Providing comparable performance scores

Abstract

Disclosed is a computer-implemented method for obtaining a performance scoring for an object, the method comprising: obtaining a first type of input data, that indicates at least one aspect of performance of the object with respect to energy consumption, obtaining a second type of input data that indicates requirements based on which the performance scoring is classified, verifying the first type of input data and the second type of input data, calculating the performance scoring of the object based on at least the first type of input data, calculating the classification for the performance scoring based on at least the second type of input data, and providing the classification of the performance scoring as an output.

Description

FIELD

[0001] The exemplary embodiments discussed in the present disclosure relate to evaluating performance of one or more objects and having comparable evaluation results for the one or more objects.BACKGROUND

[0002] Objects may operate in various manners. For example, if the object is a building, for example a house, then the house may have various functionalities such as heating, ventilation, insulation and so on. The house thus consumes energy in order to be able to perform those functionalities. The energy may be obtained from external energy sources, such as from an electricity grid, from gas, from solar panels, and / or from oil. The performance of the house may then be evaluated in various manners. One such manner may be to evaluate the energy efficiency and / or carbon dioxide (CO 2 ) emissions caused by the functionalities performed by the building. As the performance may be evaluated in various manners, it may not be clear if different performance results are comparable with each other.BRIEF DESCRIPTION

[0003] The scope of protection sought for various embodiments is defined by the independent claims. Dependent claims define further embodiments included in the scope of protection. Exemplary embodiments, if any, that do not fall into any scope of protection defined in the claims, are to be considered as examples useful for understanding the cope of protection.

[0004] According to a first aspect there is provided a computer-implemented method for obtaining a performance scoring for an object, the method comprising: obtaining a first type of input data, that indicates at least one aspect of performance of the object with respect to energy consumption, obtaining a second type of input data that indicates requirements based on which the performance scoring is classified, verifying the first type of input data and the second type of input data, calculating the performance scoring of the object based on at least the first type of input data, calculating the classification for the performance scoring based on at least the second type of input data, and providing the classification of the performance scoring as an output.

[0005] According to a second aspect there is provided a computing system comprising means for performing the computer-implemented method of the first aspect.

[0006] In some examples according to the second aspect, the means comprises at least one processor, and at least one memory including computer program code which, when executed by the at least one processor, causes the performance of the computing device.

[0007] According to a third aspect there is provided a computer program product comprising instructions, which, when executed by a computing system, cause the computing device to perform a computer-implemented method according to the first aspect.

[0008] According to a fourth aspect there is provided a non-volatile computer-readable medium comprising program instructions stored thereon which, when executed on a computing system, cause the computing system to perform a computer-implemented method according to the first aspect.

[0009] According to a fifth aspect there is provided a system comprising a computing system comprising one or more computer devices, at least one interface to a service providing metered data regarding a building, and at least one interface to obtaining data regarding external aspects affecting functionality of the building, wherein the system is configured to perform the computer-implemented method according to the first aspect.BRIEF DESCRIPTION OF THE DRAWINGS

[0010] Some of the exemplary embodiments are discussed with reference to the figures in which: FIG. 1 illustrates examples of buildings and certificates regarding efficiency of their functionalities. FIG. 2 illustrates an exemplary embodiment a block diagram, which schematically represents an exemplary manner of producing performance scoring for an object. FIG. 3 illustrates a flow chart according to an exemplary embodiment. FIG. 4 illustrates an exemplary embodiment of a computing device. DETAILED DESCRIPTION

