculate the reactive power output of each wind turbine and the reactive power compensation device as the grid connection optimization result.

2. The reactive power optimization configuration method for offshore wind farms according to claim 1, characterized in that, The main parameters of the offshore wind power AC grid-connected system include: wind turbine capacity, submarine cable length, line impedance, onshore AC grid voltage level, submarine cable charging power, and transformer no-load loss.

3. The method for optimizing reactive power allocation in offshore wind farms according to claim 1, characterized in that, The equivalence principle satisfies the following relationship: （1） In the formula, , The equivalent active power of the i-th wind turbine and the impedance of the wind turbine step-up transformer; , , This represents the number of parallel branches, the active power of the wind turbines, and the impedance of the wind turbine step-up transformer in a real wind farm.

4. The reactive power optimization configuration method for offshore wind farms according to claim 1, characterized in that, S2 includes: Given that the active power output of the wind turbine is 0, and the reactive power compensation device capacity on the side of the submarine cable closest to the offshore wind farm is 0, the first set of constraints is established as follows: （2） The objective function is to minimize the internal network loss of the offshore wind farm, as follows: （3） （4） In the formula, These are the weighting coefficients. This is the penalty coefficient; For internal grid losses within the wind farm; , These are the voltages at each node and the system's rated voltage, respectively. , These represent the minimum and maximum active power output of the fan at different locations; , These represent the minimum and maximum reactive power output of the fan at different locations; The power factor of the fan; Rated capacity; , These represent the capacity of the compensation device and the maximum capacity of the compensation device, respectively. It contributes power to the wind turbines in different locations. The minimum voltage at each node. The maximum voltage at each node. To provide reactive power output for wind turbines in different locations, This represents the value indicating whether the voltage at each node exceeds the limit.

5. The method for optimizing reactive power allocation in offshore wind farms according to claim 1, characterized in that, S3 includes: Input the wind farm system parameters and particle swarm optimization parameters, including the number of particles N, maximum number of iterations, inertia weight w, and acceleration coefficient. , Minimum particle velocity Maximum particle velocity ; Assuming the active power output of the wind turbines is the same at different locations, To increase from 0 to Based on the power factor requirements and the requirement that the fan power does not exceed its rated capacity, the minimum reactive power output of the fan at different locations is obtained. Maximum value ; Initialize particle positions and velocities, and randomly generate an N*R random matrix; N represents the number of particles, and each particle has R dimensions, corresponding to the reactive power output of R wind turbines. , … N feasible solutions are obtained; the system power flow is solved to obtain N objective function values. Update the particle velocity and position. If the particle velocity and position do not exceed the limits, calculate the updated fitness value of the particle and find the optimal solution. If the particle velocity and position exceed the limits, set the current particle velocity and position as extreme values. If the number of particle iterations is exceeded, stop the calculation and obtain the reactive power output of the wind turbine at different positions. Solve for system power flow: Given the active power and reactive power of node m in the system as follows: , The voltage at node n is The active power and reactive power of node n are respectively , The impedance between the two nodes is The susceptance is b. Calculate the power loss between nodes m and n to charge the submarine cable. as follows: （5） In the formula, U n This refers to the voltage at the beginning of the submarine cable. During steady-state operation of an offshore wind farm, the voltages at the two nodes are assumed to be the same. , ... Among them, the impedance between the two nodes = ; Power flowing into node n , They are respectively: （6） In the formula, , Let be the complex powers of nodes n and m, respectively. The power loss between nodes m and n; in, = + j ; The voltage at node m is calculated as follows: （7） In the formula, This represents the longitudinal component of the voltage drop between nodes m and n.

6. The reactive power optimization configuration method for offshore wind farms according to claim 1, characterized in that, The method of increasing the active power output of the wind turbine by ΔP includes: Increase the reactive power compensation capacity from 0, increasing it by 0.1 each time. , Power to charge the submarine cable; Assuming the capacity is d, if the system voltage meets the requirements, take d / 2; if the voltage meets the constraints, take d / 4; if the system voltage does not meet the requirements, take 3d / 4 of the capacity. Repeat this process until the compensation capacity is x*. At that time, the system voltage satisfies the constraint, and the compensation capacity is (x-0.01)*. When the system voltage does not meet the constraint, x* It is considered as the capacity of the reactive power compensation device.

7. The method for optimizing reactive power allocation in offshore wind farms according to claim 1, characterized in that, The calculation of the improvement benefit k of the reactive power compensation device based on the active power output of the wind turbine, the capacity of the reactive power compensation device, and the reactive power output of each wind turbine includes: The ratio of the increase in active power to reactive power compensation capacity in a wind farm is used as the efficiency improvement k. The increase in active power in a wind farm is the sum of the active power output of R wind turbines when the reactive power compensation device has a fixed capacity, minus the sum of the active power output of R wind turbines when the reactive power compensation device has zero capacity.

8. The reactive power optimization configuration method for offshore wind farms according to claim 4, characterized in that, The second set of constraints is as follows: （8） In the formula, This indicates the minimum capacity of the compensation device.

9. A reactive power optimization configuration system for offshore wind farms, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of any of the methods described in claims 1-8.

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