Mathematical Approaches to Smart and Huge Energy Systems Design

We are trying to apply a wide range of technique and knowledge such as

Systems and Control Theory, Informatics, Big Data Science, Mathematical Optimization, Software Engineering

to designing a smarter energy system from the perspective of mathematical sciences.

A smart grid is a huge-scale system consisting of a number of events and phenomena at various spatiotemporal scales. For example, not only electromechanical characteristics of generators and transmission networks, but also weather conditions, natural disasters, human behaviors, commercial activities, and so forth are all essential ingredients in a smart grid.

Therefore, it is crucial to fully integrate a wide range of technique and knowledge such as

  • prediction of renewable power generation via machine learning

  • management of human behaviors based on behavioral economics

  • utilization of EVs and FCVs as a new energy carrier

  • UX design to enhance public consciousness about new energy solutions

as well as the control of traditional energy infrastructure. We are working on this challenging problem based on mathematical approaches.

Major Research Topics

(We challenge ourselves to advanced research topics for smart society)

Modularity-in-Design for Decentralized Control Systems and Its Applications

We are studying retrofit control theory for modular design of large-scale control systems where multiple independent entities make their own decision for local system management. Current work is on data-adaptive control based on machine learning techniques. [more]

Commendation for Science and Technology by MEXT

Development of Co-creation Simulation Platform "GUILDA"

We are developing an energy system simulator to support students and researchers in systems and control community for starting energy-related research work, named GUILDA: Grid & Utility Infrastructure Linkage Dynamics Analyzer.

Management of Renewable Power Generators via Robust Optimization

We are developing an energy management method robust against the volatility of renewable power generation, modeled as confidence intervals and stochastic variables. [more]

Market Modeling for Spatio-Temporal Pricing of Distributed Energy Resources

We are developing a spatio-temporal energy market model in terms of an adjustable robust convex program towards smart management of distributed energy resources. Numerical simulations are conducted for analyzing optimal share of future energy resources. [more]

Analysis and Synthesis of Complex Systems via Set-based Modeling

We are studying a systems control theory for complex systems based on the notion of set-based modeling, towards designing smart human and social systems. [more]

Model Reduction Theory for Large-Scale Systems and Its Applications

We are studying a model reduction theory for large-scale network systems and distributed control systems, where the notion of data clustering is applied. [more]