WO2019148775A1 - 风电机组的功率控制方法和设备 - Google Patents

风电机组的功率控制方法和设备 Download PDF

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Publication number
WO2019148775A1
WO2019148775A1 PCT/CN2018/095609 CN2018095609W WO2019148775A1 WO 2019148775 A1 WO2019148775 A1 WO 2019148775A1 CN 2018095609 W CN2018095609 W CN 2018095609W WO 2019148775 A1 WO2019148775 A1 WO 2019148775A1
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Prior art keywords
wind
wind turbine
design life
resource data
output power
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PCT/CN2018/095609
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English (en)
French (fr)
Inventor
余梦婷
张鹏飞
周桂林
王明辉
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北京金风科创风电设备有限公司
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First worldwide family litigation filed litigation Critical https://patents.darts-ip.com/?family=64325989&utm_source=google_patent&utm_medium=platform_link&utm_campaign=public_patent_search&patent=WO2019148775(A1) "Global patent litigation dataset” by Darts-ip is licensed under a Creative Commons Attribution 4.0 International License.
Application filed by 北京金风科创风电设备有限公司 filed Critical 北京金风科创风电设备有限公司
Priority to AU2018406114A priority Critical patent/AU2018406114B2/en
Priority to US16/763,224 priority patent/US11506174B2/en
Priority to EP18903654.4A priority patent/EP3696401B1/en
Publication of WO2019148775A1 publication Critical patent/WO2019148775A1/zh

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    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
    • F03D—WIND MOTORS
    • F03D7/00—Controlling wind motors 
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
    • F03D—WIND MOTORS
    • F03D7/00—Controlling wind motors 
    • F03D7/02—Controlling wind motors  the wind motors having rotation axis substantially parallel to the air flow entering the rotor
    • F03D7/028—Controlling wind motors  the wind motors having rotation axis substantially parallel to the air flow entering the rotor controlling wind motor output power
    • F03D7/0292—Controlling wind motors  the wind motors having rotation axis substantially parallel to the air flow entering the rotor controlling wind motor output power to reduce fatigue
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
    • F03D—WIND MOTORS
    • F03D7/00—Controlling wind motors 
    • F03D7/02—Controlling wind motors  the wind motors having rotation axis substantially parallel to the air flow entering the rotor
    • F03D7/04—Automatic control; Regulation
    • F03D7/042—Automatic control; Regulation by means of an electrical or electronic controller
    • F03D7/043—Automatic control; Regulation by means of an electrical or electronic controller characterised by the type of control logic
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F03—MACHINES OR ENGINES FOR LIQUIDS; WIND, SPRING, OR WEIGHT MOTORS; PRODUCING MECHANICAL POWER OR A REACTIVE PROPULSIVE THRUST, NOT OTHERWISE PROVIDED FOR
    • F03D—WIND MOTORS
    • F03D7/00—Controlling wind motors 
    • F03D7/02—Controlling wind motors  the wind motors having rotation axis substantially parallel to the air flow entering the rotor
    • F03D7/04—Automatic control; Regulation
    • F03D7/042—Automatic control; Regulation by means of an electrical or electronic controller
    • F03D7/043—Automatic control; Regulation by means of an electrical or electronic controller characterised by the type of control logic
    • F03D7/045—Automatic control; Regulation by means of an electrical or electronic controller characterised by the type of control logic with model-based controls
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05B—INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
    • F05B2260/00—Function
    • F05B2260/82—Forecasts
    • F05B2260/821—Parameter estimation or prediction
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05B—INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
    • F05B2270/00—Control
    • F05B2270/10—Purpose of the control system
    • F05B2270/103—Purpose of the control system to affect the output of the engine
    • F05B2270/1033—Power (if explicitly mentioned)
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05B—INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
    • F05B2270/00—Control
    • F05B2270/10—Purpose of the control system
    • F05B2270/109—Purpose of the control system to prolong engine life
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05B—INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
    • F05B2270/00—Control
    • F05B2270/10—Purpose of the control system
    • F05B2270/20—Purpose of the control system to optimise the performance of a machine
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05B—INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
    • F05B2270/00—Control
    • F05B2270/30—Control parameters, e.g. input parameters
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05B—INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
    • F05B2270/00—Control
    • F05B2270/30—Control parameters, e.g. input parameters
    • F05B2270/32—Wind speeds
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05B—INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
    • F05B2270/00—Control
    • F05B2270/30—Control parameters, e.g. input parameters
    • F05B2270/321—Wind directions
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05B—INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
    • F05B2270/00—Control
    • F05B2270/30—Control parameters, e.g. input parameters
    • F05B2270/332—Maximum loads or fatigue criteria
    • F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
    • F05—INDEXING SCHEMES RELATING TO ENGINES OR PUMPS IN VARIOUS SUBCLASSES OF CLASSES F01-F04
    • F05B—INDEXING SCHEME RELATING TO WIND, SPRING, WEIGHT, INERTIA OR LIKE MOTORS, TO MACHINES OR ENGINES FOR LIQUIDS COVERED BY SUBCLASSES F03B, F03D AND F03G
    • F05B2270/00—Control
    • F05B2270/40—Type of control system
    • F05B2270/404—Type of control system active, predictive, or anticipative

Definitions

  • the present disclosure relates to the field of control of wind turbines. More particularly, it relates to a power control method and apparatus for a wind turbine.
  • Wind energy has become a renewable energy source with a wide range of research due to its large, renewable, widely distributed and pollution-free nature.
  • Wind turbines generally follow the principle of optimizing their power generation capacity under standard wind parameters when determining the power curve during the design phase.
  • the power control is generally performed according to the power curve determined in the design stage, but the wind parameters of the actual wind farm differ greatly from the standard wind parameters. Therefore, the existing power control methods cannot be simultaneously considered. Safety and economy of the unit operation.
  • the purpose of the present disclosure is to provide a power control method and apparatus for a wind turbine to solve the problem that the existing power control method cannot simultaneously consider the safety and economy of the unit operation.
  • An aspect of the present disclosure provides a power control method for a wind turbine, the power control method including: predicting wind resource data in a predetermined predetermined time period according to historical wind resource data; and estimating a wind turbine in the future according to a remaining design life of the wind turbine.
