Patent Description:
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 one or more rotor blades. The rotor blades are the primary elements for converting wind energy into electrical energy. The blades typically have the cross-sectional profile of an airfoil such that, during operation, air flows over the blade producing a pressure difference between its sides. Consequently, a lift force, which is directed from the pressure side towards the suction side, acts on the blade. The lift force generates torque on the main rotor shaft, which is connected to a generator for producing electricity.

Typically, wind turbines are designed to operate at a rated power output over a predetermined or anticipated operating life. For instance, a typical wind turbine is designed for a <NUM>-year life. However, in many instances, this anticipated overall operating life is limited or based on the anticipated fatigue life of one or more of the wind turbine components. The life consumption or operational usage of the wind turbine (which can include fatigue or extreme loads, wear, and/or other life parameters) as used herein generally refers to the life of the wind turbine or its components that has been consumed or exhausted by previous operation. Furthermore, auxiliary loads also play an important role in a wind turbine as most of the functionalities and components' operation are powered through the auxiliary interface. For example, the total rated power of auxiliary loads generally represent about <NUM>% or more of a wind turbine's rated power.

Thus, an improved system and method for tracking real-time operation of different kinds of loads can be beneficial for optimizing auxiliary loads. Accordingly, the present disclosure is directed to systems and methods for optimizing auxiliary loads based on tracked operational usage. <CIT> describes a turbine farm comprising a plurality of individual turbines each having an auxiliary component circuit. The farm further comprises; a master transformer arranged to be coupled between each of the plurality of individual turbines and an electrical grid and an auxiliary transformer coupled between the sub-station transformer and the auxiliary component circuit in each of the individual turbines. When in use power is transmitted from the sub-station transformer back to each auxiliary component circuit. <CIT> describes a standby control method and device for a wind generating set. The standby control method comprises the following steps: controlling each wind generating set to enter a standbystate when an average value of predicted wind speed in each predetermined time interval in a future first predetermined time period is smaller than a cut-in wind speed; or, when a power limiting instruction is received, determining a power limiting proportion according to the average value of the predicted wind speed in each predetermined time interval in the future first predetermined time period, and controlling at least one wind generating set corresponding to the determined power limiting proportion to enter the standby state.

The present invention is defined by a method according to claim <NUM>, and a system according to claim <NUM>. The dependent claims defined embodiments thereof.

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and, together with the description, explain the principles of the invention.

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 refers to the appended figures, in which:.

In general, the present disclosure is directed to a flexible approach to optimizing auxiliary loads of a wind turbine and/or a wind farm. Most of the functionalities and wind turbine components' operation are powered through the auxiliary interface. Therefore, auxiliary loads can account for about <NUM>% of the total rated power of a wind turbine. By implementing a tracking system to determine the real-time operation of the different loads, it is possible to optimize the auxiliary loads at a farm level. As such, in an embodiment, the control implementation can perform an online estimation of the time operation of each load, by tracking the amount of time that has passed after a rising or falling control command. This can play an important role in optimizing the performance of different sites by reducing the losses and improving the power output. Additionally, the systems and methods of the present disclosure can impact the way auxiliary loads are designed to meet the requirements, specially to meet the lifetime of the wind turbines.

Moreover, the systems and methods of the present disclosure produce a real-time diagnostic of the power consumption of the auxiliary loads. This diagnostic adds flexibility to the system and to help track all the power consumption from the loads during their lifetime. If one of the loads changes, the diagnostic feature can help determine the operating conditions of that load at any time. Such information can be retrofit back into the design phase for auxiliary loads to validate assumptions and help to improve new designs. Also, the collected data can be used to perform trade-off analysis that assists the system in understanding the impacts of auxiliary loads into the performance of the wind turbine and overall wind farm.

In addition, the systems and methods of the present disclosure allow for be real-time optimization. For example, in an embodiment, the present disclosure can compare the spot price and the weather forecast, e.g. using a computer-implemented model. By combining the spot price and the weather forecast, it is possible to optimize the auxiliary loads in a real-time based on weather and market conditions. Both features can also be implemented in a computer application to provide a user-friendly platform.

