Demonstrating Plug-in Electric Vehicles Smart Charging and Storage Supporting the Grid

Artificial intelligence-based control system for optimized electric vehicle charging

Regents of the University of California, Los Angeles

Recipient

Los Angeles, CA

Recipient Location

26th

Senate District

54th

Assembly District

beenhere

$1,844,906

Amount Spent

closed

Completed

Project Status

Project Result

The final report was published in August 2018: http://www.energy.ca.gov/2018publications/CEC-500-2018-020/CEC-500-2018…. The research demonstrated that large numbers of PEVs can be managed for the benefit of the PEV and facility owners. The recipient successfully developed a system, utilizing existing charging infrastructure and without adding large amounts of power capacity, that could control and balance charging through scheduling algorithms that met the needs of the PEV and facility owners. The recipient also demonstrated how the system can be used by facility (e.g., garage) owners to save money through demand charge reduction and demand response, while supporting their employees or customers.

The Issue

Plug-in electric vehicles (PEV) offer a promising alternative to meet the state's transportation needs. However, the increase of PEVs in California presents both a challenge and opportunity for the grid. Specifically, charging large numbers of PEVs can result in load spikes, if the charging is not coordinated and controlled. However, PEVs can potentially be a resource to the grid when plugged in, providing power when needed by the grid. Research is needed to determine the best approaches to managing a group of PEVs, such as in a parking garage.

Project Innovation

This project installed PEV charging equipment in five sites in Santa Monica to demonstrate scenarios that represented new power needs, including smart charging, peak shaving, load management, and load smoothing while improving power quality and grid stability. The selected sites reflected a variety of scenarios including public charging, fleet charging, integration of solar generation with charging, and integration of energy storage with fast charging. Further, the project assessed the usefulness of vehicle to grid and vehicle to building technologies for allowing bi-directional energy flow and using PEVs as distributed energy storage. The project objective was to provide a model (using simulations to predict grid behavior and emulations using real-world power flows) that could be used by fleet owners or building owners for grid planning, pricing, and incentive decisions.

Project Benefits

Most current electric vehicle service equipment (EVSE) provide uncontrolled charging without using smart algorithms, software, or standard network technologies. This project demonstrated a pre-commercial PEV infrastructure that used a control center, communicating over a wireless communication network, to control the charging operations of the EVSEs using smart charging algorithms. The pre-commercial infrastructure (WINSmartEV TM) developed by UCLA was advanced so that it is able to determine optimized charging and/or vehicle to grid services based on PEV profiles, user preferences, grid-related events, and grid capacities.

Lower Costs

Affordability

Smart charging of vehicles showed that PEVs can participate in demand charge reduction and demand response to enable a site owner or fleet manager to avoid demand charges and take advantage of time-of-use pricing. This saves mon

Greater Reliability

Reliability

Application of the smart charging algorithms can potentially increase grid reliability by using the PEVs as the equivalent of energy storage. This was compared with the grid impacts of the surrounding area to determine the effect

Key Project Members

Project Member

Rajit Gadh

Subrecipients

Lawrence Berkeley National Laboratory logo

Lawrence Berkeley National Laboratory

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