  • the maximum design life allowed for a predetermined period of time wherein the design life is the time during which the wind turbine is operating under the design load; and the wind speed is determined in the future predetermined time period based on the predicted wind resource data and the estimated maximum design life.
  • the optimal output power of the wind turbine of the segment; the wind turbine operation is controlled according to the determined optimal output power of the wind turbines in each of the determined wind speed segments in a predetermined time period in the future.
  • a power control apparatus for a wind turbine, the power control apparatus including: a prediction unit that predicts wind resource data in a future predetermined time period based on historical wind resource data; and an estimation unit according to remaining of the wind turbine
  • the design life estimates the maximum design life that the wind turbine is allowed to consume for a predetermined period of time in the future, wherein the design life is the time at which the wind turbine is operating under the design load; the determination unit, based on the predicted wind resource data and the estimated maximum design
  • the life determines the optimal output power of the wind turbines in each wind speed segment in the future predetermined time period; the control unit controls the wind turbine operation according to the determined optimal output power of the wind turbines in each of the determined wind speed segments in the future predetermined time period.
  • Another aspect of the present disclosure provides a computer readable storage medium storing a computer program that, when executed by a processor, causes a processor to perform a power control method of a wind turbine as described above.
  • a power control method and apparatus for a wind turbine determines an optimal output power of a wind turbine of each wind speed section by predicting wind resource data and a design life consumed by the wind turbine, thereby ensuring safe operation of the wind turbine At the same time, as much as possible to increase power generation capacity.
  • FIG. 1 is a flowchart illustrating a power control method of a wind turbine according to an embodiment of the present disclosure
  • FIG. 2 is a block diagram showing a power control device of a wind turbine according to an embodiment of the present disclosure.
  • FIG. 1 is a flowchart illustrating a power control method of a wind turbine according to an embodiment of the present disclosure.
  • the wind resource data in the future predetermined time period is predicted based on the historical wind resource data.
  • the wind resource data may include wind speed, or include at least one of wind speed and below: turbulence intensity, wind shear, wind direction, inflow dip, wind frequency distribution, and air density.
  • the present disclosure does not limit the specific manner of predicting wind resource data in a predetermined time period in the future, and various existing wind resource prediction methods may be employed to predict wind resource data in a predetermined time period in the future.
  • various existing wind resource prediction methods may be employed to predict wind resource data in a predetermined time period in the future.
  • step S20 the maximum design life allowed for the wind turbine to be consumed for a predetermined period of time in the future is estimated based on the remaining design life of the wind turbine.
  • Design life is the time it takes for a wind turbine to operate under design load.
  • the maximum design life allowed for the wind turbine to be consumed for a predetermined period of time in the future is determined based on the remaining design life of the wind turbine and in conjunction with the time actually used by the wind turbine, the rated design life, and the length of time for a predetermined period of time in the future.
  • the remaining time of the wind turbine can be determined according to the actual used time and rated design life of the wind turbine, and the time length of the future predetermined time period and wind power can be determined.
  • the product of the ratio of the remaining operating time of the unit to the remaining design life of the wind turbine is used as the maximum design life allowed for the wind turbine to be consumed for a predetermined period of time in the future.
  • the remaining design life of the wind turbine can be obtained by subtracting the nominal design life from the actual used time of the wind turbine.
  • the present disclosure does not limit the specific manner of estimating the maximum design life allowed to be consumed in a predetermined period of time in the future, and may be estimated in other ways.
  • the present disclosure may also determine the design life consumed by the wind turbine by fatigue load simulation based on historical wind resource data and historical operational data of the wind turbine, according to the rated design life and the designed design life consumed. Determine the remaining design life. The remaining design life can be obtained by subtracting the designed design life from the rated design life.
  • the historical operational data may include at least one of the following: fault data, the number of occurrences of the shutdown, and the duration of the idle state.
  • fault data In the wind turbine design stage, the fault conditions and the number of occurrences of the start and stop in the fatigue load simulation are usually in accordance with the recommendations of the relevant standards.
  • the duration of the idle condition is only based on the probability density distribution of the wind speed, and is not considered.
  • the idling state in this case also needs to be counted. In a preferred embodiment, historical operational data needs to distinguish between different sectors.
  • the fatigue load simulation can be performed based on the historical wind resource data and the historical operation data of the wind turbine to obtain the equivalent fatigue load of the wind turbine, and then according to the equivalent fatigue load and the equivalent fatigue load and the consumed design life.
  • the correspondence yields the designed design life that has been consumed.
  • the fatigue load simulation of the wind turbine is based on historical wind resource data and historical operational data, and the equivalent fatigue load of each of the predefined key components of the wind turbine is obtained, according to the equivalent fatigue load of each key component and each key component.
  • the design fatigue load is the design life that has been consumed by each critical component, and the life that the wind turbine has consumed is determined based on the design life that each critical component has consumed.
  • the maximum value of the design life that has been consumed by each key component is taken as the life that the wind turbine has consumed.
  • the corresponding fatigue load simulation conditions can be determined according to historical wind resource data and historical operation data, and parameters of fatigue load simulation (such as fatigue occurrence time and number of times) are set according to wind frequency distribution and historical operation data in historical wind resource data. ), the fatigue load simulation is used to determine the equivalent fatigue load of each key component in each year.
  • the fatigue load simulation is performed in units of years, the fatigue occurrence time and the number of times of each sector can be allocated according to the wind frequency distribution, the total time of occurrence of fatigue is 1 year, and the number of occurrences of fatigue can be set to 500,000 times.
  • the present disclosure does not limit the numerical value of the number of occurrences of fatigue, and may also be the number of occurrences of fatigue of other values.
  • the design life that has been consumed by a critical component to the Nth year can be determined according to the following equation (1).
  • Life consume is the accumulated design life of a key component to the Nth year.
  • EQ design represents the fatigue load of a key component design
  • EQ n represents the equivalent fatigue load of the nth year.
  • an optimal output power of the wind turbines of each wind speed segment in a predetermined time period in the future is determined based on the predicted wind resource data and the estimated maximum design life.
  • the predicted wind resource data and the maximum design life that can be consumed can be estimated in the future predetermined time period, and the wind turbine is allowed to ensure that the equivalent load does not exceed the equivalent load corresponding to the maximum design life.
  • Maximum output power ie, optimal output power
  • the power output range of the wind turbines in each wind speed segment may be determined first, and the optimal output power of the wind turbines in each wind speed segment may be determined within the power output range of each wind speed segment.
