WO2019100721A1 - 高电压穿越能力仿真评估模型、基于其的仿真评估方法及储存介质 - Google Patents

高电压穿越能力仿真评估模型、基于其的仿真评估方法及储存介质 Download PDF

Info

Publication number
WO2019100721A1
WO2019100721A1 PCT/CN2018/093806 CN2018093806W WO2019100721A1 WO 2019100721 A1 WO2019100721 A1 WO 2019100721A1 CN 2018093806 W CN2018093806 W CN 2018093806W WO 2019100721 A1 WO2019100721 A1 WO 2019100721A1
Authority
WO
WIPO (PCT)
Prior art keywords
wind turbine
model
high voltage
stator
rotor
Prior art date
Application number
PCT/CN2018/093806
Other languages
English (en)
French (fr)
Inventor
褚景春
袁凌
潘磊
陈文超
焦冲
谢法
杜雯
李彦平
王千
蔺雪峰
丁岩
Original Assignee
国电联合动力技术有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 国电联合动力技术有限公司 filed Critical 国电联合动力技术有限公司
Priority to US16/609,743 priority Critical patent/US11288422B2/en
Publication of WO2019100721A1 publication Critical patent/WO2019100721A1/zh
Priority to PH12019502494A priority patent/PH12019502494A1/en
Priority to ZA2019/07434A priority patent/ZA201907434B/en

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F30/00—Computer-aided design [CAD]
    • G06F30/20—Design optimisation, verification or simulation
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Electricity, gas or water supply
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2111/00—Details relating to CAD techniques
    • G06F2111/10—Numerical modelling
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F2113/00—Details relating to the application field
    • G06F2113/06—Wind turbines or wind farms
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02P—CONTROL OR REGULATION OF ELECTRIC MOTORS, ELECTRIC GENERATORS OR DYNAMO-ELECTRIC CONVERTERS; CONTROLLING TRANSFORMERS, REACTORS OR CHOKE COILS
    • H02P9/00—Arrangements for controlling electric generators for the purpose of obtaining a desired output
    • H02P9/10—Control effected upon generator excitation circuit to reduce harmful effects of overloads or transients, e.g. sudden application of load, sudden removal of load, sudden change of load
    • H02P9/107—Control effected upon generator excitation circuit to reduce harmful effects of overloads or transients, e.g. sudden application of load, sudden removal of load, sudden change of load for limiting effects of overloads

