Method and device for evaluating maximum available droop coefficient of offshore wind farm, and electronic device

Abstract

The present invention discloses a method and device for evaluating the maximum available droop coefficient of an offshore wind farm, and an electronic device, including: solving the frequency time-domain analytical formula of the power system during a frequency fault and the active power output expressions of the wind turbine generator sets and the energy storage system; solving the rotor speed expression of the wind turbine generator sets and the state of charge expression of the energy storage system; taking the minimization of the maximum frequency deviation as the optimization objective and the non-exceedance of the overall active power output of the wind farm as the constraint condition to solve the preliminary evaluation result of the maximum available droop coefficient of the station; taking the maximization of the droop coefficient of the station as the optimization objective and the non-exceedance of the active power output of the wind turbine generator sets and the energy storage system, as well as the non-exceedance of the rotor speed and the state of charge as the constraint conditions to solve the preliminary evaluation result of the maximum available droop coefficient of a single unit; determining whether the two results match, and if they do not match, adding the preliminary evaluation result of the single unit as a new constraint condition, and then solving the evaluation results of the maximum available droop coefficient of the station and the single unit again until the two results match.

Description

Technical Field

[0001] The present application relates to the technical field of wind power generation, and in particular to a method and device for evaluating the maximum available droop coefficient of an offshore wind farm, and electronic equipment. Background Art

[0002] The power supply structure of the power system is changing as the proportion of renewable energy, especially wind and solar energy, increases. Traditional power systems rely on large synchronous generators (such as thermal power and hydropower), which can provide the inertia and frequency regulation capabilities required by the system. However, renewable energy generation usually uses different technologies from traditional synchronous machines, such as permanent magnet direct drive or doubly fed asynchronous wind turbines, which are not designed to provide the same inertia and frequency regulation support to the system. Since new energy generation devices (such as wind power and photovoltaics) do not have the rotating mass of traditional synchronous machines, they do not naturally contribute to the inertia of the system. This causes the system frequency to drop faster when a power imbalance event occurs, and additional measures are required to maintain system stability. This means that the control strategy must change from simply responding to grid commands (grid following type) to being able to actively provide support to maintain grid stability (grid supporting type). Considering that different wind turbines and energy storage systems may face different operating conditions, it is necessary to develop intelligent algorithms to adaptively adjust the droop factor of each unit to optimize its support for system frequency. Summary of the invention

[0003] The purpose of the embodiments of the present application is to provide a method and device for evaluating the maximum available droop coefficient of an offshore wind farm, and electronic equipment, so as to solve the problem in the related art that the primary frequency regulation effect is poor and endangers the safety and stability of wind turbines or energy storage systems.

[0004] According to a first aspect of an embodiment of the present application, a method for evaluating a maximum available droop coefficient of an offshore wind farm is provided, comprising:

[0005] According to the frequency response model of the power system including the offshore wind farm, the time-domain analytical expression of the frequency of the power system during the frequency fault is obtained;

[0006] According to the frequency time domain analytical expression, the maximum frequency deviation expression is solved, and the active output expressions of the wind turbine and the energy storage system during the frequency fault are obtained respectively;

[0007] Obtain measured data of wind energy capture coefficient of wind turbines, fit the wind energy capture coefficient of wind turbines, obtain an approximate expression of wind energy capture coefficient, and obtain an approximate expression of mechanical power captured by wind turbines by combining wind speed data and actual parameters of wind turbines;

[0008] According to the active output expression and the approximate expression of mechanical power, respectively solving the expression of wind turbine rotor speed during frequency fault and the expression of energy storage system charge state;

[0009] According to the maximum frequency deviation expression and the active output expression, with minimizing the maximum frequency deviation as the optimization goal and with the overall active output of the offshore wind farm not exceeding the limit as the constraint condition, the preliminary evaluation result of the maximum available droop coefficient of the offshore wind farm is solved;

[0010] According to the preliminary evaluation results of the maximum available droop coefficient of the offshore wind farm, the expression of the rotor speed of the wind turbine and the expression of the state of charge of the energy storage system, taking maximizing the droop coefficient of the offshore wind farm as the optimization goal, and taking the active output of the wind turbine and the energy storage system not exceeding the limit and the rotor speed and state of charge not exceeding the limit as the constraints, the preliminary evaluation results of the maximum available droop coefficient of a single unit of the wind turbine and the energy storage system are solved;

[0011] According to the preliminary evaluation results of the maximum available droop coefficient of the offshore wind farm station and the preliminary evaluation results of the maximum available droop coefficient of a single machine, it is determined whether the two results are consistent. If they are not consistent, the preliminary evaluation results of the maximum available droop coefficient of a single machine are added as new constraints, and then the evaluation results of the maximum available droop coefficient of the offshore wind farm station and the maximum available droop coefficient of a single machine are obtained again, and this process is repeated until the two results are consistent.

[0012] Furthermore, according to the frequency time domain analytical expression, the maximum frequency deviation expression is solved, and the active output expressions of the wind turbine and the energy storage system during the frequency fault are obtained respectively, including:

[0013] According to the frequency time domain analytical expression, the maximum frequency deviation expression is obtained by solving the moment when its derivative is 0;

[0014] According to the frequency time domain analytical expression, after being multiplied by the droop coefficient of each wind turbine and energy storage system respectively, combined with their respective active outputs before the frequency fault, the active output expressions of the wind turbine and energy storage system during the frequency fault are obtained.

[0015] Furthermore, the measured data of the wind energy capture coefficient of the wind turbine is obtained, the wind energy capture coefficient of the wind turbine is fitted, and an approximate expression of the wind energy capture coefficient is obtained. After combining the wind speed data and the actual parameters of the wind turbine, an approximate expression of the mechanical power captured by the wind turbine is obtained, including:

[0016] Obtain measured data of the wind energy capture coefficient of the wind turbine generator set, and use the tip speed ratio of the wind turbine generator set as a variable to fit the wind energy capture coefficient of the wind turbine generator set to obtain a fitting coefficient;

[0017] According to the fitting coefficient, combined with air density, blade length, measured wind speed and rotor speed data, an approximate expression for capturing mechanical power of the wind turbine is obtained.