[0011] Different objects may perform functionalities that require energy. The energy may be obtained from external energy sources and the energy obtained may have been produced based on for example renewable energy sources, nuclear, power, coal, natural gas, liquid natural gas, and / or oil. When performing the functionalities, the efficiency of how the energy is used and / or CO 2 emissions may be taken into account when evaluating the performance of the object. Other aspects that may be taken into account comprise for example energy required, and emissions caused, when producing the object, as well as external conditions such as weather conditions. The object may be for example a vehicle, such as a car or a vessel, or the object may be a building or a group of buildings. The object may also be a system comprising a plurality of energy consuming and / or energy producing units. For example, a building may provide charging to one or more electrical vehicles and thus, the one or more electrical vehicles may be considered to be part of the same system as the building and thus forming one object. Additionally, or alternatively, the building may be one building or a group of buildings that are considered to form a system that may be considered as the object. Also additionally, or alternatively, there may be a building that is associated with an energy production unit, such as wind turbine(s) and / or solar panel(s), biomass, waste to energy, etc and the energy production unit may be connected to the building, or otherwise adjacent to the building such that they are considered to form a system that can be considered as the object, and so on. The adjacent energy production unit may be understood as a nearby energy production unit that thus may be attached to the building, or adjacent to the building. In the context of this document, buildings are discussed, but it is to be noted that also other types of objects may be evaluated using the principles outlined in the context of this document.

[0012] Figure 1 illustrates an example how different buildings may have a certificate indicating their energy efficiency. For example, in Europe, a house 110 that is in Southern Europe may have a certificate 115 that is for describing the energy efficiency of the house 110. The house 120 may have a certificate 125 describing its energy efficiency. The house 120 is located in Central Europe. In this example, the building 130 has a certificate 135 describing its energy efficiency, and the building 130 is located in Northern Europe.

[0013] While all of the buildings 110, 120, and 130 are located in Europe 100, their respective certificates 115, 125, and 135 may have been issued by different authorities. Such different authorities may use different methods for evaluating the energy efficiency that is then indicated in the certificate they issue. Thus, the certificates 115, 125, and 135 may have been issued using different criteria and thus their comparison may not be advisable. While the way in which the actual calculations are made may vary, also the data used for the calculations that form the basis for a certificate may vary. For example, the weather conditions may vary significantly and unless that is taken into account, comparing the certificate 115 and the certificate 135 for example may not be sensible. Additionally, or alternatively, the house 120 may utilize trees for shade thus reducing the need for cooling during hot summer days, while the house 110 may not have any trees in vicinity, for example, and this may not necessarily be taken into account when comparing the certificates 115 and 125. Further additionally, or alternatively, the building 130 has many floors and thus its energy efficiency per square meter may be better than that of the house 120 or 110. Yet, this may not be comparably reflected on the certificates 135 and 125, or 115.

[0014] While the buildings 110, 120 and 130, that are all in Europe, may have location in different countries, and thus their respective certificates 115, 125, and 135, may be issued by authorities in different countries, there may be different authorities in one country as well. Then the same situation may occur as the certificates issued by the different authorities, within the same country, may not be comparable. As illustrated in the example of figure 1, there are buildings 160 located in Alaska, and there is the certificate 165 issued for this group of buildings. There are also buildings 170 located in Florida and a certificate 175 has been issued for this group of buildings by different authority. It may not be clear if the different authorities have taken into account the weather conditions that are greatly different in Florida and in Alaska such that the certificates issued are comparable. Further, the groups of buildings 160 and 170 are both located in the USA 150, so both authorities issuing the certificates may issue certificates to buildings in Alaska and buildings in Florida. Then it may remain unclear whether the criteria used for the certificates issued in Alaska, or in Florida, by these companies are comparable such that in one state the certificates that are issued by different companies are comparable. It may also remain unclear whether certificates issued by one or both of the authorities are comparable when the authority issues certificates for buildings in different states.

[0015] Having lack of visibility to the aspect of whether certificates, that are for indicating performance of the buildings, are comparable with each other or not, may be problematic for example if there is a portfolio of buildings. Then the portfolio may lack visibility in terms of the quality of the buildings that are comprised as assets within the portfolio. Thus, it may not be possible to compare assets and to make informed decisions regarding for example where to target resource such as renovations, which may lead to the portfolio not being developed optimally. Thus, it would be beneficial to be able to identify, for example, which renovations would most benefit in terms of improving efficiency and reduction of (CO 2 ) emissions. Thus, it would be beneficial to have a verified indication of performance of an object, such as a building, that is comparable to indications of performance given to other objects, that may be located in the same geographical area or in a different geographical area. The indication of performance may be for example a performance scoring. In other words, it would be beneficial to have a harmonized manner of producing the performance scoring such that the performance scoring given to an object, such as a building and / or a vehicle, would be comparable to other performance scorings.