Definitions

  • the present disclosure relates to the technical field of wind turbines, and in particular to a high voltage ride through capability simulation evaluation model, a simulation evaluation method based on the model, and a storage medium.
  • the wind turbine should have the capability of continuous operation without off-grid within the specified voltage and time range, and quickly realize power recovery after the voltage returns to normal. During the fault period, the wind turbine should provide inductive reactive current support to assist the grid voltage recovery. Specific requirements are as follows:
  • the wind turbine should have the capability of continuous operation for 10s without off-grid when the voltage at the grid connection point of the unit rises to 1.15pu;
  • the purpose of the present disclosure is to provide a high voltage ride through capability simulation evaluation model, a simulation evaluation method based thereon, and a storage medium, which can simulate a high voltage fault and can evaluate the operating state of the wind turbine during the fault process to achieve Verify that the wind turbine has high voltage ride through capability.
  • the present disclosure provides a high voltage ride through capability simulation evaluation model, including a wind turbine aerodynamic model, a torque control model, a converter model, and a high voltage fault occurrence device model; the wind turbine aerodynamic model Configuring to calculate an airflow input power based on the input initialization evaluation parameter; the torque control model configured to calculate a rotor electromagnetic torque based on the airflow input power; the high voltage fault occurrence device model configured to be input based
  • the initialization evaluation parameter simulates a high voltage fault and outputs a given voltage on the low voltage side of the transformer; the converter model is configured to calculate the high voltage according to the input current of the air flow, the electromagnetic torque of the rotor, and the given voltage of the low voltage side of the transformer. Stator reactive current, active power and reactive power of the wind turbine during voltage faults.
  • the wind turbine aerodynamic model is further configured to obtain input wind turbine blade length, wind speed, air density, wind turbine blade angular velocity, and wind energy availability
  • Initializing the evaluation parameters includes: the wind turbine blade length, the wind speed, the air density, the wind turbine blade angular velocity, and the wind energy availability; obtaining a leaf according to a ratio of the blade tip line speed to the wind speed a tip speed ratio; bringing the wind turbine blade length, the wind speed, the air density, the wind energy availability, the blade pitch angle, and the tip speed ratio to a preset airflow input power
  • the calculation formula is calculated to obtain the airflow input power.
  • the input power P m air flow of the air stream input power is calculated as follows: Wherein P m is the airflow input power, ⁇ is the pi, r b is the wind turbine blade length, v w is the wind speed, ⁇ is the air density, and ⁇ is the tip speed ratio, ie The ratio of the tip line speed to the wind speed, w b is the wind turbine blade angular velocity, ⁇ is the blade pitch angle, and c p is the wind energy availability.
  • the torque control model is further configured to bring the obtained rotor mechanical inertia, rotor motion damping coefficient, and rotor mechanical angular velocity into the torque control model
  • the preset rotor electromagnetic torque calculation formula is calculated to obtain the rotor electromagnetic torque.
  • the rotor electromagnetic torque calculation formula of the rotor electromagnetic torque T e is as follows: Where T e is the rotor electromagnetic torque, P m is the air flow input power, J r is the rotor mechanical inertia, k r is the rotor motion damping coefficient, and w rm is the rotor mechanical angular velocity .
  • the high voltage fault occurrence device model is further configured to obtain an input series reactor impedance value, a grid impedance, and a wind turbine capacity, wherein the initialization evaluation
  • the parameters include: an impedance value of the series reactor, the grid impedance, and the wind turbine capacity; bringing the impedance value of the series reactor, the grid impedance, and the wind turbine capacity to a preset configuration Calculate the formula for calculating the voltage on the low-voltage side of the transformer that simulates a high-voltage fault, and output the calculated voltage at the low-voltage side of the transformer.
  • the low voltage side given voltage of the transformer low voltage side given voltage u s is calculated as follows: Where u s is the given voltage on the low voltage side of the transformer, that is, the stator voltage of the converter, X 1 is the impedance value of the series reactor, X grid is the impedance of the grid, and S WT is the wind turbine capacity.
  • the converter model is further configured to obtain a q-axis stator flux linkage, a preset stator self-inductance, a preset stator self-inductance, and The preset q-axis rotor current is brought into a preset stator reactive current calculation formula to calculate the stator reactive current.
  • the converter model is further configured to calculate the obtained stator rotational speed, the airflow input power, the rotor electromagnetic torque, and the low voltage side given voltage of the transformer into a preset active power calculation formula for calculation Obtaining the active power.
  • the converter model is further configured to obtain the obtained d-axis rotor current, d-axis stator voltage, stator mutual inductance, the q-axis rotor current, the stator rotational speed, the airflow input power, and the rotor electromagnetic rotation The moment is brought into a preset reactive power calculation formula for calculation to obtain the reactive power.
  • stator reactive current calculation formula of the stator reactive current i qs is as follows: Where i qs is the q-axis stator current, that is, the stator reactive current, ⁇ qs is the q-axis stator flux linkage, and L S and L M are respectively the stator self-inductance and the stator mutual inductance, i qr For the q-axis rotor current.
  • the active power calculation formula and the reactive power calculation formula of the active power P S and the reactive power Q S are respectively as follows: Wherein P S is the active power, Q S is the reactive power, P m is the air flow input power, T e is the rotor electromagnetic torque, ⁇ s is the stator rotational speed, i dr And i qr are the d-axis rotor current and the q-axis rotor current, respectively, v ds is the d-axis stator voltage, and L M is the stator mutual inductance.
  • the present disclosure provides a high voltage ride through capability simulation evaluation method based on the above high voltage ride through capability simulation evaluation model, including the following steps: S1.
  • the wind turbine aerodynamic model calculates air according to an initial initialization evaluation parameter.
  • S2 according to the obtained airflow input power, the rotor electromagnetic torque is obtained by the torque control model calculation;
  • S3, the high voltage fault occurrence device model simulates a high voltage fault according to the input initialization evaluation parameter, and The output voltage of the low-voltage side of the output transformer;
  • the converter model calculates the stator reactive current of the wind turbine during the high-voltage fault according to the input power of the airflow, the electromagnetic torque of the rotor, and the given voltage of the low-voltage side of the transformer , active power and reactive power;
  • S5 determining whether the wind turbine has high voltage ride-through capability according to the obtained voltage of the low-voltage side of the transformer, the stator reactive current, the active power and the reactive power.
  • the wind turbine aerodynamic model calculates the airflow input power according to the input initialization evaluation parameter, including: the wind turbine aerodynamic model obtains an input. Wind turbine blade length, wind speed, air density, wind turbine blade angular velocity, and wind energy availability, wherein the initial evaluation parameters include: the wind turbine blade length, the wind speed, the air density, and the wind turbine blade angular velocity And the wind energy availability; the wind turbine aerodynamic model obtains a tip speed ratio according to a ratio of the blade tip line speed to the wind speed; the wind turbine aerodynamic model sets the wind turbine blade length, the wind speed The air density, the wind energy availability, the blade pitch angle, and the tip speed ratio are calculated by a preset airflow input power calculation formula to obtain the airflow input power.
  • the obtaining, according to the obtained airflow input power, obtaining the rotor electromagnetic torque by the torque control model includes: the torque control model The obtained rotor mechanical inertia, the rotor motion damping coefficient and the rotor mechanical angular velocity are brought into the rotor electromagnetic torque calculation formula preset by the torque control model to calculate the rotor electromagnetic torque.
  • the high voltage fault occurrence device model simulates a high voltage fault according to an input initialization evaluation parameter, and outputs a given voltage of a low voltage side of the transformer, including:
  • the high voltage fault occurrence device model obtains an impedance value of the input series reactor, a grid impedance, and a wind turbine capacity, wherein the initialization evaluation parameter includes: an impedance value of the series reactor, the grid impedance, and the wind turbine Capacity;
  • the high voltage fault occurrence device model brings the impedance value of the series reactor, the grid impedance, and the wind turbine capacity to a predetermined voltage setting of a low voltage side of a transformer configured to simulate a high voltage fault
  • the formula is calculated, and the calculated voltage on the low voltage side of the transformer is calculated.
  • the converter model is configured according to the airflow input power, the rotor electromagnetic torque, and a given voltage of a low voltage side of the transformer.
  • Calculating the stator reactive current, active power and reactive power of the wind turbine during the high voltage fault process including: the q-axis stator flux linkage obtained by the converter model, the preset stator self-inductance, the preset stator The self-inductance and the preset q-axis rotor current are brought into a preset stator reactive current calculation formula to calculate the stator reactive current; the converter model obtains the stator rotational speed and the air flow input The power, the electromagnetic torque of the rotor, and a given voltage of the low voltage side of the transformer are brought into a preset active power calculation formula to calculate the active power; the d-axis rotor current obtained by the converter model, The d-axis stator voltage, the stator mutual inductance, the q-axis rotor current, the
  • the present disclosure provides a readable storage medium storing executable instructions that, when executed by one or more processors, implement the high voltage ride through capability simulation evaluation model High voltage ride through capability simulation evaluation method.
  • the present disclosure has at least the following advantages:
  • the high voltage ride through capability simulation evaluation model and the simulation evaluation method based thereon can simulate the high voltage fault occurring in the actual high-frequency DC debugging process of the power grid, or the reactive power generation of multiple wind farms generated by the low voltage fault linkage.
  • the equipment does not exit the generated chain high voltage fault after the low voltage traverse, and can evaluate the running state of the wind turbine fault process. It can verify whether the wind turbine has the capability of high voltage traversing through the simulation method, and can replace the high voltage traversal in the field. Mobile test equipment vehicle testing saves test costs.
  • Figure 1 is a high voltage fault curve in the wind turbine generator fault ride through capability test procedure (work discussion draft);
  • FIG. 2 is a schematic structural diagram of a high voltage ride through capability simulation evaluation model of the present disclosure
  • 3 is a simulation result curve of a converter stator voltage standard value when the simulation evaluation method of the present disclosure performs a three-phase symmetrical voltage fault evaluation
  • FIG. 4 is a simulation result curve of a stator reactive current standard value when the simulation evaluation method of the present disclosure performs a three-phase symmetrical voltage fault evaluation
  • 5 is a simulation result curve of a reactive power standard value when the simulation evaluation method of the present disclosure performs a three-phase symmetrical voltage fault evaluation
  • FIG. 6 is a simulation result curve of an active power standard value when the simulation evaluation method of the present disclosure performs a three-phase symmetrical voltage fault evaluation
  • FIG. 10 is a simulation result curve of the active power standard value when the two-phase asymmetric voltage fault evaluation is performed by the simulation evaluation method of the present disclosure.
  • the present disclosure provides a high voltage ride through capability simulation evaluation model, which includes a wind turbine aerodynamic model, a torque control model, a converter model, and a high voltage fault occurrence device model.