[0018] Furthermore, according to the active output expression and the approximate expression of mechanical power, the expression of the rotor speed of the wind turbine during the frequency fault and the expression of the state of charge of the energy storage system are solved respectively, including:

[0019] According to the active output expression of the energy storage system during the frequency fault, the state of charge expression of the energy storage system during the frequency fault is solved in combination with the state of charge model of the energy storage system;

[0020] According to the approximate expression of the mechanical power captured by the wind turbine and the active output expression of the wind turbine during the frequency fault, the expression of the rotor speed of the wind turbine during the frequency fault is solved in combination with the rotor motion model of the wind turbine.

[0021] Furthermore, according to the maximum frequency deviation expression and the active output expression, with minimizing the maximum frequency deviation as the optimization goal and with the overall active output of the offshore wind farm not exceeding the limit as the constraint condition, the preliminary evaluation result of the maximum available droop coefficient of the offshore wind farm is solved, including:

[0022] Construct an optimization model for the maximum available droop coefficient of an offshore wind farm: the optimization goal is to minimize the maximum frequency deviation, constraint 1 is that the overall active output of all wind turbines in the offshore wind farm does not exceed the upper limit, and constraint 2 is that the overall active output of all energy storage systems in the offshore wind farm does not exceed the upper limit;

[0023] The optimization model of the maximum available droop coefficient of the offshore wind farm is solved, and the optimization result is the preliminary evaluation result of the maximum available droop coefficient of the offshore wind farm.

[0024] Further, according to the preliminary evaluation result of the maximum available droop coefficient of the offshore wind farm, the expression of the rotor speed of the wind turbine and the expression of the state of charge of the energy storage system, with maximizing the droop coefficient of the offshore wind farm as the optimization goal, and with the active output of the wind turbine and the energy storage system not exceeding the limit and the rotor speed and state of charge not exceeding the limit as the constraint conditions, the preliminary evaluation result of the maximum available droop coefficient of a single unit of the wind turbine and the energy storage system is solved, including:

[0025] Construct an optimization model for the maximum available droop coefficient of a single wind turbine and energy storage system: The optimization goal is to maximize the droop coefficient of the offshore wind farm. Constraint 1 is that the active output of any wind turbine in the offshore wind farm does not exceed the upper limit. Constraint 2 is that the active output of any energy storage system in the offshore wind farm does not exceed the upper limit. Constraint 3 is that the rotor speed of any wind turbine in the offshore wind farm is not lower than the lower limit. Constraint 4 is that the state of charge of any energy storage system in the offshore wind farm is not lower than the lower limit.

[0026] The optimization model of the maximum available droop coefficient of a single unit of a wind turbine and an energy storage system is solved, and the optimization result is the preliminary evaluation result of the maximum available droop coefficient of a single unit of a wind turbine and an energy storage system.

[0027] Further, according to the sum of the preliminary evaluation result of the maximum available droop coefficient of the offshore wind farm and the preliminary evaluation result of the maximum available droop coefficient of a single machine, it is judged whether the two results meet the threshold range. If not, the preliminary evaluation result of the maximum available droop coefficient of a single machine is added as a new constraint condition, and then the evaluation result of the maximum available droop coefficient of the offshore wind farm and the evaluation result of the maximum available droop coefficient of a single machine are obtained again, and this process is repeated until the two results meet the threshold range, including:

[0028] Compare the sum of the preliminary evaluation result of the maximum available droop coefficient of the offshore wind farm and the preliminary evaluation result of the maximum available droop coefficient of a single unit, and when the difference between the two is within a threshold range, set the preliminary evaluation result of the maximum available droop coefficient of the offshore wind farm as the final result under the current working condition;

[0029] When the difference between the two does not meet the threshold range, the preliminary evaluation result of the maximum available droop coefficient of a single machine is added as a new constraint condition, and the evaluation result of the maximum available droop coefficient of the offshore wind farm station and the evaluation result of the maximum available droop coefficient of a single machine are solved cyclically until the two results meet the threshold range.

[0030] According to a second aspect of an embodiment of the present application, a device for evaluating a maximum available droop coefficient of an offshore wind farm is provided, comprising:

[0031] An acquisition module, for obtaining a time-domain analytical expression of a frequency of the power system during a frequency fault according to a frequency response model of the power system including the offshore wind farm;

[0032] The first solving module is used to solve the maximum frequency deviation expression according to the frequency time domain analytical expression, and simultaneously obtain the active output expressions of the wind turbine and the energy storage system during the frequency fault period;

[0033] A fitting module is used to obtain the measured data of the wind energy capture coefficient of the wind turbine, fit the wind energy capture coefficient of the wind turbine, obtain an approximate expression of the wind energy capture coefficient, and obtain an approximate expression of the mechanical power captured by the wind turbine by combining the wind speed data and the actual parameters of the wind turbine;

[0034] A second solving module is used to solve the wind turbine rotor speed expression and the energy storage system charge state expression during the frequency fault period according to the active output expression and the approximate expression of the mechanical power;

[0035] The third solution module is used to solve the preliminary evaluation result of the maximum available droop coefficient of the offshore wind farm station based on the maximum frequency deviation expression and the active output expression, with minimizing the maximum frequency deviation as the optimization goal and with the overall active output of the offshore wind farm station not exceeding the limit as the constraint condition;

