System and Method for Evaluating Loads of a Potential Wind Farm Site for Multiple Wind Scenarios

A system and method for evaluating loads of a potential wind farm site for multiple wind scenarios includes (a) receiving, via a computer server, site data of the potential wind farm site representing at least one wind scenario for at least one wind turbine at the potential wind farm site. Further, the method includes (b) selecting, via a user interface, a wind farm configuration based on the at least one wind scenario. The method also includes (c) selecting, via the user interface, a time period for the at least one wind scenario. Thus, the method includes (d) automatically generating, via the computer server, a mechanical loads analysis for the selected wind farm configuration and the time period.

FIELD

The present invention relates generally to wind turbines, and more particularly, to systems and methods for evaluating loads of a potential wind farm site for multiple wind scenarios.

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. A modern wind turbine typically includes a tower, a generator, a gearbox, a nacelle, and a rotor. The rotor typically includes a rotatable hub having one or more rotor blades attached thereto. A pitch bearing is typically configured operably between the hub and a blade root of the rotor blade to allow for rotation about a pitch axis. The rotor blades capture kinetic energy of wind using known airfoil principles. The rotor blades transmit the kinetic energy in the form of rotational energy so as to turn a shaft coupling the rotor blades to a gearbox, or if a gearbox is not used, directly to the generator. The generator then converts the mechanical energy to electrical energy that may be deployed to a utility grid.

A plurality of wind turbines are commonly used in conjunction with one another to generate electricity and are commonly referred to as a “wind farm.” Wind turbines on a wind farm typically include their own meteorological monitors that perform, for example, temperature, wind speed, wind direction, barometric pressure, and/or air density measurements. In addition, a separate meteorological mast or tower (“met mast”) having higher quality meteorological instruments that can provide more accurate measurements at one point in the farm is commonly provided. The correlation of meteorological data with power output allows the empirical determination of a “power curve” for the individual wind turbines.

Traditionally, wind farms are controlled in a decentralized fashion to generate power such that each turbine is operated to maximize local energy output and to minimize impacts of local fatigue and extreme loads. To this end, each turbine includes a control module, which typically attempts to maximize power output of the turbine in the face of varying wind and grid conditions, while satisfying constraints like sub-system ratings and component loads. Based on the determined maximum power output, the control module controls the operation of various turbine components, such as the generator/power converter, the pitch system, the brakes, and the yaw mechanism to reach the maximum power efficiency.

Amplified wind power demand and customer desire of extracting maximum energy from a wind farm has driven the production of wind turbines having a larger rotor diameter. Such rotor diameters improve energy production of individual wind turbines, but introduce new challenges such as higher fatigue loads. One of the contributing factors to higher fatigue loads is the collective impact of turbine shadow from the increased number of nearby turbines in one or more wind direction(s). Often, these higher fatigue loads exceed nominal/design loads for the turbine model and give few options for developers. More specifically, farm developers must either relocate the turbine(s) or reduce turbine operation in one or more wind direction(s). Thus, since most siting techniques do not account for fatigue load calculations because of the complexity involved and extensive computational requirements, developers end up either with opting suboptimal location(s) with low energy production or loads infeasible location(s) for one or more turbine(s) in the wind farm layout.

Conventional practice is to build the wind farm with a suboptimal layout and opt for post-installation techniques to improve the turbine(s) performance. Such post-installation techniques generally calculate the optimal value(s) of one or more turbine operating parameter(s) based on measured values of one or more site parameter(s). The disadvantages of these available post-installation techniques include but are not limited to: (1) additional investment by the wind farm owner, (2) farm-level operation that requires suboptimal performance by one or more wind turbine(s) in the wind farm to improve the performance of other turbines, (3) trivial annual energy production (AEP) benefits from suboptimal site conditions at one or more turbine location(s), and/or (4) time-consuming implementation and/or validation.

Accordingly, the present disclosure is directed to systems and methods for evaluating loads of a potential wind farm site for multiple wind scenarios that does not require such post-installations techniques.