Referring now to the drawings, <FIG> illustrates a perspective view of one embodiment of a wind turbine <NUM> configured to implement the control technology according to the present disclosure. As shown, the wind turbine <NUM> generally includes a tower <NUM> extending from a support surface <NUM>, a nacelle <NUM> mounted on the tower <NUM>, and a rotor <NUM> coupled to the nacelle <NUM>. The rotor <NUM> includes a rotatable hub <NUM> and at least one rotor blade <NUM> coupled to and extending outwardly from the hub <NUM>. For example, in the illustrated embodiment, the rotor <NUM> includes three rotor blades <NUM>. However, in an alternative embodiment, the rotor <NUM> may include more or less than three rotor blades <NUM>. Each rotor blade <NUM> may be spaced about the hub <NUM> to facilitate rotating the rotor <NUM> to enable kinetic energy to be transferred from the wind into usable mechanical energy, and subsequently, electrical energy. For instance, the hub <NUM> may be rotatably coupled to an electric generator (<FIG>) positioned within the nacelle <NUM> to permit electrical energy to be produced.

The wind turbine <NUM> may also include a wind turbine controller <NUM> centralized within the nacelle <NUM>. However, in other embodiments, the controller <NUM> may be located within any other component of the wind turbine <NUM> or at a location outside the wind turbine. Further, the controller <NUM> may be communicatively coupled to any number of the components of the wind turbine <NUM> in order to control the operation of such components and/or to implement a corrective action. As such, the controller <NUM> may include a computer or other suitable processing unit. Thus, in several embodiments, the controller <NUM> may include suitable computer-readable instructions that, when implemented, configure the controller <NUM> to perform various functions, such as receiving, transmitting and/or executing wind turbine control signals.

Accordingly, the controller <NUM> may generally be configured to control the various operating modes of the wind turbine <NUM> (e.g., start-up or shut-down sequences), de-rate the wind turbine <NUM>, and/or control various components of the wind turbine <NUM>. For example, the controller <NUM> may be configured to control the blade pitch or pitch angle of each of the rotor blades <NUM> (i.e., an angle that determines a perspective of the rotor blades <NUM> with respect to the direction of the wind) to control the power output generated by the wind turbine <NUM> by adjusting an angular position of at least one rotor blade <NUM> relative to the wind. For instance, the controller <NUM> may control the pitch angle of the rotor blades <NUM> by rotating the rotor blades <NUM> about a pitch axis <NUM>, either individually or simultaneously, by transmitting suitable control signals to a pitch drive or pitch adjustment mechanism (not shown) of the wind turbine <NUM>.

Referring now to <FIG>, a simplified, internal view of one embodiment of the nacelle <NUM> of the wind turbine <NUM> shown in <FIG> is illustrated. As shown, the generator <NUM> may be coupled to the rotor <NUM> for producing electrical power from the rotational energy generated by the rotor <NUM>. For example, as shown in the illustrated embodiment, the rotor <NUM> may include a rotor shaft <NUM> coupled to the hub <NUM> for rotation therewith. The rotor shaft <NUM> may, in turn, be rotatably coupled to a generator shaft <NUM> of the generator <NUM> through a gearbox <NUM>. As is generally understood, the rotor shaft <NUM> may provide a low speed, high torque input to the gearbox <NUM> in response to rotation of the rotor blades <NUM> and the hub <NUM>. The gearbox <NUM> may then be configured to convert the low speed, high torque input to a high speed, low torque output to drive the generator shaft <NUM> and, thus, the generator <NUM>.

Each rotor blade <NUM> may also include a pitch adjustment mechanism <NUM> configured to rotate each rotor blade <NUM> about its pitch axis <NUM>. Further, each pitch adjustment mechanism <NUM> may include a pitch drive motor <NUM> (e.g., any suitable electric, hydraulic, or pneumatic motor), a pitch drive gearbox <NUM>, and a pitch drive pinion <NUM>. In such embodiments, the pitch drive motor <NUM> may be coupled to the pitch drive gearbox <NUM> so that the pitch drive motor <NUM> imparts mechanical force to the pitch drive gearbox <NUM>. Similarly, the pitch drive gearbox <NUM> may be coupled to the pitch drive pinion <NUM> for rotation therewith. The pitch drive pinion <NUM> may, in turn, be in rotational engagement with a pitch bearing <NUM> coupled between the hub <NUM> and a corresponding rotor blade <NUM> such that rotation of the pitch drive pinion <NUM> causes rotation of the pitch bearing <NUM>. Thus, in such embodiments, rotation of the pitch drive motor <NUM> drives the pitch drive gearbox <NUM> and the pitch drive pinion <NUM>, thereby rotating the pitch bearing <NUM> and the rotor blade <NUM> about the pitch axis <NUM>. Similarly, the wind turbine <NUM> may include one or more yaw drive mechanisms <NUM> communicatively coupled to the controller <NUM>, with each yaw drive mechanism(s) <NUM> being configured to change the angle of the nacelle <NUM> relative to the wind (e.g., by engaging a yaw bearing <NUM> of the wind turbine <NUM>).

