Electricity Generation and Delivery

Principle Power (PPI) plans to lead a consortium of public and private institutions to develop, validate, and operate the world’s first digital twin software tailored to floating offshore wind applications. This digital twin model will be a real-time, high-fidelity numerical representation of the WindFloat Atlantic Project, which is composed of three semi-submersible platforms and the world’s largest FOWTs ever installed in the ocean. A fleet of interconnected ocean buoys that will be deployed at the WFA site will estimate and predict the local wind and wave environmental conditions.

Traditional wind turbines have grown larger to reach the higher wind speeds found at greater heights and enable the blades to intercept a larger area of wind. The stiffness required to hold up the blades and nacelle has caused turbines to become extremely heavy and consequently expensive.

The National Renewable Energy Laboratory (NREL) in collaboration with the University of Maine (UMaine) will develop and execute the Floating Offshore-wind and Controls Advanced Laboratory (FOCAL) experimental program. The project’s goal is to generate the first public FOWT scale-model dataset to include advanced turbine controls, floating hull load mitigation technology, and hull flexibility. Current FOWT numerical tools require new capabilities to adequately capture advanced designs based upon control co-design methods.

Southwest Research Institute (SwRI) is developing a battery management system to track the performance characteristics of lithium-ion batteries during charge and discharge cycles to help analyze battery capacity and health. No two battery cells are alike—they differ over their life-times in terms of charge and discharge rates, capacity, and temperature characteristics, among other things. In SwRI's design, a number of strain gauges would be strategically placed on the cells to monitor their state of charges and overall health during operation.

Feasible will develop a non-invasive, low-cost, ultrasonic diagnostic system that links the electrochemical reactions taking place inside a battery with changes in how sound waves propagate through the battery. This Electrochemical Acoustic Signal Interrogation (EASI) analysis will bridge the gap in battery diagnostics between structural insights and electrical measurements, offering both speed and scalability. The physical processes of a battery that affect performance are nearly impossible to monitor with standard diagnostic methods.

Lawrence Livermore National Laboratory (LLNL) is developing a wireless sensor system to improve the safety and reliability of lithium-ion (Li-Ion) battery systems by monitoring key operating parameters of Li-Ion cells and battery packs. This system can be used to control battery operation and provide early indicators of battery failure. LLNL's design will monitor every cell within a large Li-Ion battery pack without the need for large bundles of cables to carry sensor signals to the battery management system.

University of Washington (UW) is developing a predictive battery management system that uses innovative modeling software to manage how batteries are charged and discharged, helping to optimize battery use. A significant problem with today's battery packs is their lack of internal monitoring capabilities, which interferes with our ability to identify and manage performance issues as they arise.

Eaton is developing advanced battery and vehicle systems models that will enable fast, accurate estimation of battery health and remaining life. The batteries used in hybrid vehicles are highly complex and require advanced management systems to maximize their performance. Eaton's battery models will be coupled with hybrid powertrain control and power management systems of the vehicle enabling a broader, more comprehensive vehicle management system for better optimization of battery life and fuel economy.

Robert Bosch is developing battery monitoring and control software to improve the capacity, safety, and charge rate of electric vehicle batteries. Conventional methods for preventing premature aging and failures in electric vehicle batteries involve expensive and heavy overdesign of the battery and tend to result in inefficient use of available battery capacity.

Det Norske Veritas (DNV KEMA) is testing a new gas monitoring system developed by NexTech Materials to provide early warning signals that a battery is operating under stressful conditions and at risk of premature failure. As batteries degrade, they emit low level quantities of gas that can be measured over the course of a battery's life-time. DNV KEMA is working with NexTech to develop technology to accurately measure these gas emissions.