Power generation fleet and power distribution fleet monitoring method and device

Abstract

The present invention refers to a method to monitor a fleet (54) of power generation assets (51, 52, 53) or power distribution assets (55, 56, 57). Herein, making best use of the data available and providing outputs being possible to generated based on the selected data and tailored to address the needs of a person being tasked with such monitoring allows to solve the problems available for such tasks that will be available in the future making best use of synergistic effects and challenges that are identified during the development. Furthermore, the present invention refers to a computer program product or a storage device containing such computer program product to realise such method. Additionally, the present invention refers to the device executing such method.

Description

[0001] Description

[0002] Power generation f leet and power distribution fleet monitoring method and device

[0003] The present method refers to a method of monitoring a fleet of power generation assets and / or a fleet of power distribution assets . Furthermore , the present invention refers to a computer program product including instructions operable to cause a computing entity to execute an inventive method . Additionally, the present invention refers to a storage device for providing an inventive computer program product . Furthermore , the present invention refers to a monitoring device adapted to realize the inventive method .

[0004] Power generation and power distribution are integral parts of modern life . Modern society would not being able to avoid or replace systems and devices in place and is being challenged with continuous demands to further improve the systems . In fact , power generation and power distribution does not become les s important but more and more important . For example , the change from fos sil energy to renewable energy repre sent s a significant challenge in thi s context . Increas ing the burden on , for example , existing power generation and power di stribution facilities . Like being required to compensate for fluctuations within the renewable energy generation to maintain the stability of the power grid . Or distributing f luctuating located power generation within certain areas in a continuous and reliable way . Furthermore , changes like switching from gas or oil ba sed heatings to heat pumps requires not only change s in the hardware of the re spective buildings , but also a far more flexible solutions addres sing the needs this context on the power generation and distribution side .

[0005] For example , it wa s always the challenge to provide monitoring respective solutions especially required being extremely reliable to ensure that the power grid representing a lifeline of modern society is running smoothly . However , ta king into account changes as mentioned above it becomes more and more challenging to keep track for an expert. Now typically not only being tasked with monitoring only a single or a low number of big assets, but being tasked with monitoring a constantly increasing number of assets. The system changing from a localized system utilizing big assets to the distributed system containing a plurality of assets, wherein the assets can also be significantly different and deviating from assets the expert can rely on his or her personal experience. Thus, there is a need to provide solutions to support an expert being challenged with such task to ensure safe and smooth operation of the corresponding assets. Especially, there is a need to support such expert being required to keep track what power generation assets or power distribution assets might, for example be subject to preemptive maintenance or in which cases such maintenance can be postponed taking into account higher priority needs. Or, for example in which cases an additional inspection might be beneficial to ensure the safe operation of such asset. While not simply being required to keep track of such single assets, but being challenged with monitoring the whole fleet.

[0006] This and further problems are solved by the products and methods as disclosed hereafter and in the claims. Further beneficial embodiments are disclosed in the dependent claims and the further description and figures. These benefits can be used to adapt the corresponding solution to specific needs or to solve additional problems .

[0007] According to one aspect the present invention refers to a method of monitoring a fleet of power generation assets and / or a fleet of power distribution assets, fleet of power generation assets and / or a fleet of power distribution assets, wherein the method contains the steps of

[0008] - retrieving condition data containing sensor data and / or manual data,

[0009] - retrieving predefined schedule data regarding a maintenance schedule and / or inspection schedule, - retrieving failure data regarding a failure analysis from a failure database,

[0010] - processing the condition data and the failure data utilizing a first calculation engine, wherein the first calculation engine generates a failure analysis data taking into account the failure data and the predefined schedule data, wherein the failure analysis data contains data with regard to a failure mode of at least a part of the power generation assets and / or at least a part of the power distribution assets, wherein the failure analysis data preferably contains evaluation data with regard to the probability and / or criticality, more preferred with regard to the probability and the criticality of a failure, of at least a part of the power generation assets and / or power distribution assets, more preferred wherein the evaluation data provides at least one summarized evaluation of a plurality of the power generation assets and / or power distribution assets, wherein the failure analysis data is forwarded to a first user interface and / or a first output database like a distributed database, wherein the method contains a step of retrieving predefined recommendation data containing recommended tasks related to the fleet of power generation assets and / or power distribution assets, wherein the method contains the step of processing the predefined recommendation data, the condition data and the failure data utilizing a second calculation engine, wherein the second calculation engine utilizes an artificial intelligence to generate a recommendation data, wherein the recommendation data preferably contains a recommended workorder, wherein the recommendation data contains data regarding a recommended task regarding servicing, inspecting and / or operation, preferably servicing and / or inspecting, of at least one of the power generation assets and / or power distribution assets , wherein the recommendation data is forwarded to a second user interface and / or second output database like a distributed database , wherein the f irst user interface and the second user interface can be the same user interface , wherein the f irst output database and the second output databa se can be the same database , wherein the f irst calculation engine and the second calculation engine can be the same calculation engine .

[0011] The invention as described above provides a significant beneficial solution of real-life application cases as it is able to not only solve several problems an operator or someone tas ked with monitoring the power generation as sets or power distribution as set s is challenged with . Surpri singly, it become s pos sible to combine multiple required solutions working together to overall increase the eff iciency and reliability of managing such power generation as sets or power distribution as sets . Especially, making use of the data provided by such calculation engine to optimize the servicing or operation of such power generation as sets or power distribution as sets is a surpri singly eff icient method to manage a plurality of such a s sets allowing to make better use of existing experts being more and more conf ronted with the tas k to keep track of an increa sed number of as sets . As it was noted that the existing power generation fleets and even the power distribution facilities and devices are developing from central locations to a distributed layout the requirements of the already burdened experts keep increasing . While there is a predictable lack of expert s to solve such challenge already noted to develop .

[0012] The term "calculation engine" as used herein refers to a computer program product or a device containing a computer program product being adapted to proces s the data as specified to create outputs and / or trigger actions , preferably to create outputs . Such outputs that can be created by such calculation engine especially contain health indexe s of the power generation as sets or the power distribution as sets and workorders related to the power generation assets or the power distribution assets.

[0013] Herein, such calculation engine preferably contains a smart model of the asset. Such smart model, for example, includes thermal model, electrical model, and the like. For example, such smart model takes condition data and generates a health index and / or work order related to the power generation assets or the power distribution assets.

[0014] The term "failure database" as used herein refers to a database containing data with regard to failures and an effect of such failures .

