The economic growth of every nation is highly related to its electricity infrastructure, network,
and availability since electricity has become the central part of everyday life in this modern …

Power imbalances from fluctuating renewable electricity generators are counteracted by
often expensive flexibility services. Heating, cooling, and air-conditioning (HVAC) of …

Power grids are transforming into flexible, smart, and cooperative systems with greater
dissemination of distributed energy resources, advanced metering infrastructure, and …

The key challenge for household load forecasting lies in the high volatility and uncertainty of
load profiles. Traditional methods tend to avoid such uncertainty by load aggregation (to …

This paper presents and discusses data-driven predictive models for the energy use of
appliances. Data used include measurements of temperature and humidity sensors from a …

One of the most important research topics in smart grid technology is load forecasting,
because accuracy of load forecasting highly influences reliability of the smart grid systems …

Literature is rich in methodologies for “aggregated” load forecasting which has helped
electricity network operators and retailers in optimal planning and scheduling. The recent …

In this paper, we introduce a data set of appliance start-up measurements from several
locations. The appliances were recorded with a low-cost custom sound card meter. The …

As the new generation of smart sensors is evolving towards high sampling acquisitions
systems, the amount of information to be handled by learning algorithms has been …

Renewable energy sources are now being used with buildings like PV panels.
Consequently, short-term household load forecast plays an important role in managing …