الفهرس 
SPOT MARKET DEVELOPMENTS AND ELECTRIC VEHICLE AGGREGATION CHALLENGESOnly 14 pages are availabe for public view
 |  | from | 92 |  |  |
| | | from | 92 | | |
Abstract
Global efforts to reduce greenhouse gases emissions by 2050 have set the aim of many countries to shift their electricity generation to clean renewable energy sources. To ensure safe transition, the energy system flexibility should be improved to compensate for renewable energy intermittent generation.
The recent advances of Electric Vehicle (EV) related technologies, such as Vehicle-to-Grid (V2G) integration, fast charging infrastructure, advanced Li-ion batteries, and smart grid communication and monitoring features, have the potential to transform passive and inflexible EV loads into active and flexible grid assets. Using these technologies through coordinated charging and discharging of EVs offers valuable compensation for renewables variability. However, this raises many research challenges. One of these challenges is to transform EVs data into marketable products that allows EVs’ aggregator to participate in wholesale energy market.
Implementing successful aggregated charging strategies for electric vehicles to participate in wholesale market requires an accurate battery model that can operate at scale while capturing critical battery dynamics. Existing models either lack precision or pose computational challenges for fleet-level coordination. To our knowledge, most of the literature widely adopts battery models that neglect critical battery polarization dynamics favoring scalability over accuracy denoted as Constant Power Models (CPMs).
This PhD thesis proposes a novel Linear Battery Model (LBM) intended specifically for use in aggregated charging strategies. The LBM considers battery dynamics through a linear representation, addressing limitations of existing models while maintaining scalability. The model dynamic behavior is evaluated for the four commonly used lithium-ion chemistries in EVs: Lithium Iron Phosphate (LFP), Nickel Manganese Cobalt (NMC), Lithium Manganese Oxide (LMO), and Nickel Cobalt Aluminum (NCA). Results showed that the LBM closely matches the high-fidelity Thevenin Equivalent Circuit Model (Th-ECM) with substantially improved accuracy over the CPM, especially at higher charging rates. Finally, several case studies were carried out for bidding in wholesale energy market, that proved the ability of the model to scale compared to Th-ECM with more trackable bids compared to CPM.
We believe this work makes an important contribution by advancing battery modeling capabilities critical for optimizing aggregated vehicle-grid integration. The proposed LBM holds promise to enhance the performance of aggregated charging strategies and facilitate more efficient grid support through more sustainable electric transportation.