  • various existing methods can be employed to determine the power output range of the wind turbine at each wind speed segment.
  • the first way determines the optimal output power by iterative calculation.
  • the initial value of the set output power of the wind turbine in each wind speed section is set.
  • the initial value of the set output power of each wind speed segment is preferably the maximum value in the power output range of each wind speed segment.
  • a load calculation step is performed: determining an equivalent load of the wind turbine for a predetermined period of time according to the predicted wind resource data and the set output power of the wind speed section where the wind speed is located in the wind resource data.
  • the equivalent load of the wind turbine set in the future predetermined time period is determined by various existing load calculation methods.
  • the design life of the wind turbine in the future predetermined time period is estimated based on the equivalent load.
  • the optimal output power when the absolute value is not less than the predetermined value, updates the set output power, returns the load calculation step, and performs the next iteration calculation.
  • the power output range of each wind speed segment can be divided by the rated power, and the power output range is divided into two intervals, which are determined by the dichotomy method.
  • the set output power calculated in the next iteration is the power output range of each wind speed segment.
  • the second method first determines a first equivalent load of the wind turbine for a predetermined time period based on the maximum design life; and determines, according to the first equivalent load and the predicted wind resource data, each wind speed in the wind resource data.
  • the optimal output power of the wind turbine of the wind speed section is such that the absolute value of the difference between the second equivalent load and the first equivalent load of the wind turbine set in the future predetermined time period calculated based on the wind resource data and the determined optimal output power Less than the predetermined value.
  • the optimal output power of the wind turbine can be calculated by optimizing the way, and the optimization target is the second equivalent load of the wind turbine in the future predetermined time period and the first equivalent.
  • the absolute value of the difference in load is less than a predetermined value.
  • step S40 the wind turbine operation is controlled in accordance with the determined optimal output power of the wind turbines of the respective wind speed segments in a predetermined period of time in the future.
  • the wind turbine in the future predetermined period of time, is controlled to output the optimal output power of the wind speed section where the actual wind speed is located, so that the wind turbine set under the harsh wind resource condition can sacrifice a certain power generation capability to ensure its Safety, while wind turbines under better wind conditions increase power generation capacity as much as possible while ensuring safety.
  • the actual wind speed can be detected, the wind speed section where the actual wind speed is located, and the optimal output power of the wind speed section in which the wind turbine output the actual wind speed is controlled.
  • FIG. 2 is a block diagram showing a power control device of a wind turbine according to an embodiment of the present disclosure.
  • the power control device of the wind turbine includes a prediction unit 10, an estimation unit 20, a determination unit 30, and a control unit 40.
  • the prediction unit 10 predicts wind resource data in a predetermined predetermined time period based on the historical wind resource data.
  • the wind resource data may include wind speed, or include at least one of wind speed and below: turbulence intensity, wind shear, wind direction, inflow dip, wind frequency distribution, and air density.
  • the present disclosure does not limit the specific manner of predicting wind resource data in a predetermined time period in the future, and various existing wind resource prediction methods may be employed to predict wind resource data in a predetermined time period in the future.
  • various existing wind resource prediction methods may be employed to predict wind resource data in a predetermined time period in the future.
  • the estimation unit 20 estimates the maximum design life that the wind turbine is allowed to consume for a predetermined period of time in the future based on the remaining design life of the wind turbine.
  • Design life is the time it takes for a wind turbine to operate under design load.
  • the maximum design life allowed for the wind turbine to be consumed for a predetermined period of time in the future is determined based on the remaining design life of the wind turbine and in conjunction with the time actually used by the wind turbine, the rated design life, and the length of time for a predetermined period of time in the future.
  • the remaining time of the wind turbine can be determined according to the actual used time and rated design life of the wind turbine, and the time length of the future predetermined time period and wind power can be determined.
  • the product of the ratio of the remaining operating time of the unit to the remaining design life of the wind turbine is used as the maximum design life allowed for the wind turbine to be consumed for a predetermined period of time in the future.
  • the remaining design life of the wind turbine can be obtained by subtracting the nominal design life from the actual used time of the wind turbine.
  • the present disclosure does not limit the specific manner of estimating the maximum design life allowed to be consumed in a predetermined period of time in the future, and may be estimated in other ways.
  • the present disclosure may also determine the design life consumed by the wind turbine by fatigue load simulation based on historical wind resource data and historical operational data of the wind turbine, according to the rated design life and the designed design life consumed. Determine the remaining design life. The remaining design life can be obtained by subtracting the designed design life from the rated design life.
  • the historical operational data may include at least one of the following: fault data, the number of occurrences of the shutdown, and the duration of the idle state.
  • fault data In the wind turbine design stage, the fault conditions and the number of occurrences of the start and stop in the fatigue load simulation are usually in accordance with the recommendations of the relevant standards.
  • the duration of the idle condition is only based on the probability density distribution of the wind speed, and is not considered.
  • the idling state in this case also needs to be counted. In a preferred embodiment, historical operational data needs to distinguish between different sectors.
  • the fatigue load simulation can be performed based on the historical wind resource data and the historical operation data of the wind turbine to obtain the equivalent fatigue load of the wind turbine, and then according to the equivalent fatigue load and the equivalent fatigue load and the consumed design life.
  • the correspondence yields the designed design life that has been consumed.
  • the fatigue load simulation of the wind turbine is based on historical wind resource data and historical operational data, and the equivalent fatigue load of each of the predefined key components of the wind turbine is obtained, according to the equivalent fatigue load of each key component and each key component.
  • the design fatigue load is the design life that has been consumed by each critical component, and the life that the wind turbine has consumed is determined based on the design life that each critical component has consumed.
  • the maximum value of the design life that has been consumed by each key component is taken as the life that the wind turbine has consumed.
  • the corresponding fatigue load simulation conditions can be determined according to historical wind resource data and historical operation data, and parameters of fatigue load simulation (such as fatigue occurrence time and number of times) are set according to wind frequency distribution and historical operation data in historical wind resource data. ), the fatigue load simulation is used to determine the equivalent fatigue load of each key component in each year.
  • the fatigue load simulation is performed in units of years, the fatigue occurrence time and the number of times of each sector can be allocated according to the wind frequency distribution, the total time of occurrence of fatigue is 1 year, and the number of occurrences of fatigue can be set to 500,000 times.
