AUTHOR=Wang Rujun 

TITLE=Enhancing energy efficiency with smart grid technology: a fusion of TCN, BiGRU, and attention mechanism

JOURNAL=Frontiers in Energy Research

VOLUME=Volume 11 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/energy-research/articles/10.3389/fenrg.2023.1283026

DOI=10.3389/fenrg.2023.1283026

ISSN=2296-598X

ABSTRACT=The smart grid (SG), as a form of intelligent system, has become a pivotal element for the efficient operation of power grids. With the escalating global energy demand and growing environmental concerns, the significance of energy conservation and sustainable energy sources has become increasingly pronounced. Energy supply and management encounter challenges, particularly in energy-intensive sectors like large-scale buildings. These structures require substantial energy supply during specific periods, yet may witness energy wastage during others.The smart grid technology establishes a network that facilitates the flow of both electricity and data. Leveraging this data enables intelligent decision-making, thereby optimizing grid operations. Consequently, the application of smart grid technology in energy conservation has garnered attention and become a focal point of research. Applying smart grid technology to energy conservation in large buildings necessitates accurate prediction of energy requirements.In this study, a TCN-BiGRU model was constructed utilizing spatiotemporal sequence data, complemented by the incorporation of an attention mechanism to forecast future energy consumption. The research findings underscore that the integration of smart grid technology, TCN, BiGRU, and attention mechanisms facilitates precise and stable prediction of energy consumption demands. This approach contributes to the optimization of energy scheduling, enhancement of energy utilization efficiency, and realization of a more intelligent, efficient, and sustainable energy management and utilization strategy.