阅读说明：本技术 优化低风速时段期间风力涡轮健康检查计划的系统和方法 (System and method for optimizing wind turbine health check plans during periods of low wind speeds ) 是由 A·马宗达 K·阿普拉伊 S·D·贝尔特朗 于 2020-10-16 设计创作，主要内容包括：一种用于改进风力涡轮的功率产量的方法,包括由具有一个或多个处理器的控制器获得风力涡轮的风预测数据。该方法还包括至少部分地基于风预测数据,由控制器计划关于风力涡轮的一个或多个构件的一项或多项健康检查。此外,该方法包括基于计划,经由控制器实施一项或多项健康检查,使得该一项或多项健康检查在具有低于预定阈值的风速的时间段期间实施。(A method for improving power production of a wind turbine includes obtaining, by a controller having one or more processors, wind forecast data for the wind turbine. The method also includes planning, by the controller, one or more health checks with respect to one or more components of the wind turbine based at least in part on the wind forecast data. Further, the method includes implementing, via the controller, one or more health checks based on the plan, such that the one or more health checks are implemented during a time period having a wind speed below a predetermined threshold.)

1. A method for improving power production of a wind turbine, the method comprising:

obtaining, by a controller having one or more processors, wind prediction data for the wind turbine;

planning, by the controller, one or more health checks with respect to one or more components of the wind turbine based at least in part on the wind forecast data; and

based on the plan, implementing, via the controller, the one or more health checks such that the one or more health checks are implemented during a time period having a wind speed below a predetermined threshold.

2. The method of claim 1, wherein the wind prediction data comprises online or time series based statistical wind prediction data comprising at least one of wind speed or wind direction.

3. The method of claim 1, further comprising planning the one or more health checks based on the wind forecast data and at least one of prior test data and historical field data analysis based on a periodic predetermined wind threshold.

4. The method of claim 1, further comprising automatically planning the one or more health checks.

5. The method of claim 1, further comprising adjusting the plan based on changes in wind data and/or technician availability that are different from wind forecast data for the wind turbine.

6. The method of claim 1, wherein the wind turbine is part of a wind farm comprising a plurality of wind turbines.

7. The method of claim 6, further comprising planning the one or more health checks based on the wind forecast data and at least one of a maximum power output of the wind farm or a maximum power loss allowed for each wind turbine in the wind farm.

8. The method of claim 6, further comprising prioritizing the one or more health checks with respect to the plurality of wind turbines in the wind farm based on at least one of the wind forecast data or previous test data.

9. The method of claim 1, further comprising determining wind forecast data for the wind turbine up to five days in advance.

10. The method of claim 1, further comprising tracking the one or more health checks and monitoring the time elapsed between health checks.

Technical Field

The present disclosure relates generally to wind turbines, and more particularly to a system and method for optimizing a plan for technical standby testing/health checks so that testing occurs during periods of low wind speeds in order to minimize energy loss.

Background

Wind power is considered one of the cleanest, most environmentally friendly energy sources presently available, and wind turbines have gained increased attention in this regard. Modern wind turbines typically include a tower, generator, gearbox, nacelle, and one or more rotor blades. The rotor blades capture kinetic energy of wind using known airfoil (airfoil) principles. For example, rotor blades typically have an airfoil-shaped cross-sectional profile such that, during operation, air flows over the blade to create a pressure differential between the sides. Therefore, a lift force directed from the pressure side toward the suction side acts on the blade. The lift force generates torque on the main rotor shaft, which is meshed to a generator for producing electrical power. Additionally, a plurality of wind turbines may be arranged in predetermined geographical locations and electrically connected together to form a wind farm.

During operation, wind strikes rotor blades of the wind turbine, and the blades transform wind energy into a mechanical torque that rotationally drives a low-speed shaft. The low speed shaft is configured to drive a gearbox which subsequently steps up the low rotational speed of the low speed shaft to drive the high speed shaft at an increased rotational speed. The high speed shaft is generally rotatably coupled to the generator to rotatably drive the generator rotor. Thus, a rotating magnetic field may be induced by the generator rotor and a voltage may be induced within the generator stator, which is magnetically coupled to the generator rotor. In certain configurations, the associated electrical power may be transmitted to a turbo-transformer, which is typically connected to the power grid via a grid breaker. Thus, the turbo-transformer increases the voltage amplitude of the electrical power, so that the transformed electrical power may be further transmitted to the power grid.