BRIEF DESCRIPTION

In one aspect, the present disclosure is directed to a method for evaluating loads of a potential wind farm site for multiple wind scenarios. The method includes (a) receiving, via a computer server, site data of the potential wind farm site representing at least one wind scenario for at least one wind turbine at the potential wind farm site. Further, the method includes (b) selecting, via a user interface, a wind farm configuration based on the at least one wind scenario. The method also includes (c) selecting, via the user interface, a time period for the at least one wind scenario. Thus, the method includes (d) automatically generating, via the computer server, a mechanical loads analysis for the selected wind farm configuration and the time period.

In one embodiment, the method may further include repeating steps (a) through (d) for multiple wind scenarios. Thus, in such embodiments, the method may include selecting a site layout for the potential wind farm site based on the mechanical loads analysis for the multiple wind scenarios.

In another embodiment, the wind farm configuration may include controller settings for a plurality of wind turbines at the potential wind farm site. In further embodiments, the site data may correspond to wind conditions, time of day, seasonal variations, or atmospheric conditions and/or stability. More specifically, in certain embodiments, the wind conditions may include wind direction, wind speed, wind shear, wake, wind gusts, turbine shadow, wind turbulence, wind acceleration, wind veer, or any other suitable wind condition.

In additional embodiments, the time period may correspond to an annual percentage of time for the wind scenario(s). As such, in several embodiments, the method may include scaling the mechanical loads analysis by the annual percentage of time. In particular embodiments, the mechanical loads analysis may correspond to a fatigue mechanical loads analysis.

In further embodiments, the method may include automatically generating the mechanical loads analysis for the selected wind farm configuration and the time period utilizing a rainflow-counting algorithm programmed in a software module of the computer server.

In additional embodiments, the method may include generating the site data via at least one of sensors, the user interface, or a wind mesoscale wind model.

In another aspect, the present disclosure is directed to a system for evaluating loads of a potential wind farm site for multiple wind scenarios. The system includes a user interface having at least one wind farm configuration selection module for selecting a wind farm configuration based on at least one wind scenario for at least one wind turbine at the potential wind farm site and at least one time period selection module for selecting a time period for the at least one wind scenario. Further, the system includes a computer server communicatively coupled to the user interface. The computer server is configured to perform one or more operations, including but not limited to receiving site data of the potential wind farm site representing the at least one wind scenario, receiving a selected wind farm configuration and a selected time period from the user interface, and automatically generating a mechanical loads analysis for the selected wind farm configuration and the selected time period. It should be understood that the system may further include any of the additional features as described herein.

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

DETAILED DESCRIPTION

Generally, the present subject matter is directed to a system and method for evaluating loads of a potential wind farm site for multiple wind scenarios. More specifically, the present disclosure is directed to an automated method using a web-based system configured to determine site-specific fatigue loads on a wind turbine using different wind scenarios which are representative of different wind regimes at a potential wind farm site. Thus, the system and method of the present disclosure is configured to generate a site layout that maximizes energy output while staying within a defined mechanical loads constraint. The wind scenarios may be representative of different times of the day, atmospheric stability class, and/or seasonal wind variations. As such, the wind farm analysis, by leveraging multiple wind scenarios, allows engineers to test, recommend, and define different controller software settings for each scenario. Accordingly, operating recommendations can be made that increase annual energy production and minimize fatigue loads, while also increasing wind turbine life for the proposed site.

Referring now toFIG. 2, a simplified, internal view of one embodiment of the nacelle16of the wind turbine10shown inFIG. 1is illustrated. As shown, the generator24may be coupled to the rotor18for producing electrical power from the rotational energy generated by the rotor18. For example, as shown in the illustrated embodiment, the rotor18may include a rotor shaft34coupled to the hub20for rotation therewith. The rotor shaft34may, in turn, be rotatably coupled to a generator shaft36of the generator24through a gearbox38. As is generally understood, the rotor shaft34may provide a low speed, high torque input to the gearbox38in response to rotation of the rotor blades22and the hub20. The gearbox38may then be configured to convert the low speed, high torque input to a high speed, low torque output to drive the generator shaft36and, thus, the generator24.

