Evolution and Applications of Smart Meters : Advancing Energy Management and Efficiency

Abstract

The widespread deployment of smart meters has transformed the energy industry by enabling the collection of detailed electricity consumption data at an unprecedented scale. This evolution, alongside the on-going deregulation of the power sector, particularly in distribution networks, offers significant opportunities to improve the efficiency and sustainability of power grids. However, effectively harnessing this vast data resource remains a considerable challenge. This paper presents an extensive review of smart meter data analytics, with a particular focus on their application within distribution networks. The research is organized around three key stages of analytics: descriptive, predictive, and prescriptive. Through this framework, we examine essential application areas such as load analysis, load forecasting, and load management, and explore the various techniques and methodologies employed to address these challenges. Furthermore, this review highlights emerging research directions, addressing issues such as big data management, the integration of advanced machine learning technologies, the development of new business models, the shift in energy systems, and the critical concerns surrounding data privacy and security. By offering a comprehensive overview, this paper seeks to guide future research and innovation in smart meter data analytics, ultimately contributing to a more secure, reliable and resilient power grid.