[0015] The term "servicing" as used herein refers to service actions as commonly understood by the skilled person. Preferably, such action includes a physical interaction with a respective asset especially including maintenance and upgrading actions.

[0016] The term "inspecting" as used herein refers to an inspection as commonly understood by the skilled person. Especially, it refers to reviewing, measuring and testing an asset without maintenance or upgrading actions .

[0017] The term "predefined schedule data" as used herein refers predefined data regarding a maintenance schedule and / or inspection schedule. Like a maintenance schedule and / or inspection schedule as provided by an asset manufacturer like a power distribution asset manufacturer. Herein, said predefined schedule data was created without knowledge of the current condition of the power generation assets or power distribution assets as utilized in the inventive method.

[0018] The term "predefined recommendation data" as used herein refers to recommended tasks as planned or suggested. Herein, the current condition of the power generation assets and / or power distribution assets was not known at this point the predefined recommendation data was created. Like a task list as provided by an asset manufacturer like a power distribution asset manufacturer.

[0019] As the predefined schedule data and the predefined recommendation data are different types of data. Predefined recommendation data relates to recommended tasks based on a condition. Such condition being measured by sensors or / and related to a manual data entry. On the contrary predefined schedule data relates to predefined data regarding a maintenance schedule and / or inspection schedule in relation to time. They are typically preferred to be stored in separate databases. However, it is naturally possible to artificially store the respective data in a single database and merge the data accordingly. In such case the predefined schedule database and the predefined recommendation database are a single database containing predefined schedule data and the predefined recommendation data.

[0020] The term "manual data" as used herein refers to, for example, manually selected sensor data, manually entered inspection data, manually entered observations. Such manual sensor data can be, for example, sensor data from sensors not being directly connected to a system executing the inventive method. Requiring said data to be actively provided to the respective databases. Like being sent to a mailbox automatically processing and storing the respective data in such database. Or the respective sensor data is entered manually in a user interface to be stored in the respective database. The same applies for manually entered inspection data or manually entered observations .

[0021] The term "failure analysis data" as used herein refers to data regarding a potential failure mode, like a failure mode having an increased or high risk at the specific time, taking into account the predefined schedule data of at least one of the power generation assets or power distribution assets. For example, such failure analysis data can be or contain some code associated to a failure mode contained in the failure database or might directly be some failure mode data contained in the failure databa se .

[0022] The present invention allows to centralize the monitoring or deci sion making actively supporting an expert with the tas k to keep track and react reasonable while simply lacking more and more the time to review the specific cases in detail . Making use of the described solution allows to provide a comprehensive overview and provision of recommendations ba sed on the data available for such power generation a s sets or power distribution as set s enabling to utilize such calculation engine to provide data enabling the method for such application to run smoothly and reliably .

[0023] According to a further aspect the present invention refers to a computer program product , tangibly embodied in a machine- readable storage medium, including instructions operable to cause a computing entity to execute an inventive method .

[0024] According to a further aspect the present invention refers to the storage device for providing an inventive computer program product , wherein the device stores the computer program product and / or provides the computer program product for further use .

[0025] According to a further aspect the present invention refers to a monitoring device containing at least one proces sor and at least one data storage , wherein the at least one data storage contains an inventive computer program product , wherein the at lea st one proces sor i s adapted to execute an inventive method .

[0026] To s implify understanding of the pre sent invention it i s referred to the detailed description hereafter and the figures attached as well a s their de scription . Herein , the figures are to be understood being not limiting the scope of the present invention as they are merely di sclos ing preferred embodiments explaining the invention further . Fig. 1 shows a scheme of an inventive system being adapted to utilize the inventive method.

[0027] Fig. 2 shows a scheme of an alternative inventive system being adapted to utilize the inventive method.

[0028] Preferably, the embodiments hereafter contain, unless specified otherwise, at least one processor and / or data storage unit to implement the inventive method.

[0029] Unless specified otherwise terms like „calculate", "process", "determine", "generate", "configure", "reconstruct" and comparable terms refer to actions and / or processes and / or steps modifying data and / or creating data and / or converting data, wherein the data are presented as physical variable or are available as such.

[0030] The term „data storage" or comparable terms as used herein, for example, refer to a temporary data storage like RAM (Random Access Memory) or long-term data storage like hard drives or data storage units like CDs, DVDs, USB sticks and the like. Such data storage can additionally include or be connected to a processing unit to allow a processing of the data stored on the data storage.

[0031] Examples of power generation assets are continuous flow engines like gas turbines. It was noted that the application of the inventive method for such power generation assets is especially beneficial. Corresponding continuous flow engines are, for example, typically utilized as base power providing units in a power generation and distribution network additionally having to handle the fluctuations resulting from the inhomogeneous power generation resulting from renewable energy. While such continuous flow engine represents an especially beneficial application case for the inventive method the should not be deemed to be limited with regard to power generation assets. Power distribution assets are, for example, transformers, switchgears, capacitors, inductors. For example, substations contain such power distribution assets.

[0032] According to one aspect the present invention refers to a method as described above.

[0033] Utilizing simulation data was noted to further improve the benefits obtained easily outbalancing the additional effort and processing power required in this context. Such simulation data can be beneficially utilized by the first calculation engine and / or the second calculation engine, preferably by the second calculation engine, when these calculation engines generate the failure analysis data or the recommendation data. According to further embodiments it is preferred that the method contains wherein the method contains the steps of

[0034] - retrieving condition data containing sensor data and / or manual data,

[0035] - retrieving predefined schedule data regarding a maintenance schedule and / or inspection schedule,

[0036] - retrieving failure data regarding a failure analysis from a failure database,

[0037] - optionally retrieving simulation data from a model of the power generation assets and / or the power distribution assets

[0038] - processing the condition data and the failure data utilizing a first calculation engine (1, 31) , wherein the first calculation engine generates a failure analysis data taking into account the failure data, the condition data, wherein the failure analysis data contains data with regard to a failure mode of at least a part of the power generation assets and / or at least a part of the power distribution assets, wherein the failure analysis data preferably contains evaluation data with regard to the probability and / or criticality, preferably with regard to the probability and the criticality of a failure, of at least a part of the power generation as- sets and / or power distribution assets, more preferred wherein the evaluation data provides at least one summarized evaluation of a plurality of the power generation assets and / or power distribution assets, wherein the failure analysis data is forwarded to a first user interface and / or a first output database like a distributed database, wherein the method contains a step of retrieving predefined recommendation data containing recommended tasks related to the fleet of power generation assets and / or power distribution assets, wherein the method contains the step of processing the predefined recommendation data, the condition data, the failure data and the simulation data utilizing a second calculation engine , wherein the second calculation engine utilizes an artificial intelligence to generate a recommendation data, wherein the recommendation data preferably contains a recommended workorder, wherein the recommendation data contains data regarding a recommended task regarding servicing, inspecting and / or operation, preferably servicing and / or inspecting, of at least one of the power generation assets and / or power distribution assets , wherein the recommendation data is forwarded to a second user interface and / or second output database like a distributed database , wherein the first user interface and the second user interface can be the same user interface, wherein the first output database and the second output database can be the same database, wherein the first calculation engine and the second calculation engine

