Sandia National Laboratories
Exceptional service in the national interest
Analytics is an important component of Sandia’s energy storage research. We perform research that develops and analyzes storage-based solutions to a variety of technical challenges for the electrical grid such as improving grid reliability and resilience and enhancing renewable energy integration. Our research includes developing/validating models and simulations such as QuESt, a free, open source, Python-based application suite for energy storage simulation and analysis developed to bring Sandia energy storage analytics research tools to your desktop. Sandia also evaluates the economic and technical benefits of energy storage systems and develops optimal control schemes and energy management systems.
The key elements of energy storage analytics at Sandia include:
For the efficient operation of large scale energy storage systems, there are two main engineering challenges that need to be adequately addressed: 1) optimal control of grid energy storage to guarantee safe operation while delivering the maximum benefit, and 2) coordination of multiple grid energy storage systems that vary in size and technology.
Our research in this area focuses on addressing these challenges by developing the core functions of ESMS software (e.g., optimal dispatch, state estimation and visualization) and core capabilities of ESMS hardware (e.g., sensoring, control and communication).