Abstract: An energy consumption alerting method includes measuring location-specific energy consumption values over a specific period at a sensor deployed at a location of a monitored site, and decomposing the location-specific energy consumption values according to a first characteristic. The method further includes decomposing the location-specific energy consumption values according to a second characteristic, and obtaining a first decomposed energy consumption value. The method additionally includes determining a corresponding first reference value based on the decomposed values, and comparing the first decomposed energy consumption value with the determined corresponding first reference value. Additionally, the method includes notifying a user if the first decomposed energy consumption value and the determined corresponding first reference value differ from each other. Furthermore, an energy consumption alerting system and a cloud-based energy consumption alerting platform is provided.

Abstract: According to one embodiment of the present invention, a prediction system is provided. The system comprises a first data decomposition facility configured to decompose a provided time series of consumption data into a plurality of different training sets for different types of days and a second data decomposition facility configured to decompose each one of the plurality of training sets into at least a seasonal component and a trend component. The system further comprises a regression facility configured to perform a regression analysis on the decomposed consumption data based on at least the trend component and chronological information associated with the consumption data of the respective training set to train a prediction function and a prediction facility configured to estimate predicted energy consumption data based on the trained prediction function and the type of a day for which the prediction is performed.

Abstract: An energy consumption alerting system is provided. The system includes a plurality of sensors deployed at different locations of at least one monitored site, the sensors being able to provide location-specific energy consumption values. The system further includes a data aggregation facility so as to sum up location-specific energy consumption values associated with at least two corresponding predetermined sensors of the plurality of sensors to obtain an aggregated energy consumption value. The system further includes an alerting facility this is able to compare the aggregated energy consumption value with an user-defined threshold level and notify a user if the at least one aggregated energy consumption value exceeds the at least one user-defined threshold level. A cloud-based energy consumption alerting platform and an energy consumption alerting method are also provided.

Abstract: A cloud-based method for identifying a energy profile of an end user is provided. The method includes obtaining information including a total amount of consumed energy and a total equivalent for at least one previous period from at least one listing of the end user, and estimating a consumption profile for a plurality of time slots based on the total amount of consumed energy.

Abstract: According to one embodiment of the present invention, a prediction system is provided. The system comprises a first data decomposition facility configured to decompose a provided time series of consumption data into a plurality of different training sets for different types of days and a second data decomposition facility configured to decompose each one of the plurality of training sets into at least a seasonal component and a trend component. The system further comprises a regression facility configured to perform a regression analysis on the decomposed consumption data based on at least the trend component and chronological information associated with the consumption data of the respective training set to train a prediction function and a prediction facility configured to estimate predicted energy consumption data based on the trained prediction function and the type of a day for which the prediction is performed.

Abstract: An energy consumption alerting system is provided. The system includes a plurality of sensors deployed at different locations of at least one monitored site, the sensors being able to provide location-specific energy consumption values. The system further includes a data aggregation facility so as to sum up location-specific energy consumption values associated with at least two corresponding predetermined sensors of the plurality of sensors to obtain an aggregated energy consumption value. The system further includes an alerting facility this is able to compare the aggregated energy consumption value with an user-defined threshold level and notify a user if the at least one aggregated energy consumption value exceeds the at least one user-defined threshold level. A cloud-based energy consumption alerting platform and an energy consumption alerting method are also provided.

Abstract: A method for operating an energy consumption metering system is provided. The method includes determining a first value of energy consumption at a central supply point by a first energy consumption metering device, and determining a second value of energy consumption of a sub-location of the central supply point by a second energy consumption metering device. A deviation of the first value and the second value is determined and based on the determined deviation, calibration data for calibrating at least one of the first and the second energy consumption metering device is determined.

Abstract: An energy consumption alerting system is provided. The system includes a plurality of sensors deployed at different locations of at least one monitored site, the sensors being able to provide location-specific energy consumption values. The system further includes a data aggregation facility so as to sum up location-specific energy consumption values associated with at least two corresponding predetermined sensors of the plurality of sensors to obtain an aggregated energy consumption value. The system further includes an alerting facility this is able to compare the aggregated energy consumption value with an user-defined threshold level and notify a user if the at least one aggregated energy consumption value exceeds the at least one user-defined threshold level. A cloud-based energy consumption alerting platform and an energy consumption alerting method are also provided.

Abstract: According to one embodiment of the present invention, a monitoring system for monitoring resource consumption of at least one monitored site is disclosed. The system comprises a plurality of sensors deployed at different locations of the at least one monitored site, the sensors being configured to provide measurement values over a data network; a data association facility connected to the data network, the data association facility being configured to associate each measurement value with a location information within the at least one monitored site based on a hierarchical model of the monitored site and type information associated with a corresponding sensor of the plurality of sensors; and a graphical interface facility connected to the data network, the graphical interface facility being configured to selectively display the plurality of measurement values based on the associated location information and type information.

Abstract: A cloud-based method for identifying a energy profile of an end user is provided. The method includes obtaining information including a total amount of consumed energy and a total equivalent for at least one previous period from at least one listing of the end user, and estimating a consumption profile for a plurality of time slots based on the total amount of consumed energy.

Abstract: An energy consumption alerting method includes measuring location-specific energy consumption values over a specific period at a sensor deployed at a location of a monitored site, and decomposing the location-specific energy consumption values according to a first characteristic. The method further includes decomposing the location-specific energy consumption values according to a second characteristic, and obtaining a first decomposed energy consumption value. The method additionally includes determining a corresponding first reference value based on the decomposed values, and comparing the first decomposed energy consumption value with the determined corresponding first reference value. Additionally, the method includes notifying a user if the first decomposed energy consumption value and the determined corresponding first reference value differ from each other. Furthermore, an energy consumption alerting system and a cloud-based energy consumption alerting platform is provided.

Abstract: According to one embodiment of the present invention, a prediction system is provided. The system comprises a first data decomposition facility configured to decompose a provided time series of consumption data into a plurality of different training sets for different types of days and a second data decomposition facility configured to decompose each one of the plurality of training sets into at least a seasonal component and a trend component. The system further comprises a regression facility configured to perform a regression analysis on the decomposed consumption data based on at least the trend component and chronological information associated with the consumption data of the respective training set to train a prediction function and a prediction facility configured to estimate predicted energy consumption data based on the trained prediction function and the type of a day for which the prediction is performed.