Patent Application
20150101401
The subject matter disclosed herein generally relates to wind turbines and more particularly to methods and systems to generate reliability forecasts for wind turbines.
Wind turbines typically include multiple blades extending from a central hub. The hub is rotatably coupled to a nacelle suspended above the ground by a tower. Generally, the nacelle houses an electric generator coupled to the hub and configured to generate electrical power as the blades are driven to rotate by the wind.
During operation, a wind turbine may endure varying temperatures, pressures, and mechanical loads. Due to these stresses, a wind turbine requires maintenance at regular intervals. It is desirable that maintenance of a wind turbine not be performed prematurely in order to keep the wind turbine online for as long as possible and to reduce operational costs. It is also desirable that maintenance of a wind turbine is performed in advance of any component failure.
Disclosed herein are methods and systems to determine the reliability of a wind turbine. In an embodiment, a method may comprise obtaining an environmental factor of a wind turbine based on geospatial data of a first area and location data of a second area, obtaining an operating factor of the wind turbine, and determining a reliability forecast based on the environmental factor and the operating factor.
In an embodiment, a system may have a processor and a memory coupled to the processor, with the memory storing executable instructions that cause the processor to effectuate operations including obtaining an environmental factor of a wind turbine based on geospatial data of a first area and location data of a second area, obtaining an operating factor of the wind turbine, and determining a reliability forecast based on the environmental factor and the operating factor.
This Brief Description of the Invention is provided to introduce a selection of concepts in a simplified form that are further described below in the Detailed Description of the Invention. This Brief Description of the Invention is not intended to identify key features or essential features of the claimed subject matter, nor is it intended to be used to limit the scope of the claimed subject matter. Furthermore, the claimed subject matter is not limited to limitations that solve any or all disadvantages noted in any part of this disclosure.
A more detailed understanding may be had from the following description, given by way of example in conjunction with the accompanying drawings wherein:
Various models may forecast the reliability of wind turbines and in turn determine maintenance schedules. Factors which may be included in such a model include the accumulated operating time, the number of starts, internal temperatures, properties of the materials, manufacturing variations, and operating parameters such as load and shaft revolution speed. The reliability of a wind turbine may also be affected by environmental factors such as temperature (e.g., causing blade icing), humidity, precipitation, and particulates in the air.
For example, with regard to environmental factors, wind turbine blades are typically designed and manufactured to efficiently transfer wind energy into rotational motion, thereby providing the generator with sufficient rotational energy for power generation. Blade efficiency is generally dependent upon blade shape and surface smoothness. During operation, dirt, bugs, sea salt, ice, and the like may collect on the blades, thereby altering performance of the wind turbine. Environmental factors that may affect reliability include the presence of wind speed and direction, icing, lightning strikes, bird flights (e.g., direction, number of birds, size or type of bird, flying altitude, patterns or tendency of the bird, or the like) wave height (e.g., particularly regarding off-shore units), and sea salt aerosols, among other things. Accordingly, it may be useful to include one or more environmental factors in a model to forecast the reliability of a wind turbine.
Step 110 provides for obtaining one or more environmental factors relating to a wind turbine by use of a geographic information system. Step 110 may include obtaining geospatial data of an area. In general, geospatial data is a body of data that associates geographic location with one or more values. Geospatial data may take the form of raster data or vector data.
Raster data is composed of a grid of cells, with each cell having a value. The most common value of a raster cell is a color value—which is the basis for the majority of digital image formats—but it is not necessarily so limited. The color of a raster cell in geospatial data may be cross referenced with an associated legend, which provides information on what each color represents.
Conversely, a raster cell value may be a raw data value which may later be depicted as a particular color, shade, or transparency in a visual display of the data. A raster cell value may also be a compound value, such as a data type which includes both a wind speed and a wind direction component.
Raster data may also include raw image data, such as a photograph or drawing.
