posted Apr 6, 2016, 9:26 AM by Samveg Saxena
updated Apr 6, 2016, 9:39 AM
After a long time of not updating this news section, there are many exciting updates to share:
- V2G-Sim was a recipient of a 2015 R&D 100 Award. See here for more info about all of Berkeley Lab's 2015 R&D 100 awards.
- The V2G-Sim team was successful in a large proposal in simulations for vehicle-grid integration to the U.S. Department of Energy.
- A new study is underway to quantify the impact of vehicle-grid services on vehicle battery degradation. Stay tuned for upcoming publications.
- A new study is underway to quantify that impact that plug-in vehicles can have to mitigate the challenges introduced for grid systems by large amounts of intermittent renewables generation, namely in mitigating sharp up-ramps, sharp down-ramps, valleys, and peaks in the load profiles. Stay tuned for upcoming publications.
The new DOE vehicle-grid integration project (#2 above) has the following central objectives:
- Determining the feasibility of VGI by quantifying the potential value, cost, complexity, and risks in different VGI implementations
- Allocating available value among stakeholders and determining pathways for electrification of transportation to enable beneficial grid services such as mitigating renewables intermittency
Within this project, the vehicle-grid simulations will be applied towards several targeted case studies to assess VGI feasility:
- Quantifying the feasibility (i.e. cost, value, complexity, risk, etc.) for VGI with collections of vehicles offering many available grid services.
- Determining how value is distributed amongst stakeholders, including drivers, aggregators, utility shareholders and ratepayers, etc.
- Quantifying the ability for PEVs to mitigate the variability and costs of renewables intermittency at various temporal and spatial scales.
- Quantifying the magnitude and costs from battery degradation for several VGI services.
Finally, the VGI simulation tools will be applied towards developing strategies to aggregate and control large collections of vehicles by:
- Assess real-time scheduling and control strategies for dispatching capacity from aggregate collections of vehicles (e.g. EDF, LLF, model-predictive, etc.)
- Development of virtual battery models for integrating capacity from aggregate collections of vehicles into ISO, RTO, and Utility operations
The project will last three years.