Referring now to <FIG>, there is illustrated a block diagram of one embodiment of suitable components that may be included within a controller in accordance with aspects of the present disclosure. It should be understood that the various components of the controller of <FIG> may be applicable to any suitable controller, including for example, the controller <NUM> (which is described in more detail below with respect to FIGS. 7A, and 7B), the turbine controller <NUM>, and/or the farm-level controller <NUM> described herein.

As shown, the controller may include one or more processor(s) <NUM> and associated memory device(s) <NUM> configured to perform a variety of computer-implemented functions (e.g., performing the methods, steps, calculations and the like disclosed herein). 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, and other programmable circuits. Additionally, the memory device(s) <NUM> may generally comprise 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), a floppy disk, a compact disc-read only memory (CD-ROM), a magneto-optical disk (MOD), a digital versatile disc (DVD) and/or other suitable memory elements.

Additionally, the controller may also include a communications module <NUM> to facilitate communications between the controller and the various components of the wind turbine <NUM>. For instance, the communications module <NUM> may include a sensor interface <NUM> (e.g., one or more analog-to-digital converters) to permit the signals transmitted by one or more sensors <NUM>, <NUM>, <NUM> to be converted into signals that can be understood and processed by the controller. It should be appreciated that the sensors <NUM>, <NUM>, <NUM> may be communicatively coupled to the communications module <NUM> using any suitable means. For example, as shown in <FIG>, the sensors <NUM>, <NUM>, <NUM> are coupled to the sensor interface <NUM> via a wired connection. However, in other embodiments, the sensors <NUM>, <NUM>, <NUM> may be coupled to the sensor interface <NUM> via a wireless connection, such as by using any suitable wireless communications protocol known in the art. As such, the processor <NUM> may be configured to receive one or more signals from the sensors <NUM>, <NUM>, <NUM>.

The sensors <NUM>, <NUM>, <NUM> of the wind turbine <NUM> may be any suitable sensors configured to measure any operational condition and/or wind parameter at or near the wind turbine. For example, the sensors <NUM>, <NUM>, <NUM> may include blade sensors for measuring a pitch angle of one of the rotor blades <NUM> or for measuring a loading acting on one of the rotor blades <NUM>; generator sensors for monitoring the generator (e.g. torque, rotational speed, acceleration and/or the power output); and/or various wind sensors for measuring various wind parameters. In addition, the sensors <NUM>, <NUM>, <NUM> may be located near the ground of the wind turbine, on the nacelle, or on a meteorological mast of the wind turbine.

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 analog sensors, digital sensors, optical/visual sensors, accelerometers, pressure sensors, angle of attack sensors, vibration sensors, MIMU sensors, fiber optic systems, temperature sensors, wind sensors, Sonic Detection and Ranging (SODAR) sensors, infra lasers, Light Detecting and Ranging (LIDAR) sensors, radiometers, pitot tubes, rawinsondes, and/or any other suitable sensors. It should be appreciated that, as used herein, the term "monitor" and variations thereof indicate that the various sensors of the wind turbine may be configured to provide a direct measurement of the parameters being monitored or an indirect measurement of such parameters. Thus, the sensors <NUM>, <NUM>, <NUM> may, for example, be used to generate signals relating to the parameter being monitored, which can then be utilized by the controller to determine the actual condition.