[0036] The fourth solution module is used to solve the preliminary evaluation result of the maximum available droop coefficient of the wind turbine generator set and the energy storage system based on the preliminary evaluation result of the maximum available droop coefficient of the offshore wind farm station, the expression of the rotor speed of the wind turbine generator set and the expression of the state of charge of the energy storage system, with maximizing the droop coefficient of the offshore wind farm station as the optimization goal, and with the active output of the wind turbine generator set and the energy storage system not exceeding the limit and the rotor speed and state of charge not exceeding the limit as the constraint conditions, to solve the preliminary evaluation result of the maximum available droop coefficient of the single machine of the wind turbine generator set and the energy storage system;

[0037] The iterative optimization module is used to determine whether the preliminary evaluation results of the maximum available droop coefficient of the offshore wind farm station and the preliminary evaluation results of the maximum available droop coefficient of the single machine are consistent with each other. If they are inconsistent, the preliminary evaluation results of the maximum available droop coefficient of the single machine are added as new constraints, and then the evaluation results of the maximum available droop coefficient of the offshore wind farm station and the evaluation results of the maximum available droop coefficient of the single machine are obtained again, and this process is repeated until the two results are consistent.

[0038] According to a third aspect of an embodiment of the present application, there is provided an electronic device, including:

[0039] one or more processors;

[0040] A memory for storing one or more programs;

[0041] When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in the first aspect.

[0042] According to a fourth aspect of an embodiment of the present application, a computer-readable storage medium is provided, on which computer instructions are stored, and when the instructions are executed by a processor, the steps of the method described in the first aspect are implemented.

[0043] The technical solution provided by the embodiments of the present application may have the following beneficial effects:

[0044] The purpose of this application is to ensure that wind farms can maximize their frequency regulation potential without sacrificing system stability: the maximum available droop coefficient evaluation of wind farm stations and the maximum available droop coefficient evaluation of single machines included therein can maintain the stability of system frequency when the load changes by reasonably setting the droop coefficient, avoiding excessive fluctuations in system frequency due to over-regulation or under-regulation; the wind turbine rotor speed expression during frequency faults based on the wind turbine capture mechanical power approximate expression can help wind farms more effectively utilize wind energy resources and reduce energy losses caused by wind speed fluctuations. The energy storage system charge state expression can be combined with the capabilities of the energy storage system to more flexibly adjust power, extend the service life of energy storage equipment, and reduce maintenance costs. With the increase in the proportion of renewable energy, the power grid needs to adapt to more uncertainty and volatility. By evaluating the maximum available droop coefficient, the adaptability of the power grid to renewable energy fluctuations can be improved. Wind farms can participate in the electricity market by providing frequency regulation services, thereby increasing revenue sources and improving economic efficiency. By improving the frequency regulation capabilities of new energy, it can reduce dependence on traditional thermal power, hydropower and other power sources, and help promote the green transformation of the energy structure.

[0045] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0047] Figure 1 The figure is a flow chart of a method for evaluating a maximum available droop coefficient of an offshore wind farm according to an embodiment of the present invention.

[0048] Figure 2 This is the topology diagram of the nine-node power system.

[0049] Figure 3 The frequency response waveform diagrams according to the embodiments of the present invention are shown with different parameter settings.

[0050] Figure 4 The waveform diagrams are of active power output and rotor speed of a wind turbine according to an embodiment of the present invention under different parameter settings.

[0051] Figure 5 The figure is a flow chart of a device for evaluating a maximum available droop coefficient of an offshore wind farm according to an embodiment of the present invention.

[0052] Figure 6 The figure is a block diagram of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0053] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0054] The terms used in this application are for the purpose of describing specific embodiments only and are not intended to limit this application. The singular forms of "a", "said" and "the" used in this application and the appended claims are also intended to include plural forms unless the context clearly indicates other meanings. It should also be understood that the term "and / or" used herein refers to and includes any or all possible combinations of one or more associated listed items.

[0055] Figure 1 Flow chart of a method for evaluating the maximum available droop coefficient of an offshore wind farm according to an embodiment of the present invention; Figure 1 As shown, the method comprises the following steps:

[0056] S1: Based on the frequency response model of the power system including the offshore wind farm, the time domain analytical expression of the frequency of the power system during the frequency fault is obtained;

[0057] S2: according to the frequency time domain analytical expression, solving the maximum frequency deviation expression, and obtaining the active output expressions of the wind turbine and the energy storage system during the frequency fault period respectively;

[0058] S3: Obtain measured data of the wind energy capture coefficient of the wind turbine, fit the wind energy capture coefficient of the wind turbine, obtain an approximate expression of the wind energy capture coefficient, and obtain an approximate expression of the mechanical power captured by the wind turbine by combining the wind speed data and the actual parameters of the wind turbine;

[0059] S4: according to the active output expression and the approximate expression of mechanical power, respectively solving the expression of wind turbine rotor speed during frequency fault and the expression of energy storage system state of charge;

[0060] S5: According to the maximum frequency deviation expression and the active output expression, with minimizing the maximum frequency deviation as the optimization goal and with the overall active output of the offshore wind farm not exceeding the limit as the constraint condition, solve the preliminary evaluation result of the maximum available droop coefficient of the offshore wind farm;

[0061] S6: Based on the preliminary evaluation results of the maximum available droop coefficient of the offshore wind farm, the expression of the rotor speed of the wind turbine and the expression of the state of charge of the energy storage system, taking maximizing the droop coefficient of the offshore wind farm as the optimization goal, and taking the active output of the wind turbine and the energy storage system not exceeding the limit and the rotor speed and state of charge not exceeding the limit as the constraints, solving the preliminary evaluation results of the maximum available droop coefficient of a single unit of the wind turbine and the energy storage system;

[0062] S7: Based on the preliminary evaluation result of the maximum available droop coefficient of the offshore wind farm and the preliminary evaluation result of the maximum available droop coefficient of a single machine, determine whether the two results are consistent; if not, add the preliminary evaluation result of the maximum available droop coefficient of a single machine as a new constraint condition, and then obtain the evaluation result of the maximum available droop coefficient of the offshore wind farm and the evaluation result of the maximum available droop coefficient of a single machine again, and repeat this process until the two results are consistent.