Each rotor blade22may also include a pitch adjustment mechanism32configured to rotate each rotor blade22about its pitch axis28. Further, each pitch adjustment mechanism32may include a pitch drive motor40(e.g., any suitable electric, hydraulic, or pneumatic motor), a pitch drive gearbox42, and a pitch drive pinion44. In such embodiments, the pitch drive motor40may be coupled to the pitch drive gearbox42so that the pitch drive motor40imparts mechanical force to the pitch drive gearbox42. Similarly, the pitch drive gearbox42may be coupled to the pitch drive pinion44for rotation therewith. The pitch drive pinion44may, in turn, be in rotational engagement with a pitch bearing46coupled between the hub20and a corresponding rotor blade22such that rotation of the pitch drive pinion44causes rotation of the pitch bearing46. Thus, in such embodiments, rotation of the pitch drive motor40drives the pitch drive gearbox42and the pitch drive pinion44, thereby rotating the pitch bearing46and the rotor blade22about the pitch axis28. Similarly, the wind turbine10may include one or more yaw drive mechanisms48communicatively coupled to a turbine controller26, with each yaw drive mechanism(s)48being configured to change the angle of the nacelle16relative to the wind (e.g., by engaging a yaw bearing50of the wind turbine10).

Still referring toFIG. 2, the wind turbine10may also include one or more sensors65,66,68for measuring operating and/or wind conditions of the wind turbine10. For example, the sensors may include blade sensors65for measuring a pitch angle of one of the rotor blades22or for measuring a loading acting on one of the rotor blades22; generator sensors66for monitoring the generator (e.g. torque, rotational speed, acceleration and/or the power output); and/or various wind sensors68for measuring various wind parameters (e.g. wind speed, wind direction, etc.). Further, the sensors65,66,68may be located near the ground of the wind turbine10, on the nacelle16, on a meteorological mast of the wind turbine10, or any other location in the wind farm.

It should also be understood that any other number or type of sensors may be employed and at any location. For example, the sensors may be accelerometers, pressure sensors, strain gauges, angle of attack sensors, vibration sensors, MIMU sensors, camera systems, fiber optic systems, anemometers, wind vanes, Sonic Detection and Ranging (SODAR) sensors, infra lasers, Light Detecting and Ranging (LIDAR) sensors, radiometers, pitot tubes, rawinsondes, other optical sensors, and/or any other suitable sensors. It should be appreciated that, as used herein, the term “monitor” and variations thereof indicates that the various sensors of the wind turbine10may be configured to provide a direct measurement of the parameters being monitored or an indirect measurement of such parameters. Thus, the sensors65,66,68may, for example, be used to generate signals relating to the parameter being monitored, which can then be utilized by the controller26to determine the actual condition.

Referring back toFIG. 1, the wind turbine controller26may be centralized within the nacelle16. However, in other embodiments, the controller26may be located within any other component of the wind turbine10or at a location outside the wind turbine. Further, the controller26may be communicatively coupled to any number of the components of the wind turbine10in order to control the operation of such components and/or to implement a control action. As such, the controller26may include a computer or other suitable processing unit. Thus, in several embodiments, the controller26may include suitable computer-readable instructions that, when implemented, configure the controller26to perform various different functions, such as receiving, transmitting and/or executing wind turbine control signals.

Accordingly, the controller26may generally be configured to control the various operating modes of the wind turbine10(e.g., start-up or shut-down sequences), de-rate or up-rate the wind turbine10, and/or control various components of the wind turbine10. For example, the controller26may be configured to control the blade pitch or pitch angle of each of the rotor blades22(i.e., an angle that determines a perspective of the rotor blades22with respect to the direction of the wind) to control the power output generated by the wind turbine10by adjusting an angular position of at least one rotor blade22relative to the wind. For instance, the controller26may control the pitch angle of the rotor blades22by rotating the rotor blades22about a pitch axis28, either individually or simultaneously, by transmitting suitable control signals to a pitch drive or pitch adjustment mechanism (not shown) of the wind turbine10.