In many wind turbines, the generator rotor is electrically coupled to a bi-directional power converter, which includes a rotor-side converter linked to a line-side converter via a regulated DC link. More particularly, some wind turbines, such as wind driven Doubly Fed Induction Generator (DFIG) systems or full power conversion systems, may include a power converter having an AC-DC-AC topology.

Current wind turbine maintenance strategies include various technical standby tests or health checks (e.g., as recommended by the International Electrotechnical Commission (IEC)) performed during specific time periods in order to ensure safe operation of the wind turbine. For example, for certain wind turbines, a Technical Standby (TS) test/check is performed periodically and/or conditionally to check the health of the wind turbine subsystem by stopping the wind turbine. Thus, each test is scheduled to run after a certain period of time has elapsed since the last time the test was successfully performed.

Although the duration of each test may vary between about 8 and 45 minutes, the cumulative downtime due to each test over the course of a year may be significant. Thus, such tests affect the availability of the wind turbine to the customer. In addition, because these tests are performed over time, there is a high likelihood of higher Annual Energy Production (AEP) losses as the tests are performed during higher wind speed conditions. In addition to negatively impacting AEP, the current process for planning tests also increases the time elapsed for each test of each wind turbine to be tracked and then re-plan the test.

In view of the foregoing, it would be advantageous to optimize the health check plan so that the checks occur during the lowest wind periods possible in order to minimize AEP losses.

Disclosure of Invention

Aspects and advantages of the invention will be set forth in part in the following description, or may be obvious from the description, or may be learned through practice of the invention.

In one aspect, the present disclosure relates to a method for improving power production of a wind turbine. The method includes obtaining, by a controller having one or more processors, wind forecast data for a wind turbine. The method also includes planning, by the controller, one or more health checks with respect to one or more components of the wind turbine based at least in part on the wind forecast data. Further, the method includes implementing, via the controller, one or more health checks based on the plan, such that the one or more health checks are implemented during a time period having a wind speed below a predetermined threshold.

In embodiments, the wind forecast data may include, for example, statistical wind forecast data that is online or based on a time series. Additionally, the wind forecast data may include wind speed and/or wind direction.

In another embodiment, the method may include planning one or more health checks based on wind forecast data as well as previous test data and/or historical field data analysis based on regularly scheduled wind thresholds. In further embodiments, the method may include automatically planning one or more health checks.

In additional embodiments, the method may include adjusting the plan based on changes in wind data that are different from wind forecast data for the wind turbine.

In several embodiments, the wind turbine may be part of a wind farm having a plurality of wind turbines. In such embodiments, the method may include planning a health check based on the wind forecast data and at least one of a maximum power output of the wind farm or a maximum power loss allowed for each wind turbine in the wind farm.

In other embodiments, the method may further include prioritizing health checks of the plurality of wind turbines in the wind farm based on at least one of a wind forecast or previous test data.

In particular embodiments, the method may include determining wind forecast data for the wind turbine up to five days in advance or any other suitable time frame. In additional embodiments, the method may include tracking the health check and monitoring the time elapsed between the health checks.

In several embodiments, obtaining wind forecast data for a wind turbine may include calibrating an estimation mode of wind data with actual measured wind data.

In another aspect, the present disclosure is directed to a system for improving power production of a wind farm having a plurality of wind turbines. The system includes a field level controller configured to perform a plurality of operations including, but not limited to, obtaining a plurality of wind conditions from a plurality of wind turbines, determining a plan for one or more health checks with respect to one or more components of the plurality of wind turbines based at least in part on the one or more wind conditions, and sending the plan to a turbine controller of the plurality of wind turbines. The system also includes a plurality of turbine stage controllers communicatively coupled to the field stage controller. Each of the plurality of turbine stage controllers is further configured to perform a plurality of operations including, but not limited to, implementing a health check based on the schedule such that the health check is implemented during a time period in which the power output is below a predetermined threshold.

In yet another aspect, the present disclosure relates to a method for improving power production of a wind turbine. The method includes obtaining, by a controller having one or more processors and one or more memory devices, one or more wind conditions at a wind turbine. The method also includes planning, by the controller, one or more health checks with respect to one or more components of the wind turbine based at least in part on the one or more wind conditions. Further, the method includes implementing, via the controller, a health check based on the schedule, such that the health check is implemented during a time period in which the power output is below a predetermined threshold.

It should be understood that variations and modifications may be made to these exemplary embodiments of the present disclosure.

