Monitoring and Optimization for Power Grids: A Signal Processing Perspective

TL;DR

This paper discusses how signal processing techniques can enhance smart grid monitoring and optimization by leveraging sensing, communication, and control technologies to improve security, stability, and efficiency.

Contribution

It provides an analytical overview of signal processing applications in power systems, highlighting challenges and future opportunities for smart grid advancements.

Findings

Signal processing enables intelligent monitoring and control in smart grids.

Advanced algorithms improve grid security and stability.

Opportunities exist for growth in energy informatics and optimization.

Abstract

The smart grid vision is to revitalize the electric power network by leveraging the proven sensing, communication, control, and machine learning technologies to address pressing issues related to security, stability, environmental impact, market diversity, and novel power technologies. Significant effort and investment have been committed to architect the necessary infrastructure by installing advanced metering systems and establishing data communication networks throughout the grid. Signal processing methodologies are expected to play a major role in this context by providing intelligent algorithms that fully exploit such pervasive sensing and control capabilities to realize the vision and manifold anticipated benefits of the smart grid. In this feature article, analytical background and relevance of signal processing tools to power systems are delineated, while introducing major challenges and opportunities for the future grid engineering. From grid informatics to inference for monitoring and optimization tools, energy-related issues are shown to offer a fertile ground for signal processing growth whose time has come.