  • the high voltage ride through capability simulation evaluation model can be run on a terminal device, wherein the terminal device can be a hardware device such as a personal computer or a mobile device.
  • the wind turbine aerodynamic model may be a software module configured to calculate an airflow input power according to the input initialization evaluation parameter.
  • the wind turbine aerodynamic model first obtains initial evaluation parameters, wherein the initial evaluation parameters include: wind turbine blade length, wind speed, air density, wind turbine blade angular velocity, and wind energy availability. Then, the wind turbine aerodynamic model first obtains the tip speed ratio based on the obtained wind turbine blade length, wind speed, air density, wind turbine blade angular velocity, and wind energy availability ratio of the blade tip line speed to the wind speed. After that, the wind turbine aerodynamic model recalls the preset airflow input power calculation formula, based on the wind turbine blade length, wind speed, air density, wind energy availability, blade pitch angle and tip speed ratio, The air flow input power.
  • the initial evaluation parameters include: wind turbine blade length, wind speed, air density, wind turbine blade angular velocity, and wind energy availability.
  • the input power P m air flow of the air stream preset input power is calculated as follows:
  • P m is the airflow input power
  • ⁇ is the pi
  • r b is the wind turbine blade length
  • v w is the wind speed
  • ⁇ is the air density
  • ⁇ is the tip speed ratio, ie the ratio of the blade tip line speed to the wind speed
  • w b is the blade angular velocity of the wind turbine
  • ⁇ is the blade pitch angle
  • c p is the wind energy availability.
  • the wind energy availability c p takes the empirical value as shown in Table 1 below:
  • the torque control model is configured to calculate the rotor electromagnetic torque based on the airflow input power output by the wind turbine aerodynamic model.
  • the wind turbine impeller, the drive shaft and the generator rotor are simulated into an inertial body, and the shaft torque transmission process is simulated by a first-order inertia link.
  • the torque control model obtains the rotor electromagnetic torque in the following manner:
  • the torque control model can call a preset rotor electromagnetic torque calculation formula, and the obtained rotor control model is calculated based on the obtained rotor mechanical inertia, rotor motion damping coefficient and rotor mechanical angular velocity, so that the rotor electromagnetic torque can be obtained. .
  • the torque control model of the rotor electromagnetic torque T e is calculated as follows:
  • T e is the rotor electromagnetic torque
  • T m is the generator torque
  • J r is the rotor mechanical inertia
  • k r is the rotor motion damping coefficient
  • w rm is the rotor mechanical angular velocity
  • a high voltage fault occurrence device model configured to simulate a high voltage fault based on an input initialization evaluation parameter and calculate a given voltage on the low voltage side of the transformer.
  • the high voltage fault occurrence device model calculates a given voltage of the low voltage side of the transformer, which may be:
  • the initialization evaluation parameters also include: the impedance value of the series reactor, the grid impedance, and the capacity of the wind turbine. Therefore, the high voltage fault occurrence device model can also obtain the input series reactor impedance value, grid impedance and wind turbine capacity. After that, the high voltage fault occurrence device model can call the preset calculation formula for simulating the low voltage side of the high voltage fault transformer, and calculate based on the impedance value of the series reactor, the grid impedance and the wind turbine capacity, so that the output calculation can be performed. The obtained voltage on the low voltage side of the transformer is given.
  • the formula for calculating the set voltage of the low voltage side of the transformer with the given voltage u s on the low voltage side of the transformer is as follows:
  • u s is the given voltage on the low voltage side of the transformer, ie the stator voltage of the converter
  • X 1 is the impedance value of the series reactor
  • X grid is the grid impedance
  • S WT is the wind turbine capacity. According to different test requirements, adjust X 1 to produce different transformer low voltage side given voltage u s .
  • the converter model can calculate the stator reactive current, active power and reactive power of the wind turbine in the process of high voltage fault according to the airflow input power, the rotor electromagnetic torque and the given voltage on the low voltage side of the transformer.
  • the converter model calculates the stator reactive current, active power and reactive power of the wind turbine can be:
  • the converter model first obtains a q-axis stator flux linkage that can be input by the user.
  • the converter model calculates the obtained q-axis stator flux, preset stator self-inductance, preset stator self-inductance and preset q-axis rotor current into a preset stator reactive current calculation formula. Thereby, the stator reactive current can be obtained.
  • the converter speed can also be obtained from the converter model, wherein the stator speed can also be input by the user.
  • the converter model calculates the obtained stator rotational speed, airflow input power, rotor electromagnetic torque, and the voltage of the low-voltage side of the transformer into a preset active power calculation formula, so that active power can be obtained.
  • the converter model can also obtain the d-axis rotor current, the d-axis stator voltage, and the stator mutual inductance.
  • the manner of obtaining the d-axis rotor current, the d-axis stator voltage and the stator mutual inductance can be input by the user.
  • the converter model then brings the d-axis rotor current, the d-axis stator voltage, the stator mutual inductance, the q-axis rotor current, the stator rotational speed, the airflow input power and the rotor electromagnetic torque to a preset reactive power calculation formula. By calculation, reactive power can be obtained.
  • the converter model is configured to output a stator reactive current i qs of the wind turbine during a high voltage fault according to the airflow input power P m , the rotor electromagnetic torque T e , and the transformer low voltage reference voltage u s . , active power P s and reactive power Q s .
  • the rotor electromagnetic torque T e can be expressed as follows:
  • i ds and i qs are the d-axis and q-axis stator currents, respectively, the stator reactive current and the stator active current, and ⁇ ds and ⁇ qs are the d-axis and q-axis stator fluxes, ⁇ ds and ⁇ qs , respectively.
  • L S and L M are stator self-inductance and stator mutual inductance
  • i dr and i qr are d-axis and q-axis rotor currents respectively, that is, rotor reactive current and rotor active current
  • i ds , i qs are obtained .
  • the rotor electromagnetic torque T e can be expressed as a function of the rotor current and the stator flux linkage.
  • v ds is the d-axis stator voltage
  • v qs is the q-axis stator voltage
  • the rotor electromagnetic torque T e can be expressed as a function of the d-axis rotor current i dr and the stator voltage v ds .
  • the active power P S and the reactive power Q S can be calculated from the d and q-axis rotor currents.
  • the present disclosure also provides a high voltage ride through capability simulation evaluation method based on the above high voltage ride through capability simulation evaluation model, comprising the following steps:
  • the wind turbine group aerodynamic model calculates the airflow input power according to the input initialization evaluation parameter
  • the high voltage fault occurrence device model simulates a high voltage fault according to the input initialization evaluation parameter, and outputs a given voltage of the low voltage side of the transformer;
  • the converter model calculates the stator reactive current, active power and reactive power of the wind turbine during the high voltage fault according to the airflow input power, the rotor electromagnetic torque and the set voltage of the low voltage side of the transformer;
  • the stator reactive current, the active power and the reactive power determine whether the wind turbine has high voltage ride through capability.
  • step S1 specifically includes:
  • the wind turbine group aerodynamic model obtains an input wind turbine blade length, a wind speed, an air density, a wind turbine blade angular velocity, and a wind energy availability, wherein the initial evaluation parameter comprises: the wind turbine blade length, the wind speed, and the wind turbine The air density, the wind turbine blade angular velocity, and the wind energy availability.
  • the wind turbine aerodynamic model obtains a tip speed ratio according to a ratio of the blade tip line speed to the wind speed.
  • the step S2 specifically includes: the torque control model brings the obtained rotor mechanical inertia, the rotor motion damping coefficient, and the rotor mechanical angular velocity into the rotor electromagnetic rotation preset by the torque control model.
  • the moment calculation formula is calculated to obtain the rotor electromagnetic torque.
  • step S3 specifically includes:
  • the high voltage fault occurrence device model obtains an impedance value of the input series reactor, a grid impedance, and a wind turbine capacity, wherein the initialization evaluation parameter includes: an impedance value of the series reactor, the grid impedance, and the Wind turbine capacity.
  • the high voltage fault occurrence device model brings the impedance value of the series reactor, the grid impedance and the wind turbine capacity into a predetermined voltage setting of a low voltage side of a transformer configured to simulate a high voltage fault.
  • the formula is calculated, and the calculated voltage on the low voltage side of the transformer is calculated.
  • step S4 specifically includes:
  • Step S41 The converter model obtains the obtained q-axis stator flux, preset stator self-inductance, preset stator self-inductance and preset q-axis rotor current to preset stator reactive current calculation The formula is calculated to obtain the stator reactive current.
  • Step S42 The converter model calculates the obtained stator rotational speed, the airflow input power, the rotor electromagnetic torque, and the voltage on the low voltage side of the transformer into a preset active power calculation formula, The active power is obtained.
  • Step S4 the d-axis rotor current, the d-axis stator voltage, the stator mutual inductance, the q-axis rotor current, the stator rotational speed, the airflow input power, and the rotor electromagnetic torque to be obtained by the converter model
  • the calculation is carried out to a preset reactive power calculation formula to obtain the reactive power.
  • embodiments of the present application can be provided as a method, system, or computer program product. Therefore, the embodiments of the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Moreover, embodiments of the present application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) including computer usable program code.
  • computer-usable storage media including but not limited to disk storage, CD-ROM, optical storage, etc.
  • the high voltage ride through capability simulation evaluation method in this embodiment is simulated and evaluated by a wind turbine with a rated power of 2000 kW and an impeller diameter of 96 m.
  • the results are as follows:
  • the wind turbine emits inductive reactive power. After 30ms adjustment, the reactive power is stabilized at a rated power of -75% stable value.
  • the active power of the wind turbine suddenly increases to 1.2 times of the rated power when the voltage suddenly changes, and then gradually decreases, when the grid voltage returns to normal, The active power drops to 90% of the rated power and is then adjusted to the rated power after 3 cycles.
  • the active power of the wind turbine suddenly increases to 1.2 times the rated power when the voltage is suddenly changed, and then stabilizes at 0.4 times the rated power, at the grid voltage.
  • the active power drops to 10% of the rated power, and then is adjusted to the rated power after 3 cycles.
  • the high voltage ride through capability simulation evaluation model and the simulation evaluation method based thereon can simulate the high voltage fault occurring in the actual high-frequency DC debugging process of the power grid, or the reactive power generation of multiple wind farms generated by the low voltage fault linkage.
  • the equipment does not exit the generated chain high voltage fault after the low voltage traverse, and can evaluate the running state of the wind turbine fault process. It can verify whether the wind turbine has the capability of high voltage traversing through the simulation method, and can replace the high voltage traversal in the field. Mobile test equipment vehicle testing saves test costs.
  • the high voltage ride through capability simulation evaluation model and the simulation evaluation method based thereon can simulate the high voltage fault occurring in the actual high-frequency DC debugging process of the power grid, or the reactive power generation of multiple wind farms generated by the low voltage fault linkage.
  • the equipment does not exit the generated chain high voltage fault after the low voltage traverse, and can evaluate the running state of the wind turbine fault process. It can verify whether the wind turbine has the capability of high voltage traversing through the simulation method, and can replace the high voltage traversal in the field. Mobile test equipment vehicle testing saves test costs.

