Control and Optimisation of Power Grids Using Smart Meter Data: A Review.

Area of Science:

• Electrical Engineering
• Computer Science
• Energy Systems

Background:

• Smart grids face complexity from renewable energy integration and electric vehicles (EVs).
• Traditional model-based approaches struggle with the variability and low inertia of modern power systems.
• Advanced Metering Infrastructure (AMI) enables real-time data collection from consumers.

Purpose of the Study:

• To comprehensively review smart meter applications in power grid control and optimization.
• To explore the role of smart meters in facilitating the renewable energy transition.
• To identify challenges and opportunities associated with smart meter implementation in smart grids.

Main Methods:

• Literature review of state-of-the-art smart meter applications.
• Analysis of data-driven algorithms for power system operations and planning.
• Examination of privacy-preserving and cybersecurity challenges.

Main Results:

• Smart meters facilitate data-driven algorithms for infrastructure planning, forecasting, and demand-side management.
• Applications include integrating EVs, 5G/6G networks, and cloud computing.
• Key challenges include privacy preservation and cybersecurity for data-driven approaches.

Conclusions:

• Smart meters are essential for managing complex smart grids and enabling a renewable energy future.
• Addressing privacy and cybersecurity is critical for realizing the full potential of smart metering.
• Future research should focus on the interplay between smart meters, smart grids, and emerging technologies.