[0063] Through the above-mentioned embodiments of the present invention, the maximum available droop coefficient evaluation of the offshore wind farm station and the preliminary evaluation of the maximum available droop coefficient of a single machine based on the expression of the rotor speed of the wind turbine set and the expression of the charge state of the energy storage system can adaptively adjust the droop coefficient. Therefore, the offshore wind farm can not only maintain the stable operation of the internal power generation units, but also provide effective frequency support when the power grid needs it, which is crucial for future power systems based on renewable energy.

[0064] In a specific implementation of S1: according to a frequency response model of a power system including an offshore wind farm, a time-domain analytical expression of the frequency of the power system during a frequency fault is obtained.

[0065] Specifically, the frequency response model of the power system including offshore wind farms during frequency fault is:

[0066]

[0067] Where Δf is the system frequency deviation, H is the system inertia time constant, and D is the system damping time constant; ΔP SG is the additional active power output of the thermal power station during the frequency fault, ΔP WF is the additional active power generated by the offshore wind farm during the frequency fault, ΔP D is the disturbance power in the system, and s is the Laplace operator. ΔP WF The expression is

[0068] ΔP WF =-D P Δf

[0069] Among them, D P is the overall droop coefficient of the offshore wind farm, which is obtained by aggregating the droop coefficients of each wind turbine and the energy storage system.

[0070] The frequency domain form of the power system frequency response model is:

[0071]

[0072] The definitions of the parameters are as follows:

[0073]

[0074] The time domain form of the power system frequency response model is:

[0075]

[0076] The definitions of the parameters are as follows:

[0077] Through the above-mentioned embodiments of the present invention, a time-domain analytical expression of the frequency of the power system during a frequency fault is obtained, which helps to quantify the supporting effect of the droop coefficient of the offshore wind farm station on the frequency of the power system and lays a mathematical foundation for the evaluation of the maximum droop coefficient of the offshore wind farm station.

[0078] In the specific implementation of S2: according to the frequency time domain analytical expression, the maximum frequency deviation expression is solved, and the active output expressions of the wind turbine and the energy storage system during the frequency fault are obtained respectively. This step includes the following sub-steps:

[0079] S21: According to the frequency-time domain analytical expression, the maximum frequency deviation expression is obtained by solving the moment when its derivative is 0.

[0080] Specifically, the time when the derivative of the time domain analytical expression of the system frequency model is 0 is

[0081]

[0082] According to this moment, the expression of maximum frequency deviation can be derived:

[0083]

[0084] S22: According to the frequency-time domain analytical expression, after multiplying with the droop coefficient of each wind turbine generator set and energy storage system respectively, combined with their respective active outputs before the frequency fault, the active output expression of the wind turbine generator set and energy storage system during the frequency fault is obtained.

[0085] Specifically, the active output expression of the wind turbine during the frequency fault is:

[0086] P We,i =P Ini,i -D P,i Δf

[0087] Among them, D P,iis the droop coefficient of the wind turbine, the subscript i represents the wind turbine number, P Ini,i It is the active power output of the wind turbine before the frequency fault occurs.

[0088] The active output expression of the energy storage system during frequency fault is:

[0089] P ESS,j =P Ini,j -D P,j Δf

[0090] Among them, D P,j is the droop coefficient of the energy storage system, the subscript j represents the energy storage system number, P Ini,j It is the active output of the energy storage system before the frequency fault occurs.

[0091] Through the above-mentioned embodiments of the present invention, the maximum frequency deviation expression and the active output expression of the wind turbine and the energy storage system during the frequency fault are obtained, which is helpful to evaluate the influence of the droop coefficient of the offshore wind farm on the frequency of the power system and the influence on the active output of the wind turbine and the energy storage system during the frequency fault.

[0092] In the specific implementation of S3: the measured data of the wind energy capture coefficient of the wind turbine is obtained, the wind energy capture coefficient of the wind turbine is fitted, an approximate expression of the wind energy capture coefficient is obtained, and an approximate expression of the mechanical power captured by the wind turbine is obtained by combining the wind speed data and the actual parameters of the wind turbine. This step includes the following sub-steps:

[0093] S31: Acquire measured data of the wind energy capture coefficient of the wind turbine generator set, and fit the wind energy capture coefficient of the wind turbine generator set with the tip speed ratio of the wind turbine generator set as a variable to obtain a fitting coefficient.

[0094] Specifically, the measured data of wind energy capture coefficient of wind turbines are obtained, and the wind energy capture coefficient of wind turbines can be fitted as follows:

[0095] C P =a 0 λ 2 +c 0

[0096] Among them, λ is the tip speed ratio of the wind turbine, a 0 and c 0 is the fitting coefficient of wind energy capture coefficient.

[0097] S32: According to the fitting coefficient, combined with air density, blade length, measured wind speed and rotor speed data, an approximate expression for capturing mechanical power of the wind turbine is obtained.

[0098] Specifically, the approximate expression for the mechanical power captured by the wind turbine is:

[0099]

[0100] Where ρ is the air density, R is the blade length, v is the wind speed, ω r is the rotor speed, a and c are the fitting coefficients of the wind turbine to capture the mechanical power.

[0101] Through the above embodiments of the present invention, an approximate expression for mechanical power captured by a wind turbine is obtained, which helps to further derive the expression for the rotor speed of the wind turbine during a frequency fault and solves the problem of excessive complexity of the mechanical power captured by the wind turbine.

