Due to various seasonal and monthly changes in electricity consumption, it is difficult to model it with conventional methods. This paper illustrates an Artificial Neural Network (ANN) approach based on supervised multi layer perceptron (MLP) network for household electricity consumption forecasting. This is the first study which uses MLP for forecasting household electricity consumption. Previ...

As the Malaysian residential electricity consumption continued to increase rapidly, effective energy policies, which address factors affecting residential electricity consumption, is urgently needed. This study attempts to investigate the relationship between residential electricity consumption (EC), real disposable income (Y), price of electricity (Pe) and population (Po) in Malaysia for 1978-...

A solution to the problem of producing long-range forecasts on a short sampling interval is proposed. It involves the incorporation of information from a long sampling interval series, which could come from an independent source, into forecasts produced by a state-space model based on a short sampling interval. The solution is motivated by the desire to incorporate yearly electricity consumptio...

Identifying the factors that influence electricity demand in the continental United States and mathematically characterizing them are important for developing electricity consumption projections. The price elasticity of demand is especially important, since the electricity price effects of policy implementation can be substantial and the demand response to policy-induced changes in prices can s...

China has experienced great social and economic vicissitudes that caused the vast complexity and uncertainty for electricity consumption. This paper attempts to identify the main determinants of the electricity consumption intensity by using the data from Chinese cities at subprovince and prefecture levels in 2009. The key category factors, including urban morphology, industrial structure, regu...

The data presented in this article are related to the research article entitled: "Information strategies for energy conservation: a field experiment in India" (Chen et al., 2017) [1]. The availability of high-resolution electricity data offers benefits to both utilities and consumers to understand the dynamics of energy consumption for example, between billing periods or times of peak demand. H...

Several demand response (DR) strategies rely on real-time pricing and selfish local optimization, which may not result in optimal electricity consumption patterns from the viewpoint of an energy supplier or a power system. Thus, this paper proposes a strategy enabling centralized adjustments to cost-minimize consumers’ load. By employing the strategy, an aggregator is able to alter electricity ...

This paper presents the data that is used in the article entitled "Climate sensitivity of end-use electricity consumption in the built environment: An application to the state of Florida, United States" (Mukhopadhyay and Nateghi, 2017) [1]. The data described in this paper pertains to the state of Florida (during the period of January 1990 to November 2015). It can be classified into four categ...

This study examines the Granger causality between electricity consumption and Gross Domestic Product (GDP) for Pakistan using annual data covering the period 1971 to 2007. Augmented Dickey-Fuller test and Phillips-Perron test reveal that both the series, after logarithmic transformation, are non-stationary and individually integrated at order one. Engle and Granger Cointegration test exhibits t...

Large-scale deployment of reliable smart electricity metering networks has been considered as the first step towards a smart, integrated and efficient grid. On the consumer’s side, however, the real impact is still uncertain and limited. This paper evaluates the consumer’s perspective in the city of Västerås, Sweden, where full implementation of smart meters has been reached. New services, such...