Patent Application
20110106747
The subject matter disclosed herein relates to turbines and, in particular, to when to inspect turbines and when to replace various component of turbine.
Electrical power generation typically includes the utilization of one or more turbines. These turbines, like any other mechanical device, may need inspection from time to time to ensure proper operation. One approach has been to have periodic inspections. In some cases, however, it may be determined that particular turbines (or portions thereof) may not need to be inspected as often as others even if they are of the same type. Thus, an inspection may not be necessary for one turbine while it may be for another. One factor that may influence such decisions is based on environmental conditions where the turbine is located.
High availability and reliability of power generation systems has been a major requisite of the electric utility industry for many years. The high cost of unreliability and forced outages is well known. Improper maintenance or operational anomoly detection may lead to turbine-forced outages. Early detection of such anomolies is important in preventing and reducing lengthy turbine forced outages.
A typical inspection may require that a turbine be shut down during the inspection. In such a case, at least a portion of a power generation plant's production capability may be hampered. Reducing the ability to generate power may have real economic costs associated with it. In addition, the inspection itself costs money. For at least these two reasons, it may be beneficial to perform inspections only when needed.
According to one aspect of the invention, a system for creating an inspection recommendation or part replacement recommendation for a unit forming a part of a fleet is provided. The system of this aspect includes an assessment module that receives inputs from at least one portion of at least one turbine and produces an inspection recommendation or part replacement recommendation. The assessment module includes a health assessment module that creates a risk of event estimate based on the inputs and historical operations data and a performance analyzer coupled to the health assessment module that creates the inspection recommendation based on the risk of event estimate and information related to a cost.
According to another aspect of the invention, a method of forming a unit inspection recommendation for a unit forming a part of a fleet is provided. The method of this aspect includes receiving inputs at an assessment module from at least one portion of at least one turbine; forming at a health assessment module a risk of event estimate based on the inputs and historical operations data; and creating the inspection recommendation based on the risk of event estimate and cost information.
These and other advantages and features will become more apparent from the following description taken in conjunction with the drawings.
The subject matter, which is regarded as the invention, is particularly pointed out and distinctly claimed in the claims at the conclusion of the specification. The foregoing and other features, and advantages of the invention are apparent from the following detailed description taken in conjunction with the accompanying drawings in which:
The detailed description explains embodiments of the invention, together with advantages and features, by way of example with reference to the drawings.
Embodiments disclosed herein may provide life assessment, asset planning and inspection recommendations using some or all of field data, operational profile, site conditions, hardware configuration, inlet conditioning, sensor information, reliability models, expert rules, classifiers and multivariate statistical techniques. In utilizing the systems or implementing the methods disclosed herein, accurate inspect of units may be planned and it may also increase the availability of the units in the fleet.
In particular, inspection recommendations may be based on information fusion of risk models and hardware configurations. The system can provide more accurate inspection recommendations and prevent unplanned outage in the field. Using the invention disclosed herein may also allow for the improvement of turbine life based on operating profile changes. In addition, tracking particular failures or risks may allow for determination that additional devices are needed for proper turbine operation. For example, inlet air filtration systems may be needed for turbines operating in high-risk geographic regions.
In the event the turbine 60 is a gas turbine, the turbine 60 may include a compressor 52 to draw in and compress air; a combustor 54 (or burner) to add fuel to heat the compressed air; and a turbine 56 to extract power from the hot air flow. The gas turbine is an internal combustion (IC) engine employing a continuous combustion process. The following description may focus on the compressor 42. However, it shall be understood that the teachings herein are not so limited and may be applied, for example, to any portion of the turbine 60.
The system 50 may also include a controller 62 coupled to the turbine 60. The controller 62 receives information from the turbine 60 and, based on that information, may vary the operation of the turbine 60. Accordingly, the communication between the controller 62 and the turbine 60 may be bidirectional as indicated by communication pathway 64.
The controller 62 is coupled to an assessor 64. In one embodiment, the assessor 64 receives information from the controller 62 and additional information 66 from additional information sources (not shown) to produce one or both of a lifetime prediction 68 and an inspection recommendation 70.
The additional information 66 may include, but is not limited to, on-site monitoring information. In one embodiment, the on-site monitoring information is related to the compressor 52. This on-site monitoring information may include, but is not limited to, hours of operation, inlet conditioning, fogger information, part load operation, water wash information, inlet air quality and other sensor information. The additional information 66 could also include information related to a cost of one or more possible inspections and the cost (either actual or estimated) of a particular event, such as but not limited to, a failure or unplanned outage (hereinafter “event”).
