PNNL

Efficient Learning of Power Grid Voltage Control Strategies via Model-based Deep Reinforcement Learning

Guest Editorial: Special section on Resilient Control of Cyber-Physical Power and Energy Systems

Physics-informed Deep Reinforcement Learning-based Adaptive Generator Out-of-step Protection for Power Systems

High-Fidelity Dataset Generation for Sensor Anomalies in Power Grids using Hardware-in-the-Loop Testbed

Spokane Eco-District Campus Performance under Alternative Electricity Rates: Benefits for virtual power plant participants and suppliers

A Hybrid Dynamic/Steady-State Tool with Protection Simulation for Cascading-Outage Analysis of Extreme Events in Power Systems

Cassidy Anderson selected to participate in the Epistimi-Women in STEMM Leadership Workshop

Anderson is one of only 25 women from throughout the world selected to participate in the Epistimi-Women in STEMM Leadership Workshop on “Women in the Energy Sector,” held July 15–19 in Athens, Greece.

Are Microgrids a Key to Grid Resiliency?

With an eye on renewable, accessible, and resilient power, PNNL researchers show hyper-local microgrids are a viable option, if designed with the right mix of sources.

Slowing Climate Change is Possible—Here’s How Nations Could Make it Happen

Policy changes in power, energy, buildings, and more could help slow global temperature rise, according to a new report with co-authors from PNNL’s Joint Global Change Research Institute.

E-COMP

The E-COMP Initiative is creating new capabilities that enable the optimized design and operation of energy systems subject to multiple objectives and with high levels of power electronics.