In recent years, the terms “Smart Energy” and “Smart Energy Systems” have been used to
express an approach that reaches broader than the term “Smart grid”. Where Smart Grids …

Ever growing population and progressive municipal business demands for constructing new
buildings are known as the foremost contributor to greenhouse gasses. Therefore …

How to predict building energy performance with low computational times and good
reliability? The study answers this question by employing artificial neural networks (ANNs) to …

The path towards energy sustainability is commonly referred to the incremental adoption of
available technologies, practices and policies that may help to decrease the environmental …

District heating is an efficient way to provide heat to residential, tertiary and industrial users.
Heat is often produced by CHP (combined heat and power) plants, usually designed to …

Energy planning can be defined as a roadmap for meeting the energy needs of a nation and
is accomplished by considering multiple factors such as technology, economy, environment …

Refined control is significant to ensure on-demand heating and efficient operation in district
heating system (DHS). This paper proposes a dynamic control strategy for substations …

Abstract Machine learning (ML) has been recognised as a powerful method for modelling
building energy consumption. The capability of ML to provide a fast and accurate prediction …

This paper presents the building heating demand prediction model with occupancy profile
and operational heating power level characteristics in short time horizon (a couple of days) …

The cost of heat savings in buildings increase as more heat savings are achieved and
hence, alternatives other than savings typically become more economically feasible at a …