Abstract

本公开提供了一种高电压穿越能力仿真评估模型，包括依次连接的风电机组气动模型、转矩控制模型、变流器模型及高电压故障发生设备模型；风电机组气动模型，配置成计算空气气流输入功率；转矩控制模型，配置成根据空气气流输入功率计算转子电磁转矩；高电压故障发生设备模型，配置成模拟高电压故障并输出变压器低压侧给定电压；变流器模型，配置成根据空气气流输入功率、转子电磁转矩及变压器低压侧给定电压，计算在高电压故障过程中风电机组的定子无功电流、有功功率和无功功率。本公开还公开了一种基于上述模型的高电压穿越能力仿真评估方法，能够模拟出高电压故障，评估风电机组故障过程中的运行状态，验证风电机组是否具备高电压穿越的能力。

Description

高电压穿越能力仿真评估模型、基于其的仿真评估方法及储存介质
相关申请的交叉引用
本申请要求于2017年11月24日提交中国专利局的申请号为201711192186.5名称为“高电压穿越能力仿真评估模型及基于其的仿真评估方法”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本公开涉及风力发电机组技术领域，特别是涉及一种高电压穿越能力仿真评估模型、基于该模型的仿真评估方法及储存介质。
背景技术
此前，中国电力科学研究院牵头提出了风力发电机组故障穿越能力测试规程(工作讨论稿)，以下是该规程中对风电机组高电压穿越能力的具体要求：
风电机组在规定的电压和时间范围内应具备不脱网连续运行的能力，并在电压恢复正常后快速实现功率恢复，在故障期间，风电机组应提供感性无功电流支撑协助电网电压恢复。具体要求如下：
A)风电机组在机组并网点电压升高至1.3pu时，应具备不脱网连续运行200ms的能力；
B)风电机组在机组并网点点电压升高至1.25pu时，应具备不脱网连续运行1s的能力；
C)风电机组在机组并网点点电压升高至1.2pu时，应具备不脱网连续运行2s的能力；
D)风电机组在机组并网点电压升高至1.15pu时，应具备不脱网连续运行10s的能力；
E)风电机组在机组并网点点电压升高至1.1pu时，应具备长时间不脱网连续运行的能力。
即当电力系统发生三相短路时，电压在虚线范围以下，实线以上正常发电的风电机组原则上在故障期间需要不脱网连续运行，详见图1。现有技术中主要采用高电压穿越移动测试设备车，在现场对风电机组的高电压穿越能力进行测试，测试过程复杂，成本较高。在现有技术中有对风电机组低电压穿越能力 仿真评估方法，但并未记载高电压穿越能力仿真评估方法。
因此，如何创设一种高电压穿越能力仿真评估模型及基于其的仿真评估方法，使其能够模拟出高电压故障，并能够评估风电机组在故障过程中的运行状态，以实现验证风电机组是否具备高电压穿越能力的目的，成为本领域技术人员亟待解决的问题。
发明内容
本公开的目的是提供一种高电压穿越能力仿真评估模型、基于其的仿真评估方法及储存介质，使其能够模拟出高电压故障，并能够评估风电机组在故障过程中的运行状态，以实现验证风电机组是否具备高电压穿越能力的目的。
为实现上述目的，本公开采用如下技术方案：
第一方面，本公开提供了一种高电压穿越能力仿真评估模型，包括依次连接的风电机组气动模型、转矩控制模型、变流器模型及高电压故障发生设备模型；所述风电机组气动模型，配置成根据输入的初始化评估参数计算空气气流输入功率；所述转矩控制模型，配置成根据所述空气气流输入功率计算转子电磁转矩；所述高电压故障发生设备模型，配置成根据输入的初始化评估参数模拟高电压故障，并输出变压器低压侧给定电压；所述变流器模型，配置成根据所述空气气流输入功率、转子电磁转矩及变压器低压侧给定电压，计算在高电压故障过程中风电机组的定子无功电流、有功功率和无功功率。
结合第一方面，作为本公开的一种可选的实施方式，风电机组气动模型，还配置成获得输入的风电机组叶片长度、风速、空气密度、风电机组叶片角速度和风能可利用率，其中，初始化评估参数包括：所述风电机组叶片长度、所述风速、所述空气密度、所述风电机组叶片角速度和所述风能可利用率；根据所述叶片顶端线速度与所述风速的比值获得叶尖速比；将所述风电机组叶片长度、所述风速、所述空气密度、所述风能可利用率、所述叶片桨距角和所述叶尖速比带入预设的空气气流输入功率计算公式进行计算，获得所述空气气流输入功率。
结合第一方面，作为本公开的一种可选的实施方式，所述空气气流输入功 率P m所述空气气流输入功率计算公式如下：
Figure PCTCN2018093806-appb-000001
其中，P m为所述空气气流输入功率，π为圆周率，r b为所述风电机组叶片长度，v w为所述风速，ρ为所述空气密度，λ为所述叶尖速比，即叶片顶端线速度与风速的比值，
Figure PCTCN2018093806-appb-000002
w b为所述风电机组叶片角速度，β为所述叶片桨距角，c p为所述风能可利用率。
结合第一方面，作为本公开的一种可选的实施方式，所述转矩控制模型，还配置成将获得的转子机械惯量、转子运动阻尼系数和转子机械角速度带入所述转矩控制模型预设的转子电磁转矩计算公式进行计算，获得所述转子电磁转矩。
结合第一方面，作为本公开的一种可选的实施方式，所述转子电磁转矩T e的所述转子电磁转矩计算公式如下：
Figure PCTCN2018093806-appb-000003
式中，T e为所述转子电磁转矩，P m为所述空气气流输入功率，J r为所述转子机械惯量，k r为所述转子运动阻尼系数，w rm为所述转子机械角速度。
结合第一方面，作为本公开的一种可选的实施方式，所述高电压故障发生设备模型，还配置成获得输入的串联电抗器的阻抗值、电网阻抗和风电机组容量，其中，初始化评估参数包括：所述串联电抗器的阻抗值、所述电网阻抗和所述风电机组容量；将所述串联电抗器的阻抗值、所述电网阻抗和所述风电机组容量带入到预设的配置成模拟高电压故障的变压器低压侧给定电压计算公式进行计算，输出计算得到的所述变压器低压侧给定电压。
结合第一方面，作为本公开的一种可选的实施方式，所述变压器低压侧给定电压u s的所述变压器低压侧给定电压计算公式如下：
Figure PCTCN2018093806-appb-000004
式中，u s为所述变压器低压侧给定电压，也即变流器定子电压，X 1为所述串联电抗器的阻抗值，X grid为所述电网阻抗，S WT为所述风电机组容量。
结合第一方面，作为本公开的一种可选的实施方式，所述变流器模型，还配置成将获得的q轴定子磁链、预设的定子自感、预设的定子自感和预设的q轴转子电流带入到预设的定子无功电流计算公式进行计算，获得所述定子无功电流。所述变流器模型，还配置成将获得的定子转速、所述空气气流输入功率、所述转子电磁转矩及所述变压器低压侧给定电压带入到预设的有功功率计算公式进行计算，获得所述有功功率。所述变流器模型，还配置成将获得的d轴转子电流、d轴定子电压、定子互感、所述q轴转子电流、所述定子转速、所述空气气流输入功率和所述转子电磁转矩带入到预设的无功功率计算公式进行计算，获得所述无功功率。
结合第一方面，作为本公开的一种可选的实施方式，所述定子无功电流i qs 的所述定子无功电流计算公式如下：
Figure PCTCN2018093806-appb-000005
式中，i qs为所述q轴定子电流，即定子无功电流，λ qs为所述q轴定子磁链，L S、L M分别为所述定子自感和所述定子互感，i qr为所述q轴转子电流。所述有功功率P S和无功功率Q S的所述有功功率计算公式和所述无功功率计算公式分别如下：
Figure PCTCN2018093806-appb-000006
式中，P S为所述有功功率，Q S为所述无功功率，P m为所述空气气流输入功率，T e为所述转子电磁转矩，ω s为所述定子转速，i dr、i qr分别为所述d轴转子电流和所述q轴转子电流，v ds为所述d轴定子电压，L M为所述定子互感。
第二方面，本公开提供了一种基于上述高电压穿越能力仿真评估模型的高电压穿越能力仿真评估方法，包括如下步骤：S1、所述风电机组气动模型根据输入的初始化评估参数，计算获得空气气流输入功率；S2、根据获得的空气气流输入功率，通过所述转矩控制模型计算获得转子电磁转矩；S3、所述高电压故障发生设备模型根据输入的初始化评估参数模拟高电压故障，并输出变压器低压侧给定电压；S4、所述变流器模型根据所述空气气流输入功率、转子电磁转矩及变压器低压侧给定电压，计算在高电压故障过程中风电机组的定子无功电流、有功功率和无功功率；S5、根据获得的所述变压器低压侧给定电压、定子无功电流、有功功率和无功功率，判断所述风电机组是否具备高电压穿越能力。
结合第二方面，作为本公开的一种可选的实施方式，所述的所述风电机组气动模型根据输入的初始化评估参数，计算获得空气气流输入功率，包括：所述风电机组气动模型获得输入的风电机组叶片长度、风速、空气密度、风电机组叶片角速度和风能可利用率，其中，初始化评估参数包括：所述风电机组叶片长度、所述风速、所述空气密度、所述风电机组叶片角速度和所述风能可利用率；所述风电机组气动模型根据所述叶片顶端线速度与所述风速的比值获得叶尖速比；所述风电机组气动模型将所述风电机组叶片长度、所述风速、所述空气密度、所述风能可利用率、所述叶片桨距角和所述叶尖速比带入预设的空气气流输入功率计算公式进行计算，获得所述空气气流输入功率。