Technical solution 1. a method for improving the power production of a wind turbine, the method comprising:

obtaining, by a controller having one or more processors, wind prediction data for the wind turbine;

planning, by the controller, one or more health checks with respect to one or more components of the wind turbine based at least in part on the wind forecast data; and

based on the plan, implementing, via the controller, the one or more health checks such that the one or more health checks are implemented during a time period having a wind speed below a predetermined threshold.

Technical solution 2 the method of claim 1, wherein the wind forecast data comprises statistical wind forecast data online or based on a time series, the wind forecast data comprising at least one of wind speed or wind direction.

Solution 3. the method of solution 1, wherein the method further comprises planning the one or more health checks based on the wind forecast data and at least one of prior test data and historical site data analysis based on a periodic predetermined wind threshold.

Solution 4. the method of solution 1, wherein the method further comprises automatically planning the one or more health checks.

Solution 5. the method of solution 1, wherein the method further comprises adjusting the plan based on changes in wind data and/or technician availability that are different from wind forecast data for the wind turbine.

Solution 6. the method of solution 1, wherein the wind turbine is part of a wind farm comprising a plurality of wind turbines.

Technical solution 7 the method of claim 6, wherein the method further comprises planning the one or more health checks based on the wind forecast data and at least one of a maximum power output of the wind farm or a maximum power loss allowed for each wind turbine in the wind farm.

Technical solution 8 the method of claim 6, wherein the method further comprises prioritizing the one or more health checks with respect to the plurality of wind turbines in the wind farm based on at least one of the wind forecast data or previous test data.

Solution 9. the method of solution 1, wherein the method further comprises determining wind forecast data for the wind turbine up to five days in advance.

Solution 10. the method of solution 1, wherein the method further comprises tracking the one or more health checks and monitoring the time elapsed between health checks.

Solution 11. the method of solution 1, wherein obtaining wind forecast data for the wind turbine further comprises calibrating an estimation mode of wind data with actual measured wind data.

Technical solution 12. a system for improving power production of a wind farm having a plurality of wind turbines, the system comprising:

a field level controller configured to perform a plurality of operations including:

obtaining a plurality of wind conditions from the plurality of wind turbines;

determining a plan for one or more health checks with respect to one or more components of the plurality of wind turbines based at least in part on one or more wind conditions; and

sending the plan to a turbine controller of the plurality of wind turbines; and

a plurality of turbine stage controllers communicatively coupled to the field stage controller, each of the plurality of turbine stage controllers configured to perform a plurality of operations including:

implementing the one or more health checks based on the plan such that the one or more health checks are implemented during a time period in which power output is below a predetermined threshold.

Solution 13. the system of solution 12, wherein the one or more wind conditions comprise at least one of an actual wind speed, an actual wind direction, a predicted wind speed, a predicted wind direction, and/or combinations thereof.

Technical solution 14 the system of claim 12, wherein the plurality of operations of the field level controller further comprise automatically planning the one or more health checks.

Solution 15. the system of solution 12, wherein the system further comprises adjusting the plan based on changes in wind data that are different from wind forecast data for the wind turbine.

Technical solution 16 the system of claim 12, wherein the plurality of operations of the plant level controller further comprise planning the one or more health checks based on the one or more wind conditions and at least one of a maximum power output of the wind plant or a maximum power loss allowed for each wind turbine in the wind plant.

Technical solution 17 the system of claim 12, wherein the plurality of operations of the farm level controller further comprise prioritizing the one or more health checks with respect to the plurality of wind turbines in the wind farm based on at least one of wind forecast data or previous test data.

Technical solution 18 the system of claim 12, wherein the plurality of operations of the farm level controller further comprise determining wind forecast data for the wind turbine up to five days in advance.

Solution 19. the system of solution 12, wherein obtaining wind forecast data for the wind turbine further comprises calibrating an estimation mode of wind data with actual measured wind data.

Technical solution 20. a method for improving power production of a wind turbine, the method comprising:

obtaining, by a controller having one or more processors and one or more memory devices, one or more wind conditions at the wind turbine;

planning, by the controller, one or more health checks with respect to one or more components of the wind turbine based at least in part on the one or more wind conditions; and

implementing, via the controller, the one or more health checks based on the schedule such that the one or more health checks are implemented during a time period in which power output is below a predetermined threshold.

These and other features, aspects, and advantages of the present invention will become better understood with reference to the following description and appended claims. The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description, serve to explain the principles of the invention.

