Details of the Initiative

●Efforts in the class: Lecture subject “Network design special lecture A” of the Department of Network Design focuses on carbon dioxide reduction and cost reduction to build a sustainable society effectively. To this end, we are learning about V2G (Vehicle to Grid), which is the coordination of Electric Vehicles (EVs) and power networks; smart communities, which are the coordination of renewable energy such as photovoltaic (PV) and wind power generation with Energy Storage Systems (ESS); DR (Demand Response), which balances power generation and power demand on the demand side without the need for additional thermal power plants; and blockchain technology, which enables P2P (Peer to Peer) transactions of renewable energy. In addition, lecture subject “Introduction to intelligent informatics,” covers deep learning neural networks that realize real-time prediction and control in a sustainable society, evolutionary computation that enables global optimization, and Data Mining that discovers rules from a data base by Machine Learning.

● Efforts through research activities: we have conducted research on the following topics: (1) Photovoltaic power output prediction with deep Boltzmann machine; (2) Wind power output prediction with recurrent deep neural network LSTM (Long Short Term Memory); (3) Global optimization of power peak-shifting DR with evolutionary computation

Smart grid components (Smart Meters, PMU (Phasor Measurement Unit), Photovoltaic & Wind power, Energy Storage Systems, Electric Vehicles (EVs), Demand Response, Power Markets, prosumers)
Neural network with deep Boltzmann machine
Structure of recurrent deep neural network LSTM