[0039] It was further noted that the data can be utilized to generate condition based workorder. According to further embodiments it is preferred that the recommendation data is utilized to generate a condition based workorder. The term "workorder" as used herein refers to a task or a list of tasks arranged in a timely relation or with a specified time to be executed. For example, such workorder can a list of tasks like inspections of the power generation assets and / or power distribution assets to be executed in the timely order as specified by the workorder. Typically, it is preferred that such workorder additionally includes data like detection date, last update, state, consequence priority number, last state active, failure mode, failure mechanism, failure effect, recommended tasks and safety instructions. For example, it is preferred for typical embodiments that the workorder contains failure mode, recommended tasks and safety instructions .

[0040] Such condition based workorder represents a workorder based on the failures analysis data. Surprisingly, it was noted that creating such workorder allows to significantly optimize the operation of even extensive numbers of power generation and power distribution assets as potential problems can be addressed in a very flexible manner focusing on really required actions. Taking into account the growing number of assets to be monitored based on the recently observed development from single units or small number of units to be monitored to fleets of small assets combined with a decreasing number of experts available the solution as described herein provides a surprisingly significant benefit when being confronted with the task to optimize the management and operation of such assets.

[0041] Furthermore, it was noted that the inventive method can further be optimized by utilizing manufacturer data. According to further embodiments of this preferred that the method contains the step of retrieving a manufacturer workorder from a predefined recommendation database containing manufacturer workorder like yearly maintenance data, wherein the predefined recommendation database can be a local database or a distributed database, wherein the method contains the step of retrieving manufacturer scheduled workorder from a predefined schedule database containing manufacturer scheduled workorder li ke yearly maintenance data , wherein the predef ined schedule database can be a local database or a distributed databa se , wherein the manufacturer scheduled workorder i s utilized by the second calculation engine utiliz ing an artificial intelligence to create a servicing output and / or an inspection output , wherein the recommended workorder is automatically utilized to modify the servicing output and / or the inspection output . Utilizing such solution allows to optimize the regular maintenance and inspection planning . Enabling to adapt such required actions according to the specific needs and, for example , avoid additional maintenance and inspection actions by rearranging the regular scheduled actions .

[0042] According to further embodiments it is preferred that the method contains the step of retrieving manufacturer recommended workorder f rom a predefined recommendation database containing a manufacturer workorder like yearly maintenance data , wherein the predef ined recommendation database can be a local database or a distributed databa se , wherein the manufacturer workorder i s utilized to create a servicing output and / or an inspection output , wherein the recommended workorder is used together with the servicing output and / or the inspection output to automatically create a workorder , wherein the workorder contains a schedule of the maintenance tas ks and / or a schedule of the inspection tas ks . It was noted that based on the specific application providing , for example , a very long time application and usage it is benef icial to take into account such change s occurring over months , years and even decades and s imulate a corresponding change of the behavior like acquired sensor data within the f leet of power generation a s sets and / or power distribution a s set s . Otherwise the accumulation of small changes during maintenance or upgrades typically slowly tend to change the characteristics of the fleet of power generation assets and / or power distribution assets over time and in the end render it difficult to make use of existing historic data and the like as the boundaries of the system like limit values and the like change over time. Which was noted to potentially provide single incorrect failure analysis in the beginning before the overall assessment can even become critical, as it is not sure anymore what historic data can be utilized.

[0043] Furthermore, it was noted that utilizing an artificial intelligence in the first calculation engine is typically preferred to further improve the processing. According to further embodiments the first calculation engine contains an artificial intelligence, wherein the artificial intelligence of the first calculation engine is adapted to generate the failure analysis data. It was noted that training and utilizing an artificial intelligence for this is a very effective and beneficial way to further increase the efficiency of the data processing .

[0044] It was noted that for real-life applications it is even preferred to include a work order assistance system. According to further embodiments of this preferred that the method contains the step of retrieving manufacturer workorder from a predefined recommendation database containing manufacturer workorder like yearly maintenance data, wherein the predefined recommendation database can be a local database or a distributed database, wherein the manufacturer workorder is utilized to create a servicing output and / or an inspection output, wherein the recommended workorder is used together with the servicing output and / or the inspection output to automatically create a workorder, wherein the workorder contains a schedule of the maintenance tasks and / or a schedule of the inspection tasks. It was noted that utilizing the inventive method it is possible to auto- matically create such schedule of tasks in any desired order and especially continuously update such last based on the condition of the assets. For example, the workorder can be provided with dates and / or times to provide an optimized maintenance and service action. For example, it is very beneficial to aggregated maintenance and / or service actions for specified periods. Herein, the regularly scheduled maintenance or service actions can be used as fixed dates and all actions required until the subsequent maintenance and service action are aggregated and provided as output.

[0045] Also, it is possible and typically very beneficial to include a functionality including to request upcoming maintenance and service actions on demand. For example, in case an irregular maintenance or service action is required additional possible actions can be automatically provided to, for example, directly include additional actions and, for example, skip a subsequent regular scheduled maintenance or service action. Additionally or alternatively, it is beneficial to make use of the possibility to retrieve localized information. Herein, a workorder of available maintenance and / or service actions for a plurality of assets within a specified area is automatically created. For example, it is specified that all relevant tasks are to be provided for all assets or a specified type of asset at a specified location or within a specified range from, for example, a specified asset. Herein, automatically a workorder is created specifying all tasks within a certain reach. Based on the possibility to automatically provide such data with the inventive method is becomes possible to even on short term optimize service and maintenance actions and bundle certain tasks and make best use of still available time in case a different maintenance or service tasks takes less time than expected.