[0016] Figure 2 illustrates an exemplary embodiment of a block diagram, which schematically represents an exemplary manner of producing performance scoring for an object, which is an object such as discussed above. It is to be noted that the block diagram illustrates logical blocks the implementation of which may vary. In this exemplary embodiment, the object is a building, and its performance is evaluated with respect to its CO 2 emissions. It is to be noted that while this exemplary embodiment is discussed in view of one building, a group of buildings could also be evaluated in a corresponding manner. The evaluation in this exemplary embodiment comprises calculations that are performed by an engine 200 that is for providing the performance scoring, which could also be referred to as performance score. The engine 200 may perform the calculations as a computer-implemented method and the method may be implemented by a computing system comprising one or more computer devices. For example, the engine may be a software product, that comprises computer instructions executed using the computer system. The computer system may be understood as a server, that may be a stand-alone computing system that comprises one or more computing devices, a backend, and / or a cloud-based computing system. The engine 200 may be understood as a service provided using the computing system that implements the computer-implemented method that is configured to provide the performance scoring.

[0017] For the engine 200 to be able to perform the calculations that are required for the performance scoring, the engine receives input regarding the object, which in this exemplary embodiment is a building. The input may be data that may be referred to as input data or data input. The input data may be classified as being of certain type of input data based on for example where the data originates from. In this exemplary embodiment, there are three different types of input data, the first, the second and the third type of input data. Yet, it I to be noted that the first, the second and the third are merely indicating that the data is of different classification, not a specific order. Thus, for example the third type of input data could also be referred to as the second type of input data and so on. In the first type of input data 210, the data is received as a result of metering an aspect regarding the building. Such aspect may be a factor of the functionality of the building, such as energy consumption caused by heating domestic hot water, operating ventilation, and so on. At least some of the input data in this first type may be received in an automated manner. For example, the input data may comprise metered data regarding energy consumption of the building, such as consumption of gas, electricity and / or heating, and so on. In other words, this first type of input data comprises data that has been metered regarding the building. Such data may optionally be received as input data automatically from the respective meters. The time period from which the data of this first type is received may be pre-determined. For example, the time period may be a day, a week, a month, half a year, a year, and so on. The more there is historical data available, the more reliably long-term evaluation of the performance of the building may be calculated. Such long-term evaluation may be beneficial in terms of receiving a more reliable performance scoring, and / or being able to make more precise predictions for the future behaviour of the building.

[0018] The second data input type 220 may comprise metered data regarding external factors affecting the energy consumption of the building. For example, the weather, the energy spot prices, occupancy of the building at the given moment in time, CO 2 factors, and so on. In other words, external aspects that increase or decrease energy consumption of the building. The CO 2 emissions of the building may thus be comparable to the energy consumption of the building as well as to the energy efficiency of the building and the type of energy source from which the building receives the energy it consumes for its functionality that is affected by the external factors, which are received as the second type of data input 220. As with the first type of data input 210, the second type of data input 220 may be received from a pre-determined period of time, thus allowing historical behaviour to be better calculated. The time period may be the same for the first type of data input 210 and for the second type of data input 220.

[0019] In this exemplary embodiment, there is also the third type of data input 230. This data input 230 may originate from a user. The user may be for example a client who is interested in obtaining the performance scoring for the particular building. The third type of data input 230 may thus be received as user input, and it may comprise data such as overview of energy sources, fugitive emissions usage, certificates received from other entities, information regarding regulations, such as EU taxonomy requirements, and so on. Such data may thus bring further information regarding the external factors affecting the evaluation of the performance of the building.