结合第二方面，作为本公开的一种可选的实施方式，所述根据获得的空气 气流输入功率，通过所述转矩控制模型计算获得转子电磁转矩，包括：所述转矩控制模型将获得的转子机械惯量、转子运动阻尼系数和转子机械角速度带入所述转矩控制模型预设的转子电磁转矩计算公式进行计算，获得所述转子电磁转矩。
结合第二方面，作为本公开的一种可选的实施方式，所述的所述高电压故障发生设备模型根据输入的初始化评估参数模拟高电压故障，并输出变压器低压侧给定电压，包括：所述高电压故障发生设备模型获得输入的串联电抗器的阻抗值、电网阻抗和风电机组容量，其中，初始化评估参数包括：所述串联电抗器的阻抗值、所述电网阻抗和所述风电机组容量；所述高电压故障发生设备模型将所述串联电抗器的阻抗值、所述电网阻抗和所述风电机组容量带入到预设的配置成模拟高电压故障的变压器低压侧给定电压计算公式进行计算，输出计算得到的所述变压器低压侧给定电压。
结合第二方面，作为本公开的一种可选的实施方式，所述的所述变流器模型根据所述空气气流输入功率、所述转子电磁转矩及所述变压器低压侧给定电压，计算在高电压故障过程中风电机组的定子无功电流、有功功率和无功功率，包括：所述变流器模型将获得的q轴定子磁链、预设的定子自感、预设的定子自感和预设的q轴转子电流带入到预设的定子无功电流计算公式进行计算，获得所述定子无功电流；所述变流器模型将获得的定子转速、所述空气气流输入功率、所述转子电磁转矩及所述变压器低压侧给定电压带入到预设的有功功率计算公式进行计算，获得所述有功功率；所述变流器模型将获得的d轴转子电流、d轴定子电压、定子互感、所述q轴转子电流、所述定子转速、所述空气气流输入功率和所述转子电磁转矩带入到预设的无功功率计算公式进行计算，获得所述无功功率。
结合第三方面，作为本公开提供了一种可读存储介质，存储有可执行的指令，所述指令在被一个或多个处理器执行时，实现所述的高电压穿越能力仿真评估模型的高电压穿越能力仿真评估方法。
由于采用上述技术方案，本公开至少具有以下优点：
本公开高电压穿越能力仿真评估模型及基于其的仿真评估方法，能够模拟出实际中电网直流高端调试过程中出现的高电压故障，或是由低电压故障连锁产生的多个风电场无功发生设备在低电压穿越后未及时退出产生的连锁高电压故障，并能够评估风电机组故障过程中的运行状态，通过仿真方法验证风电机组是否具备高电压穿越的能力，能够替代在现场使用高电压穿越移动测试设 备车测试，节约了测试成本。
附图说明
上述仅是本公开技术方案的概述，为了能够更清楚了解本公开的技术手段，以下结合附图与具体实施方式对本公开作进一步的详细说明。
图1是风力发电机组故障穿越能力测试规程(工作讨论稿)中的高电压故障曲线；
图2是本公开高电压穿越能力仿真评估模型的结构示意图；
图3是本公开仿真评估方法在进行三相对称电压故障评估时的变流器定子电压标幺值仿真结果曲线；
图4是本公开仿真评估方法在进行三相对称电压故障评估时的定子无功电流标幺值仿真结果曲线；
图5是本公开仿真评估方法在进行三相对称电压故障评估时的无功功率标幺值仿真结果曲线；
图6是本公开仿真评估方法在进行三相对称电压故障评估时的有功功率标幺值仿真结果曲线；
图7是本公开仿真评估方法在进行两相不对称电压故障评估时的变流器定子电压标幺值仿真结果曲线；
图8是本公开仿真评估方法在进行两相不对称电压故障评估时的定子无功电流标幺值仿真结果曲线；
图9是本公开仿真评估方法在进行两相不对称电压故障评估时的无功功率标幺值仿真结果曲线；
图10是本公开仿真评估方法在进行两相不对称电压故障评估时的有功功率标幺值仿真结果曲线。
具体实施方式
参见图2所示，本公开提供了一种高电压穿越能力仿真评估模型，包括依次连接的风电机组气动模型、转矩控制模型、变流器模型及高电压故障发生设备模型。该高电压穿越能力仿真评估模型可以运行在终端设备上，其中，终端设备可以为个人电脑或移动设备等硬件设备。
其中，风电机组气动模型可以为软件模块，配置成根据输入的初始化评估参数计算出空气气流输入功率。
于本实施例中，风电机组气动模型首先可以获得初始化评估参数，其中，初始化评估参数包括：风电机组叶片长度、风速、空气密度、风电机组叶片角速度和风能可利用率。那么，风电机组气动模型首先基于获得的风电机组叶片长度、风速、空气密度、风电机组叶片角速度和风能可利用率中的该叶片顶端线速度与该风速的比值获得叶尖速比。之后，风电机组气动模型再调用预设的空气气流输入功率计算公式，基于风电机组叶片长度、风速、空气密度、风能可利用率、叶片桨距角和叶尖速比进行计算，便能够获得所述空气气流输入功率。
可选的，空气气流输入功率P m的预设的空气气流输入功率计算公式如下：
Figure PCTCN2018093806-appb-000007
其中，P m为空气气流输入功率，π为圆周率，r b为风电机组叶片长度，v w为风速，ρ为空气密度，λ为叶尖速比，即叶片顶端线速度与风速的比值，
Figure PCTCN2018093806-appb-000008
w b为风电机组叶片角速度，β为叶片桨距角，c p为风能可利用率。
风能可利用率c p取经验数值如下表1所示：
表1风能可利用率c p取值表
Figure PCTCN2018093806-appb-000009
转矩控制模型，配置成根据风电机组气动模型输出的空气气流输入功率计算转子电磁转矩。即将风电机组叶轮、传动轴及发电机转子模拟成一个惯性体，将轴系扭矩传递过程用一个一阶惯性环节模拟。
于本实施例中，转矩控制模型获得转子电磁转矩的方式可以为：
转矩控制模型可以调用预设的转子电磁转矩计算公式，基于获得的转子机械惯量、转子运动阻尼系数和转子机械角速度带入该转矩控制模型进行计算，从而便可以获得该转子电磁转矩。
可选的，转子电磁转矩T e的转矩控制模型计算公式如下：
Figure PCTCN2018093806-appb-000010
Figure PCTCN2018093806-appb-000011
式中，T e为转子电磁转矩，T m为发电机转矩，J r为转子机械惯量，k r为转 子运动阻尼系数，w rm为转子机械角速度。
Figure PCTCN2018093806-appb-000012
高电压故障发生设备模型，配置成根据输入的初始化评估参数模拟高电压故障并计算出变压器低压侧给定电压。
于本实施例中，高电压故障发生设备模型计算出变压器低压侧给定电压的方式可以为：
首先，初始化评估参数还包括：串联电抗器的阻抗值、电网阻抗和述风电机组容量。故该高电压故障发生设备模型还可以获得输入的串联电抗器的阻抗值、电网阻抗和风电机组容量。之后，高电压故障发生设备模型可以调用预设的配置成模拟高电压故障变压器低压侧给定电压计算公式，基于串联电抗器的阻抗值、电网阻抗和风电机组容量进行计算，从而便能够输出计算得到的变压器低压侧给定电压。
可选的，变压器低压侧给定电压u s的变压器低压侧给定电压计算公式如下：
Figure PCTCN2018093806-appb-000013
式中，u s为变压器低压侧的给定电压，即变流器定子电压，X 1为串联电抗器的阻抗值，X grid为电网阻抗，S WT为风电机组容量。根据不同测试要求，调整X 1，即可产生不同的变压器低压侧给定电压u s。
变流器模型可以根据空气气流输入功率、转子电磁转矩及变压器低压侧给定电压，分别计算在高电压故障过程中风电机组的定子无功电流、有功功率和无功功率。
于本实施例中，变流器模型计算出风电机组的定子无功电流、有功功率和无功功率的方式可以为：
变流器模型首先可以获得q轴定子磁链，该q轴定子磁链可以为用户输入的。变流器模型将该获得的q轴定子磁链、预设的定子自感、预设的定子自感和预设的q轴转子电流带入到预设的定子无功电流计算公式进行计算，从而便能够获得定子无功电流。
其次，变流器模型也可以获得定子转速，其中，该定子转速也可以为用户输入的。变流器模型将该获得的定子转速、空气气流输入功率、转子电磁转矩及所述变压器低压侧给定电压带入到预设的有功功率计算公式进行计算，从而便能够获得有功功率。
再者，变流器模型还可以获得d轴转子电流、d轴定子电压、定子互感。其中，获得该d轴转子电流、d轴定子电压和定子互感的方式可以为用户输入的。之后，变流器模型再将d轴转子电流、d轴定子电压、定子互感、q轴转子电流、定子转速、空气气流输入功率和转子电磁转矩带入到预设的无功功率计算公式进行计算，便能够获得无功功率。
可选的，变流器模型配置成根据空气气流输入功率P m、转子电磁转矩T e及变压器低压侧给定电压u s，输出在高电压故障过程中风电机组的定子无功电流i qs、有功功率P s和无功功率Q s。
转子电磁转矩T e可表示如下：
T e＝1.5P m(i qsλ ds-i dsλ qs)(6)
式中，i ds、i qs分别为d轴和q轴定子电流，即定子无功电流和定子有功电流，λ ds、λ qs分别为d轴和q轴定子磁链，λ ds和λ qs的计算公式如下：
Figure PCTCN2018093806-appb-000014
式中，L S、L M别为定子自感和定子互感，i dr、i qr分别为d轴和q轴转子电流，即转子无功电流和转子有功电流，得出i ds，i qs的计算公式如下：