In addition, according to one aspect of the present disclosure, the controller26may be programmed with various settings that are determined pre-installation of the wind turbine site. Referring particularly toFIG. 3, a block diagram of one embodiment of suitable components that may be included within the controller26is illustrated in accordance with aspects of the present disclosure. As shown, the controller26may include one or more processor(s)58and associated memory device(s)60configured to perform a variety of computer-implemented functions. 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 refers to a controller, a microcontroller, a microcomputer, a programmable logic controller (PLC), an application specific integrated circuit, application-specific processors, digital signal processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs), and/or any other programmable circuits. Further, the memory device(s)60may generally include memory element(s) including, but are not limited to, computer readable medium (e.g., random access memory (RAM)), computer readable non-volatile medium (e.g., a flash memory), one or more hard disk drives, a floppy disk, a compact disc-read only memory (CD-ROM), compact disk-read/write (CD-R/W) drives, a magneto-optical disk (MOD), a digital versatile disc (DVD), flash drives, optical drives, solid-state storage devices, and/or other suitable memory elements.

Additionally, the controller26may also include a communications module62to facilitate communications between the controller26and the various components of the wind turbine10. For instance, the communications module62may include a sensor interface64(e.g., one or more analog-to-digital converters) to permit the signals transmitted by one or more sensors65,66,68to be converted into signals that can be understood and processed by the controller26. Furthermore, it should be appreciated that the sensors65,66,68may be communicatively coupled to the communications module62using any suitable means. For example, as shown inFIG. 3, the sensors65,66,68are coupled to the sensor interface64via a wired connection. However, in alternative embodiments, the sensors65,66,68may be coupled to the sensor interface64via a wireless connection, such as by using any suitable wireless communications protocol known in the art. For example, the communications module62may include the Internet, a local area network (LAN), wireless local area networks (WLAN), wide area networks (WAN) such as Worldwide Interoperability for Microwave Access (WiMax) networks, satellite networks, cellular networks, sensor networks, ad hoc networks, and/or short-range networks. As such, the processor58may be configured to receive one or more signals from the sensors65,66,68.

Referring now toFIG. 4, a wind farm100that is controlled according to the system and method of the present disclosure is illustrated. As shown, the wind farm100may include a plurality of wind turbines102, including the wind turbine10described above, and a farm controller104. For example, as shown in the illustrated embodiment, the wind farm100includes twelve wind turbines, including wind turbine10. However, in other embodiments, the wind farm100may include any other number of wind turbines, such as less than twelve wind turbines or greater than twelve wind turbines. In one embodiment, the controller26of the wind turbine10may be communicatively coupled to the farm controller104through a wired connection, such as by connecting the controller26through suitable communicative links106or networks (e.g., a suitable cable). Alternatively, the controller26may be communicatively coupled to the farm controller104through a wireless connection, such as by using any suitable wireless communications protocol known in the art. In addition, the farm controller104may be generally configured similar to the controllers26for each of the individual wind turbines102within the wind farm100.

In several embodiments, one or more of the wind turbines102in the wind farm100may include a plurality of sensors108,110for monitoring various operational data of the individual wind turbines102and/or one or more wind parameters of the wind farm100. For example, as shown, each of the wind turbines102includes a wind sensor108, such as an anemometer or any other suitable device, configured for measuring wind speeds or any other wind parameter. For example, in one embodiment, the wind parameters include information regarding at least one of or a combination of the following: a wind gust, a wind speed, a wind direction, a wind acceleration, a wind turbulence, a wind shear, a wind veer, a wake, SCADA information, or similar. Further, each of the wind turbines102also includes a sensor110for monitoring additional operational parameters of the wind turbine102.