[0020] It is to be noted that in the different types of input data, some of the data may be mandatory input data such that the engine 200 is capable of calculating the performance scoring, while some of the data may be optional. The optional data may allow more precise evaluation of the performance scoring, while even without it the performance scoring may still be considered as reliable enough. It is also to be noted that any suitable manner of performing the calculation may be utilized provided that the manner remains the same for all the objects for which the performance scoring is to be calculated.

[0021] After receiving the input data, the engine 200 performs the calculations that result in the performance scoring for the building. The calculations may comprise any suitable algorithms that allow obtaining information regarding energy consumption of the building in different conditions and evaluating the CO 2 emissions caused by the building in accordance with its energy consumption. The scoring may then optionally be used to indicate the classification to which the building belongs to. For example, the classification may be dependent on the location, and / or the age of the building, on the regulations applicable to the building, and so on. There may be for example pre-determined threshold values regarding what the performance scoring should be for each classification. Therefore, as an output 240, the engine 200 then provides information regarding the performance scoring and the output may comprise the performance scoring itself and / or the classification determined based on the performance scoring. Thus, the building may be determined a category for example, and the classification for a particular performance scoring may be dependent on the category determined for the building. This allows to take into account aspects such as the age of the building, its location, purpose and so on. For example, the regulations that were applicable to buildings that were built decades ago have been different that those applicable to newly built buildings and thus their classification may take into account that aspect. Also, there may be regulations, such as how to achieve national target levels of the CO 2 emissions, such as the net-zero target, that are different for different buildings.

[0022] As the engine 200 calculates the output 240 in the same manner for each object, the output 240 received for one building may be considered as comparable to other outputs received from the engine 200 for other buildings.

[0023] Figure 3 illustrates a flow chart according to another exemplary embodiment in which a performance scoring, that is comparable to other performance scorings, is obtained. The flow chart may be implemented using a computer-implemented method and the computer-implemented method may be executed for example by the engine 200 discussed above. Thus, this exemplary embodiment is combinable with the exemplary embodiments discussed above.

[0024] First in S1, input data, which may also be referred to as data input, is obtained. As discussed above, the input data may be of different types depending on for example how the input data is obtained, from where it is obtained, and so on. It is also to be noted that the data included in the one or more type of input data may vary as some data may be mandatory and some optional.

[0025] For example, at least one type of input data may be obtained as a response to a query. The query may be such that a user then provides user input that comprises the type of input requested using a query provided to a user via a user interface to the computer-implemented method. For example, there may be a file that is provided by the user, the file may be of any suitable type such as an excel sheet, a word document or a csv-file. Additionally, or alternatively, some data may be received through an application programming interface (API), from a service interface, etc.

[0026] The data that is first collected as input may comprise aspects that are regarding the building itself and regarding external factors of the building. For example, there may be data regarding when the building was built, regarding renovation plans for the building, or data regarding how a building is planned to be constructed. As data regarding the building itself, there may be historical data that is received as input data. The historical data may be measured data, and / or estimated data. For example, there may be data received from the past 12 months regarding consumption of electricity, district heating data, district cooling data, natural gas data, and / or fugitive emissions data. At least some of this data may be accessed through external services provided by external data providers. The user may in such case provide access data to such services such that the data can be obtained. Additionally, or alternatively, some data may be obtained through publicly available services.

[0027] In S2, the obtained input data is saved to the service implementing the exemplary embodiment of the computer-implemented method according to this flow chart. The input data may further be categorized into different categories depending on how the data is utilized in determining the performance scoring. For example, if the data is utilized in the calculations for determining the performance scoring for the building, the data may be of a first category, for example, of input type. On the other hand, if the data is for determining classification for the calculated performance score, its type may be of a second category, for example of an output type. The performance scoring may be considered to be an overall indication of one or more aspects of performance of the building with respect to energy consumption. The calculation may thus take into account different aspects of the performance with respect to energy consumption, including the energy consumption as such as well as other aspects that are based on the energy consumption, such as efficiency of the usage of the energy and / or emissions caused by the building and / or emissions per floor area, and so on.

