2019 IEEE General Meeting 8/7 Panel Presentation: Cybersecurity and Resiliency for the Power Grid Leveraging Data-Driven Models and Analytics

In recent years, cyber threats to the power grid has been growing both in numbers and sophistication, including two attacks on Ukrainian power grid and several attack attempts targeted towards energy and other critical infrastructures around the world. While data analytics and machine learning techniques have fostered many social, economic, and business advances; they also introduce potential solutions to many current grid cybersecurity challenges. Moreover, the adoption of data-driven models, algorithms, and tools has been gaining momentum for energy management system (EMS) and market applications in the utility industry. Although there are potentially significant benefits from the adoption of data-driven models, algorithms, and applications for the power grid, there are several challenges that need to be addressed, namely, the quality of the data and robust datasets for training, the nature of the models, the effectiveness of the machine learning algorithms, and more importantly the compelling applications that can benefit from such data analytics. The goal of this panel is to discuss the opportunities and challenges associated with data-driven analytics for cybersecurity and resiliency of the grid, and also showcase sample case studies of successful applications and tools. The panel will bring international experts both from academia and industry/government laboratories to have a broad discussion on the practical insights into data-driven analytics and articulate potential R&D directions in cybersecurity and resiliency of the power grid.