Advanced Cyber-Physical Infrastructures of Next-Generation Grids with Big Data Penetrations

The special collection Advanced Cyber-Physical Infrastructures of Next-Generation Grids with Big Data Penetrations is available in the ASCE Library (https://ascelibrary.org/jleed9/cyber_physical_infrastructures).

With the increasing integration of Information and communication technologies (ICTs), modern power systems have been rapidly evolving towards complex cyber-physical systems (Mo et al. 2012). The coupling of advanced metering facilities and distributed energy resources not only provides a ubiquitous sensing environment and generates unprecedented data volume to support the decision-making of different grid stakeholders; it also brings new challenges in building the effective cyber-physical infrastructure of future grids. As an example, the 2015 Ukraine blackout event (Liang et al. 2016), the first known blackout event caused by cyber-attackers, has raised worldwide awareness of security and related issues concerning the grid’s cyber-physical infrastructure. Recent technical advances in ICTs provide new opportunities for developing new solutions for cyber-physical infrastructures of future grids in a big data–penetrated environment. In this special collection, we collect original and unpublished submissions on modeling, architecture, security, and analytical methods for the cyber-physical infrastructure of next-generation power grids.

To name a few, Zhang et al. (2019) propose the concept of Power Big Data and discuss its definition, structure, characteristics, and applications. Wang et al. (2019) develop a two-layer power control scheme for controlling distributed energy resources in a cyber-physical microgrid. Zhang and Xu (2019) propose a data-driven preventive control technique for power systems based on an online sequential extreme learning machine. Zhang and Xu’s work demonstrate big data-driven analytics techniques can enhance the security of power grids. Li et al. (2019) develop an integrated task scheduling and resource provisioning model for the dynamic operation of an Internet of Things (IOT) Cloud system for future grids.

We hope the papers collected in this special collection will provide useful references on the research in and development of future energy systems.