[0028] In S3, the data is then verified. Verification of the data received as data input may comprise verifying that the mandatory data input is received and is in correct format. For example, that the format is text, if text is required and / or numbers if numbers are required. Further, the verification may comprise verifying that range of numerical values is within an allowed range, and so on. The data verification may be automated such that it is part of the computer-implemented method performed by the service, or it may be at least partly performed manually by a user and then the user may provide input to indicate that the verification has been made. In case it is noted that some of the data cannot be verified, the processing of the data may be paused and an indication regarding the inability to verify the data may be provided for example using an output on a user interface. Then, once the data has been corrected, the verification may be performed again, and the processing may continue, provided that the data can be verified.

[0029] It is to be noted that optionally there may be quality scores associated with at least some of the input data. The quality scoring may be used for example as a weighing factor for that part of the input data when performing the calculations. For example, if actual metered data is used instead of an estimated value, the metered data may be associated with a higher quality score than the estimated value. The metered data may represent for example a factor of electricity consumption and if that factor is accurately metered, it may receive a higher quality score than the estimated electricity consumption.

[0030] Next, in S4, the calculations to obtain energy efficiency and CO 2 emissions of the building are performed based on the input data of the first category. The calculations may be performed using any suitable software algorithm(s). Optionally, there may be a time period specified, which in this exemplary embodiment is the past 12 months, for which the calculations are performed.

[0031] Once the calculations are performed on the first category of input data, then the actual performance of the building may be obtained. Yet, since there are different types of buildings, the buildings may be located in different environmental conditions, and / or there may be different regulations applicable for the performance of the buildings, the actual performance may need to be classified based on these external factors that may be obtained from the second category of input data. For example, the scoring of a new building with tight regulations applicable may be at the first level of classifications when the performance of the building is at a certain level, which is higher level of performance than what is expected from an older building in less favourable weather conditions to be in the first level of classification, even though the same regulatory requirements may apply to both buildings.

[0032] Thus, the performance scoring may be affected by the data input in the second category, such that the performance scoring is a classified performance scoring. Thus, the performance scoring may be the performance scoring as such or a classified performance scoring. Once the effect of the data input in the second category is calculated, either automatically or, at least partially, based on user input received, the output is provided as illustrated in S5. The output may be the performance scoring for the building in a comparable format, in other words, in the classified format. Additionally, or alternatively, the output may also comprise the performance scoring as such. The output may then be associated with a timestamp indicating when the result was obtained. The output may then be provided to be available and / or it may be transmitted to a receiver in any suitable format, for example, as a file or as an e-mail.

[0033] Based on the calculations made, there may optionally be further calculations made that may then provide a trajectory regarding how the performance of the building is expected to develop in future. The trajectory may also be referred to as projection. The calculations may be made based on the data received as input, and optionally further input may be received based on which estimations regarding development of the performance may be made. Such further input may be for example performance information regarding similar types of buildings, information regarding one or more components of the building that are involved in performing functionalities of the building and so on. A benefit that is associated with calculating the trajectory is that it allows to see for example how the performance of the building could be improved and from where further reductions of CO 2 emissions could be obtained. This may be beneficial for example if national targets regarding the CO 2 emissions are to be obtained. It is to be noted that the trajectory may be comprised in the output as well.

[0034] Further optionally, once the results are available, they may be manually reviewed. The results may optionally indicate the data that was received as an input, the different types of input data received as well as the categories of the input data. In case it is noticed that some aspects of the input data were missing, and / or were incorrect, then the calculations may be re-done, and the flow chart may return to S1. Additionally, or alternatively, the process may also return to S1 in case the calculations are to be made for a modified input data. The modified input data may be used for example to obtain indication regarding what the result of the calculations, and thereby of the performance score received as an output, would be in case one or more factors were different. This may allow to calculate for example what would be the effect of a certain renovation of the building would have on the performance scoring of the building. Further, then, based on the revised calculations performed to obtain the information regarding the effect a renovation would have, a new trajectory regarding the development of the performance of the house would have in future, could be made. Additionally, there may be more than one renovation that are planned to be made. By obtaining the calculations for input data that comprises the evaluated effect on the factor that is affected by one or more of the planned renovations, it may be estimated how the performance of the building may improve over time. This may then be used for example as an input to apply for a loan for the renovation or as a guidance regarding when the optimal time would be to do which renovation in order to fulfil regulatory requirements and / or improve performance of the building. In other words, the flow chat illustrates how various options may be explored to identify most suitable options regarding maintenance and / or updating of the building.