[0046] Furthermore, it was noticed that the inventive methods are especially beneficial and to be utilized for power distribution assets. According to further embodiments of this preferred that a fleet of power distribution assets is moni- tored, preferably a fleet of high-voltage power distribution assets is monitored. The constant monitoring of power generation assets as described herein is already very beneficial to support an expert being required to monitor such fleet. However, it was noted that especially monitoring a fleet of power distribution assets benefits significantly and even more than the monitoring of the fleet of power generation assets by the inventive method. While it should not be expected starts means as used in this context for power generation assets might also be utilized at all in such different field it was noted that the recent changes also demand from power distribution assets to include the flexibility and optimized maintenance not required before. In fact, it becomes more and more necessary to constantly monitor devices not even monitored before. Generating on the spot a significant amount of additional work that needs to be handled by available experts. Herein, the inventive method is especially beneficial and allows to tremendously reduce the time, efforts as well as expertise of an expert being confronted with such challenge. Especially, as such expert was not tasked with such challenge before.

[0047] For example, such high voltage power distribution assets are part of a single substation as available at a power plant or at a city or at least two, more preferred at least four, even more preferred a plurality of substations located at different locations. Like providing a distance of at least 10km from each other. It was noted that the inventive solution is especially beneficial to monitor a fleet of power generation assets or power distribution assets being distanced from each other like being distanced at least 10km, more preferred at least 50km. Bringing the data together and enabling to monitor a plurality of assets as described herein allows to highly efficiently and reliably even handle such application case, wherein an expert being confronted with such task typically easily has problems to solve such demanding problem. According to further preferred embodiment s the power di stribution as sets contain a plurality of high voltage trans formers . It was noted that the inventive method is very suitable to monitor a plurality of such power distribution a s set s . As already mentioned above applying the inventive method to power distribution as sets is surpri singly beneficial a s the increa sed insight and supportive monitoring capabilities of the inventive methods allow to highly ef ficiently improve the monitoring of an expert challenged with continuously increas ing amounts of as sets to be monitored .

[0048] While it is pos sible and for many applications beneficial to locate such calculation engines as utilized in the present invention on a local monitoring device it is not only pos sible but can even be beneficial to utilize a cloud to store and run the calculation engines . According to further embodiment s it is preferred that the f irst calculation engine and / or the second calculation engine are located in a cloud or remotely located database , preferably wherein the first and the second calculation engine are located in a cloud or remotely located databa se . It wa s noted that despite expected problems of acces s ibility especially to be expected for the intended purpose of enabling an expert to make on the spot analysis locating the calculation engines on a cloud or remote database , preferably a cloud, was surpris ingly beneficial . For example , providing an increased pos s ibility to optimi ze such calculation engine and instantly switch to different calculation engines utili zed for different facilities to check whether different calculation engines might be preferred . For example , the pos sibility to easily manage a plurality of calculation engine s in a cloud enables new means to further optimize the method easily compensating for , for example , available misfit s like the increased dependency from a required connection to such cloud impairing the availability and the like of such embodiment .

[0049] According to further embodiments it is preferred that the first calculation engine and / or the second calculation engine are located in a cloud, preferably that the first calculation engine and the second calculation engine are located in a cloud . It was noted that especially the in case of grid systems cons isting of small single unit s and their management such cloud-ba sed solution can be beneficial .

[0050] Additionally, it was noted that the inventive method allows to , for example , optimi ze an on- site working routine . According to further embodiments of this preferred that the method contains the step of receiving a request input from a third user interface , wherein the third user interface , preferably wherein the third user interface is a mobile device like a PDA or a smartphone , wherein the request input contains data regarding a localization of an expert and / or available working time of an expert and / or a selection of the power generation as sets and / or a selection of the power distribution as set s , wherein the method contains the step of automatically creating an additional tas k output , wherein the additional tas k output contains at least one tas k related to the power generation as sets and / or the power distribution as sets taking into account the reque st input . Utilizing the inventive method allows to even on short term identify opportunities to ma ke best use of available experts tas ked with maintenance or service actions . For example , a current or planned localization of an expert visiting several site s or being on a specific and finishing his tas ks earlier than expected can be utilized to automatically provide an output containing pos sibilities of beneficially addres sed matters . Like an upcoming maintenance action that can be directly executed or an inspection of an as set of multiple assets showing an irregular behavior . Typically, it i s especially beneficial to combine data regarding a localization of an expert and / or available working time of an expert with a selection of the power generation as sets and / or a selection of the power distribution as sets . In many case s a specific expert is either not able to execute all actions for all assets or might simply be lacking the corre sponding material it is especially useful to further make use of a specification of the relevant assets. Allowing to provide a tailored list of possible tasks that do not need to manually be reviewed.

[0051] Additionally, it was noted that it is typically not required to utilize different self-care calculation engines. According to further embodiments of this preferred that the first calculation engine and the second calculation engine are the same calculation engine. Surprisingly, it was noted that the specific application case as described herein allows to make use of the same calculation engine for the providing of both outputs. While the commercial benefit to simplify the system to a single calculation engine is less relevant based on the effort and money invested in such power generation assets or power distribution assets it becomes very interesting to simplify upgrade solutions . Additionally, it was especially noted that enabling to make use of the same calculation engine for both tasks allow to easily switch the tasks from one calculation engine to another in case some irregularity of such calculation engine is noted. Or in case one server is damaged it is possible to at least temporarily switch to a second calculation engine .

[0052] According to further preferred embodiments it is preferred that the power generation assets contain a plurality of continuous flow engines, more preferred a plurality of gas turbines. As already mentioned above it was noted that such power generation assets are especial beneficially monitored utilizing an inventive method as described herein.

[0053] For typical application cases it is furthermore often beneficial to include a special handling for problem assets identified using the inventive method. According to further embodiments it is preferred that the failure analysis data is utilized to identify at least one problem asset of the power generation assets or power distribution assets being especially endangered based on a high risk of failure and / or a high criticality in case of failure, wherein the method contains a step of automatically generating an higher repetition of checks of the at least one problem asset, for example, by adding the at least problem asset on a problem asset list until the at least one problem asset is serviced and / or a manually order to remove such labelling as problem asset is received. It was noted that such automatic procedure to identify and label power generation assets or power distribution assets in such way allows to easily keep track of negative developments and inform an operator very early of possible developments. While it still is possible, for example, based on personal experience to remove such label from specific assets. For example, in case a temporary maintenance or detailed check was executed allowing to ensure that such risk assessment is not valid anymore.