  • the present disclosure does not limit the numerical value of the number of occurrences of fatigue, and may also be the number of occurrences of fatigue of other values.
  • the design life that has been consumed by a critical component to the Nth year can be determined according to the above equation (1).
  • the determining unit 30 determines the optimal output power of the wind turbines of each wind speed segment in the future predetermined time period based on the predicted wind resource data and the estimated maximum design life.
  • the predicted wind resource data and the maximum design life that can be consumed can be estimated in the future predetermined time period, and the wind turbine is allowed to ensure that the equivalent load does not exceed the equivalent load corresponding to the maximum design life.
  • Maximum output power ie, optimal output power
  • the power output range of the wind turbines in each wind speed segment may be determined first, and the optimal output power of the wind turbines in each wind speed segment may be determined within the power output range of each wind speed segment.
  • various existing methods can be employed to determine the power output range of the wind turbine at each wind speed segment.
  • the first way determines the optimal output power by iterative calculation.
  • the initial value of the set output power of the wind turbine in each wind speed section is set.
  • the initial value of the set output power of each wind speed segment is preferably the maximum value in the power output range of each wind speed segment.
  • a load calculation step is performed: determining an equivalent load of the wind turbine for a predetermined period of time according to the predicted wind resource data and the set output power of the wind speed section where the wind speed is located in the wind resource data.
  • the equivalent load of the wind turbine set in the future predetermined time period is determined by various existing load calculation methods.
  • the design life of the wind turbine in the future predetermined time period is estimated based on the equivalent load.
  • the optimal output power when the absolute value is not less than the predetermined value, updates the set output power, returns the load calculation step, and performs the next iteration calculation.
  • the power output range of each wind speed segment can be divided by the rated power, and the power output range is divided into two intervals, which are determined by the dichotomy method.
  • the set output power calculated in the next iteration is the power output range of each wind speed segment.
  • the second method first determines a first equivalent load of the wind turbine for a predetermined time period based on the maximum design life; and determines, according to the first equivalent load and the predicted wind resource data, each wind speed in the wind resource data.
  • the optimal output power of the wind turbine of the wind speed section is such that the absolute value of the difference between the second equivalent load and the first equivalent load of the wind turbine set in the future predetermined time period calculated based on the wind resource data and the determined optimal output power Less than the predetermined value.