Drawings

A full and enabling disclosure of the present invention, including the best mode thereof, directed to one of ordinary skill in the art, is set forth in the specification, which makes reference to the appended figures, in which:

FIG. 1 illustrates a schematic view of an embodiment of a wind turbine system according to the present disclosure;

FIG. 2 illustrates a schematic view of an embodiment of a wind farm having a plurality of wind turbines according to the present disclosure;

FIG. 3 shows a schematic view of another embodiment of a wind turbine system according to the present disclosure;

FIG. 4 shows a schematic view of another embodiment of a wind farm having a plurality of wind turbines according to the present disclosure;

FIG. 5 illustrates a schematic view of an embodiment of a controller of a wind turbine according to the present disclosure;

FIG. 6 illustrates a flow diagram of an embodiment of a method for improving power production of a wind turbine according to the present disclosure;

FIG. 7 illustrates a flow diagram of another embodiment of a method for improving power production of a wind turbine according to the present disclosure.

Detailed Description

Reference now will be made in detail to embodiments of the invention, one or more examples of which are illustrated in the drawings. Each example is provided by way of explanation of the invention, not limitation of the invention. In fact, it will be apparent to those skilled in the art that various modifications and variations can be made in the present invention without departing from the scope or spirit of the invention. For instance, features illustrated or described as part of one embodiment, can be used with another embodiment to yield a still further embodiment. It is therefore intended that the present invention cover the modifications and variations of this invention provided they come within the scope of the appended claims and their equivalents.

Referring now to the drawings, FIG. 1 illustrates one embodiment of a wind turbine system 100 according to the present disclosure. For purposes of illustration and discussion, exemplary aspects of the present disclosure are discussed with reference to wind turbine system 100 of FIG. 1. Those of ordinary skill in the art having access to the disclosure provided herein will appreciate that the exemplary aspects of the present disclosure may also be applied to other power systems, such as synchronous, asynchronous, permanent magnet, and full power conversion wind turbines, solar, gas turbines, or other suitable power generation systems.

In the exemplary system 100, the rotor 106 includes a plurality of rotor blades 108 coupled to a rotating hub 110. Rotor 106 is coupled to an optional gearbox 118, which gearbox 118 is in turn coupled to a generator 120. According to aspects of the present disclosure, the generator 120 may be a doubly-fed induction generator (DFIG) 120. Accordingly, the DFIG120 may include a rotor and a stator. Further, as shown, DFIG120 is typically coupled to stator bus 154 and power converter 162 via rotor bus 156. Stator bus 154 provides output multi-phase power (e.g., three-phase power) from the stator of DFIG120, while rotor bus 156 provides output multi-phase power (e.g., three-phase power) from the rotor of DFIG 120. Referring to power converter 162, DFIG120 is coupled to a rotor-side converter 166 via rotor bus 156. Rotor-side converter 166 is coupled to line-side converter 168, which is in turn coupled to line-side bus 188.

In an exemplary configuration, the rotor-side converter 166 and the line-side converter 168 are configured for a normal mode of operation in a three-phase Pulse Width Modulation (PWM) arrangement using Insulated Gate Bipolar Transistors (IGBTs) or similar switching elements. Rotor-side converter 166 and line-side converter 168 may be coupled via DC link 136, across which DC link capacitor 138 is connected. In an embodiment, a transformer 178 (such as a three-winding transformer) may be coupled to line bus 188, stator bus 154, and system bus 160. Transformer 178 may convert the voltage of the power from line bus 188 and stator bus 154 to a voltage suitable for provision to grid 184 via system bus 160.

The power conversion system 162 may be coupled to a control device 174 to control the operation of the rotor-side converter 166 and the line-side converter 168. It should be noted that, in the exemplary embodiment, control device 174 is configured as an interface between power conversion system 162 and turbine control system 176. In one embodiment, the control device 174 may include a processing device (e.g., a microprocessor, a microcontroller, etc.) that executes computer-readable instructions stored in a computer-readable medium. The instructions, when executed by the processing device, may cause the processing device to perform operations including providing control commands (e.g., pulse width modulation commands) to switching elements of the power converter 162 and other aspects of the wind turbine system 100.

In operation, alternating current generated at DFIG120 by rotation of rotor 106 is provided to grid 184 via dual paths. The dual paths are defined by a stator bus 154 and a rotor bus 156. On the rotor bus side 156, sinusoidal multi-phase (e.g., three-phase) Alternating Current (AC) power is provided to a power converter 162. Rotor-side power converter 166 converts the AC power provided from rotor bus 156 to Direct Current (DC) power and provides the DC power to DC link 136. Switching elements (i.e., IGBTs) in the bridge circuit for rotor-side power converter 166 may be modulated to convert AC power provided from rotor bus 156 to DC power suitable for DC link 136.

