This article introduces a dataset containing electricity consumption records of residential
households in Uruguay (mostly in Montevideo). The dataset is conceived to analyze …

This article presents an approach applying computational intelligence for detecting the use
of air conditioners in households. The main objective is determining the intensive use of air …

This paper examines a contextual paradigm for energy disaggregation using Non-Intrusive
Load Monitoring (NILM). Due to numerous issues including low sampling rates, missing …

This article presents electricity demand forecasting models for industrial and residential
facilities, developed using ensemble machine learning strategies. Short term electricity …

Residential energy flexibility is considered one of the efficient concepts to alleviate the ever-
increasing concerns of better balancing supply and demand. A positive assumption that all …

Featured Application The methodology described in this article is applicable to design
proper management strategies for demand response in smart electricity grids to fairly select …

Climate change, primarily driven by human activities such as burning fossil fuels, is causing
significant long-term changes in temperature and weather patterns. To mitigate these …

In the last decades, cities have increased the number of activities and services that depends
on an efficient and reliable electricity service. In particular, households have had a sustained …

Modern Smart Cities are highly dependent on an efficient energy service since electricity is
used in an increasing number of urban activities. In this regard, Time-of-Use prices for …

Non-intrusive load monitoring (NILM) is among successful approaches aiding residential
energy management. However, the presence of multi-mode appliances and appliances with …