  • the optimal output power of the wind turbine can be calculated by optimizing the way, and the optimization target is the second equivalent load of the wind turbine in the future predetermined time period and the first equivalent.
  • the absolute value of the difference in load is less than a predetermined value.
  • the control unit 40 controls the operation of the wind turbine in accordance with the determined optimal output power of the wind turbines of the respective wind speed segments for a predetermined period of time in the future.
  • the wind turbine in the future predetermined period of time, is controlled to output the optimal output power of the wind speed section where the actual wind speed is located, so that the wind turbine set under the harsh wind resource condition can sacrifice a certain power generation capability to ensure its Safety, while wind turbines under better wind conditions increase power generation capacity as much as possible while ensuring safety.
  • the actual wind speed can be detected, the wind speed segment where the actual wind speed is located, and the optimal output power of the wind speed segment where the actual wind speed is output by the wind turbine group is controlled.
  • a power control method and apparatus for a wind turbine determines an optimal output power of a wind turbine of each wind speed section by predicting wind resource data and a design life consumed by the wind turbine, thereby ensuring safe operation of the wind turbine At the same time, as much as possible to increase power generation capacity.
  • a computer readable storage medium stores a computer program that, when executed by a processor, causes the processor to perform a power control method of the wind turbine as described above.
  • a computing device is also provided in accordance with an embodiment of the present disclosure.
  • the computing device includes a processor and a memory.
  • the memory is used to store program instructions.
  • the program instructions are executed by a processor such that the processor executes a computer program of the power control method of the wind turbine as described above.
  • each program module in the power control device of the wind turbine may be implemented entirely by hardware, such as a field programmable gate array or an application specific integrated circuit; or may be implemented by a combination of hardware and software. It can also be implemented in software entirely through a computer program.

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  • Life Sciences & Earth Sciences (AREA)
  • Sustainable Development (AREA)
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  • Chemical & Material Sciences (AREA)
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Abstract

一种风电机组的功率控制方法及设备，该功率控制方法包括：根据历史风资源数据预测未来预定时间段内的风资源数据（S10）；根据风电机组的剩余设计寿命估计风电机组在未来预定时间段内允许消耗的最大设计寿命（S20）；根据预测的风资源数据以及估计的最大设计寿命确定在未来预定时间段内各风速段的风电机组的最优输出功率（S30）；在未来预定时间段内按照确定的各风速段的风电机组的最优输出功率控制风电机组运行（S40）。

Description

风电机组的功率控制方法和设备 技术领域
本公开涉及风电机组的控制领域。更具体地讲，涉及一种风电机组的功率控制方法和设备。
背景技术
随着全球范围内能源危机形势愈发明显，开发可再生能源已成为世界各国能源发展战略的重大举措。风能因其在全球范围内蕴藏量巨大、可再生、分布广和无污染的特性，使风力发电成为研究较为广泛的一种可再生能源。
风电机组在设计阶段确定功率曲线时通常遵循在标准风参数下使其发电能力最优的原则。风电机组的时间运行过程中，一般都是按照在设计阶段确定的功率曲线进行功率控制，但实际风电场的风参数与标准风参数差异较大，因此，现有的功率控制方法并不能同时兼顾机组运行的安全性和经济性。
发明内容
本公开的目的在于提供一种风电机组的功率控制方法和设备，以解决现有的功率控制方法并不能同时兼顾机组运行的安全性和经济性的问题。