Line-side converter 168 converts the DC power on DC link 136 to AC output power suitable for grid 184, such as AC power synchronized with grid 184, which may be transformed by transformer 178 before being provided to grid 184. In particular, switching elements (e.g., IGBTs) in the bridge circuit for line-side power converter 168 may be modulated to convert DC power on DC link 136 to AC power on line-side bus 188. The AC power from power converter 162 may be combined with power from the stator of DFIG120 to provide multi-phase power (e.g., three-phase power) having a frequency substantially maintained at the frequency of grid 184 (e.g., 50Hz/60 Hz).

The power converter 162 may receive control signals from, for example, the control system 174. The control signals may be based on, inter alia, sensed conditions or operating characteristics of the wind turbine system 100. Typically, the control signal provides control of the operation of the power converter 162. For example, feedback in the form of sensed speed of DFIG120 may be used to control conversion of output power from rotor bus 156 to maintain a suitable and balanced multi-phase (e.g., three-phase) power supply. Other feedback from other sensors may also be used by the controller 174 to control the power converter 162, including, for example, stator and rotor bus voltage and current feedback. Using various forms of feedback information, switching control signals (e.g., gate timing commands for IGBTs), stator synchronization control signals, and breaker signals can be generated.

Various circuit breakers and switches, such as line bus breaker 186, stator bus breaker 158, and grid breaker 182 may be included in the system 100 to connect or disconnect corresponding buses, for example, when the current is excessive and may damage components of the wind turbine system 100 or for other operational considerations. Additional protective components may also be included in the wind turbine system 100.

Referring now to FIG. 2, wind turbines 100 may be arranged together in a common geographic location, referred to as a wind farm 200, and connected to a power grid 184. More specifically, as shown, each wind turbine 100 may be connected to a power grid 184 via a main transformer 178. Further, as shown, a cluster 206 of wind turbines 100 in the wind farm 200 may be connected to the power grid 184 via a cluster or substation transformer 202. Thus, as shown, the wind farm 200 may also include a transformer controller 210 and/or an automatic voltage regulator 212 (e.g., a tap changer).

Referring now to FIGS. 3 and 4, an alternative embodiment of a DFIG wind turbine system 100 is illustrated, according to additional example aspects of the present disclosure. Elements that are the same as or similar to elements in fig. 1 are denoted by the same reference numerals. As shown, in some embodiments, the stator 124 of the DFIG120 may be coupled to a stator bus 154. Power from power converter 162 may be combined with power from stator bus 154 and provided to transformer 180. In some embodiments, as shown, transformer 180 may be a dual winding partial transformer. In some embodiments, as shown in FIG. 4, the plurality of DFIG wind turbine systems 100 shown in FIG. 3 may be arranged together in a common geographic location referred to as a wind farm 105. Further, as shown, the DFIG wind turbine systems 100 within the wind farm 105 may be coupled together in clusters 137, and power from each respective cluster 137 of the wind turbine systems 100 may be provided to cluster transformers 140, 142, 144, respectively, before the power is provided to the power grid. More particularly, as shown, each cluster 137 may be connected to a separate transformer 140, 142, 144 via switches 150, 151, 152, respectively, to increase the voltage magnitude of the electrical power from each cluster 137 so that the converted electrical power may be further transmitted to the power grid.

However, the local power transformer 180 of fig. 3 and 4 provides for increasing the voltage magnitude of the electrical power from the power converter 122 compared to conventional systems (such as those shown in fig. 1 and 2) so that the converted electrical power may be further transmitted to the power grid. Thus, as shown, the illustrated system 102 does not include the conventional three-winding main transformer described above. Conversely, as shown in the illustrated embodiment, the local power transformer 180 may correspond to a dual-winding transformer having a primary winding 146 connected to the power grid and a secondary winding 148 connected to the rotor-side converter 168.

Additionally, as shown, the transformers 140, 142, 144 may be connected to a main line 155 that combines the voltages from each cluster 137 prior to sending power to the grid. Further, as mentioned, each cluster 137 may be communicatively coupled with a cluster-level controller 109 that controls each transformer 140, 142, 144. Additionally, as shown, the wind farm 105 may include one or more automatic voltage regulators (e.g., tap changers 164) arranged with each of the transformers 140, 142, 144 and/or one or more reactive power devices 170. For example, as shown, the reactive power device 170 may include any of the following: a capacitor bank 172, a reactor bank 175, and/or a static synchronous compensator (STATCOM) 177.