Figure PCTCN2018093806-appb-000015
将式(8)带入式(6)可得：
Figure PCTCN2018093806-appb-000016
由上式可知，转子电磁转矩T e可表示为转子电流和定子磁链的函数。
又由于发电机稳态时的定子电压矢量
Figure PCTCN2018093806-appb-000017
可表示为：
Figure PCTCN2018093806-appb-000018
式中，
Figure PCTCN2018093806-appb-000019
为定子电压矢量，Rs为定子电阻，
Figure PCTCN2018093806-appb-000020
为定子电流矢量，j为矢量虚部，ω s为定子转速，
Figure PCTCN2018093806-appb-000021
为定子磁链矢量。
经d、q轴坐标转化后可表示为：
(v ds+jv qs)＝R S(i ds+ji qs)+jω s(λ ds+j)(11)
式中，v ds为d轴定子电压，v qs为q轴定子电压。
由上式可知，d轴和q轴定子磁链可分别表示为：
Figure PCTCN2018093806-appb-000022
将式(12)带入到式(9)，可得：
Figure PCTCN2018093806-appb-000023
在定子电压定向控制中，令v qs＝0,方程可简化，且在双馈发电机中，Rs很小，方程最终简化为：
Figure PCTCN2018093806-appb-000024
由上式可知，转子电磁转矩T e可表示为d轴转子电流i dr和定子电压v ds的函数。
有功功率计算公式和无功功率的计算公式为：
Figure PCTCN2018093806-appb-000025
式中，P S为有功功率，Q S为无功功率，采用定子电压定向控制，令v qs＝0，上式可简化为：
Figure PCTCN2018093806-appb-000026
将式(8)带入到式(16)可得：
Figure PCTCN2018093806-appb-000027
由上式可得：
Figure PCTCN2018093806-appb-000028
将式(12)带入到式(18)可得：
Figure PCTCN2018093806-appb-000029
当v qs＝0时，忽略定子电阻R S，可得：
Figure PCTCN2018093806-appb-000030
以上可得出，在给定定子电压后，有功功率P S和无功功率Q S可通过d、q轴转子电流计算得到。
将式(14)带入式(20)可得：
Figure PCTCN2018093806-appb-000031
本公开还提供了一种基于上述高电压穿越能力仿真评估模型的高电压穿越能力仿真评估方法，包括如下步骤：
S1、风电机组气动模型根据输入的初始化评估参数，计算获得空气气流输入功率；
S2、根据获得的空气气流输入功率，通过转矩控制模型计算获得转子电磁转矩；
S3、高电压故障发生设备模型根据输入的初始化评估参数模拟高电压故障，并输出变压器低压侧给定电压；
S4、变流器模型根据空气气流输入功率、转子电磁转矩及变压器低压侧给定电压，计算在高电压故障过程中风电机组的定子无功电流、有功功率和无功功率；
S5、根据获得的变压器低压侧给定电压、定子无功电流、有功功率和无功功率，判断风电机组是否具备高电压穿越能力。
其中，作为一种可选的方式，步骤S1具体包括：
S11：所述风电机组气动模型获得输入的风电机组叶片长度、风速、空气密度、风电机组叶片角速度和风能可利用率，其中，初始化评估参数包括：所述风电机组叶片长度、所述风速、所述空气密度、所述风电机组叶片角速度和所述风能可利用率。
S12：所述风电机组气动模型根据所述叶片顶端线速度与所述风速的比值获得叶尖速比。
S13：所述风电机组气动模型将所述风电机组叶片长度、所述风速、所述空气密度、所述风能可利用率、所述叶片桨距角和所述叶尖速比带入预设的空气气流输入功率计算公式进行计算，获得所述空气气流输入功率。
其中，作为一种可选的方式，步骤S2具体包括：所述转矩控制模型将获 得的转子机械惯量、转子运动阻尼系数和转子机械角速度带入所述转矩控制模型预设的转子电磁转矩计算公式进行计算，获得所述转子电磁转矩。
其中，作为一种可选的方式，步骤S3具体包括：
S31：所述高电压故障发生设备模型获得输入的串联电抗器的阻抗值、电网阻抗和风电机组容量，其中，初始化评估参数包括：所述串联电抗器的阻抗值、所述电网阻抗和所述风电机组容量。
S31：所述高电压故障发生设备模型将所述串联电抗器的阻抗值、所述电网阻抗和所述风电机组容量带入到预设的配置成模拟高电压故障的变压器低压侧给定电压计算公式进行计算，输出计算得到的所述变压器低压侧给定电压。
其中，作为一种可选的方式，步骤S4具体包括：
步骤S41：所述变流器模型将获得的q轴定子磁链、预设的定子自感、预设的定子自感和预设的q轴转子电流带入到预设的定子无功电流计算公式进行计算，获得所述定子无功电流。
步骤S42：所述变流器模型将获得的定子转速、所述空气气流输入功率、所述转子电磁转矩及所述变压器低压侧给定电压带入到预设的有功功率计算公式进行计算，获得所述有功功率。
步骤S4：所述变流器模型将获得的d轴转子电流、d轴定子电压、定子互感、所述q轴转子电流、所述定子转速、所述空气气流输入功率和所述转子电磁转矩带入到预设的无功功率计算公式进行计算，获得所述无功功率。
需要说明的是，由于所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，上述描述方法具体执行过程，可以参考前述的系统、装置和单元实施例中的对应过程，在此不再赘述。
本领域内的技术人员应明白，本申请实施例可提供为方法、系统、或计算机程序产品。因此，本申请实施例可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且，本申请实施例可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。
本实施例中的高电压穿越能力仿真评估方法，以额定功率2000kW，叶轮直径96m风电机组进行仿真评估，结果如下：
1、三相对称电压故障仿真评估，风电机组变流器定子电压升高至额定电压1.3PU，故障持续时间500ms：
参见图3所示，为高电压穿越过程中的变流器定子电压标幺值仿真结果曲线。由于风电机组输出感性无功功率，高电压发生点在风电场并网点高压侧， 以及线路阻抗的分压作用，变流器定子电压实际仅上升至额定电压的1.22PU。
配合图4所示，为高电压穿越过程中的定子无功电流标幺值仿真结果曲线，风电机组发出感性无功电流，经过30ms调整，定子无功电流稳定在额定电流-65％。
配合图5所示，为高电压穿越过程中的无功功率标幺值仿真结果曲线，风电机组发出感性无功功率，经过30ms调整，无功功率稳定在额定功率-75％稳定值。
配合图6所示，为高电压穿越过程中的有功功率标幺值仿真结果曲线，风电机组有功功率在电压突变时突增至额定功率的1.2倍，之后逐渐下调，在电网电压恢复正常时，有功功率下降至额定功率的90％，之后经过3个周期调整至额定功率。
2、两相不对称电压故障仿真评估，风电机组变流器定子电压升高至额定电压的1.3PU，故障持续时间500ms：
配合图7所示，为高电压穿越过程中变流器定子电压标幺值仿真结果曲线，由于风电机组输出感性无功功率，以及线路阻抗的分压作用，变流器定子电压实际仅上升至额定电压的1.1PU。
配合图8所示，为高电压穿越过程中定子无功电流标幺值仿真结果曲线，风电机组发出感性无功电流，经过30ms调整，定子无功电流稳定在额定电流的-35％。
配合图9所示，为高电压穿越过程中的无功功率标幺值仿真结果曲线，风电机组发出感性无功功率，经过30ms调整，无功功率稳定在额定功率-35％
配合图10所示，为高电压穿越过程中的有功功率标幺值仿真结果曲线，风电机组有功功率在电压突变时突增至额定功率的1.2倍，之后稳定在0.4倍额定功率，在电网电压恢复正常时，有功功率下降至额定功率的10％，之后经过3个周期调整至额定功率。
本公开高电压穿越能力仿真评估模型及基于其的仿真评估方法，能够模拟出实际中电网直流高端调试过程中出现的高电压故障，或是由低电压故障连锁产生的多个风电场无功发生设备在低电压穿越后未及时退出产生的连锁高电压故障，并能够评估风电机组故障过程中的运行状态，通过仿真方法验证风电机组是否具备高电压穿越的能力，能够替代在现场使用高电压穿越移动测试设备车测试，节约了测试成本。
以上所述，仅是本公开的较佳实施例而已，并非对本公开作任何形式上的限制，本领域技术人员利用上述揭示的技术内容做出些许简单修改、等同变化或修饰，均落在本公开的保护范围内。
工业实用性
本公开高电压穿越能力仿真评估模型及基于其的仿真评估方法，能够模拟出实际中电网直流高端调试过程中出现的高电压故障，或是由低电压故障连锁产生的多个风电场无功发生设备在低电压穿越后未及时退出产生的连锁高电压故障，并能够评估风电机组故障过程中的运行状态，通过仿真方法验证风电机组是否具备高电压穿越的能力，能够替代在现场使用高电压穿越移动测试设备车测试，节约了测试成本。