本公开的一方面提供一种风电机组的功率控制方法，所述功率控制方法包括：根据历史风资源数据预测未来预定时间段内的风资源数据；根据风电机组的剩余设计寿命估计风电机组在未来预定时间段内允许消耗的最大设计寿命，其中，所述设计寿命是指风电机组在设计载荷下运行的时间；根据预测的风资源数据以及估计的最大设计寿命确定在未来预定时间段内各风速段的风电机组的最优输出功率；在未来预定时间段内按照确定的各风速段的风电机组的最优输出功率来控制风电机组运行。
本公开的另一方面提供一种风电机组的功率控制设备，所述功率控制设备包括：预测单元，根据历史风资源数据预测未来预定时间段内的风资源数据；估计单元，根据风电机组的剩余设计寿命估计风电机组在未来预定时间段内允许消耗的最大设计寿命，其中，所述设计寿命是指风电机组在设计载 荷下运行的时间；确定单元，根据预测的风资源数据以及估计的最大设计寿命确定在未来预定时间段内各风速段的风电机组的最优输出功率；控制单元，在未来预定时间段内按照确定的各风速段的风电机组的最优输出功率控制风电机组运行。
本公开的另一方面提供一种计算机可读存储介质，该计算机可读存储介质存储有当被处理器执行时使得处理器执行如上所述的风电机组的功率控制方法的计算机程序。
本公开的另一方面提供一种计算装置，该计算装置包括：处理器；存储器，用于存储当被处理器执行使得处理器执行如上所述的风电机组的功率控制方法的计算机程序。
根据本公开的实施例的风电机组的功率控制方法和设备，通过预测风资源数据以及风电机组已消耗的设计寿命来确定各风速段的风电机组的最优输出功率，可在保证风电机组安全运行的同时尽可能地提高发电能力。
将在接下来的描述中部分阐述本公开另外的方面和/或优点，还有一部分通过描述将是清楚的，或者可以经过本公开的实施而得知。
附图说明
通过下面结合附图进行的详细描述，本公开的上述和其它目的、特点和优点将会变得更加清楚，其中：
图1是示出根据本公开的实施例的风电机组的功率控制方法的流程图；
图2是示出根据本公开的实施例的风电机组的功率控制设备的框图。
具体实施方式
下面参照附图详细描述本公开的实施例。
图1是示出根据本公开的实施例的风电机组的功率控制方法的流程图。
在步骤S10，根据历史风资源数据预测未来预定时间段内的风资源数据。这里，风资源数据可包括风速，或者包括风速和以下至少一项：湍流强度、风剪切、风向、入流倾角、风频分布和空气密度。
本公开不对预测未来预定时间段内的风资源数据的具体方式进行限制，可采用各种现有的风资源预测方法来预测未来预定时间段内的风资源数据。在预测未来预定时间段内的风资源数据时，不需要考虑不同扇区。
在步骤S20，根据风电机组的剩余设计寿命估计风电机组在未来预定时间段内允许消耗的最大设计寿命。
设计寿命是指风电机组在设计载荷下运行的时间。
作为示例，根据风电机组的剩余设计寿命，并且结合风电机组实际已使用的时间、额定设计寿命以及未来预定时间段的时间长度来确定风电机组在未来预定时间段内允许消耗的最大设计寿命。
在假设风电机组在未来使用时间内均匀消耗剩余设计寿命的情况下，可根据风电机组的实际已使用的时间和额定设计寿命确定风电机组的剩余使用时间，将未来预定时间段的时间长度与风电机组的剩余使用时间之间的比值与风电机组的剩余设计寿命的乘积作为风电机组在未来预定时间段内允许消耗的最大设计寿命。这里，可将额定设计寿命减去风电机组的实际已使用的时间得到风电机组的剩余使用时间。
本公开不对估计未来预定时间段内允许消耗的最大设计寿命的具体方式进行限制，还可以采用其他方式来估计。
在剩余设计寿命是未知的情况下，本公开还可根据历史风资源数据和风电机组的历史运行数据，通过疲劳载荷仿真确定风电机组已消耗的设计寿命，根据额定设计寿命和已消耗的设计寿命确定剩余设计寿命。可将额定设计寿命减去已消耗的设计寿命得到剩余设计寿命。
历史运行数据可包括以下至少一项：故障数据、启停机发生次数和空转状态的持续时间。在风电机组设计阶段，在疲劳载荷仿真中故障工况、启停机发生次数通常都按照相关标准的建议取值，空转工况的持续时间也仅仅是按照风速的概率密度分布取值，都没有考虑现场风电机组实际运行情况。因此，在本公开中进行疲劳载荷仿真时，为了更加准确地准确评估机组运行状态，在一个优选的实施例中，需要统计以下运行数据：故障数据、启停机发生次数和空转状态的持续时间。需要注意，在设计阶段疲劳载荷仿真中只考虑在切入转速之前或切出转速之后的空转状态，而现场风电机组实际运行时，由于扇区管理等原因，在运行风速区间内，风电机组也可能处于空转状态，在一个优先的实施例中，这种情况下的空转状态也需要统计。在一个优先的实施例中，历史运行数据需要区分不同的扇区。
作为示例，可根据历史风资源数据和风电机组的历史运行数据进行疲劳载荷仿真，得到风电机组的等效疲劳载荷，再根据等效疲劳载荷以及等效疲 劳载荷与已消耗的设计寿命之间的对应关系得到已消耗的设计寿命。
具体说来，根据历史风资源数据和历史运行数据对风电机组进行疲劳载荷仿真，得到风电机组的预定义的各个关键部件的等效疲劳载荷，根据各个关键部件的等效疲劳载荷以及各个关键部件的设计疲劳载荷得到各个关键部件已消耗的设计寿命，根据各个关键部件已消耗的设计寿命来确定风电机组已消耗的寿命。将各个关键部件已消耗的设计寿命中的最大值作为风电机组已消耗的寿命。
这里，可根据历史风资源数据和历史运行数据制定相应的疲劳载荷仿真工况，并根据历史风资源数据中的风频分布和历史运行数据设置疲劳载荷仿真的参数(例如疲劳发生时间和次数等)，通过疲劳载荷仿真确定各个关键部件在各年的等效疲劳载荷。作为示例，在以年为单位进行疲劳载荷仿真时，可按风频分布分配各个扇区的疲劳发生时间和次数，疲劳发生的总时间为1年，疲劳发生次数可设置为50万次。本公开不对疲劳发生次数的数值进行限制，还可以时其他数值的疲劳发生次数。
某个关键部件到第N年累计已消耗的设计寿命可根据以下等式(1)进行确定。
Figure PCTCN2018095609-appb-000001
其中，Life consume为某个关键部件到第N年累计已消耗的设计寿命，EQ design表示某个关键部件设计疲劳载荷，EQ n表示第n年的等效疲劳载荷。
在步骤S30，根据预测的风资源数据以及估计的最大设计寿命确定在未来预定时间段内各风速段的风电机组的最优输出功率。
这里，在一定风况下，风电机组输出越多的功率，其所承受的载荷就越大。因此，可通过预测的风资源数据和可消耗的最大设计寿命，估算在未来预定时间段内，在保证等效载荷不超过该最大设计寿命对应的等效载荷的情况下，风力发电机组允许的最大输出功率(即最优输出功率)，以兼顾风电机组运行的安全性和经济性。
作为示例，在确定最优输出功率之前，可先确定风电机组的在各风速段的功率输出范围，各风速段的风电机组的最优输出功率可在各风速段的功率输出范围内进行确定。这里，可采用各种现有的方法来确定风电机组的在各风速段的功率输出范围。
以下将列举两种确定最优输出功率的方式。
第一种方式通过迭代计算的方式来确定最优输出功率。
具体说来，首先设置风电机组在各风速段的设定输出功率的初始值。为了减少迭代次数，各风速段的设定输出功率的初始值优选为各风速段的功率输出范围中的最大值。
然后进行载荷计算步骤：根据预测的风资源数据以及风资源数据中的风速所在的风速段的设定输出功率，确定风电机组在未来预定时间段的等效载荷。这里，根据预测的风资源数据以及风资源数据中的风速所在的风速段的设定输出功率，通过各种现有的载荷计算方法，确定风电机组在未来预定时间段的等效载荷。
根据等效载荷估计风电机组在未来预定时间段内的设计寿命。
确定估计的设计寿命与所述最大设计寿命之间的差值的绝对值是否小于预定值；当绝对值小于预定值时，将各风速段当前的设定输出功率作为各风速段的风电机组的最优输出功率，当绝对值不小于预定值时，更新设定输出功率，返回载荷计算步骤，进行下一次迭代计算。
这里，在更新用于下一次迭代计算的设定输出功率时，可将各风速段的功率输出范围以额定功率为界，将功率输出范围分为为两个区间，采用二分法来确定用于下一次迭代计算的设定输出功率。
