Smart grid and application of big data: Opportunities and challenges

• Main Authors: Mohanty A., Ramasamy A.K., Verayiah R., Bastia S., Swaroop Dash S., Soudagar M.E.M., Yunus Khan T.M., Cuce E.
• Other Authors: 55521129800
• Format: Review
• Published: Elsevier Ltd 2025
• Subjects: Control issues; Demand response; Electrical energy; Energy sector; Grid users; Market players; Smart applications; Smart grid; System operator; Technological advancement; data set; demand analysis; electricity supply; smart grid

The rapid technological advancements in the electrical energy sector are generating a significant volume of data that profoundly influences the operations of system operators, grid users, and GENCOs. In this context, Big Data emerges as a valuable tool for state estimation, addressing control issues, facilitating forecasting, and enhancing the involvement of various market agents and players in the energy sector. Intelligent or smart devices, utilizing information and communication technologies, oversee and manage equipment across the entire energy generation to utilization spectrum. To earn the distinction of being ?intelligent or smart,? substantial data exchange occurs between grid instruments and project or business entities. This exchange of information, tailored to consumption and application needs, facilitates cost-effective optimized bidirectional power flow between power plants and end-use customers. For the effective control, monitoring, and coordination of smart appliances within a smart grid subsystem; the exchange of data is indispensable. Energy companies, however, confront challenges in efficiently managing vast amounts of data. The optimal and apt implementation of smart-grid big data analytics becomes imperative to successfully navigate and address these challenges. This work sheds light on the execution and utilization of BDA (Big Data Analysis) in the smart grid. The advantages, challenges, and consequences of implementing these techniques; and strategies for the computation and transmission of data are proposed here. ? 2024 Elsevier Ltd