[0035] In the exemplary embodiments discussed above regarding performance of a building, data received as an input may be of different quality, and as discussed above, the quality of the data may be indicated, and the indication may be associated with the aspects of data that are relevant to the quality indication. For example, there may be actual building energy consumption available as metered data. Then the emissions may be calculated based on the metered energy consumption. Based on the information available for the energy source, the quality of this data may be on the top level, or on the second highest level for example. The highest level of quality may be obtained for example if there are supplier-specific emission factors available, that are specific to the respective energy source. The second highest quality may be obtained if the average emission factors specific to the respective energy source are available.

[0036] Thus, metered data is of higher quality than estimated data. One example of estimating the data is that there is an estimation of CO 2 emissions caused by the building, the estimation being based on the floor area of the building. Then, if estimated data is used, the highest quality is for an estimation of energy consumption of the building per floor area based on official building energy labels and the floor area available in the building. The CO 2 emissions may then be calculated using estimated building energy consumption and average emission factors specific to the respective energy source. The second highest quality for estimated data is then when the CO 2 emissions of the building are estimated based on estimated building energy consumption per floor area based on building type and location specific statistical data and the floor area available in the building. Thus, the estimation of CO 2 emissions may be calculated using estimated building energy consumption and average emission factors specific to the respective energy source.

[0037] The lowest quality score may then be for example when CO 2 emissions of a building are estimated based on a number of buildings. For example, estimated building energy consumption per building based on building type and location-specific statistical data and the number of buildings. The estimation of theCO 2 emissions may then be calculated using estimated building energy consumption and average emission factors specific to the respective energy source.

[0038] The exemplary embodiments discussed above may have various benefits. For example, by obtaining the comparable performance scores, that may include the performance scoring as such as well as the classified performance scoring, for buildings, different buildings can be evaluated in a consistent manner thus making the results comparable with each other. This help to anticipate renovations that would be good to have and their effect on the performance of the building. It may also help to evaluate when such renovations would be good to make with the help of a trajectory. The calculations performed based on the input data, using the data engine 200 for example, an output may be obtained. The output may comprise different parts. The parts may comprise the performance scoring, which may include the actual performance scoring and / or classified performance scoring, indications regarding quality scores and / or one or more trajectories for different scenarios for the building indicating the path with respect to CO 2 emission targets depending on if no renovations are made and / or if some renovations are made. Such output helps to compare the performance of different buildings in an objective manner and also to see how the targets may be received for different buildings.

[0039] Figure 4 illustrates an exemplary embodiment of a device 400 that may be or may be comprised in a computing system comprising one or more computing devices. This exemplary embodiment is compatible with the previous exemplary embodiments, and they may be combined in any suitable manner. In this exemplary embodiment, there is at least one processor 440, at least one memory 430, at least one connectivity unit 410 and at least one unit for receiving input and providing output 420. It is to be noted that the units described here are logical units and thus the actual implementation may vary. The at least one processor 440, at least one memory 430, at least one connectivity unit 410 and at least one unit for receiving input and providing output 420 may be connected to each other. It is to be noted that the connectivity unit 410 may provide connection to an API that allows receiving data and the API may be considered to be part of the input and output unit 420.