第二种方式先基于所述最大设计寿命确定风电机组在未来预定时间段的第一等效载荷；再基于第一等效载荷和预测的风资源数据，确定风资源数据中的各个风速所在的风速段的风电机组的最优输出功率，使得基于风资源数据和确定的最优输出功率计算得到的风电机组在未来预定时间段的第二等效载荷与第一等效载荷之差的绝对值小于预定值。在第二种方式中，可通过寻优的方式来计算得到风速段的风电机组的最优输出功率，寻优的目标为风电机组在未来预定时间段的第二等效载荷与第一等效载荷之差的绝对值小于预定值。
在步骤S40，在未来预定时间段内按照确定的各风速段的风电机组的最优输出功率来控制风电机组运行。
也就是说，在未来预定时间段内，控制风电机组输出实际的风速所在的风速段的最优输出功率，从而使得处于较为恶劣的风资源条件下的风电机组可牺牲一定的发电能力来保证其安全性，而处于较好风资源条件下的风电机组在保证安全性地前提下尽可能增加发电能力。具体地说，在未来预定时间 段内，可检测实际的风速，确定实际的风速所在的风速段，控制风电机组输出实际的风速所在的风速段的最优输出功率。
图2是示出根据本公开的实施例的风电机组的功率控制设备的框图。
根据本公开的实施例的风电机组的功率控制设备包括预测单元10、估计单元20、确定单元30和控制单元40。
预测单元10根据历史风资源数据预测未来预定时间段内的风资源数据。这里，风资源数据可包括风速，或者包括风速和以下至少一项：湍流强度、风剪切、风向、入流倾角、风频分布和空气密度。
本公开不对预测未来预定时间段内的风资源数据的具体方式进行限制，可采用各种现有的风资源预测方法来预测未来预定时间段内的风资源数据。在预测未来预定时间段内的风资源数据时，不需要考虑不同扇区。
估计单元20根据风电机组的剩余设计寿命估计风电机组在未来预定时间段内允许消耗的最大设计寿命。
设计寿命是指风电机组在设计载荷下运行的时间。
作为示例，根据风电机组的剩余设计寿命，并且结合风电机组实际已使用的时间、额定设计寿命以及未来预定时间段的时间长度来确定风电机组在未来预定时间段内允许消耗的最大设计寿命。
在假设风电机组在未来使用时间内均匀消耗剩余设计寿命的情况下，可根据风电机组的实际已使用的时间和额定设计寿命确定风电机组的剩余使用时间，将未来预定时间段的时间长度与风电机组的剩余使用时间之间的比值与风电机组的剩余设计寿命的乘积作为风电机组在未来预定时间段内允许消耗的最大设计寿命。这里，可将额定设计寿命减去风电机组的实际已使用的时间得到风电机组的剩余使用时间。
本公开不对估计未来预定时间段内允许消耗的最大设计寿命的具体方式进行限制，还可以采用其他方式来估计。
在剩余设计寿命是未知的情况下，本公开还可根据历史风资源数据和风电机组的历史运行数据，通过疲劳载荷仿真确定风电机组已消耗的设计寿命，根据额定设计寿命和已消耗的设计寿命确定剩余设计寿命。可将额定设计寿命减去已消耗的设计寿命得到剩余设计寿命。
历史运行数据可包括以下至少一项：故障数据、启停机发生次数和空转状态的持续时间。在风电机组设计阶段，在疲劳载荷仿真中故障工况、启停 机发生次数通常都按照相关标准的建议取值，空转工况的持续时间也仅仅是按照风速的概率密度分布取值，都没有考虑现场风电机组实际运行情况。因此，在本公开中进行疲劳载荷仿真时，为了更加准确地准确评估机组运行状态，在一个优选的实施例中，需要统计以下运行数据：故障数据、启停机发生次数和空转状态的持续时间。需要注意，在设计阶段疲劳载荷仿真中只考虑在切入转速之前或切出转速之后的空转状态，而现场风电机组实际运行时，由于扇区管理等原因，在运行风速区间内，风电机组也可能处于空转状态，在一个优先的实施例中，这种情况下的空转状态也需要统计。在一个优先的实施例中，历史运行数据需要区分不同的扇区。
作为示例，可根据历史风资源数据和风电机组的历史运行数据进行疲劳载荷仿真，得到风电机组的等效疲劳载荷，再根据等效疲劳载荷以及等效疲劳载荷与已消耗的设计寿命之间的对应关系得到已消耗的设计寿命。
具体说来，根据历史风资源数据和历史运行数据对风电机组进行疲劳载荷仿真，得到风电机组的预定义的各个关键部件的等效疲劳载荷，根据各个关键部件的等效疲劳载荷以及各个关键部件的设计疲劳载荷得到各个关键部件已消耗的设计寿命，根据各个关键部件已消耗的设计寿命来确定风电机组已消耗的寿命。将各个关键部件已消耗的设计寿命中的最大值作为风电机组已消耗的寿命。
这里，可根据历史风资源数据和历史运行数据制定相应的疲劳载荷仿真工况，并根据历史风资源数据中的风频分布和历史运行数据设置疲劳载荷仿真的参数(例如疲劳发生时间和次数等)，通过疲劳载荷仿真确定各个关键部件在各年的等效疲劳载荷。作为示例，在以年为单位进行疲劳载荷仿真时，可按风频分布分配各个扇区的疲劳发生时间和次数，疲劳发生的总时间为1年，疲劳发生次数可设置为50万次。本公开不对疲劳发生次数的数值进行限制，还可以时其他数值的疲劳发生次数。
某个关键部件到第N年累计已消耗的设计寿命可根据上述等式(1)进行确定。
确定单元30根据预测的风资源数据以及估计的最大设计寿命确定在未来预定时间段内各风速段的风电机组的最优输出功率。
这里，在一定风况下，风电机组输出越多的功率，其所承受的载荷就越大。因此，可通过预测的风资源数据和可消耗的最大设计寿命，估算在未来 预定时间段内，在保证等效载荷不超过该最大设计寿命对应的等效载荷的情况下，风力发电机组允许的最大输出功率(即最优输出功率)，以兼顾风电机组运行的安全性和经济性。
作为示例，在确定最优输出功率之前，可先确定风电机组的在各风速段的功率输出范围，各风速段的风电机组的最优输出功率可在各风速段的功率输出范围内进行确定。这里，可采用各种现有的方法来确定风电机组的在各风速段的功率输出范围。
以下将列举两种确定最优输出功率的方式。
第一种方式通过迭代计算的方式来确定最优输出功率。
具体说来，首先设置风电机组在各风速段的设定输出功率的初始值。为了减少迭代次数，各风速段的设定输出功率的初始值优选为各风速段的功率输出范围中的最大值。
然后进行载荷计算步骤：根据预测的风资源数据以及风资源数据中的风速所在的风速段的设定输出功率，确定风电机组在未来预定时间段的等效载荷。这里，根据预测的风资源数据以及风资源数据中的风速所在的风速段的设定输出功率，通过各种现有的载荷计算方法，确定风电机组在未来预定时间段的等效载荷。
根据等效载荷估计风电机组在未来预定时间段内的设计寿命。
确定估计的设计寿命与所述最大设计寿命之间的差值的绝对值是否小于预定值；当绝对值小于预定值时，将各风速段当前的设定输出功率作为各风速段的风电机组的最优输出功率，当绝对值不小于预定值时，更新设定输出功率，返回载荷计算步骤，进行下一次迭代计算。
这里，在更新用于下一次迭代计算的设定输出功率时，可将各风速段的功率输出范围以额定功率为界，将功率输出范围分为为两个区间，采用二分法来确定用于下一次迭代计算的设定输出功率。
第二种方式先基于所述最大设计寿命确定风电机组在未来预定时间段的第一等效载荷；再基于第一等效载荷和预测的风资源数据，确定风资源数据中的各个风速所在的风速段的风电机组的最优输出功率，使得基于风资源数据和确定的最优输出功率计算得到的风电机组在未来预定时间段的第二等效载荷与第一等效载荷之差的绝对值小于预定值。在第二种方式中，可通过寻优的方式来计算得到风速段的风电机组的最优输出功率，寻优的目标为风电 机组在未来预定时间段的第二等效载荷与第一等效载荷之差的绝对值小于预定值。
控制单元40在未来预定时间段内按照确定的各风速段的风电机组的最优输出功率来控制风电机组运行。
也就是说，在未来预定时间段内，控制风电机组输出实际的风速所在的风速段的最优输出功率，从而使得处于较为恶劣的风资源条件下的风电机组可牺牲一定的发电能力来保证其安全性，而处于较好风资源条件下的风电机组在保证安全性地前提下尽可能增加发电能力。具体地说，在未来预定时间段内，可检测实际的风速，确定实际的风速所在的风速段，控制风电机组输出实际的风速所在的风速段的最优输出功率。