Referring now toFIG. 5, a flow chart illustrating a method200for evaluating loads of a potential wind farm site, such as the wind farm100ofFIG. 4, for multiple wind scenarios is illustrated. As shown at202, the method200includes receiving, via a computer server251, site data from the potential wind farm site representing at least one wind scenario for at least one wind turbine102at the potential wind farm site. As used herein, the computer server251generally refers to a remote computer server251separate from the turbine controller26. As such, the mechanical loads analysis described herein can be completed before the wind farm is installed. Further, the computer server251may operate similar to the controller26illustrate inFIG. 3. It should also be understood, however, that the turbine controller26may also be configured to perform the mechanical loads analysis described herein. In certain embodiments, the site data may correspond to wind conditions, time of day, seasonal variations, or atmospheric conditions and/or stability. More specifically, in certain embodiments, the wind conditions may include wind direction, wind speed, wind shear, wake, wind gusts, turbine shadow, wind turbulence, wind acceleration, wind veer, or any other suitable wind condition. As shown at204, the computer server251converts the site data202to input files that can be read by the processor(s) thereof. As shown at106, the computer server251reads the input files204.

As shown at208and210, a user selects a wind farm configuration for each wind scenario and a time period for each of the wind scenarios via a user interface communicatively coupled to the computer server251. In certain embodiments, the wind farm configuration(s) as described herein may include controller settings for a plurality of wind turbines102at the potential wind farm site100. In addition, the time period(s) as described herein may correspond to day or night periods, periods for each season, periods for when the atmosphere is stable versus unstable, an annual percentage of time for the wind scenario(s), and/or the percentage of a certain controller setting in the overall simulation (e.g. 1 year, 10 years, 20 years, etc.). Therefore, the meteorological data could represent any of the above situations and/or multiple scenarios. For example, a user may select a site having two wind scenarios of day and night, which on an annual basis would include 50% of the time each.

For example, as shown inFIG. 6, a schematic diagram of one embodiment of a system250for evaluating loads of a potential wind farm site, such as the wind farm100ofFIG. 4, for multiple wind scenarios is illustrated. More specifically, as shown, the system250includes a computer server251and a user interface252having a plurality of wind farm configuration selection modules254for selecting a wind farm configuration based on at least one wind scenario for at least one wind turbine102at the potential wind farm site. In addition, as shown, the user interface252also includes a plurality of time period selection modules256for selecting a time period for the wind scenario(s). It should be understood that the user interface252may include any suitable number of wind farm configuration selection modules254as well as time period selection modules256. In addition, the wind farm configuration selection modules254and/or the time period selection modules256may have any suitable format. For example, as shown, the wind farm configuration selection modules254are configured as drop-down menus, whereas, the time period selection modules256are configured as fill-in boxes.

Referring back toFIG. 5, as shown within box212and after the user makes the required selections, the computer server251performs a plurality of processing steps to generate a mechanical loads analysis for the selected wind farm configuration(s) and the selected time period(s). More specifically, as shown at214, the computer server251may generate input files that can be read by simulation software programmed therein. As shown at216, the controller26runs the simulation software to generate the mechanical loads analysis (e.g. a fatigue analysis) on the wind turbine(s)102. As shown at218, the computer server251generates the results. As shown at220, the computer server251may optionally scale the results based on the time period (e.g. the annual percentage). In addition, as shown at222, the computer server251may also run the mechanical loads analysis through a rainflow-counting algorithm that is programmed in a software module of the computer server251. As used herein, a rainflow counting algorithm generally refers to an algorithm that can be used in to the analysis of fatigue data to reduce a spectrum of varying stress into a set of simple stress reversals.

Referring now toFIG. 7, a flow diagram of another embodiment of a method300for evaluating loads of a potential wind farm site, such as the wind farm100ofFIG. 4, for multiple wind scenarios is illustrated. As shown at302, the method300includes receiving, via the computer server251, site data of the potential wind farm site representing at least one wind scenario for at least one wind turbine at the potential wind farm site. As shown at304, the method300includes selecting, via the user interface252, a wind farm configuration based on the at least one wind scenario. As shown at306, the method300includes selecting, via the user interface252, a time period for the at least one wind scenario. As shown at308, the method300includes automatically generating, via the computer server251, a mechanical loads analysis for the selected wind farm configuration and the time period. As shown by arrow310, in one embodiment, the method300may further include repeating steps302through308for multiple wind scenarios. Thus, as shown at312, the method300may include selecting a site layout for the potential wind farm site based on the mechanical loads analysis for the multiple wind scenarios.