[0102] In the specific implementation of S4: according to the active output expression and the approximate expression of mechanical power, the expression of the rotor speed of the wind turbine during the frequency fault and the expression of the state of charge of the energy storage system are solved respectively. This step includes the following sub-steps:

[0103] S41: Solving the state of charge expression of the energy storage system during the frequency fault period according to the active output expression of the energy storage system during the frequency fault period in combination with the state of charge model of the energy storage system.

[0104] Specifically, the state of charge expression of the energy storage system during frequency fault is:

[0105]

[0106] Among them, η j is the charging and discharging power of the energy storage system, E n Represents the rated energy of the energy storage system, SOC Ini,j It is the charge state of the energy storage system before the frequency fault occurs.

[0107] S42: solving the expression of the wind turbine rotor speed during the frequency fault period according to the approximate expression of the mechanical power captured by the wind turbine and the expression of the active power output of the wind turbine during the frequency fault period in combination with the wind turbine rotor motion model.

[0108] Specifically, the wind turbine rotor motion model is:

[0109]

[0110] Among them, J WT,i is the moment of inertia of the wind turbine. Combined with the above power expression, the rotor motion equation can be transformed into

[0111]

[0112] Where y represents the square of the rotor speed. The above equation is a linear differential equation, so its analytical solution is

[0113]

[0114] The definitions of the parameters are as follows:

[0115]

[0116] Through the above-mentioned embodiments of the present invention, the expression of the rotor speed of the wind turbine and the charge state of the energy storage system during the frequency fault are obtained, which provides a theoretical basis for preventing excessive deceleration of the rotor and excessive discharge of energy storage while evaluating the maximum droop coefficient of the offshore wind farm, and improves the accuracy of the evaluation strategy.

[0117] In the specific implementation of S5: according to the maximum frequency deviation expression and the active output expression, minimizing the maximum frequency deviation is taken as the optimization goal, and the overall active output of the offshore wind farm station does not exceed the limit is taken as the constraint condition, and the preliminary evaluation result of the maximum available droop coefficient of the offshore wind farm station is solved.

[0118] Specifically, the optimization goal is to minimize the maximum frequency deviation:

[0119]

[0120] Constraint 1 is that the overall active output of all wind turbines in the offshore wind farm does not exceed the upper limit:

[0121]

[0122] Constraint 2 is that the overall active output of all energy storage systems in the offshore wind farm does not exceed the upper limit:

[0123]

[0124] The optimization result is a preliminary evaluation result of the maximum available droop coefficient of the offshore wind farm.

[0125] Through the above-mentioned embodiments of the present invention, a preliminary evaluation result of the maximum available droop coefficient of the offshore wind farm is obtained, which helps the offshore wind farm to play the best supporting effect on the power system frequency while ensuring power safety.

[0126] In the specific implementation of S6: based on the preliminary evaluation results of the maximum available droop coefficient of the offshore wind farm, the expression of the rotor speed of the wind turbine and the expression of the state of charge of the energy storage system, with maximizing the droop coefficient of the offshore wind farm as the optimization goal, and with the active output of the wind turbine and the energy storage system not exceeding the limit and the rotor speed and state of charge not exceeding the limit as constraints, the preliminary evaluation results of the maximum available droop coefficient of a single machine of the wind turbine and the energy storage system are solved.

[0127] Specifically, the optimization objective is to maximize the droop coefficient of the offshore wind farm:

[0128]

[0129] Constraint 1 is that the active output of any wind turbine in the offshore wind farm does not exceed the upper limit:

[0130] P Ini,i +D P,i |Δf nadir |≤P Max,i

[0131] Constraint 2 is that the active output of any energy storage system in the offshore wind farm does not exceed the upper limit:

[0132] P Ini,j +D P,j |Δf nadir |≤P Max,j

[0133] Constraint 3 is that the rotor speed of any wind turbine in the offshore wind farm shall not be lower than the lower limit:

[0134]

[0135] in,

[0136]

[0137] Constraint 4 is that the state of charge of any energy storage system in the offshore wind farm is not less than the lower limit:

[0138]

[0139] The optimization result is a preliminary evaluation result of the maximum available droop coefficient of the wind turbine and the energy storage system.

[0140] Through the above-mentioned embodiments of the present invention, preliminary evaluation results of the maximum available droop coefficient of a single unit of a wind turbine and an energy storage system are obtained, which helps offshore wind farms to provide the best support for the frequency of the power system while ensuring power safety, speed safety and charge state safety.

[0141] In the specific implementation of S7: based on the sum of the preliminary evaluation results of the maximum available droop coefficient of the offshore wind farm and the preliminary evaluation results of the maximum available droop coefficient of a single machine, determine whether the two results meet the threshold range; if not, add the preliminary evaluation results of the maximum available droop coefficient of a single machine as a new constraint condition, and then obtain the maximum available droop coefficient evaluation results of the offshore wind farm and the maximum available droop coefficient evaluation results of a single machine again, and repeat this process until the two results meet the threshold range.

[0142] Specifically, the sum of the preliminary evaluation results of the maximum available droop coefficient of the offshore wind farm and the preliminary evaluation results of the maximum available droop coefficient of a single machine are compared. When the difference between the two is within the threshold range, this indicates that the active output of each wind turbine unit and the energy storage system under the preliminary evaluation results of the maximum available droop coefficient of the offshore wind farm does not exceed the upper limit, and the rotor speed of each wind turbine unit and the state of charge of the energy storage system are not lower than the lower limit. At this time, the preliminary evaluation results of the maximum available droop coefficient of the offshore wind farm are the final results under the current operating conditions. When the difference between the two does not meet the threshold range, this indicates that the preliminary evaluation results of the maximum available droop coefficient of the offshore wind farm conflict with the safety constraints of each wind turbine unit and the energy storage system. At this time, the preliminary evaluation results cannot be used as the final results under the current operating conditions, and the preliminary evaluation results of the maximum available droop coefficient of a single machine need to be added as a new constraint condition, and the evaluation results of the maximum available droop coefficient of the offshore wind farm and the evaluation results of the maximum available droop coefficient of a single machine are solved cyclically until the two results meet the threshold range.