[0054] Also, it is typically beneficial to include a check whether recommended actions were executed. According to further embodiments it is preferred that the method contains the step of storing the recommended workorder, wherein the method contains the step of automatically verifying whether the recommended task regarding maintenance and / or inspection of at least one of the power generation assets and / or power distribution assets has been realized. Surprisingly, such apparently simple cross check is highly beneficial for the application case as described. As the time periods between service actions is rather long and the often distanced location of the power generation assets or power distribution assets does not allow to swiftly check whether a corresponding action has been executed it is highly beneficial for real cases to implement such check. For example, the power generation assets or power distribution assets can be provided with respective devices creating data like sensor data to verify whether an inspection or maintenance action as realized .

[0055] Depending on whether corresponding actions have been realized or not it can also be beneficial for typical application cases to include in our dramatic action being triggered. Accord- ing to further embodiments it is preferred that the method contains the step of automatically reevaluating the failure analysis data and / or recommended workorder based on an information whether the recommended task regarding maintenance and / or inspection of at least one of the power generation assets and / or power distribution assets has been realized, wherein in case reevaluating the failure analysis data and / or recommended workorder results in a risk of endangering at least one of the power generation assets and / or power distribution assets beyond a predefined threshold value an action is automatically triggered. Such action can be a signal to trigger an alarm. However, it can also be an order limiting the operation of the power generation assets and / or power distribution assets, wherein such limitation includes shutting down the power generation assets and / or power distribution assets. Alternatively of additionally it was noted to be very beneficial to adapt an overall workorder based on such information. Herein, the action includes to reevaluate and eventually adapt an existing workorder relating to maintenance or inspection of the power generation assets and / or power distribution assets in case the recommended task regarding maintenance and / or inspection of at least one of the power generation assets and / or power distribution assets has not been realized, wherein available possibilities to execute maintenance or inspection on different power generation assets and / or power distribution assets than the one the recommended task regarding maintenance and / or inspection was not executed are prioritized to ensure an operation of the plurality of power generation assets and / or power distribution assets. It was noted that in case certain maintenance and / or inspection tasks were not executed it is often difficult to ensure that a timely alternative date can be provided without undue effort. However, making use of possibilities to ensure the operation of different assets to compensate for a potential failure of the non-serviced asset surprisingly allows to overall ensure the operation of the plurality of the fleet of the assets as monitored by the inventive method. Typically, it is beneficial that the method additionally includes the step of retrieving interrelations data from an interrelations database, wherein the interrelations data contains data with regard to the connection between the plurality of assets, wherein the interrelations data is utilized to identify the power generation assets and / or power distribution assets being able to compensate for a failure of one of the power generation assets and / or power distribution assets the maintenance and / or inspection has not be carried out. For example, such interrelations data is based on functional data the power generation assets and / or power distribution assets are providing like a power transmission possibility or power generation possibility, data with regard to usual operation allowing to predict possibilities to increase the load for a respective time period, power line connections between power plants allowing to transmit additionally product electric power into a different part of the grid, locally available different transformers allowing to compensate for a nonserviced transformer to be taken off the grid, and the like.

[0056] According to a further aspect the present invention refers to a computer program product as described above.

[0057] According to further aspect of the present image refers to storage devices described above.

[0058] According to a further aspect the present invention refers to monitoring devices described above.

[0059] The following detailed description of the figure uses the figure to discuss illustrative embodiments, which are not to be construed as restrictive, along with the features and further advantages thereof.

[0060] Figure 1 shows a scheme of an inventive system being adapted to utilize the inventive method. Herein, a huge number of power distribution assets and power generation assets are monitored. To simplify the scheme said power distribution as- sets and power generation assets are not shown in this figure .

[0061] Herein, condition data from a condition database 3 containing sensor data 4 and manual data 5 is retrieved. Furthermore, predefined schedule data regarding a maintenance schedule and inspection schedule are retrieved from a predefined schedule database 14 as well as failure data regarding a failure analysis from a failure database 7. Said failure database contains asset information 9, 10 regarding the power generation assets and power distribution assets. The data as contained in the failure database 7 originated from the external failure database 8 being uploaded in the cloud 16. However, while the failure database 7 can subsequently run on its own the connection to the external failure database 8 is still maintained allowing to upload updates to the failure database 7.

[0062] The condition data and the failure data are processed utilizing a first calculation engine 1, wherein the first calculation engine 1 generates a failure analysis data 11 taking into account the failure data and the predefined schedule data. Said failure analysis data 11 contains data with regard to a failure mode of the specified assets. However, in case it is determined by the first calculation engine 1 that no relevant failure analysis data 11 is available for some part of the power generation assets or power generation assets the failure analysis data 11 can be limited to relevant assets. In such case the failure analysis data 11 only refers to at least a part of the power generation assets and at least a part of the power distribution assets or maybe even only to at least a part of the power generation assets or at least a part of the power distribution assets.

[0063] The failure analysis data 11 in this context contains evaluation data with regard to the probability and / or criticality of at least a part of the power generation assets and / or power distribution assets. The utilized system furthermore is able to group a plurality of power generation assets and power distribution assets and provide a summarized evaluation of such plurality of the power generation assets or power distribution assets accordingly. Furthermore, the system as shown in figure 1 contains the option for a user to specify such group and request a correspondingly summarized evaluation. The respective failure analysis data 11 is forwarded to a first user interface 12 and a first output database 13 being a distributed database in this case.