根据本公开的实施例的风电机组的功率控制方法和设备，通过预测风资源数据以及风电机组已消耗的设计寿命来确定各风速段的风电机组的最优输出功率，可在保证风电机组安全运行的同时尽可能地提高发电能力。
根据本公开的实施例还提供一种计算机可读存储介质。该计算机可读存储介质存储有当被处理器执行时使得处理器执行如上所述的风电机组的功率控制方法的计算机程序。
根据本公开的实施例还提供一种计算装置。该计算装置包括处理器和存储器。存储器用于存储程序指令。所述程序指令被处理器执行使得处理器执行如上所述的风电机组的功率控制方法的计算机程序。
此外，根据本公开的实施例的风电机组的功率控制设备中的各个程序模块可完全由硬件来实现，例如现场可编程门阵列或专用集成电路；还可以由硬件和软件相结合的方式来实现；也可以完全通过计算机程序来以软件方式实现。
尽管已经参照其示例性实施例具体显示和描述了本公开，但是本领域的技术人员应该理解，在不脱离权利要求所限定的本公开的精神和范围的情况下，可以对其进行形式和细节上的各种改变。

Claims (14)

  1. 一种风电机组的功率控制方法，其特征在于，包括：
    根据历史风资源数据预测未来预定时间段内的风资源数据；
    根据风电机组的剩余设计寿命估计风电机组在未来预定时间段内允许消耗的最大设计寿命，其中，所述设计寿命是指风电机组在设计载荷下运行的时间；
    根据预测的风资源数据以及估计的最大设计寿命确定在未来预定时间段内各风速段的风电机组的最优输出功率；
    在未来预定时间段内按照确定的各风速段的风电机组的最优输出功率控制风电机组运行。
  2. 根据权利要求1所述的功率控制方法，其特征在于，根据风电机组的剩余设计寿命估计风电机组在未来预定时间段内允许消耗的最大设计寿命的步骤包括：
    根据风电机组的实际已使用的时间和额定设计寿命确定风电机组的剩余使用时间，将未来预定时间段的时间长度与风电机组的剩余使用时间的比例与风电机组的剩余设计寿命的乘积，作为风电机组在未来预定时间段内允许消耗的最大设计寿命。
  3. 根据权利要求1所述的功率控制方法，其特征在于，在根据风电机组的剩余设计寿命估计风电机组在未来预定时间段内允许消耗的最大设计寿命步骤之前，还包括：
    根据历史风资源数据和历史运行数据对风电机组进行疲劳载荷仿真，得到风电机组的预定义的各个关键部件的等效疲劳载荷；
    根据各个关键部件的等效疲劳载荷以及各个关键部件的设计疲劳载荷得到各个关键部件已消耗的设计寿命；
    根据各个关键部件已消耗的设计寿命来确定风电机组已消耗的寿命；
    根据额定设计寿命和风电机组已消耗的设计寿命确定风电机组的剩余设计寿命。
  4. 根据权利要求3所述的功率控制方法，其特征在于，风资源数据包括风速，或者，风资源数据包括风速和以下至少一项：湍流强度、风剪切、风向、入流倾角、风频分布和空气密度；和/或，
    历史运行数据包括以下至少一项：故障数据、启停机发生次数和空转状态的持续时间。
  5. 根据权利要求1所述的功率控制方法，其特征在于，根据预测的风资源数据以及估计的最大设计寿命确定在未来预定时间段内各风速段的风电机组的最优输出功率的步骤包括：
    设置风电机组在各风速段的设定输出功率的初始值；
    载荷计算步骤：根据预测的风资源数据以及风资源数据中的风速所在的风速段的设定输出功率，确定风电机组在未来预定时间段的等效载荷；
    根据等效载荷估计风电机组在未来预定时间段内的设计寿命；
    确定估计的设计寿命与所述最大设计寿命之间的差值的绝对值是否小于预定值；
    当所述绝对值小于预定值时，将各风速段当前的设定输出功率作为各风速段的风电机组的最优输出功率，当所述绝对值不小于所述预定值时，更新设定输出功率，返回载荷计算步骤。
  6. 根据权利要求1所述的功率控制方法，其特征在于，根据预测的风资源数据以及估计的最大设计寿命确定在未来预定时间段内各风速段的风电机组的最优输出功率的步骤包括：
    基于所述最大设计寿命确定风电机组在未来预定时间段的第一等效载荷；
    基于第一等效载荷和预测的风资源数据，确定风资源数据中的各个风速所在的风速段的风电机组的最优输出功率，使得基于风资源数据和确定的最优输出功率计算得到的风电机组在未来预定时间段的第二等效载荷与第一等效载荷之差的绝对值小于预定值。
  7. 根据权利要求1-6中任一项所述的功率控制方法，其特征在于，各风速段对应的最优输出功率在各风速段的功率输出范围内。
  8. 一种风电机组的功率控制设备，其特征在于，包括：
    预测单元，根据历史风资源数据预测未来预定时间段内的风资源数据；
    估计单元，根据风电机组的剩余设计寿命估计风电机组在未来预定时间段内允许消耗的最大设计寿命，其中，所述设计寿命是指风电机组在设计载荷下运行的时间；
    确定单元，根据预测的风资源数据以及估计的最大设计寿命确定在未来预定时间段内各风速段的风电机组的最优输出功率；
    控制单元，在未来预定时间段内按照确定的各风速段的风电机组的最优输出功率控制风电机组运行。
  9. 根据权利要求8所述的功率控制设备，其特征在于，
    所述估计单元，具体根据风电机组的实际已使用的时间和额定设计寿命确定风电机组的剩余使用时间，将未来预定时间段的时间长度与风电机组的剩余使用时间的比例与风电机组的剩余设计寿命的乘积，作为风电机组在未来预定时间段内允许消耗的最大设计寿命。
  10. 根据权利要求8所述的功率控制设备，其特征在于，
    所述估计单元，具体根据历史风资源数据和历史运行数据对风电机组进行疲劳载荷仿真，得到风电机组的预定义的各个关键部件的等效疲劳载荷，根据各个关键部件的等效疲劳载荷以及各个关键部件的设计疲劳载荷得到各个关键部件已消耗的设计寿命，根据各个关键部件已消耗的设计寿命来确定风电机组已消耗的寿命，根据额定设计寿命和风电机组已消耗的设计寿命确定风电机组的剩余设计寿命。
  11. 根据权利要求8所述的功率控制设备，其特征在于，所述确定单元具体用于：
    设置风电机组在各风速段的设定输出功率的初始值；
    载荷计算步骤：根据预测的风资源数据以及风资源数据中的风速所在的风速段的设定输出功率，确定风电机组在未来预定时间段的等效载荷；
    根据等效载荷估计风电机组在未来预定时间段内的设计寿命；
    确定估计的设计寿命与所述最大设计寿命之间的差值的绝对值是否小于预定值；
    当所述绝对值小于预定值时，将各风速段当前的设定输出功率作为各风速段的风电机组的最优输出功率，当所述绝对值不小于所述预定值时，更新设定输出功率，返回载荷计算步骤。
  12. 根据权利要求8所述的功率控制设备，其特征在于，所述确定单元具体用于：
    基于所述最大设计寿命确定风电机组在未来预定时间段的第一等效载荷；
    基于第一等效载荷和预测的风资源数据，确定风资源数据中的各个风速所在的风速段的风电机组的最优输出功率，使得基于风资源数据和确定的最优输出功率计算得到的风电机组在未来预定时间段的第二等效载荷与第一等 效载荷之差的绝对值小于预定值。
  13. 一种计算机可读存储介质，存储有当被处理器执行时使得处理器执行如权利要求1至7中任意一项所述的风电机组的功率控制方法的计算机程序。
  14. 一种计算装置，包括：
    处理器；
    存储器，用于存储当被处理器执行使得处理器执行如权利要求1至7中任意一项所述的风电机组的功率控制方法的计算机程序。
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CN111310341A (zh) * 2020-02-20 2020-06-19 华润电力技术研究院有限公司 风机运行参数确定方法、装置、设备及可读存储介质
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