Further, as shown, the wind turbine system 100 described herein may include one or more controllers. For example, the system 100 may include a field level controller 190, one or more cluster level controllers 179, one or more turbine level controllers 176, and/or one or more converter controllers 174. As such, the various controllers described herein are configured to control any of wind farm 105, wind turbine cluster 137, and/or components of each wind turbine 100 and/or to implement method steps as described herein.

Referring now to fig. 5, a block diagram of one embodiment of a control/controller 510 is shown, according to an example embodiment of the present disclosure. As mentioned, the controller 510 may be, for example, a field level controller 190, one or more cluster level controllers 179, one or more turbine level controllers 176, and/or one or more converter controllers 174. As such, the controller 510 may include one or more control devices associated with aspects of the wind turbine system, such as one or more control devices configured to control the power converter 162. In some embodiments, one or more control devices 510 may include one or more processors 512 and one or more memory devices 514. Processor 512 and memory device 514 may be distributed such that they are located at another location or have different devices.

Processor 512 and memory device 514 may be configured to perform a variety of computer-implemented functions and/or instructions (e.g., to perform methods, steps, calculations, etc., and to store related data as disclosed herein). The instructions, when executed by the processor 512, may cause the processor 512 to perform the operations of the exemplary aspects of the present disclosure. For example, the instructions, when executed by the processor 512, may cause the processor 512 to implement the methods discussed herein.

Additionally, control device 510 may include a communication interface 516 to facilitate communication between control device 510 and various components of a wind turbine system, wind farm, or power system, including reactive power production requirements or sensed operating parameters as described herein. Further, communication interface 518 may include a sensor interface 518 (e.g., one or more analog-to-digital converters) to allow signals transmitted from one or more sensors 520, 522 to be converted into signals that may be understood and processed by processor 512. It should be appreciated that sensors (e.g., sensors 520, 522) can be communicatively coupled to communication interface 518 using any suitable means, such as a wired or wireless connection. The signals may be transmitted using any suitable communication protocol. The sensors (520, 522) may be, for example, voltage sensors, current sensors, power sensors, DFIG rotational speed sensors, temperature sensors, or any other sensor device described herein.

Thus, the processor 512 may be configured to receive one or more signals from the sensors 520, 522. For example, in some embodiments, processor 512 may receive signals from sensors 520 indicative of voltage or current. In some embodiments, processor 512 may receive signals from sensors 522 indicative of temperature (e.g., DFIG temperature, line side converter temperature).

As used herein, the term "processor" refers not only to integrated circuits referred to in the art as being included in a computer, but also to control devices, micro-computers, programmable logic control devices (PLCs), application specific integrated circuits, and other programmable circuits. Additionally, memory device 514 may generally include memory elements including, but not limited to, computer-readable media (e.g., Random Access Memory (RAM), computer-readable non-volatile media (e.g., flash memory), compact disc read only memory (CD-ROM), magneto-optical disks (MOD), Digital Versatile Discs (DVD), and/or other suitable memory elements). Such memory device 514 may generally be configured to store suitable computer-readable instructions that, when implemented by the processor 512, configure the control device 510 to perform various functions as described herein.

Referring now to FIG. 6, a flow diagram of an embodiment of a method 300 for improving power production of a wind turbine (such as wind turbine system 100 described herein) is shown. The method 300 may be implemented by any suitable controller, such as any of those described herein. Additionally, FIG. 6 depicts steps performed in a particular order for purposes of illustration and discussion. One of ordinary skill in the art, using the disclosure provided herein, will appreciate that the various steps of any of the methods disclosed herein may be altered, omitted, rearranged and/or expanded in various ways without departing from the scope of the present disclosure.

As shown at 302, method 300 may include obtaining, by a controller, wind forecast data for wind turbine 100. For example, in an embodiment, method 300 may include determining wind forecast data for wind turbine 100 over any suitable future time frame (such as up to five days in advance). Additionally, it should be understood that wind forecast data may include data corresponding to wind speed, wind turbulence, wind gusts, wind direction, wind acceleration, wind shear, wind turns, wake, or any other wind parameter. Further, the controller described herein may be operably connected to one or more sensors, such as one or more wind sensors, and may be configured to receive measurements indicative of various wind conditions in the wind farm 200, which may be used to estimate wind forecast data. Furthermore, the step of obtaining wind forecast data for wind turbine 100 may further include calibrating the estimated model of wind data with actual measured wind data and forecasting the wind forecast data based on the calibration.

