EV and ESS Optimal Control

Batteries play a key role in Smart Grid, and EV and energy storage system (ESS) can be utilized to secure the power grid. EV charging station planning and scheduling, ESS optimal control using reinforcement learning, virtual ESS are active research area where we lead the industry! 

Estimating Battery State of Health

Lithium-ion batteries are used for smart phones, EVs, and even for big ESS with GWh. However, lithium-ion batteries are still expensive, so it needs be carefully managed. Unfortunately, we still do not perfectly know the inside of the battery due to its complicated electrochemical reaction. Hence we apply deep learning techniques to estimate the state-of-health exploiting battery sensing data. Our data-driven method excels the conventional model-based approaches.

Funded by KETEP and Hyundai

EV Charging Control

The penetration of EV is not so high but it will grow fast. Where to build the charging stations? How to route EVs to which charging stations? How to schedule EV charging considering congestion, power flow burden, customer's waiting time, etc? 

Funded by KEPCO

Optimal Control of ESS

In the past energy cannot be stored. Now energy is stored in ESS, which is the fundamental game change. ESS can be used for frequency regulation, smoothing the high variation of renewable generation, reducing the peak load of customers, and increasing the maximum capacity of PV generation. But how to control it? We study optimal control.

Funded by KETEP