Batteries, particularly lithium-ion batteries, play an important role in powering our modern
world, from portable devices to electric vehicles and renewable energy storage. However …

Building energy consumption prediction models are powerful tools for optimizing energy
management. Among various methods, artificial neural networks (ANNs) have become …

The application of Photovoltaic (PV) system in buildings is growing rapidly in response to the
need for clean energy sources and building decarbonization targets. Nonetheless …

This study evaluates the effectiveness of the long and short-term (LSTM) implementation
with a particular emphasis on assessing the impact of transfer learning techniques in …

Building energy consumption accounts for about 40% of global primary energy use and 30%
of worldwide greenhouse gas (GHG) emissions. Among the energy-related factors present …

Radiant air conditioning (RAC) systems are widely used because of the advantage of higher
thermal comfort compared to convection systems. However, RAC systems exhibit …

This study investigates enhancing the self-consumption of solar panels by integrating
thermal and electrical energy storage using lithium-ion batteries in a duplex building over a …

The current ultra-short-term cooling load forecasting models have not given due attention to
the data pre-processing stage. In this paper, multivariate signal decomposition methods …

In air-conditioning load predicting, the mainstream methods mainly include mechanism
model based methods and data-driven prediction methods. The mechanism model can …

This work presents the prediction of thermal drawdown of an enhanced geothermal system
(EGS) using artificial neural network (ANN). A three-dimensional numerical model of EGS …