Still referring to fig. 6, as shown at 304, the method 300 may include: one or more health checks with respect to one or more components (including subcomponents) of wind turbine 100 are planned based, at least in part, on the wind forecast data. For example, in one embodiment, the health check described herein may include various technical standby tests or health checks (e.g., as recommended by the IEC) performed during a particular time period in order to ensure safe operation of the wind turbine 100. For example, for certain wind turbines, certain Technical Standby (TS) tests may be conducted to check the health of the wind turbine subsystems by stopping the wind turbines. Further, in embodiments, the wind forecast data may include, for example, wind speed or wind direction.

Thus, in certain embodiments, the controller may include an algorithm that optimizes the planning of such health checks by using wind forecast data to ensure that the health checks occur during periods of low wind speeds. For example, in some cases, the controller may use specialized software, such as edge computing, which generally represents a distributed computing paradigm that brings computation and data storage closer to locations where improved response time and bandwidth savings are needed. Thus, in embodiments, the algorithm may optimize the planning of the health check based on wind forecast data (e.g., by planning a health check during low or no wind), previous test data (e.g., by planning a health check at a predetermined time after successful completion of the previous test), the maximum power output of the wind farm 200, and/or the maximum power loss allowed for each wind turbine in the wind farm 200. In other embodiments, method 300 may also include prioritizing health checks of the plurality of wind turbines 100 in wind farm 200 based on predictions of wind and/or previous test data. In another embodiment, method 300 may include planning a health check for automatically or manually determining the overall health of wind turbine 100.

Moreover, in additional embodiments, method 300 may further include adjusting the plan based on changes in wind data that are different from the wind forecast data for wind turbine system 100. For example, in some cases, when predicting a change in wind speed, the algorithm may plan for a better window of opportunity (e.g., less or no wind), if available. In additional embodiments, the method 300 may further include tracking the health check and monitoring the time elapsed between the health checks. Thus, when planning, the controller may consider the time elapsed between health checks.

Referring back to FIG. 6, as shown at 306, the method 300 may include implementing, via the controller, a health check based on the schedule such that the health check is implemented during a time period having a wind speed below a predetermined threshold. Thus, the optimization algorithm is configured to plan a health check by predicting wind speed using the weather prediction service. More specifically, in embodiments, method 300 may include evaluating improvements in the performance of wind turbine 100 and/or wind farm 200, and visualizing wind predictions and test plan states and strategies for algorithmic accuracy measurements.

Referring now to FIG. 7, a flow diagram of an embodiment of a method 400 for improving power production of a wind turbine, such as wind turbine system 100 described herein, is shown. The method 400 may be implemented by any suitable controller, such as any of those described herein. Additionally, FIG. 7 depicts steps performed in a particular order for purposes of illustration and discussion. One of ordinary skill in the art, using the disclosure provided herein, will appreciate that the various steps of any of the methods disclosed herein may be altered, omitted, rearranged and/or expanded in various ways without departing from the scope of the present disclosure.

As shown at 402, method 400 may include obtaining, by a controller, one or more wind conditions at wind turbine 100. For example, in an embodiment, the one or more wind conditions at wind turbine 100 may include data corresponding to wind speed, wind turbulence, wind gusts, wind direction, wind acceleration, wind shear, wind turns, wake, or any other wind parameter. Further, as mentioned, the controller described herein may be operably connected to one or more sensors, such as one or more wind sensors, and may be configured to receive measurements indicative of various wind conditions in the wind farm 200.

As shown at 404, method 400 may include planning, by the controller, one or more health checks with respect to one or more components of wind turbine 100 based at least in part on the one or more wind conditions. As shown at 406, the method 400 may include implementing, via the controller, a health check based on the schedule, such that the health check is implemented during a time period in which the power output is below a predetermined threshold.

The techniques discussed herein make reference to computer-based systems and actions taken by computer-based systems and information sent to and from computer-based systems. Those of ordinary skill in the art will recognize that the inherent flexibility of a computer-based system allows for a wide variety of possible configurations, combinations, and divisions of tasks and functions between and among components. For example, the processes discussed herein may be implemented using a single computing device or multiple computing devices working in combination. The databases, memories, instructions, and applications may be implemented on a single system or distributed across multiple systems. The distributed components may operate sequentially or in parallel.

Although specific features of various embodiments may be shown in some drawings and not in others, this is for convenience only. In accordance with the principles of the present disclosure, any feature of a drawing may be referenced and/or suggested in combination with any feature of any other drawing.

