Data-Driven Operation of Autonomous Power Systems 

Lecturers

Florian Dörfler

Saverio Bolognani

Abstract

The electric power system is currently undergoing a period of unprecedented changes. Centralized bulk generation based on fossil fuel and interfaced with synchronous machines is substituted by distributed generation based on renewables and interfaced with power converters. Accordingly, the entire system operation is undergoing several paradigm shifts spanning decentralized device-level control, distributed coordination of energy sources, and real-time system-level optimization. Further, classical decision-making methods are challenged by the lack of accurate models concerning system dynamics, loads, and low-voltage grids. In this course, we give a tutorial introduction to emerging thrusts in the control and optimization of future autonomous power systems with distributed generation. The solutions that we present rely on recent advances in data-driven and distributed control. 

Content

• Basics of power system modeling, dynamics, analysis, & control

• Decentralized control of  converter-based resources in low-inertia systems

• Online feedback optimization for power system operation

• Data-driven approaches for control and real-time optimization

• Co-design of automation and incentives for the procurement of grid services