Claims (15)

  1. 一种高电压穿越能力仿真评估模型，其特征在于，包括依次连接的风电机组气动模型、转矩控制模型、变流器模型及高电压故障发生设备模型；
    所述风电机组气动模型，配置成根据输入的初始化评估参数计算空气气流输入功率；
    所述转矩控制模型，配置成根据所述空气气流输入功率计算转子电磁转矩；
    所述高电压故障发生设备模型，配置成根据输入的初始化评估参数模拟高电压故障，并输出变压器低压侧给定电压；
    所述变流器模型，配置成根据所述空气气流输入功率、转子电磁转矩及变压器低压侧给定电压，计算在高电压故障过程中风电机组的定子无功电流、有功功率和无功功率。
  2. 根据权利要求1所述的高电压穿越能力仿真评估模型，其特征在于，风电机组气动模型，还配置成获得输入的风电机组叶片长度、风速、空气密度、风电机组叶片角速度和风能可利用率，其中，初始化评估参数包括：所述风电机组叶片长度、所述风速、所述空气密度、所述风电机组叶片角速度和所述风能可利用率；根据所述叶片顶端线速度与所述风速的比值获得叶尖速比；将所述风电机组叶片长度、所述风速、所述空气密度、所述风能可利用率、所述叶片桨距角和所述叶尖速比带入预设的空气气流输入功率计算公式进行计算，获得所述空气气流输入功率。
  3. 根据权利要求1所述的高电压穿越能力仿真评估模型，其特征在于，所述空气气流输入功率P m所述空气气流输入功率计算公式如下：
    Figure PCTCN2018093806-appb-100001
    其中，P m为所述空气气流输入功率，π为圆周率，r b为所述风电机组叶片长度，v w为所述风速，ρ为所述空气密度，λ为所述叶尖速比，即叶片顶端线速度与风速的比值，
    Figure PCTCN2018093806-appb-100002
    w b为所述风电机组叶片角速度，β为所述叶片桨距角，c p为所述风能可利用率。
  4. 根据权利要求1-3任一权项所述的高电压穿越能力仿真评估模型，其特征在于，
    所述转矩控制模型，还配置成将获得的转子机械惯量、转子运动阻尼系数和转子机械角速度带入所述转矩控制模型预设的转子电磁转矩计算公式进行计算，获得所述转子电磁转矩。
  5. 根据权利要求4所述的高电压穿越能力仿真评估模型，其特征在于，所述转子电磁转矩T e的所述转子电磁转矩计算公式如下：
    Figure PCTCN2018093806-appb-100003
    式中，T e为所述转子电磁转矩，P m为所述空气气流输入功率，J r为所述转子机械惯量，k r为所述转子运动阻尼系数，w rm为所述转子机械角速度。
  6. 根据权利要求1-5任一权项所述的高电压穿越能力仿真评估模型，其特征在于，
    所述高电压故障发生设备模型，还配置成获得输入的串联电抗器的阻抗值、电网阻抗和风电机组容量，其中，初始化评估参数包括：所述串联电抗器的阻抗值、所述电网阻抗和所述风电机组容量；将所述串联电抗器的阻抗值、所述电网阻抗和所述风电机组容量带入到预设的配置成模拟高电压故障的变压器低压侧给定电压计算公式进行计算，输出计算得到的所述变压器低压侧给定电压。
  7. 根据权利要求6所述的高电压穿越能力仿真评估模型，其特征在于，所述变压器低压侧给定电压u s的所述变压器低压侧给定电压计算公式如下：
    Figure PCTCN2018093806-appb-100004
    式中，u s为所述变压器低压侧给定电压，也即变流器定子电压，X 1为所述串联电抗器的阻抗值，X grid为所述电网阻抗，S WT为所述风电机组容量。
  8. 根据权利要求1-7任一权项所述的高电压穿越能力仿真评估模型，其特征在于，
    所述变流器模型，还配置成将获得的q轴定子磁链、预设的定子自感、预设的定子自感和预设的q轴转子电流带入到预设的定子无功电流计算公式进行计算，获得所述定子无功电流；
    所述变流器模型，还配置成将获得的定子转速、所述空气气流输入功率、所述转子电磁转矩及所述变压器低压侧给定电压带入到预设的有功功率计算公式进行计算，获得所述有功功率；
    所述变流器模型，还配置成将获得的d轴转子电流、d轴定子电压、定子互感、所述q轴转子电流、所述定子转速、所述空气气流输入功率和所述转子电磁转矩带入到预设的无功功率计算公式进行计算，获得所述无功功率。
  9. 根据权利要求8所述的高电压穿越能力仿真评估模型，其特征在于，所述定子无功电流i qs的所述定子无功电流计算公式如下：
    Figure PCTCN2018093806-appb-100005
    式中，i qs为所述q轴定子电流，即定子无功电流，λ qs为所述q轴定子磁链，L S、L M分别为所述定子自感和所述定子互感，i qr为所述q轴转子电流。
    所述有功功率P S和无功功率Q S的所述有功功率计算公式和所述无功功率计算公式分别如下：
    Figure PCTCN2018093806-appb-100006
    式中，P S为所述有功功率，Q S为所述无功功率，P m为所述空气气流输入功率，T e为所述转子电磁转矩，ω s为所述定子转速，i dr、i qr分别为所述d轴转子电流和所述q轴转子电流，v ds为所述d轴定子电压，L M为所述定子互感。
  10. 一种基于如权利要求1-9任一项所述高电压穿越能力仿真评估模型的高电压穿越能力仿真评估方法，其特征在于，包括如下步骤：
    所述风电机组气动模型根据输入的初始化评估参数，计算获得空气气流输入功率；
    根据获得的空气气流输入功率，通过所述转矩控制模型计算获得转子电磁转矩；
    所述高电压故障发生设备模型根据输入的初始化评估参数模拟高电压故障，并输出变压器低压侧给定电压；
    所述变流器模型根据所述空气气流输入功率、所述转子电磁转矩及所述变压器低压侧给定电压，计算在高电压故障过程中风电机组的定子无功电流、有功功率和无功功率；
    根据获得的所述变压器低压侧给定电压、定子无功电流、有功功率和无功功率，判断所述风电机组是否具备高电压穿越能力。
  11. 根据权利要求10所述的高电压穿越能力仿真评估模型的高电压穿越能力仿真评估方法，其特征在于，所述的所述风电机组气动模型根据输入的初始化评估参数，计算获得空气气流输入功率，包括：
    所述风电机组气动模型获得输入的风电机组叶片长度、风速、空气密度、风电机组叶片角速度和风能可利用率，其中，初始化评估参数包括：所述风电机组叶片长度、所述风速、所述空气密度、所述风电机组叶片角速度和所述风能可利用率；
    所述风电机组气动模型根据所述叶片顶端线速度与所述风速的比值获得叶尖速比；
    所述风电机组气动模型将所述风电机组叶片长度、所述风速、所述空气密度、所述风能可利用率、所述叶片桨距角和所述叶尖速比带入预设的空气气流输入功率计算公式进行计算，获得所述空气气流输入功率。
  12. 根据权利要求10或11所述的高电压穿越能力仿真评估模型的高电压穿越能力仿真评估方法，其特征在于，所述根据获得的空气气流输入功率，通过所述转矩控制模型计算获得转子电磁转矩，包括：所述转矩控制模型将获得的转子机械惯量、转子运动阻尼系数和转子机械角速度带入所述转矩控制模型预设的转子电磁转矩计算公式进行计算，获得所述转子电磁转矩。
  13. 根据权利要求10-12任一权项所述的高电压穿越能力仿真评估模型的高电压穿越能力仿真评估方法，其特征在于，所述的所述高电压故障发生设备模型根据输入的初始化评估参数模拟高电压故障，并输出变压器低压侧给定电压，包括：
    所述高电压故障发生设备模型获得输入的串联电抗器的阻抗值、电网阻抗和风电机组容量，其中，初始化评估参数包括：所述串联电抗器的阻抗值、所述电网阻抗和所述风电机组容量；
    所述高电压故障发生设备模型将所述串联电抗器的阻抗值、所述电网阻抗和所述风电机组容量带入到预设的配置成模拟高电压故障的变压器低压侧给定电压计算公式进行计算，输出计算得到的所述变压器低压侧给定电压。
  14. 根据权利要求10-13任一权项所述的高电压穿越能力仿真评估模型的高电压穿越能力仿真评估方法，其特征在于，所述的所述变流器模型根据所述空气气流输入功率、所述转子电磁转矩及所述变压器低压侧给定电压，计算在高电压故障过程中风电机组的定子无功电流、有功功率和无功功率，包括：
    所述变流器模型将获得的q轴定子磁链、预设的定子自感、预设的定子自感和预设的q轴转子电流带入到预设的定子无功电流计算公式进行计算，获得所述定子无功电流；
    所述变流器模型将获得的定子转速、所述空气气流输入功率、所述转子电磁转矩及所述变压器低压侧给定电压带入到预设的有功功率计算公式进行计算，获得所述有功功率；
    所述变流器模型将获得的d轴转子电流、d轴定子电压、定子互感、所述q轴转子电流、所述定子转速、所述空气气流输入功率和所述转子电磁转矩带入到预设的无功功率计算公式进行计算，获得所述无功功率。
  15. 一种可读存储介质，其特征在于，存储有可执行的指令，所述指令在被一个或多个处理器执行时，实现权利要求10-14任一权项所述的高电压穿越 能力仿真评估模型的高电压穿越能力仿真评估方法。
PCT/CN2018/093806 2017-11-24 2018-06-29 高电压穿越能力仿真评估模型、基于其的仿真评估方法及储存介质 WO2019100721A1 (zh)

Priority Applications (3)

Application Number Priority Date Filing Date Title
US16/609,743 US11288422B2 (en) 2017-11-24 2018-06-29 Simulation evaluation model of high voltage ride through capability, simulation evaluation method based on the same and storage medium
PH12019502494A PH12019502494A1 (en) 2017-11-24 2019-11-06 High-voltage ride through capability simulation evaluation model, simulation evaluation method based thereon, and storage medium
ZA2019/07434A ZA201907434B (en) 2017-11-24 2019-11-08 Simulation evaluation model of high voltage ride through capability, simulation evaluation method based on the same and storage medium