[0143] Through the above-mentioned embodiments of the present invention, the final result of the maximum available droop coefficient of the offshore wind farm is obtained. This process fully considers the power system frequency model, the wind turbine model and the energy storage system model, and optimizes the support effect of the offshore wind farm on the power system frequency while ensuring power safety, speed safety and charge state safety. At the same time, a complex optimization problem is decoupled into site optimization, single-machine optimization and cyclic optimization in sequence, which effectively improves the solution efficiency. Figure 2 It is a nine-node power system topology diagram, which includes three thermal power plants with a capacity of 1000MVA and one wind farm with a capacity of 1000MVA, and the total active load in the system is 1800MW. The wind farm contains 3 rows of 666 doubly fed wind turbines, each with a rated power of 1.5MW. The wind speeds at the first row of wind turbines to the third row of wind turbines are 11m / s, 12m / s and 9m / s, respectively, and the active outputs of these wind turbines before the fault are 163MW, 213MW and 90MW, respectively. In the scenario where the active load in the power system suddenly increases by 300MW, three groups of droop coefficients are set to verify the effectiveness of the embodiment of the present invention. According to the droop coefficient 1, each wind turbine can provide active power support for the power system within 40 seconds, and the minimum rotor speed is maintained at more than 90% of the initial speed. For droop coefficients 2 and 3, the minimum rotor speed thresholds are set to 0.9pu and 0.85pu, respectively. Figure 3 and Figure 4 is based on Figure 2 The power system in FIG. 1 is a simulation verification result diagram of an embodiment of the present invention, wherein Figure 3 is a frequency response waveform diagram according to an embodiment of the present invention under different parameter settings, Figure 4The waveform diagrams of active power output and rotor speed of a wind turbine according to an embodiment of the present invention under different parameter settings are as follows: Figure 4 (a) rotor speed of the first exhaust fan (b) rotor speed of the second exhaust fan (c) rotor speed of the third exhaust fan (d) active output of the first exhaust fan (e) active output of the second exhaust fan (f) active output of the third exhaust fan. The simulation results show that under the droop coefficient 1, the wind turbine can continue to provide power support to the power system while maintaining the rotor speed higher than 90% of the initial speed; droop coefficients 2 and 3 can maintain the rotor speed above 0.9pu and 0.85pu respectively while ensuring active power support. Therefore, through the above embodiments of the present invention, through the adaptively adjusted droop coefficient, the offshore wind farm can not only maintain the stable operation of the internal power generation unit, but also provide effective frequency support when the power grid needs it.

[0144] Corresponding to the aforementioned embodiment of the method for evaluating the maximum available droop coefficient of an offshore wind farm, the present application also provides an embodiment of a device for evaluating the maximum available droop coefficient of an offshore wind farm.

[0145] Figure 5 is a block diagram of a device for evaluating the maximum available droop coefficient of an offshore wind farm according to an embodiment of the present invention. Figure 5 , the device comprises:

[0146] An acquisition module 1 is used to obtain a frequency time-domain analytical expression of the power system during a frequency fault according to a frequency response model of the power system including the offshore wind farm;

[0147] The first solving module 2 is used to solve the maximum frequency deviation expression according to the frequency time domain analytical expression, and simultaneously obtain the active output expressions of the wind turbine and the energy storage system during the frequency fault period;

[0148] Fitting module 3 is used to obtain measured data of wind energy capture coefficient of wind turbine, fit the wind energy capture coefficient of wind turbine, obtain an approximate expression of wind energy capture coefficient, and obtain an approximate expression of mechanical power captured by wind turbine by combining wind speed data and actual parameters of wind turbine;

[0149] The second solution module 4 is used to solve the wind turbine rotor speed expression and the energy storage system charge state expression during the frequency fault period according to the active output expression and the approximate expression of mechanical power;

[0150] The third solution module 5 is used to solve the preliminary evaluation result of the maximum available droop coefficient of the offshore wind farm station based on the maximum frequency deviation expression and the active output expression, with minimizing the maximum frequency deviation as the optimization goal and with the overall active output of the offshore wind farm station not exceeding the limit as the constraint condition;

[0151] The fourth solution module 6 is used to solve the preliminary evaluation result of the maximum available droop coefficient of the offshore wind farm station, the expression of the rotor speed of the wind turbine set and the expression of the state of charge of the energy storage system, with maximizing the droop coefficient of the offshore wind farm station as the optimization goal, and with the active output of the wind turbine set and the energy storage system not exceeding the limit and the rotor speed and state of charge not exceeding the limit as the constraint conditions, to solve the preliminary evaluation result of the maximum available droop coefficient of the single machine of the wind turbine set and the energy storage system;

[0152] Iterative optimization module 7 is used to determine whether the preliminary evaluation result of the maximum available droop coefficient of the offshore wind farm station and the preliminary evaluation result of the maximum available droop coefficient of the single machine are consistent with each other. If they are inconsistent, the preliminary evaluation result of the maximum available droop coefficient of the single machine is added as a new constraint condition, and then the evaluation result of the maximum available droop coefficient of the offshore wind farm station and the evaluation result of the maximum available droop coefficient of the single machine are obtained again, and this process is repeated until the two results are consistent.

[0153] Regarding the device in the above embodiment, the specific manner in which each module performs operations has been described in detail in the embodiment of the method, and will not be elaborated here.

[0154] For the device embodiment, since it basically corresponds to the method embodiment, the relevant parts can refer to the partial description of the method embodiment. The device embodiment described above is only schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present application scheme. A person of ordinary skill in the art can understand and implement it without paying any creative work.