Referring now to <FIG>, the system and method as described herein may also be combined with a wind farm controller <NUM> of a wind farm <NUM>. As shown, the wind farm <NUM> may include a plurality of wind turbines <NUM>, including the wind turbine <NUM> described above. For example, as shown in the illustrated embodiment, the wind farm <NUM> includes twelve wind turbines, including wind turbine <NUM>. However, in other embodiments, the wind farm <NUM> may include any other number of wind turbines, such as less than twelve wind turbines or greater than twelve wind turbines. In one embodiment, the controller <NUM> of wind turbine <NUM> may be communicatively coupled to the farm controller <NUM> through a wired connection, such as by connecting the controller <NUM> through suitable communicative links <NUM> (e.g., a suitable cable). Alternatively, the controller <NUM> may be communicatively coupled to the farm controller <NUM> through a wireless connection, such as by using any suitable wireless communications protocol known in the art.

In several embodiments, one or more of the wind turbines <NUM> in the wind farm <NUM> may include a plurality of sensors for monitoring various operating parameters/conditions of the wind turbines <NUM>. For example, as shown, one of the wind turbines <NUM> includes a wind sensor <NUM>, such as an anemometer or any other suitable device, configured for measuring wind speeds. As is generally understood, wind speeds may vary significantly across a wind farm <NUM>. Thus, the wind sensor(s) <NUM> may allow for the local wind speed at each wind turbine <NUM> to be monitored. In addition, the wind turbine <NUM> may also include an additional sensor <NUM>. For instance, the sensors <NUM> may be configured to monitor electrical properties of the output of the generator of each wind turbine <NUM>, such as current sensors, voltage sensors, temperature sensors, or power monitors that monitor power output directly based on current and voltage measurements. Alternatively, the sensors <NUM> may include any other sensors that may be utilized to monitor the power output of a wind turbine <NUM>. It should also be understood that the wind turbines <NUM> in the wind farm <NUM> may include any other suitable sensor known in the art for measuring and/or monitoring wind conditions and/or wind turbine conditions.

Furthermore, each of the wind turbines <NUM> in the wind farm <NUM> may include various auxiliary components/equipment such as pumps, blowers, motors, cooling systems, heating systems, etc. that generate auxiliary loads and therefore consume power. Such auxiliary components are typically divided between multiple cabinets of the wind turbines <NUM>. For example, as shown in <FIG>, the auxiliary components may be housed in a topbox cabinet <NUM>, a converter cabinet <NUM>, a downtower cabinet <NUM>, or any other suitable cabinet at any suitable location.

The total amount of power that such auxiliary loads represent can account for as much as about <NUM>% or more of the rating power for the individual wind turbines <NUM>. Further, many of these loads come directly from the topbox cabinet <NUM>, which can represent about <NUM>% of the total auxiliary power of the wind turbines <NUM> (or about <NUM>% of the entire turbine rated power). The topbox cabinet <NUM> typically contains critical loads such as the yaw and pitch systems and other loads like heaters and pump systems. Accordingly, the critical loads of the topbox cabinet <NUM> represent about <NUM>-<NUM>% of all of the auxiliary loads (or about <NUM>% of the entire turbine rating).

Thus, referring now to <FIG>, a flow diagram of one embodiment of a method <NUM> for optimizing the auxiliary loads of a wind farm, such as wind farm <NUM>, is illustrated in accordance with aspects of the present disclosure. The method <NUM> is described herein as implemented using, for example, the wind turbines <NUM> of the wind farm <NUM> described above. However, it should be appreciated that the disclosed method <NUM> may be implemented using any other suitable wind turbine or wind farm now known or later developed in the art. In addition, although <FIG> depicts steps performed in a particular order for purposes of illustration and discussion, the methods described herein are not limited to any order or arrangement. One skilled in the art, using the disclosures provided herein, will appreciate that various steps of the methods can be omitted, rearranged, combined and/or adapted in various ways.

As shown at (<NUM>), the method <NUM> includes tracking, e.g. via the farm-level controller <NUM>, operational usage for one or more auxiliary components of at least one of the wind turbines <NUM> in the wind farm <NUM> since the operational usage of the auxiliary components induces a load on the auxiliary component(s). For example, in an embodiment, the method <NUM> may include tracking the operational usage for the auxiliary component(s) in real-time online. More specifically, the processor <NUM> may be configured to determine the operational usage for the auxiliary components of the wind turbine <NUM>. As used herein, "operational usage" generally refers to the time (e.g. as measured in the number of operating seconds, minutes, hours, or similar) that the auxiliary components have operated at various operational parameters and/or under certain conditions. Such operational parameters that may be considered or tracked may include, for example, one or more of the following: torque, load, speed, temperature, wind speed, wind direction, air density, turbulence intensity, an amount of yawing, or an amount of pitching. Thus, the processor <NUM> may also be configured to record and store the operational usage in the memory device <NUM> for later use. For example, the processor <NUM> may store the operational usage in one or more look-up tables (LUTs). Moreover, the operational usage may be stored in the cloud.