[0064] Additionally, the method contains the step of retrieving predefined recommendation data 26 containing recommended tasks related to the fleet of power generation assets and / or power distribution assets from a predefined recommendation database. Said predefined recommendation data 26, the condition data and the failure data are processed utilizing a second calculation engine 2. Herein, the second calculation engine 2 utilizes an artificial intelligence 23 to generate a recommendation data 46. Said the recommendation data 46 contains data regarding a recommended task regarding servicing, inspecting and / or operation of at least one of the power generation assets and power distribution assets. Being forwarded to a second user interface 24 and a second output database 25 the recommendation data 46 can be directly utilized by a user accessing the second user interface 24 as well as be later retrieved to be further processed. Like when analyzing the wear out state of a component of such power generation asset or power distribution asset during a maintenance. However, the data can be utilized in many ways and, for example, can also be advantageously be utilized before a planned maintenance action to get a better understanding of the state of the respective asset to plan, for example, the required spare parts and time to very likely being able to execute the maintenance. The first user interface 12 and the second user interface 24 can be the same user interface, the first output database 13 and the second output database 25 can be the same database, and the first calculation engine 1 and the second calculation engine 2 can be the same calculation engine in general. However, the specific embodiment as shown in figure 1 makes use of separated units in this context. Furthermore, the method as shown as example in figure 1 contains that a manufacturer scheduled workorder is retrieved from a predefined schedule database containing manufacturer scheduled workorder like yearly maintenance data of the power generation assets and power distribution assets. Herein, the predefined schedule database can is a local database. However, alternative inventive embodiments make use of such predefined schedule database being located in a distributed database. Said manufacturer scheduled workorder is utilized by the second calculation engine 2. Herein, an artificial intelligence 23 processes the workorder and creates a servicing output and an inspection output. Said artificial intelligence 23 in this context automatically makes use of the recommended workorder to modify the servicing output or the inspection output accordingly to improve said outputs. For example, said recommended workorder is utilized as basis and the order as well as available dates for respective servicing and inspection steps are optimized by the artificial intelligence 23 based on data available in the system as shown in figure 1. For example, utilizing sensor data 4 and simulation data 6 to critically review the inspection schedule of important assets . In case of data indicating a potential problem a respective inspection date will be placed at an earlier date or at a higher place in the respective order of assets to be inspected to gain earlier insight whether a potential problem is available. It was noted that such automatic system is especially beneficial for the power generation and power distribution assets. As the complex systems operating in a fleet generate far too much data to keep track of each and every one and simply taking action based on single observations might easily lead to neglecting other assets being less visible, but not even less important that the assets being focused on.

[0065] The method as shown in figure 1 contains the step of retrieving simulation data of a model of the power generation assets and the power distribution assets, wherein the first calculation engine 1 is utilized to process the condition data, the failure data, schedule data and the simulation data, wherein the first calculation engine 1 generates the failure analysis data 11 taking into account the condition data, the failure data and the simulation data. Herein, said failure analysis data 11 is also utilized to generate a condition based workorder.

[0066] Furthermore, the method contains that a manufacturer workorder is retrieved from a predefined recommendation database containing manufacturer recommended workorders like yearly maintenance data. Herein, the predefined recommendation data 26 base is a local database in the example shown. However, such database can also be located in a distributed database. Said manufacturer workorder is utilized to create a servicing output and an inspection output. However, in other inventive examples being not shown in figure 1 it can also be utilized to only create a servicing output or only an inspection output .

[0067] In the example shown in figure 1 the servicing output and inspection output are utilized to create a workorder. Said workorder contains a schedule of the maintenance tasks and a schedule of the inspection tasks to be executed by the ones responsible for the power distribution assets and power generation assets.

[0068] Utilizing the failure analysis data 11 it becomes possible to identify problem assets of the power generation assets and of the power distribution assets being especially endangered based on a high risk of failure or a high criticality in case of failure. Surprisingly, utilizing this data and, for example, reviewing said data over time it is possible to easily identify corresponding assets. Allowing to even act accordingly to prevent a failure with a very high security. For example, the method includes to automatically generate an higher repetition of checks of such problem assets, for example, by adding the at least problem asset on a problem asset list until the at least one problem asset is serviced or a manually order is received to remove such labelling as problem asset .

[0069] Further beneficial possibilities arising from the inventive method include storing the recommended workorder to enable an automatic verification whether the recommended task regarding maintenance or inspection of respective power generation assets or power distribution assets has been realized. Bringing together the data, utilizing it as described and making use of the respective data infrastructure required in this context easily allows to further include such additional action being identified to be highly interesting and beneficial for power generation assets and power distribution assets.

[0070] Additionally, the system as shown exemplarily in figure 1 contains that the failure analysis data 11 or recommended workorder are automatically reevaluated based on the information whether an recommended task regarding maintenance or inspection of respective power generation assets or power distribution assets has been realized. Herein, in case such reevaluation results in the assessment that a risk of endangering such power generation assets or power distribution assets beyond a predefined threshold value an action is automatically triggered. Including alerts being shown to responsible persons operating and servicing such asset. Including sending a summary to be reviewed by a central manager located far remote from such asset. And even including shutting down such asset in case the danger level is considered to be too high. Herein, it is typically preferred to include a cross check whether shutting down such specific asset might result in other assets being subject to higher risks. Like resulting from higher amounts of power to be transmitted through other power distribution assets located at the respective facility. Or higher power amounts to be generated by other power generation assets located in a respective power grid. Figure 2 shows a scheme of an alternative inventive system being adapted to utilize the inventive method. Herein, a huge number of power distribution assets 55, 56, 57 and power generation assets 51, 52, 53 are monitored. Some power generation assets 51, 52, 53 and some power distribution assets 55, 56, 57 are exemplarily indicated in the figure as part of the fleet of the power generation assets 51, 52, 53 54 and the fleet of the power distribution assets 55, 56, 57 58.

[0071] Comparable to figure 1 condition data is retrieved from a condition database 33 containing sensor data 34 and manual data 35. Predefined schedule data regarding a maintenance schedule and inspection schedule is retrieved from a predefined schedule database 49 as well as failure data regarding a failure analysis from a failure database 37. Said failure database contains asset information 39, 40 regarding the power generation assets 51, 52, 53 and power distribution assets 55, 56, 57. The data as contained in the failure database 37 originated from the external failure database 38 being uploaded in the cloud 36. However, while the failure database 37 can subsequently run on its own the connection to the external failure database 38 is still maintained allowing to upload updates to the failure database 37.

[0072] The condition data and the failure data are processed utilizing a first calculation engine 31, wherein the first calculation engine 31 generates a failure analysis data 41 taking into account the failure data and the predefined schedule data 49. Said failure analysis data 41 contains data regarding a failure mode of the specified assets. However, in case it is determined by the first calculation engine 31 that no relevant failure analysis data 41 is available for some part of the power generation assets 51, 52, 53 or power generation assets 51, 52, 53 the failure analysis data 41 can be limited to relevant assets. In such case the failure analysis data 41 only refers to some of the power generation assets 51, 52, 53 and some of the power distribution assets 55, 56, 57 or maybe even only to some of the power generation assets 51, 52, 53 or some of the power distribution assets 55, 56, 57.

[0073] The failure analysis data 41 in this context contains evaluation data with regard to the probability and / or criticality of at least a part of the power generation assets 51, 52, 53 and / or power distribution assets 55, 56, 57. The utilized system furthermore is able to group a plurality of power generation assets 51, 52, 53 and power distribution assets 55, 56, 57 and provide a summarized evaluation of such plurality of the power generation assets 51, 52, 53 or power distribution assets 55, 56, 57 accordingly. Furthermore, the system as shown in figure 2 also provides the option for a user to specify such group and request a correspondingly summarized evaluation. The respective failure analysis data 41 is forwarded to a first user interface 42 and a first output database 43 being a distributed database in this case.