Vector data is one or more sets of data necessary to form one or more geometrical primitives and a value or values associated with the geometrical primitive. A geometrical primitive may include a point, line, curve, shape, or polygon. For example, a set of data necessary to form a circle would include an indication that what is to be formed is a circle, the radius of the circle, and the location of the center of the circle. Each geometrical primitive is associated with one or more values. As discussed herein, the associated value may include data relating to pollen, airborne sea salt, dust, smoke, ash, SO2 gas, sulfate aerosols, temperature, wind, cloud formations, precipitation, precipitation type, humidity, barometric pressure, or the like. For example,
Geospatial data may also be converted between data types. For example, raster data may be converted into vector data and vice versa. Geospatial data may also be converted to other data types useful for a geographic information system. For example, photographic raster data or a plurality of photographic raster data may be converted into a single numeric value or ranking representing some aspect of the photographic raster data. To illustrate, the photographic raster data 400 shown in
Geospatial data may be obtained from a satellite system, a radar system, and other sources. A satellite system may provide geospatial data by use of photographic camera, infrared camera, radiation sensor, radar, lidar, or other remote sensing equipment. The geospatial data provided by a satellite system may include data relating to, but not limited to, pollen, airborne sea salt, dust, smoke, ash, SO2 gas, sulfate aerosols, and other particulate matter. A satellite system may also provide geospatial data relating to the temperature, wind direction and speed, cloud formations, lightning strikes, and elevation. For example,
Geospatial data may be obtained using a ground-based radar system. A ground-based radar system may provide some of the same geospatial data as a satellite system such as data relating to pollen, airborne sea salt, dust, smoke, ash, and cloud formations. A ground-based radar system may also provide geospatial data relating to precipitation.
Another exemplary source of geospatial data may include an aerial surveillance system. Similar to a satellite system, an aerial surveillance system may make use of photographic camera, infrared camera, radiation sensor, radar, lidar, or other remote sensing equipment mounted on an airplane or other flying vehicle. Another exemplary source of geospatial data may include a buoy. A buoy may have data about the sea state (e.g., wave height, wave period, wave direction, and sea temperature). This data may particularly useful for wind turbines that are located off-shore.
The geospatial data is not limited to being obtained from a single source, but may be comprised of aggregated data from a plurality of sources. For example, the geospatial data may be formed by aggregating data, such as any of the aforementioned types or other types such as precipitation type, humidity, and barometric pressure, from a network of weather stations. Furthermore, obtaining geospatial data is not limited to obtaining geospatial data directly from the aforementioned sources, but also includes indirectly obtaining geospatial data from the aforementioned sources by way of a third party such as an Internet search engine resource, a national weather service database, an atmospheric research center database, or other network or Internet resource.
The geospatial data may be historical, projected, real-time, or a combination thereof. Historical geospatial data includes geospatial data relating to past conditions. For example, historical geospatial data may include data relating to the accumulated precipitation in an area over a past period of time.
Projected geospatial data includes geospatial data relating to future conditions. For example, projected geospatial data may take a form similar to that illustrated in
Real-time geospatial data includes geospatial data relating to a present condition. Real-time geospatial data as discussed herein refers to data relating to a condition which occurred in a time span ranging from the instant of the condition occurrence to a time necessary to accommodate the time-delay introduced by automated data processing or network transmission. For example, an instance of real-time geospatial data includes data relating to a condition as it existed at the current time minus the processing and transmission time. Real-time geospatial data usually includes data relating to a condition which occurred within several seconds.
Step 110 includes obtaining location data of an area. The location data may include the location of a wind turbine or the projected location of a wind turbine. A projected location of a wind turbine may be an estimated future site where a wind turbine is desired to be built. The location data is not limited to a single location, but may also include a plurality of locations. The location data may take a form reconcilable with the forms of other location data, such as in the geographical location component of the geospatial data. The location data may be comprised of a pair of latitude and longitude coordinates. The location data may also contain an additional elevation component. The location data is not limited to a discrete location, e.g., a set of latitude and longitude coordinates, but may also define a location more broadly, such as the location comprising the area within a two mile radius of a particular set of latitude and longitude coordinates.
