Advances in Energy Efficiency through Neural-Network-Based Models

Abstract

Currently, new technologies and approaches are continuously and rapidly being introduced and implemented in energy systems. In this scenario, machine learning plays a crucial role in many areas such as building design and construction, smart cities, and renewable energy systems, among many others. Consequently, measuring and modelling energy consumption is key to improving energy efficiency in these areas of application. Recently, certain types of machine learning methods, namely artificial neural networks, are growing in popularity in terms of dealing with energy-related data for energy modelling and decision-making processes. Traditionally, energy efficiency has been addressed using standard control methods in the energy industry. However, the application of intelligent techniques such as artificial neural networks has led to new and sophisticated solutions for energy efficiency improvement. This Special Issue aims to provide comprehensive coverage of energy efficiency and energy modelling using artificial neural networks