The assessor 64 may be implemented in hardware, software, or some combination thereof (firmware). The assessor 64 receives the information from the controller 62 and the additional information 66. The additional information 66 is discussed in greater detail below.
As an intermediary step, the assessor may produce a risk of event, damage indicator or an alarm for the turbine 60 based on the received information. These intermediary values may be utilized to determine if the cost of inspection or cost of part replacement outweighs the cost of an outage to create an inspection or replacement recommendation 70. In the event that the cost of inspection or cost of part replacement outweighs the cost of an outage times the likelihood of an outage, the inspection recommendation may be to not perform an inspection. In the event that the cost of inspection or cost of part replacement is less than the cost of an outage times the likelihood of an outage, the inspection recommendation may be to perform an inspection. Also, the assessor 64 may produce a lifetime prediction 68 from the information it has received. For example, in some instances, the model parameters 314 may indicate that the unit (or particular portion) is nearing the end of its projected lifecycle. In such a case, the assessor 64 may determine that the lifetime remaining is a percentage of the total projected lifecycle.
Referring to
Thus, as configured in
It will be appreciated that the system 100 can be any suitable computer or computing platform, and may include a terminal, wireless device, information appliance, device, workstation, mini-computer, mainframe computer, personal digital assistant (PDA) or other computing device. It shall be understood that the system 100 may include multiple computing devices linked together by a communication network. For example, there may exist a client-server relationship between two systems and processing may be split between the two.
Any computer operating system may be utilized by the system 100 The system 100 also includes a network interface 106 for communicating over a network 116. The network 116 can be a local-area network (LAN), a metro-area network (MAN), or wide-area network (WAN), such as the Internet or World Wide Web.
Users of the system 100 can connect to the network through any suitable network interface 116 connection, such as standard telephone lines, digital subscriber line, LAN or WAN links (e.g., T1, T3), broadband connections (Frame Relay, ATM), and wireless connections (e.g., 802.11(a), 802.11(b), 802.11(g)).
As disclosed herein, the system 100 may include machine-readable instructions stored on machine readable media (for example, the hard disk 104) to execute one or more methods disclosed herein. As discussed herein, the instructions may be referred to as “software” 120. The software 120 may be produced using software development tools as are known in the art. The software 120 may include various tools and features for providing user interaction capabilities as are known in the art.
In some embodiments, the software 120 is provided as an overlay to another program. For example, the software 120 may be provided as an “add-in” to an application (or operating system). Note that the term “add-in” generally refers to supplemental program code as is known in the art. In such embodiments, the software 120 may replace structures or objects of the application or operating system with which it cooperates.
In one embodiment, the assessor module 64 may include a health assessment module 302. The health assessment module 302 may receive inputs from one or more information sources and create an intermediary output 304. Generally, the intermediary output 304 may include one or more values including, but not limited to, a risk of event, a probability of future damage and one or more alarms.
The assessor module 64 may be coupled to and receive information from the controller 62. The controller 62 receives information from, for example, a turbine and, based on that information, may vary the operation of the turbine. The controller 62 provides at least some of the information about the operation of the turbine (in particular, the compressor) to the health assessment module. This information may include, but is not limited to, various set points, limits, accumulator values, and the like. The controller 62, in one embodiment, may receive a risk level from the intermediary output 304 that causes one or more of the received (or other) operational values to be changed by the controller 62.
The assessor module 64 may be coupled to and receive information from one or more on-site monitors 304. These monitors may provide values indicative of hours of operation, the number of starts for the turbine, inlet conditioning, fogger/chiller/evaporator/sprits, part load operation, water wash, inlet air quality, and other sensor inputs.
The assessor module 64 may also receive weather/ambient temperature information 308. This information may be from sensors at the turbine or from other sources, such as, for example, a weather reporting service or a web-page. Regardless, this information may affect any type of analysis because, as is known, weather conditions such as humidity, temperature, and the like may have effects on the operation and lifetime of a turbine.
As discussed above, the system 300 may be coupled to several turbines or locations. Indeed, some locations may include multiple turbines. To that end, for one or more of the turbines, the heath assessment module 302 may receive site location and geographical inputs 310, hardware configuration 312, and model parameters for a fleet 314. The hardware configuration 312 may indicate, in one embodiment, the particular type of turbine and components coupled together including the particular compressor. The model parameters 314 may be historical information recorded from units, such as units that failed or did not fail and the inspection schedule applied in those cases. As discussed below, the model parameters 314 may be altered over time based on the operation of the system disclosed herein.