[0040] The at least one processor 440 may also be referred to as core, a central processing unit (CPU), microprocessor or graphical processing unit (GPU). A processor may be understood as an integrated circuit for performing calculations according to instructions provided using computer code. The at least one memory 430 may comprise volatile and / or non-volatile memory. Thus, the at least one memory 430 may be understood to be one block of memory or a combination of different blocks of memory. The memory may be for storing different types of data. The at least one memory 430 stores also computer program instructions, for example in the form of an application and / or an operating system. The at least one memory 430 provides computer program instructions to the at least one processor 440 for executing and the at least one processor 440 may then be configured to store data into the at least one memory 430. Some examples of memory are random access memories (RAMs), such as static RAM (SRAM) and dynamic RAM (DRAM), read-only memory (ROM), flash memories, optical discs, and magnetic computer storage devices, such as hard disk drives. The input and output unit 420 may allow user input, such as pressing a button, touch input and / or voice input, to be received by the device 400 and output such as audio, haptic or visual output to be provided to a user. The connectivity unit 410 allows connection to be formed between the device 400 and another device. The connectivity unit may allow wireless and / or wired connections to be formed between the device 400 and other devices. Examples of connection types that may be supported by the connectivity unit 410 are cellular communication -based connections, local area networks, Bluetooth-connections, Wi-Fi connections, etc. Such connections may allow to access and API stored in the memory 430 of the device 400.

[0041] The present disclosure has been described above with reference to the exemplary embodiments. However, a person skilled in the art will understand there may be embodiments that vary from the example embodiments discussed above within the scope of the claims. Thus, skilled person will understand that the exemplary embodiments described above may, but are not required to, be combined with each other and / or other exemplary embodiments in various manners.

Claims

1. A computer-implemented method for obtaining a performance scoring for an object, the method comprising: obtaining a first type of input data, that indicates at least one aspect of performance of the object with respect to energy consumption; obtaining a second type of input data that indicates requirements based on which the performance scoring is classified; verifying the first type of input data and the second type of input data; calculating the performance scoring of the object based on at least the first type of input data; calculating the classification for the performance scoring based on at least the second type of input data; and providing the classification of the performance scoring as an output.

2. A computer-implemented method according to claim 1, wherein the output is associated with a time-stamp.

3. A computer-implemented method according to claim 1 or 2, wherein the method further comprises obtaining a third type of input data.

4. A computer-implemented method according to any previous claim, wherein the first type of input data comprises input data that is indicative of metered aspects of the object, and the third type of input data comprises metered aspects of an environment affecting the functionality of the object.

5. A computer-implemented method according to any previous claim, wherein the first type of input data is received, at least partly, in an automated manner, and the third type of input data is received as a user input in response to a query provided to a user via a user interface.

6. A computer-implemented method according to any previous claim, wherein at least some of the first, second, and / or third type of input data is received using one of the following: an API, a service, a file, or input provided by a user.

7. A computer-implemented method according to any previous claim, wherein the method further comprises verifying the third type of input data.

8. A computer-implemented method according to any previous claim, wherein the verifying comprises verifying at least one of the following: mandatory input data is provided, or format of each input data is correct.

9. A computer-implemented method according to any previous claim, wherein at least some input data of any input data type is associated with a quality score, wherein the value of the quality score depends, at least partly, on whether the input data is a metered input data or an estimated input data.

10. A computer-implemented method according to any previous claim, wherein the quality score is used as a weighting factor in the calculating.

11. A computer-implemented method according to any previous claim, wherein at least the first type of input data is obtained for a pre-determined time period, and the method further comprises calculating a trajectory for future performance scoring and classification of the performance scoring.

12. A computer-implemented method according to any previous claim, wherein the object is a building, or the object is a system comprising two or more of the following: a building, another building, an electric vehicle, and / or a nearby energy production unit.

13. A computing system comprising means for performing the computer-implemented method according to any of claims 1 to 12.

14. A computer program product comprising instructions, which, when executed by a computing system, cause the computing device to perform a computer-implemented method according to any of claims 1 to 12.

15. A system comprising a computing system comprising one or more computer devices, at least one interface to a service providing metered data regarding a building, and at least one interface to obtaining data regarding external aspects affecting functionality of the building, wherein the system is configured to perform the computer-implemented method according to any of claims 1 to 12.

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