[0074] Additionally, the method contains the step of retrieving predefined recommendation data 32 containing recommended tasks related to the fleet of power generation assets 51, 52, 53 and / or power distribution assets 55, 56, 57 from a predefined recommendation database. Contrary to figure 1 said predefined recommendation data 32, the condition data and the failure data are processed utilizing the first calculation engine 31 as the system as shown in figure 2 does not utilize a separated second calculation engine, but an extended type of first calculation engine 31 being adapted to also execute the tasks of the second calculation engine from figure 1. Herein, the first calculation engine 31 also contains and utilizes an artificial intelligence 44 to generate a recommendation data 46. Said the recommendation data 46 contains data regarding a recommended task regarding servicing, inspecting or operation of at least one of the power generation assets 51, 52, 53 and power distribution assets 55, 56, 57. Being forwarded to a second user interface 47, the first user interface 42 and the first output database 43. Herein, the recommendation data 46 can be directly utilized by a user accessing the first user interface 47. Simultaneously, the data can be used by a user utilizing the second user interface 47 to adapt a long term planning of the planned tasks and schedule workers and their time schedule accordingly. Additionally, the data can be later retrieved from the first output database 43 on demand.

[0075] Like when analyzing the wear out state of a component of such power generation asset or power distribution asset during a maintenance. However, the data can be utilized in many ways and, for example, can also be advantageously be utilized before a planned maintenance action to get a better understanding of the state of the respective asset to plan, for example, the required spare parts and time to very likely being able to execute the maintenance. The first user interface 42 and the second user interface 47 can be the same user interface. However, the specific embodiment as shown in figure 1 makes use of separated user interfaces in this context.

[0076] Furthermore, the method as shown as example in figure 1 contains that a manufacturer scheduled workorder is retrieved from a predefined schedule database containing manufacturer scheduled workorder like yearly maintenance data of the power generation assets 51, 52, 53 and power distribution assets 55, 56, 57. Herein, the predefined schedule database can is a remotely located database. Said manufacturer scheduled workorder is utilized by the first calculation engine 31. Herein, an artificial intelligence 44 processes the workorder and creates a servicing output and an inspection output. Said artificial intelligence 44 in this context automatically makes use of the recommended workorder to modify the servicing output or the inspection output accordingly to improve said outputs. For example, said recommended workorder is utilized as basis and the order as well as available dates for respective servicing and inspection steps are optimized by the artificial intelligence 44 based on data available in the system as shown in figure 1. For example, utilizing sensor data 34 to critically review the inspection schedule of important assets. In case of data indicating a potential problem a respective inspection date will be placed at an earlier date or at a higher place in the respective order of assets to be inspected to gain earlier insight whether a potential problem is available. It was noted that such automatic system is especially beneficial for the power generation and power distribution assets 55, 56, 57. As the complex systems operating in a fleet generate far too much data to keep track of each and every one and simply taking action based on single observations might easily lead to neglecting other assets being less visible, but not even less important that the assets being focused on.

[0077] Furthermore, the method contains that a manufacturer workorder is retrieved from a predefined recommendation data base. While it is not beneficial containing manufacturer recommended workorders like yearly maintenance data. Herein, the predefined recommendation database is a local database in the example shown. However, such database can also be located in a distributed database. Said manufacturer workorder is utilized to create a servicing output and an inspection output. However, in other inventive examples being not shown in figure 1 it can also be utilized to only create a servicing output or only an inspection output .

[0078] In the example shown in figure 1 the servicing output and inspection output are utilized to create a workorder. Said workorder contains a schedule of the maintenance tasks and a schedule of the inspection tasks to be executed by the ones responsible for the power distribution assets 55, 56, 57 and power generation assets 51, 52, 53.

[0079] Utilizing the failure analysis data 41 it becomes possible to identify problem assets of the power generation assets 51, 52, 53 and of the power distribution assets 55, 56, 57 being especially endangered based on a high risk of failure or a high criticality in case of failure. Surprisingly, utilizing this data and, for example, reviewing said data over time it is possible to easily identify corresponding assets. Allowing to even act accordingly to prevent a failure with a very high security. For example, the method includes to automatically generate an higher repetition of checks of such problem assets, for example, by adding the at least problem asset on a problem asset list until the at least one problem asset is serviced or a manually order is received to remove such labelling as problem asset.

[0080] Further beneficial possibilities arising from the inventive method include storing the recommended workorder to enable an automatic verification whether the recommended task regarding maintenance or inspection of respective power generation assets 51, 52, 53 or power distribution assets 55, 56, 57 has been realized. Bringing together the data, utilizing it as described and making use of the respective data infrastructure required in this context easily allows to further include such additional action being identified to be highly interesting and beneficial for power generation assets 51, 52, 53 and power distribution assets 55, 56, 57.

[0081] Additionally, the system as shown exemplarily in figure 1 contains that the failure analysis data 41 or recommended workorder are automatically reevaluated based on the information whether a recommended task regarding maintenance or inspection of respective power generation assets 51, 52, 53 or power distribution assets 55, 56, 57 has been realized. Herein, in case such reevaluation results in the assessment that a risk of endangering such power generation assets 51, 52, 53 or power distribution assets 55, 56, 57 beyond a predefined threshold value an action is automatically triggered. Including alerts being shown to responsible persons operating and servicing such asset. Including sending a summary to be reviewed by a central manager located far remote from such asset. And even including shutting down such asset in case the danger level is considered to be too high. Herein, it is typically preferred to include a cross check whether shutting down such specific asset might result in other assets being subject to higher risks. Like resulting from higher amounts of power to be transmitted through other power distribution assets 55, 56, 57 located at the respective facility. Or higher power amounts to be generated by other power generation assets 51, 52, 53 located in a respective power grid. The present invention was only described in further detail for explanatory purposes. However, the invention is not to be understood being limited to these embodiments as they represent embodiments providing benefits to solve specific problems or fulfilling specific needs. The scope of the protec- tion should be understood to be only limited by the claims attached .

