The surge of machine learning and increasing data accessibility in buildings provide great
opportunities for applying machine learning to building energy system modeling and …

Energy is the lifeblood of modern societies. In the past decades, the world's energy
consumption and associated CO 2 emissions increased rapidly due to the increases in …

During the past century, energy consumption and associated greenhouse gas emissions
have increased drastically due to a wide variety of factors including both technological and …

The energy consumption by non-residential consumers in China accounts for a significant
proportion of the total energy consumption in the society. Thus, accurate non-residential …

Meeting the energy goals of the European Union requires new ways of managing energy.
Decentralized energy management, cross-commodity energy production and usage …

The transformation of the energy system towards volatile renewable generation, increases
the need to manage decentralized flexibilities more efficiently. For this, precise forecasting of …

A building heating, ventilation, and air-conditioning (HVAC) system consumes large
amounts of energy. Energy consumption prediction is an effective strategy for operation …

Forecasting of electricity consumption for residential and industrial customers is an important
task providing intelligence to the smart grid. Accurate forecasting should allow a utility …

With the development of modern power systems (smart grid), energy consumption prediction
becomes an essential aspect of resource planning and operations. In the last few decades …

In the current energy usage scenario, the demands on energy load and the tariffs on the
usage of electricity are two main areas that require a lot of attention. Energy forecasting is an …