ViNKET, found in 2021 by experts in AI and energy science, focuses on leveraging artificial intelligence to enhance power transmission, optimize electric vehicle batteries, and improve energy storage systems.

With the mission of fostering a sustainable energy future for future generations, We utilizes artificial intelligence to analyze large data sets, enhancing energy system efficiency and longevity. This approach reduces costs and minimizes environmental impact, contributing to a greener future.

ViNKET is backed by ViNK (Vietnam Innovation Network in Korea), a organization established by NIC (Vietnam National Innovation Center), the Ministry of Planning and Investment of Vietnam, aimed at gathering Vietnamese scientists and experts in Korea.

Using alternating direction multiplier method (ADMM)-based distributed OPF solution and extending into various ways such as multiple energy storage system (ESS) coordination, voltage regulation in distribution network

Utilizing deep learning techniques, including DNN, LSTM, CNN, and ResNet, for short-term load forecasting from residential households to large-scale customers, significantly improving accuracy.

Photovoltaic (PV) generation is crucial for lowering carbon footprints and promoting sustainable energy, but it fluctuates with weather conditions. We are utilizing advanced CNN techniques to predict multi-site PV generation and enhance forecasting accuracy.

Batteries are essential for Smart Grid, with EVs and ESS enhancing grid security. Key techniques include EV charging station planning, optimal control of ESS using reinforcement learning, and virtual ESS.

Lithium-ion batteries power smartphones, EVs, and large energy storage systems, but their high cost requires careful management. Due to complex electrochemical reactions, understanding battery internals is challenging. Deep learning techniques are applied to estimate battery state-of-health using sensing data.

The growth of electric vehicles (EVs) is increasing, but their current penetration is low. Key considerations include:

• Locations for charging stations
• Routing EVs to appropriate stations
• Scheduling charging while managing congestion, power flow, and customer wait times.

Energy storage in ESS represents a significant advancement, enabling frequency regulation, smoothing renewable generation variations, reducing peak load, and maximizing PV generation capacity. The focus of solution is on optimal control methods for managing these systems.