The obtained geospatial data of an area and the obtained location data of an area may be used by a geographic information system. A geographic information system is a system which can store, manipulate, analyze, and present geospatial data.
The geospatial data representation of
As disclosed herein, the geographic information system receives and stores geospatial data along with location data of an area. If necessary, the geographic information system adjusts the coordinate systems of either or both of the geospatial data and location data of the wind turbine so that the respective coordinate systems are consistent. The geographic information system analyzes the geospatial data and creates a representation of the geospatial data. The creation of a representation of geospatial data may include converting raster data to vector data form, vector data to raster data form, and raster or vector data to a relational database or other useful form. The creation of a representation of geospatial data may also include little or no conversion, depending on the input form and the form useful to the geographic information system. The geographic information system may also combine—by intersection, for example—more than one set of geospatial data to form a single geospatial representation of that data.
Step 110 may include the geographic information system correlating the coordinates of the location data, e.g., the location or projected location of the wind turbine, with the corresponding geospatial data for that set of coordinates, thus determining an environmental factor for the location. The geographic information system may receive more than one set of geospatial data and therefore may determine more than one environmental factor for the location. The geographic information system may also present the geospatial data representation and the location in a graphical display so that they may be visually correlated by a user.
Step 120 may include obtaining one or more operating factors relating to a wind turbine. An operating factor may be historical, projected, real-time, or a combination thereof. An operating factor may include a variety of data relating to the current operational status of the wind turbine. Examples of an operating factor include a temperature within various sections of the wind turbine, a voltage and/or current associated with a component, or the like. An operating factor may include more static factors such as the model of the wind turbine, the models of the parts composing the wind turbine, and the properties of the materials with which the wind turbine and its parts are composed. An operating factor may also include data relating to stops, starts, and maintenance performed on the wind turbine.
A historical operating factor may be based on one or more past events or conditions. For example, a historical operating factor may be based on the accumulated time at load or the number of starts of a wind turbine.
A projected operating factor is an operating factor based on one or more future events or conditions. Examples of a projected operating factor include the projected total time at load one year in the future or the projected number of maintenance services performed on the wind turbine by ten years in the future. A projected operating factor may also include a single projected piece of data, as opposed to an aggregated set, such as a projected internal temperate at a time one year in the future.
A real-time operating factor may be based on one or more events or conditions occurring at the present time. A real-time operating factor may include the current blade revolution or the current power output of the wind turbine, for example. A real-time operating factor refers to a factor relating to an event or condition which occurred in a time span ranging from the instant of the event or condition occurrence to a time necessary to accommodate the time-delay introduced by automated data processing or network transmission. In other words, a real-time operating factor includes data relating to an event or condition as it existed at the current time minus the processing and transmission time. A real-time operating factor usually includes data relating to an event or condition which occurred within several seconds.
An operating factor may also be a combination of historical operation factors, projected operating factors, and real-time operating factors. For example, a running average of a wind speed would include historical winds speeds and a real-time wind speed.
Step 130 provides for determining a reliability forecast for a wind turbine based on the one or more environmental factors relating to a wind turbine and the one or more operating factors relating to the wind turbine.
Step 130 includes inputting the one or more environmental factors relating to the wind turbine, obtained in step 110, and the one or more operating factors relating to the wind turbines, obtained in step 120, into a model useful to reach a reliability forecast. Such a model may include a Bayesian model, a Dempster-Shafer model, a fuzzy reasoning model, a logic based model, a damage accumulation model, or the like.
