We are conducting research and development using big data and information technology for building and community energy systems, including highly efficient operations that contribute to energy conservation and decarbonization, the use of renewable energy, the creation of healthy and comfortable heat and air environments, and the quantification of the effects of measures based on social dynamics and stakeholder decision-making. We also conduct research and development using big data and information technology.

By utilizing a variety of sensing data obtained from time to time and information technologies such as machine learning, we are able to realize unprecedentedly efficient operation of energy systems. We are also developing advanced simulations that will serve as the basis for this.

By dynamically measuring, processing, and utilizing diverse, high-resolution big data on people, environments, systems, and spaces, we will develop new data-driven environmental controls and behavioral changes aimed at improving health and comfort in individual activity scenes.

By devising energy linkages between supply and demand (buildings and electricity (heat) supply networks), and demand and demand (buildings and buildings), and by quantitatively clarifying the effects of these linkages, we will open up new avenues for the use of renewable energy.

Effective measures are essential for energy conservation and decarbonization. It is necessary to clarify not only the energy benefits but also the non-energy benefits associated with them. We will clarify the methodologies for designing measures and appealing to owners and users.

For more detail: akashilab.com
Principal Investigator: Yasunori Akashi