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201711192186.5A CN107944142B (zh) 2017-11-24 2017-11-24 高电压穿越能力仿真评估模型及基于其的仿真评估方法
CN201711192186.5 2017-11-24

Publications (1)

Publication Number Publication Date
WO2019100721A1 true WO2019100721A1 (zh) 2019-05-31

Family

ID=61948680

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2018/093806 WO2019100721A1 (zh) 2017-11-24 2018-06-29 高电压穿越能力仿真评估模型、基于其的仿真评估方法及储存介质

Country Status (5)

Country Link
US (1) US11288422B2 (zh)
CN (1) CN107944142B (zh)
PH (1) PH12019502494A1 (zh)
WO (1) WO2019100721A1 (zh)
ZA (1) ZA201907434B (zh)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110601268A (zh) * 2019-10-29 2019-12-20 中国石油大学(华东) 一种双馈风机并网端口输出阻抗建模及稳定性分析方法
CN112526261A (zh) * 2020-11-25 2021-03-19 西安西电电力系统有限公司 一种故障控制策略试验系统及方法

Families Citing this family (11)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN107944142B (zh) 2017-11-24 2019-12-03 国电联合动力技术有限公司 高电压穿越能力仿真评估模型及基于其的仿真评估方法
US11060504B1 (en) * 2020-02-07 2021-07-13 General Electric Company Systems and methods for continuous machine learning based control of wind turbines
CN111525590A (zh) * 2020-04-27 2020-08-11 国网冀北电力有限公司电力科学研究院 动态无功补偿装置建模方法及装置
CN112186815A (zh) * 2020-09-16 2021-01-05 国网冀北电力有限公司电力科学研究院 直驱风机高电压穿越特性的电磁暂态特性模拟系统及方法
CN113098057B (zh) * 2021-04-06 2022-10-11 广西大学 一种双馈风机参数的多目标高维多分数阶优化方法
CN113364028A (zh) * 2021-05-24 2021-09-07 国网伊犁伊河供电有限责任公司 基于Matlab/Simulink的风光互补分布式电源系统
US11649804B2 (en) 2021-06-07 2023-05-16 General Electric Renovables Espana, S.L. Systems and methods for controlling a wind turbine
CN113806907B (zh) * 2021-08-02 2024-03-01 国网冀北电力有限公司电力科学研究院 双馈风电机组机电暂态数据处理方法及装置
CN114725911B (zh) * 2022-04-06 2024-03-26 合肥工业大学 一种风电场汇集站系统变压器中性点接地电阻的估算方法
CN116316906A (zh) * 2023-02-28 2023-06-23 山东大学 双馈风电机组故障穿越后有功恢复自适应整定方法及系统
CN116306010B (zh) * 2023-04-07 2023-08-18 江苏大学 一种用于放大器的功耗数据特性分析方法及系统

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050192859A1 (en) * 2004-02-27 2005-09-01 Mertins Karl-Heinz O. Method and system of establishing a wind-powered electrical energy facility
CN101383576A (zh) * 2008-10-28 2009-03-11 华北电力大学（保定） 一种大型风力发电机组穿越电网低电压故障的方法
CN103955572A (zh) * 2014-04-23 2014-07-30 国家电网公司 一种双馈式风力发电机组机电暂态模型的建模方法
CN105589985A (zh) * 2014-11-03 2016-05-18 国家电网公司 风力发电机组参数对并网特性影响的确定方法、装置
CN107944142A (zh) * 2017-11-24 2018-04-20 国电联合动力技术有限公司 高电压穿越能力仿真评估模型及基于其的仿真评估方法

Family Cites Families (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7233129B2 (en) * 2003-05-07 2007-06-19 Clipper Windpower Technology, Inc. Generator with utility fault ride-through capability
WO2013044922A1 (en) * 2011-09-28 2013-04-04 Vestas Wind Systems A/S A wind power plant and a method for operating thereof
US9461573B2 (en) * 2012-04-24 2016-10-04 Masdar Institute Of Science And Technology Fault handling system for doubly fed induction generator
US9529057B2 (en) * 2012-07-24 2016-12-27 Binod Shrestha Apparatus and method for out-of-step protection using the analysis of trajectories of electrical measurements in state plane
US9425726B2 (en) * 2013-06-25 2016-08-23 Masdar Institute Of Science And Technology Fault-tolerant wind energy conversion system
CN104901330B (zh) * 2014-03-04 2017-05-10 国家电网公司 一种预防风电场高压脱网的综合设计方法
KR101423212B1 (ko) * 2014-05-22 2014-07-24 전북대학교산학협력단 풍력발전단지의 계통연계점 전압 제어 시스템 및 방법
US9639643B2 (en) * 2014-06-06 2017-05-02 General Electric Company Method and system for generating electric load models
CN105914755B (zh) * 2016-04-21 2018-07-24 广州供电局有限公司 电力系统动态无功优化配置方法和系统

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20050192859A1 (en) * 2004-02-27 2005-09-01 Mertins Karl-Heinz O. Method and system of establishing a wind-powered electrical energy facility
CN101383576A (zh) * 2008-10-28 2009-03-11 华北电力大学（保定） 一种大型风力发电机组穿越电网低电压故障的方法
CN103955572A (zh) * 2014-04-23 2014-07-30 国家电网公司 一种双馈式风力发电机组机电暂态模型的建模方法
CN105589985A (zh) * 2014-11-03 2016-05-18 国家电网公司 风力发电机组参数对并网特性影响的确定方法、装置
CN107944142A (zh) * 2017-11-24 2018-04-20 国电联合动力技术有限公司 高电压穿越能力仿真评估模型及基于其的仿真评估方法

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110601268A (zh) * 2019-10-29 2019-12-20 中国石油大学(华东) 一种双馈风机并网端口输出阻抗建模及稳定性分析方法
CN110601268B (zh) * 2019-10-29 2023-04-14 中国石油大学(华东) 一种双馈风机并网端口输出阻抗建模及稳定性分析方法
CN112526261A (zh) * 2020-11-25 2021-03-19 西安西电电力系统有限公司 一种故障控制策略试验系统及方法
CN112526261B (zh) * 2020-11-25 2023-05-23 西安西电电力系统有限公司 一种故障控制策略试验系统及方法

Also Published As

Publication number Publication date
PH12019502494A1 (en) 2020-07-13
CN107944142A (zh) 2018-04-20
CN107944142B (zh) 2019-12-03
US11288422B2 (en) 2022-03-29
US20200082043A1 (en) 2020-03-12
ZA201907434B (en) 2021-02-24

Similar Documents

Publication Publication Date Title
WO2019100721A1 (zh) 高电压穿越能力仿真评估模型、基于其的仿真评估方法及储存介质
WO2015035892A1 (zh) 一种双馈异步发电机组暂态短路电流的计算方法
Lee et al. Releasable kinetic energy-based inertial control of a DFIG wind power plant
Zhang et al. Flicker mitigation by individual pitch control of variable speed wind turbines with DFIG
Zhu et al. Dual-loop control strategy for DFIG-based wind turbines under grid voltage disturbances
Ledesma et al. Doubly fed induction generator model for transient stability analysis
CN107330193B (zh) 计及vsg逆变器电流限幅的暂态能量函数方法
Mei et al. Modelling of doubly-fed induction generator for power system stability study
Singh et al. Performance of wind energy conversion system using a doubly fed induction generator for maximum power point tracking
US11340274B2 (en) Method and device for locating equipment-level oscillation sources of DFIG grid-connected system
Hao et al. The contribution of double-fed wind farms to transient voltage and damping of power grids
Chowdhury et al. Dynamic DFIG wind farm model with an aggregation technique
Liang et al. The modeling and numerical simulations of wind turbine generation system with free vortex method and simulink
Abedi et al. Modeling, operation and control of wind turbine with direct drive PMSG connected to power grid
Altimania Modeling of doubly-fed induction generators connected to distribution system based on eMEGASim® real-time digital simulator
Sun et al. Modelling and simulation of doubly-fed induction wind power system based on Matlab/Simulink
He et al. DFIG wind turbine modeling and validation for LVRT behavior
Xie et al. High voltage ride through control strategy of doubly fed induction wind generators based on active resistance
Wang et al. Investigation of transient models and performances for a doubly fed wind turbine under a grid fault
Xiong et al. Calculation of steady-state short-circuit current of wind turbines with doubly fed induction generator
CN107480406A (zh) 一种双馈风电机组短路电流计算的动态向量模型建立方法
Kendeck et al. Control of permanent magnet synchronous generator based wind turbine and fault ride-through improvement during faulty grid conditions
Liu et al. Power Control Characteristic of Generic Type-3 Wind Turbine Model Based on IEC 61400-27-1 Standard
CN105703677B (zh) 一种双馈式风力发电机转子暂态电流的计算方法
Iranmanesh et al. Using Flywheel Energy Storage System to mitigate voltage and power fluctuations due to aeroelastic aspects of wind turbines

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 18881877

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 18881877

Country of ref document: EP

Kind code of ref document: A1