A reliability forecast may be in the form of a probability factor relating to the reliability of the wind turbine, a remaining useful life factor of a wind turbine, or the like. A probability factor relating to a wind turbine may include a numerical probability that a wind turbine fails, sustain damages, or suffer degraded performance over a period of time. For example, a probability factor may be determined to be 90 percent that there will be no significant reliability issues in a 10 year time frame. The significance of the reliability issues may be based on degradation of performance, cost, down-time, or another metric. A remaining useful life factor of a wind turbine may be a projection of time before a wind turbine fails, sustains damage, or suffers degraded performance. For example, a remaining useful life factor may be determined to be 40 years for the wind turbine (or wind turbine component) from a selected time. A probability factor or remaining useful life factor may also be combined with prior probability factors or remaining use life factors, respectively, to determine an updated average factor. Generally the reliability forecast may be continuously displayed on a monitor for an individual wind turbine or a region.
A reliability forecast based on environmental and operating factors related to a wind turbine may assist in predicting a maintenance interval of the wind turbine and how long the wind turbine may ultimately operate. For example, if a storm (which may cause large waves and lightning) arises in the area of a wind turbine, the reliability forecast derived from the systems and methods disclosed herein may be an indicator of how many technicians to have at the site or on standby based the reliability reaching a threshold number. Conversely, the unexpected absence of environmental conditions such as waves, lightning, or dust may inform the user to postpone blade or other wind turbine part maintenance, thereby reducing costs. In an embodiment, a reliability forecast may assist in the sale of a wind turbine. For example, the reliability forecast may assist in forecasting the life of the wind turbine and enable a longer than usual guarantee period to be presented to a prospective customer.
The reliability forecast may reduce the ultimate decision making process for a user or machine to the review of the reliability forecast number (e.g., probability factor or remaining useful life). A reliability forecast as discussed herein may also be useful in the following scenarios. For example, the normal international engineering code (IEC) design envelope of a wind turbine defines loads acting on the wind energy turbine within a temperature range from about +40 degrees Celsius (° C.) (about 100 degrees Fahrenheit (° F.)) to about −20° C. (about −30° F.). Operation of a wind turbine below this temperature range may require new load calculations which will exceed the design load envelope if no countermeasures are taken, possibly resulting in the need of new, reinforced components. At least some known wind turbines, when subjected to cold weather conditions with ambient air temperature values below the lower temperature limit of the allowable temperature range, are shut off, which is disadvantageous insofar as no electric output power is generated.
Another example of environmental changes affecting wind turbine performance is that air temperature-corrected turbine performance of at least some known wind turbines may be lower in warm temperatures than in cool temperatures. For example, a probability of the rotor blades of at least some known wind turbines to stall may increase during warm conditions reflective of summer weather when ambient air temperatures are high. Such stalling reduces a potential electric power output of the wind turbine. Moreover, reestablishment of airflow around at least some known wind turbine rotor blades after stalling may cause a short-term increase in generator speed and/or electric power output that may be difficult for a controller of the wind turbine to process. Such controller processing difficulty may increase a probability of the wind turbine to be disconnected from an electric grid due to over-speed and/or over-production conditions
Without in any way limiting the scope, interpretation, or application of the claims appearing herein, a technical effect of one or more of the example embodiments disclosed herein is to provide a reliability forecast for a wind turbine. The reliability forecast may be used to predict performance and reliability of the wind turbine, among other things. A technical effect of one or more of the embodiments disclosed herein is to provide adjustments directed to maintenance of a wind turbine based on a reliability forecast.
The computer 1020 may further include a hard disk drive 1027 for reading from and writing to a hard disk (not shown), a magnetic disk drive 1028 for reading from or writing to a removable magnetic disk 1029, and an optical disk drive 1030 for reading from or writing to a removable optical disk 1031 such as a CD-ROM or other optical media. The hard disk drive 1027, magnetic disk drive 1028, and optical disk drive 1030 are connected to the system bus 1023 by a hard disk drive interface 1032, a magnetic disk drive interface 1033, and an optical drive interface 1034, respectively. The drives and their associated computer-readable media provide non-volatile storage of computer readable instructions, data structures, program modules and other data for the computer 1020. As described herein, computer-readable media is a tangible, physical, and concrete article of manufacture and thus not a signal per se.