Thus, as shown at (<NUM>), the method <NUM> also includes determining, e.g. via the farm-level controller <NUM>, a power consumption of the load induced on the auxiliary component(s) based on the operational usage. For example, in an embodiment, the processor(s) <NUM> may determine the power consumption of the load induced on the auxiliary component(s) by tracking rising and falling control commands sent by the farm-level controller <NUM> to the auxiliary component(s) and a rated power from a nameplate of the auxiliary component(s).

As shown at (<NUM>), the method <NUM> further includes receiving, e.g. via the farm-level controller <NUM>, at least one additional parameter of the wind farm <NUM>. For example, in an embodiment, the additional parameter(s) may include site location, spot price of wind energy, temperature, humidity, air pressure, wind speed, wind direction, or similar or combinations thereof. Accordingly, in an embodiment, the method <NUM> may include tracking the spot price of the wind energy and reducing the load of one or more of the auxiliary component(s) and/or scheduling a maintenance action when the spot price is above a predetermined threshold.

Accordingly, as shown at (<NUM>), the method <NUM> also includes implementing, e.g. via the farm-level controller <NUM>, a control command for one or more of the auxiliary component(s) based on the power consumption and/or the additional parameter(s). For example, in particular embodiments, the processor(s) <NUM> may turn off one or more of the auxiliary component(s) for any of the plurality of wind turbines <NUM> not producing power. In another embodiment, for example, turning off one or more of the auxiliary component(s) for any of the plurality of wind turbines <NUM> not producing power may include turning off, at least, the topbox auxiliary loads for any of the plurality of wind turbines <NUM> not producing power, such as the yaw and/or pitch systems. By just considering the yaw and pitch systems, there is an opportunity to reduce about <NUM>% of the entire auxiliary consumption, which is equivalent of increasing the power production of the wind turbine <NUM> by about <NUM>%.

When the wind turbine(s) <NUM> is producing power, there are still some instances that the wind turbine(s) <NUM> can reduce auxiliary loads. For example, in certain embodiments, the processor(s) <NUM> may be configured to reduce the load induced on the auxiliary component(s) when at least one of the plurality of wind turbines is operating at rated power. More specifically, for example, when the wind turbine(s) <NUM> is operating at rated power, the yaw and/or pitch systems can be drastically reduced (rather than turned off). By avoiding yawing at rated power, for example, the power produced by the wind turbine(s) <NUM> can be increased at every wind speed. When the wind turbine(s) <NUM> is not operating at rated power, then the optimization can be based on temperature and/or other specific conditions for each auxiliary load.

In still another embodiment, if the load induced on the auxiliary component(s) deviates by a certain threshold, the method <NUM> may also include determining at least one operating condition at the deviated load, trending the operating condition(s) over time, and storing the trended operating condition(s) in a memory device(s) <NUM> for use in future designs of the wind farm <NUM>.

Claim 1:
A method for optimizing auxiliary loads of a wind farm comprising a plurality of wind turbines, the method comprising:
tracking, via a farm-level controller of the wind farm, operational usage for one or more auxiliary components of at least one of the plurality of wind turbines in the wind farm, the operational usage for the one or more auxiliary components placing a load on the one or more auxiliary components (<NUM>);
determining, via the farm-level controller, a power consumption of the load induced on the one or more auxiliary components based on the operational usage (<NUM>);
receiving, via the farm-level controller, at least one additional parameter of the wind farm (<NUM>); and,
implementing, via the farm-level controller, a control command for one or more of the one or more auxiliary components based on the power consumption and the at least one additional parameter (<NUM>);
wherein implementing the control command for one or more of the one or more auxiliary components based on the power consumption and the at least one additional parameter (<NUM>) further comprises:
when at least one of the plurality of wind turbines is operating at rated power, reducing the load induced on the one or more auxiliary components including reducing rather than turning off a yaw system by avoiding yawing at rated power.