[0155] Accordingly, the present application also provides an electronic device, comprising: one or more processors; a memory for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the above-mentioned maximum available droop coefficient evaluation method for an offshore wind farm. Figure 6 As shown, it is a hardware structure diagram of any device with data processing capability where a device for evaluating the maximum available droop coefficient of an offshore wind farm provided by an embodiment of the present invention is located, except Figure 6 In addition to the processor and memory shown, any device with data processing capability in which the apparatus in the embodiment is located may also include other hardware, generally based on the actual functions of the device with data processing capability, which will not be described in detail.

[0156] Accordingly, the present application also provides a computer-readable storage medium having computer instructions stored thereon, which, when executed by a processor, implement the above-mentioned maximum available droop coefficient evaluation method for an offshore wind farm. The computer-readable storage medium may be an internal storage unit of any device with data processing capability described in any of the foregoing embodiments, such as a hard disk or a memory. The computer-readable storage medium may also be an external storage device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), an SD card, a flash card (Flash Card), etc. equipped on the device. Furthermore, the computer-readable storage medium may also include both an internal storage unit and an external storage device of any device with data processing capability. The computer-readable storage medium is used to store the computer program and other programs and data required by any device with data processing capability, and may also be used to temporarily store data that has been output or is to be output.

[0157] Those skilled in the art will readily appreciate other embodiments of the present application after considering the description and practicing the contents disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The description and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the claims.

[0158] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for evaluating the maximum available droop coefficient of an offshore wind farm, characterized in that: include: According to the frequency response model of the power system including the offshore wind farm, the time-domain analytical expression of the frequency of the power system during the frequency fault is obtained; According to the frequency time domain analytical expression, the maximum frequency deviation expression is solved, and the active output expressions of the wind turbine and the energy storage system during the frequency fault are obtained respectively; Obtain measured data of wind energy capture coefficient of wind turbines, fit the wind energy capture coefficient of wind turbines, obtain an approximate expression of wind energy capture coefficient, and obtain an approximate expression of mechanical power captured by wind turbines by combining wind speed data and actual parameters of wind turbines; According to the active output expression and the approximate expression of mechanical power, respectively solving the expression of wind turbine rotor speed during frequency fault and the expression of energy storage system charge state; According to the maximum frequency deviation expression and the active output expression, with minimizing the maximum frequency deviation as the optimization goal and with the overall active output of the offshore wind farm not exceeding the limit as the constraint condition, the preliminary evaluation result of the maximum available droop coefficient of the offshore wind farm is solved; According to the preliminary evaluation results of the maximum available droop coefficient of the offshore wind farm, the expression of the rotor speed of the wind turbine and the expression of the state of charge of the energy storage system, taking maximizing the droop coefficient of the offshore wind farm as the optimization goal, and taking the active output of the wind turbine and the energy storage system not exceeding the limit and the rotor speed and state of charge not exceeding the limit as the constraints, the preliminary evaluation results of the maximum available droop coefficient of a single unit of the wind turbine and the energy storage system are solved; According to the preliminary evaluation results of the maximum available droop coefficient of the offshore wind farm station and the preliminary evaluation results of the maximum available droop coefficient of a single machine, it is determined whether the two results are consistent. If they are not consistent, the preliminary evaluation results of the maximum available droop coefficient of a single machine are added as new constraints, and then the evaluation results of the maximum available droop coefficient of the offshore wind farm station and the maximum available droop coefficient of a single machine are obtained again, and this process is repeated until the two results are consistent.

2. A method for evaluating the maximum available droop coefficient of an offshore wind farm according to claim 1, characterized in that: According to the frequency time domain analytical expression, the maximum frequency deviation expression is solved, and the active output expressions of the wind turbine and the energy storage system during the frequency fault are obtained respectively, including: According to the frequency time domain analytical expression, the maximum frequency deviation expression is obtained by solving the moment when its derivative is 0; According to the frequency time domain analytical expression, after being multiplied by the droop coefficient of each wind turbine and energy storage system respectively, combined with their respective active outputs before the frequency fault, the active output expressions of the wind turbine and energy storage system during the frequency fault are obtained.

3. A method for evaluating the maximum available droop coefficient of an offshore wind farm according to claim 1, characterized in that: Obtain the measured data of the wind energy capture coefficient of the wind turbine, fit the wind energy capture coefficient of the wind turbine, obtain the approximate expression of the wind energy capture coefficient, and obtain the approximate expression of the mechanical power captured by the wind turbine by combining the wind speed data and the actual parameters of the wind turbine, including: Obtain measured data of the wind energy capture coefficient of the wind turbine generator set, and use the tip speed ratio of the wind turbine generator set as a variable to fit the wind energy capture coefficient of the wind turbine generator set to obtain a fitting coefficient; According to the fitting coefficient, combined with air density, blade length, measured wind speed and rotor speed data, an approximate expression for capturing mechanical power of the wind turbine is obtained.

4. A method for evaluating the maximum available droop coefficient of an offshore wind farm according to claim 1, characterized in that: According to the active output expression and the approximate expression of mechanical power, the expression of the rotor speed of the wind turbine during the frequency fault and the expression of the state of charge of the energy storage system are solved respectively, including: According to the active output expression of the energy storage system during the frequency fault, the state of charge expression of the energy storage system during the frequency fault is solved in combination with the state of charge model of the energy storage system; According to the approximate expression of the mechanical power captured by the wind turbine and the active output expression of the wind turbine during the frequency fault, the expression of the rotor speed of the wind turbine during the frequency fault is solved in combination with the rotor motion model of the wind turbine.