The intermediary values 304 may include output connections to the controller 62. For example, the alarm condition or risk of event may be utilized by the controller 62 to vary operation of the turbine and the compressor in particular.
The intermediary values 304 may also include an output to a performance analyzer 316. The performance analyzer 316 takes the intermediary values 304 and, in combination with cost information 318, determines one or both of a lifetime prediction 68 or an inspection recommendation. The cost information 318 may be the cost of one or more possible inspections and the cost (either actual or estimated) of a particular unplanned outage. An outage may be a partial outage, or a part-repair outage or a part-replacement outage.
For example, in the event that the cost of inspection as received from cost information 318 outweighs the cost of an outage times the likelihood of an outage (e.g. the risk as represented in the intermediary values 304) the inspection recommendation 70 may be to not perform an inspection. In the event that the cost of inspection is less than the cost of an outage times the likelihood of an outage, the inspection recommendation 70 may be to perform an inspection. Also, the performance analyzer 316 may produce a lifetime prediction 68 from the information it has received.
Both the intermediary values 304 and one or more of the outputs produced by the performance analyzer 316 may be provided to a model updater 320. The model updater 320 may include one or more updating algorithms that based on the intermediary values 304, the performance analyzer 316 outputs and data in an inspection database 322 may update the model parameters 314. In this manner, the model parameters 314 may be updated dynamically to more accurately represent the system as its operational parameters vary over time.
At a block 402, information or data related to the operation of a particular unit is received. This data may include, but is not limited to, chloride ion wet deposition levels, blade fired hours, blade fired starts, number of hours per start, temperature, relative humidity, and operating hours of inlet air cooling system (e.g evaporator coolers, foggers, sprits, chillers, and on-line and off-line water wash frequency and hours).
At a block 404, prior health related data for unhealthy units and healthy units is received. This information may be stored, for example, in the inspection database 322 and provided as model parameters 314 (
At a block 406, the distance between the current values and the prior unhealthy information is determined. In one embodiment, such a determination may include performing the following calculations:
unhealthy distance (D1)=(X−X0)′*inv(S0)*(X−X0);
where X is the current information, and X0 is the mean and S0 is the covariance matrix related to unhealthy information.
At a block 408, the distance between the current values and the prior healthy information is determined. In one embodiment, such a determination may include performing the following calculations:
healthy distance (D2)=(X−X1)′*inv(S1)*(X−X1);
where X is the current information, and X1 is the mean and S1 is the covariance matrix relate to healthy information.
Based on the relative distances calculated at blocks 406 and 408, at a block 410 a risk of event value may be calculated. This value represents the likelihood of event of the unit and is based on the operating conditions actually experienced by the unit. In one embodiment, the risk of event may be created by a comparison of the distances calculated above. Of course, other statistical techniques could be employed.
In one embodiment, the method may include an information fusion block 411. At block 411 the risk information may be fused with other information utilizing, for example, rule based systems. The fusion may include fusing various statistical (Weilbull, proportional hazard, discriminant analysis and the like), semi-empirical and physics based models. Of course, these information sources could be fused utilizing other information fusion algorithms such as Dempster-Shafer, Bayesian fusion, or fuzzy logic.
At a block 412 cost information is received. The cost information may be the cost of one or more possible inspections and the cost (either actual or estimated) of a particular unplanned outage. An outage may be a partial outage, or a part-repair outage or a part-replacement outage.
At a block 414 an inspection recommendation is created and output. For example, in the event that the cost of inspection outweighs the cost of an outage times the likelihood of an outage (e.g. the risk as represented in the intermediary values 304) the inspection recommendation may be to not perform an inspection. In the event that the cost of inspection is less than the cost of an outage times the likelihood of an outage, the inspection recommendation may be to perform an inspection.
While the invention has been described in detail in connection with only a limited number of embodiments, it should be readily understood that the invention is not limited to such disclosed embodiments. Rather, the invention can be modified to incorporate any number of variations, alterations, substitutions or equivalent arrangements not heretofore described, but which are commensurate with the spirit and scope of the invention. Additionally, while various embodiments of the invention have been described, it is to be understood that aspects of the invention may include only some of the described embodiments. Accordingly, the invention is not to be seen as limited by the foregoing description, but is only limited by the scope of the appended claims.