Although the exemplary environment described herein employs a hard disk, a removable magnetic disk 1029, and a removable optical disk 1031, it should be appreciated that other types of computer readable media which can store data that is accessible by a computer may also be used in the exemplary operating environment. Such other types of media include, but are not limited to, a magnetic cassette, a flash memory card, a digital video or versatile disk, a Bernoulli cartridge, a random access memory (RAM), a read-only memory (ROM), and the like.
A number of program modules may be stored on the hard disk, magnetic disk 1029, optical disk 1031, ROM 1024 or RAM 1025, including an operating system 1035, one or more application programs 1036, other program modules 1037 and program data 1038. A user may enter commands and information into the computer 1020 through input devices such as a keyboard 1040 and pointing device 1042. Other input devices (not shown) may include a microphone, joystick, game pad, satellite disk, scanner, or the like. These and other input devices are often connected to the processing unit 1021 through a serial port interface 1046 that is coupled to the system bus, but may be connected by other interfaces, such as a parallel port, game port, or universal serial bus (USB). A monitor 1047 or other type of display device is also connected to the system bus 1023 via an interface, such as a video adapter 1048. In addition to the monitor 1047, a computer may include other peripheral output devices (not shown), such as speakers and printers. The exemplary system of
The computer 1020 may operate in a networked environment using logical connections to one or more remote computers, such as a remote computer 1049. The remote computer 1049 may be a personal computer, a server, a router, a network PC, a peer device or other common network node, and may include many or all of the elements described above relative to the computer 1020, although only a memory storage device 1050 has been illustrated in
When used in a LAN networking environment, the computer 1020 is connected to the LAN 1051 through a network interface or adapter 1053. When used in a WAN networking environment, the computer 1020 may include a modem 1054 or other means for establishing communications over the wide area network 1052, such as the Internet. The modem 1054, which may be internal or external, is connected to the system bus 1023 via the serial port interface 1046. In a networked environment, program modules depicted relative to the computer 1020, or portions thereof, may be stored in the remote memory storage device. It will be appreciated that the network connections shown are exemplary and other means of establishing a communications link between the computers may be used.
Computer 1020 may include a variety of computer readable storage media. Computer readable storage media can be any available media that can be accessed by computer 1020 and includes both volatile and nonvolatile media, removable and non-removable media. By way of example, and not limitation, computer readable media may comprise computer storage media and communication media. Computer storage media include both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by computer 1020. Combinations of any of the above should also be included within the scope of computer readable media that may be used to store source code for implementing the methods and systems described herein. Any combination of the features or elements disclosed herein may be used in one or more embodiments.
In describing preferred embodiments of the subject matter of the present disclosure, as illustrated in the Figures, specific terminology is employed for the sake of clarity. The claimed subject matter, however, is not intended to be limited to the specific terminology so selected, and it is to be understood that each specific element includes all technical equivalents that operate in a similar manner to accomplish a similar purpose. Where the definition of terms departs from the commonly used meaning of the term, applicant intends to utilize the definitions provided herein, unless specifically indicated. The singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be understood that, although the terms first, second, etc., may be used to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. The term “and/or” includes any, and all, combinations of one or more of the associated listed items. The term “wind turbine” is not limited to a wind turbine engine, but may refer more broadly to a wind turbine system including peripheral and support equipment, structures, and systems. For example, a wind turbine, as referred herein, may also include wind turbine blades, a drive train, and a shaft, among other things. The reliability factor as discussed herein with regard to wind turbines may also apply to solar power generation. Thus there may be a solar power generation reliability factor based on similarly obtaining an environmental factor and an operating factor of the solar panels and peripheral and support equipment.
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 have 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.
