Unlike existing studies focused on the causal relationship between electricity consumption and economic growth at the macro level, this paper uses monthly data from January 2006 to December 2015 and applies the correlation coefficient, as well as Kullback-Leibler (KL) divergence, to study the time difference relationship between sectoral electricity consumption and economic growth. The empirica...

This paper presents a hybrid adaptive network based fuzzy inference system (ANFIS), computer simulation and time series algorithm to estimate and predict electricity consumption estimation. The difficulty with electricity consumption estimation modeling approach such as time series is the reason for proposing the hybrid approach of this study. The algorithm is ideal for uncertain, ambiguous and...

We build a system dynamics model to evaluate the potential dynamics of consumer adoption of “Smart Energy Behaviour”. Within this term we include different levels of: i) shift in electricity consumption towards less costly-less polluting and congestioning hours; ii) the reduction of mainly wasteful electricity consumption, that maintains similar levels of comfort; iii) the enrolment in demand r...

Information and Communication Technology (ICT) devices and services are becoming more and more widespread in all aspects of human life. Following an increased worldwide focus on the environmental impacts of energy consumption in general, there is also a growing attention to the electricity consumption associated with ICT equipment. In this paper we assess how ICT electricity consumption in the ...

When it comes to conserving electricity, it is crucial for users to know how much energy is consumed by individual appliances. However, the technical feedback provided by existing energy consumption feedback systems in the form of dry numbers and intangible units is not appropriate for most users. To address this shortcoming we developed PowerPedia, a system that provides behavior-influencing f...

This work develops Artificial Neural Networks (ANN) models applied to predict the consumption forecasting considering climatic factors. It is intended to verify the influence of climatic factors on the electricity consumption forecasting through the ANN. The case study is applied in the Campinas city, Brazil. This work used Perceptron and Backpropagation ANN models. The specific goal is compari...

Motivated by electricity consumption reconstitution, we propose a new matrix recovery method using nonnegative matrix factorization (NMF). The task tackled here is to reconstitute electricity consumption time series at a fine temporal scale from measures that are temporal aggregates of individual consumption. Contrary to existing NMF algorithms, the proposed method uses temporal aggregates as i...

tinuously increasing and now accounts for about one third of the total electrical energy produced in Europe. Many individuals would be interested in saving energy (and thus also carbon dioxide as well as money), but they lack information on their consumption. Indeed, feedback on household electricity usage is typically only provided by monthly (or even annual) utility bills and therefore remain...

a r t i c l e i n f o This paper studies the dynamic behavior of electricity consumption with special emphasis on their convergence patterns. Individual electricity indicators are modeled by allowing for apparent heterogeneous transitions. Log t convergence test results indicate that all 109 countries converge to a common stochastic trend for electricity intensity while per capita electricity c...

When it comes to conserving electricity, it is crucial for users to know how much energy is consumed by individual appliances. However, the technical feedback provided by existing energy consumption feedback systems in the form of dry numbers and intangible units is not appropriate for most users. To address this shortcoming we developed PowerPedia, a system that provides behavior-influencing f...