Various aspects and embodiments of the invention are defined by the following numbered clauses:

1. a method for improving power production of a wind turbine, the method comprising:

obtaining, by a controller having one or more processors, wind forecast data for a wind turbine;

planning, by a controller, one or more health checks with respect to one or more components of a wind turbine based at least in part on the wind forecast data; and

based on the plan, one or more health checks are implemented via the controller such that the one or more health checks are implemented during a time period having a wind speed below a predetermined threshold.

2. The method of clause 1, wherein the wind prediction data comprises online or time series based statistical wind prediction data, the wind prediction data comprising at least one of wind speed or wind direction.

3. The method of clauses 1-2, further comprising planning one or more health checks based on the wind forecast data and at least one of prior test data and historical field data analysis based on a periodic predetermined wind threshold.

4. The method of clauses 1-3, further comprising automatically planning one or more health checks.

5. The method of clauses 1-4, further comprising adjusting the plan based on changes in wind data and/or technician availability that are different from wind forecast data for the wind turbine.

6. The method of clauses 1-5, wherein the wind turbine is part of a wind farm comprising a plurality of wind turbines.

7. The method of clause 6, further comprising planning one or more health checks based on the wind forecast data and at least one of a maximum power output of the wind farm or a maximum power loss allowed for each wind turbine in the wind farm.

8. The method of clause 6, further comprising prioritizing the one or more health checks with respect to the plurality of wind turbines in the wind farm based on at least one of the wind forecast or previous test data.

9. The method of clauses 1-8, further comprising determining wind forecast data for the wind turbine up to five days in advance.

10. The method of clauses 1-9, further comprising tracking one or more health checks and monitoring the time elapsed between health checks.

11. The method of clauses 1-10, wherein obtaining wind forecast data for the wind turbine further comprises calibrating the estimation mode of the wind data with actual measured wind data.

12. A system for improving power production of a wind farm having a plurality of wind turbines, the system comprising:

a field level controller configured to perform a plurality of operations, the plurality of operations comprising:

obtaining a plurality of wind conditions from a plurality of wind turbines;

determining a plan for one or more health checks with respect to one or more components of a plurality of wind turbines based, at least in part, on one or more wind conditions; and

sending the plan to a turbine controller of the plurality of wind turbines; and

a plurality of turbine stage controllers communicatively coupled to the field stage controller, each of the plurality of turbine stage controllers configured to perform a plurality of operations, the plurality of operations comprising:

one or more health checks are implemented based on the plan such that the one or more health checks are implemented during a time period in which the power output is below a predetermined threshold.

Clause 13. the system of clause 12, wherein the one or more wind conditions include at least one of an actual wind speed, an actual wind direction, a predicted wind speed, a predicted wind direction, and/or combinations thereof.

Clause 14. the system of clauses 12-13, wherein the plurality of operations of the field level controller further comprises automatically scheduling one or more health checks.

Clause 15. the system of clauses 12-14, further comprising adjusting the plan based on changes in wind data that are different from wind forecast data for the wind turbine.

Clause 16. the system of clauses 12-15, wherein the plurality of operations of the plant-level controller further comprise planning one or more health checks based on one or more of the wind conditions and at least one of a maximum power output of the wind plant or a maximum power loss allowed for each wind turbine in the wind plant.

Clause 17. the system of clauses 12-16, wherein the plurality of operations of the farm level controller further comprise prioritizing one or more health checks with respect to the plurality of wind turbines in the wind farm based on at least one of a wind forecast or previous test data.

Clause 18. the system of clauses 12-17, wherein the plurality of operations of the farm level controller further comprises determining wind forecast data for the wind turbine up to five days in advance.

Clause 19. the system of clauses 12-18, wherein obtaining wind forecast data for the wind turbine further comprises calibrating the estimated mode of the wind data with actual measured wind data.

Clause 20. a method for improving power production of a wind turbine, the method comprising:

obtaining, by a controller having one or more processors and one or more memory devices, one or more wind conditions at a wind turbine;

planning, by the controller, one or more health checks with respect to one or more components of the wind turbine based at least in part on the one or more wind conditions; and

one or more health checks are implemented via the controller based on the schedule such that the one or more health checks are implemented during a time period in which the power output is below a predetermined threshold.

This written description uses examples to disclose the invention, including the best mode, and also to enable any person skilled in the art to practice the invention, including making and using any devices or systems and performing any incorporated methods. The patentable scope of the invention is defined by the claims, and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the claims if they include structural elements that do not differ from the literal language of the claims, or if they include equivalent structural elements with insubstantial differences from the literal languages of the claims.