5. A method for evaluating the maximum available droop coefficient of an offshore wind farm according to claim 1, characterized in that: According to the maximum frequency deviation expression and active output expression, with minimizing the maximum frequency deviation as the optimization goal and with the overall active output of the offshore wind farm not exceeding the limit as the constraint condition, the preliminary evaluation results of the maximum available droop coefficient of the offshore wind farm are solved, including: An optimization model for the maximum available droop coefficient of an offshore wind farm is constructed. The optimization objective is to minimize the maximum frequency deviation. Constraint 1 is that the overall active output of all wind turbines in the offshore wind farm does not exceed the upper limit. Constraint 2 is that the overall active output of all energy storage systems in the offshore wind farm does not exceed the upper limit. The optimization model of the maximum available droop coefficient of the offshore wind farm is solved, and the optimization result is the preliminary evaluation result of the maximum available droop coefficient of the offshore wind farm.

6. A method for evaluating the maximum available droop coefficient of an offshore wind farm according to claim 1, characterized in that: According to the preliminary evaluation results of the maximum available droop coefficient of the offshore wind farm, the expression of the rotor speed of the wind turbine and the expression of the state of charge of the energy storage system, the optimization goal is to maximize the droop coefficient of the offshore wind farm, and the constraints of the active output of the wind turbine and the energy storage system and the rotor speed and state of charge are not exceeded. The preliminary evaluation results of the maximum available droop coefficient of a single unit of the wind turbine and the energy storage system are solved, including: Construct a single-machine maximum available droop coefficient optimization model for wind turbines and energy storage systems. The optimization goal is to maximize the droop coefficient of the offshore wind farm. Constraint 1 is that the active output of any wind turbine in the offshore wind farm does not exceed the upper limit. Constraint 2 is that the active output of any energy storage system in the offshore wind farm does not exceed the upper limit. Constraint 3 is that the rotor speed of any wind turbine in the offshore wind farm is not lower than the lower limit. Constraint 4 is that the state of charge of any energy storage system in the offshore wind farm is not lower than the lower limit. The optimization model of the maximum available droop coefficient of a single unit of a wind turbine and an energy storage system is solved, and the optimization result is the preliminary evaluation result of the maximum available droop coefficient of a single unit of a wind turbine and an energy storage system.

7. A method for evaluating the maximum available droop coefficient of an offshore wind farm according to claim 1, characterized in that: According to the sum of the preliminary evaluation result of the maximum available droop coefficient of the offshore wind farm and the preliminary evaluation result of the maximum available droop coefficient of a single machine, it is judged whether the two results meet the threshold range. If not, the preliminary evaluation result of the maximum available droop coefficient of a single machine is added as a new constraint condition, and then the maximum available droop coefficient evaluation result of the offshore wind farm and the maximum available droop coefficient evaluation result of a single machine are obtained again, and this process is repeated until the two results meet the threshold range, including: Compare the sum of the preliminary evaluation result of the maximum available droop coefficient of the offshore wind farm and the preliminary evaluation result of the maximum available droop coefficient of a single unit, and when the difference between the two is within a threshold range, set the preliminary evaluation result of the maximum available droop coefficient of the offshore wind farm as the final result under the current working condition; When the difference between the two does not meet the threshold range, the preliminary evaluation result of the maximum available droop coefficient of a single machine is added as a new constraint condition, and the evaluation result of the maximum available droop coefficient of the offshore wind farm station and the evaluation result of the maximum available droop coefficient of a single machine are solved cyclically until the two results meet the threshold range.

8. A device for evaluating the maximum available droop coefficient of an offshore wind farm, characterized in that: include: An acquisition module, for obtaining a time-domain analytical expression of a frequency of the power system during a frequency fault according to a frequency response model of the power system including the offshore wind farm; The first solving module is used to solve the maximum frequency deviation expression according to the frequency time domain analytical expression, and simultaneously obtain the active output expressions of the wind turbine and the energy storage system during the frequency fault period; A fitting module is used to obtain the measured data of the wind energy capture coefficient of the wind turbine, fit the wind energy capture coefficient of the wind turbine, obtain an approximate expression of the wind energy capture coefficient, and obtain an approximate expression of the mechanical power captured by the wind turbine by combining the wind speed data and the actual parameters of the wind turbine; A second solving module is used to solve the wind turbine rotor speed expression and the energy storage system charge state expression during the frequency fault period according to the active output expression and the approximate expression of the mechanical power; The third solution module is used to solve the preliminary evaluation result of the maximum available droop coefficient of the offshore wind farm station based on the maximum frequency deviation expression and the active output expression, with minimizing the maximum frequency deviation as the optimization goal and with the overall active output of the offshore wind farm station not exceeding the limit as the constraint condition; The fourth solution module is used to solve the preliminary evaluation result of the maximum available droop coefficient of the wind turbine generator set and the energy storage system based on the preliminary evaluation result of the maximum available droop coefficient of the offshore wind farm station, the expression of the rotor speed of the wind turbine generator set and the expression of the state of charge of the energy storage system, with maximizing the droop coefficient of the offshore wind farm station as the optimization goal, and with the active output of the wind turbine generator set and the energy storage system not exceeding the limit and the rotor speed and state of charge not exceeding the limit as the constraint conditions, to solve the preliminary evaluation result of the maximum available droop coefficient of the single machine of the wind turbine generator set and the energy storage system; The iterative optimization module is used to determine whether the preliminary evaluation results of the maximum available droop coefficient of the offshore wind farm station and the preliminary evaluation results of the maximum available droop coefficient of the single machine are consistent with each other. If they are inconsistent, the preliminary evaluation results of the maximum available droop coefficient of the single machine are added as new constraints, and then the evaluation results of the maximum available droop coefficient of the offshore wind farm station and the evaluation results of the maximum available droop coefficient of the single machine are obtained again, and this process is repeated until the two results are consistent.

9. An electronic device, characterized in that: include: one or more processors; A memory for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having computer instructions stored thereon, characterized in that: When the instruction is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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