Claims

Patent claims1. Method of monitoring a fleet (54) of power generation assets (51, 52, 53) and / or a fleet (58) of power distribution assets (55, 56, 57) , wherein the method contains the steps of- retrieving condition data containing sensor data (4, 34) and / or manual data (5, 35) ,- retrieving predefined schedule data (14, 49) regarding a maintenance schedule and / or inspection schedule,- retrieving failure data regarding a failure analysis from a failure database (7, 37) ,- processing the condition data and the failure data utilizing a first calculation engine (1, 31) , wherein the first calculation engine (1, 31) generates a failure analysis data (11, 41) taking into account the failure data and the predefined schedule data (14, 49) , wherein the failure analysis data (11, 41) contains data with regard to a failure mode of at least a part of the power generation assets (51, 52, 53) and / or at least a part of the power distribution assets (55, 56, 57) , wherein the failure analysis data (11, 41) preferably contains evaluation data with regard to the probability and / or criticality, more preferred with regard to the probability and the criticality of a failure, of at least a part of the power generation assets (51, 52, 53) and / or power distribution assets (55, 56, 57) , more preferred wherein the evaluation data provides at least one summarized evaluation of a plurality of the power generation assets (51, 52, 53) and / or power distribution assets (55, 56, 57) , wherein the failure analysis data (11, 41) is forwarded to a first user interface and / or a first output database (13, 43) like a distributed database, wherein the method contains a step of retrieving predefined recommendation data (26, 32) containing recommended tasks related to the fleet (54) of power generation assets (51, 52, 53) and / or power distribution assets (55, 56, 57) , wherein the method contains the step of processing the prede-fined recommendation data (26, 32) , the condition data and the failure data utilizing a second calculation engine (2) , wherein the second calculation engine utilizes an artificial intelligence (23, 44) to generate a recommendation data (22, 46) , wherein the recommendation data (22, 46) preferably contains a recommended workorder, wherein the recommendation data (22, 46) contains data regarding a recommended task regarding servicing, inspecting and / or operation, preferably servicing and / or inspecting, of at least one of the power generation assets (51, 52, 53) and / or power distribution assets (55, 56, 57) , wherein the recommendation data (22, 46) is forwarded to a second user interface and / or second output database (25) like a distributed database , wherein the first user interface and the second user interface can be the same user interface, wherein the first output database (13, 43) and the second output database (25) can be the same database, wherein the first calculation engine (1, 31) and the second calculation engine (2) can be the same calculation engine.

2. Method according to claim 1, wherein the method contains the step of retrieving simulation data (6) of a model of the power generation assets (51, 52, 53) and / or the power distribution assets (55, 56, 57) , wherein the second calculation engine (2) is utilized to process the predefined recommendation data (26, 32) , the condition data and the simulation data (6) , wherein the second calculation engine (2) generates the recommendation data (22, 46) taking into account the predefined recommendation data (26, 32) , the condition data and the simulation data (6) .

3. Method according to any of the aforementioned claims, wherein the recommendation (22, 46) data is utilized to generate a condition based workorder.

4. Method according to any of the aforementioned claims, wherein the method contains the step of retrieving a manufacturer scheduled workorder from a predefined scheduled database containing manufacturer scheduled workorder like yearly maintenance data, wherein the scheduled time series database can be a local database or a distributed database, wherein the manufacturer scheduled workorder is utilized by the second calculation engine (2) utilizing an artificial intelligence (23, 44) to create a servicing output and / or an inspection output, wherein the recommendation data (22, 46) is automatically utilized to modify the servicing output and / or the inspection output .

5. Method according to any of the aforementioned claims, wherein the method contains the step of retrieving manufacturer recommended workorder from a predefined recommendation database containing manufacturer workorder like yearly maintenance data, wherein the predefined recommendation database can be a local database or a distributed database, wherein the manufacturer workorder is utilized to create a servicing output and / or an inspection output, wherein the recommended workorder is used together with the servicing output and / or the inspection output to automatically create a workorder, wherein the workorder contains a schedule of the maintenance tasks and / or a schedule of the inspection tasks.

6. Method according to any of the aforementioned claims, wherein a fleet (54) of power distribution assets (55, 56, 57) is monitored .

7. Method according to any of the aforementioned claims, wherein the method contains the step of receiving a request input from a third user interface, wherein the third user in-terface, preferably wherein the third user interface is a mobile device like a PDA or a smartphone, wherein the request input contains data regarding a localization of an expert and / or available working time of an expert and / or a selection of the power generation assets (51, 52, 53) and / or a selection of the power distribution assets (55, 56, 57) , wherein the method contains the step of automatically creating an additional task output, wherein the additional task output contains at least one task related to the power generation assets (51, 52, 53) and / or the power distribution assets (55, 56, 57) taking into account the request input.

8. Method according to any of the aforementioned claims, wherein the first calculation engine (1, 31) and / or the second calculation engine (2) are located in a cloud (16, 36) .

9. Method according to any of the aforementioned claims, wherein the first calculation engine (1, 31) and the second calculation engine (2) are the same calculation engine.

10. Method according to any of the aforementioned claims, wherein the failure analysis data (11, 41) is utilized to identify at least one problem asset of the power generation assets (51, 52, 53) or power distribution assets (55, 56, 57) being especially endangered based on a high risk of failure and / or a high criticality in case of failure, wherein the method contains a step of automatically generating an higher repetition of checks of the at least one problem asset, for example, by adding the at least problem asset on a problem asset list until the at least one problem asset is serviced and / or a manually order to remove such labelling as problem asset is received.

11. Method according to any of the aforementioned claims, wherein the method contains the step of storing the recommended workorder ,wherein the method contains the step of automatically verifying whether the recommended task regarding maintenance and / or inspection of at least one of the power generation assets (51, 52, 53) and / or power distribution assets (55, 56, 57) has been realized.

12. Method according to any of the aforementioned claims, wherein the method contains the step of automatically reevaluating the failure analysis data (11, 41) and / or recommended workorder based on an information whether the recommended task regarding maintenance and / or inspection of at least one of the power generation assets (51, 52, 53) and / or power distribution assets (55, 56, 57) has been realized, wherein in case reevaluating the failure analysis data (11, 41) and / or recommended workorder results in a risk of endangering at least one of the power generation assets (51, 52, 53) and / or power distribution assets (55, 56, 57) beyond a predefined threshold value an action is automatically triggered.

13. Computer program product, tangibly embodied in a machine-readable storage medium, including instructions operable to cause a computing entity to execute a method according to any of claims 1 to 12.

14. Storage device for providing a computer program product according to claim 13, wherein the device stores the computer program product and / or provides the computer program product for further use.

15. Monitoring device containing at least one processor and at least one data storage, wherein the at least one data storage contains a computer program product according to claim 13, wherein the at least one processor is adapted to execute a method according to any of claims 1 to 12.

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