Search results for "electricity consumption"
showing 7 items of 7 documents
Electricity Consumption Analysis of Tertiary Buildings: An Empirical Approach for Two University Campuses
2020
An empirical approach for the analysis of energy consumption of existing buildings of the tertiary sector is presented in this study. It allowed the organization and management of large amounts of data according to different timeframes and helped to focus on leading issues about energy uses, and dealt with compatibility with tariff structure. The analysis method, which implied a powerful graphical representation of the results, allowed us to detect critical issues in electricity energy management for public buildings and improve their energy performance. Furthermore, the authors proposed a set of electricity consumption indexes (ECIs) that gave useful insight into the main hotspots. The bas…
Functional linear regression with functional rensponse application to prediction of electricity consumption
2008
Functional linear regression model linking observations of a functional response variable with measurements of an explanatory functional variable is considered. The slope function is estimated with a tensor product splines. Some computational issues are addressed by means of a simulation study. This model serves to analyze a real data set concerning electricity consumption in Sardinia. The interest lies in predicting either incoming weekend or incoming weekdays consumption curves if actual weekdays consumption is known.
Multi-party metering: An architecture for privacy-preserving profiling schemes
2013
Several privacy concerns about the massive deploy- ment of smart meters have been arisen recently. Namely, it has been shown that the fine-grained temporal traces generated by these meters can be correlated with different users behaviors. A new architecture, called multi-party metering, for enabling privacy-preserving analysis of high-frequency metering data without requiring additional complexity at the smart meter side is here proposed. The idea is to allow multiple entities to get a share of the high-frequency metering data rather than the real data, where this share does not reveal any information about the real data. By aggregating the shares provided by different users and publishing …
Forecasting daily urban electric load profiles using artificial neural networks
2004
The paper illustrates a combined approach based on unsupervised and supervised neural networks for the electric energy demand forecasting of a suburban area with a prediction time of 24 h. A preventive classification of the historical load data is performed during the unsupervised stage by means of a Kohonen's self organizing map (SOM). The actual forecast is obtained using a two layered feed forward neural network, trained with the back propagation with momentum learning algorithm. In order to investigate the influence of climate variability on the electricity consumption, the neural network is trained using weather data (temperature, relative humidity, global solar radiation) along with h…
A Neural Network Model to Forecast Urban Electricity Consumptions from Weather Data
2004
Digital participation in service environments among senior electricity consumers in Finland
2018
Research to date suggests that older adults engage with digital technologies less frequently than young adults. Studies typically focus on chronological age, ignoring the effects of life course factors on the adoption and use of digital technologies. By utilising multiple triangulation, the article investigates the role of age and life course stage in the usage of an electricity company's online services among senior consumers. The data are derived from an internet-based survey study (N = 1366) and six focus group discussions involving Finnish electricity consumers (N = 29). The results suggest that online consumers aged 50 and over utilise electricity company online services more frequentl…
Electricity consumption prediction with functional linear regression using spline estimators
2010
A functional linear regression model linking observations of a functional response variable with measurements of an explanatory functional variable is considered. This model serves to analyse a real data set describing electricity consumption in Sardinia. The interest lies in predicting either oncoming weekends’ or oncoming weekdays’ consumption, provided actual weekdays’ consumption is known. A B-spline estimator of the functional parameter is used. Selected computational issues are addressed as well.