Hirohito Yamada received his B.E. degree in electronics engineering from Kanazawa University, Japan in 1981, and his M.E. and Ph.D. degrees in electronics engineering from Tohoku University, Japan in 1983 and 1987, respectively. In 1987, he joined NEC Corporation, where he conducted research on semiconductor lasers and Si nano-photonic devices for optical fiber communication systems. In 2006, he became a professor at Tohoku University, where he has been dedicated to teaching communication engineering and researching photonic integrated devices. Following the Great East Japan Earthquake in 2011, he expanded his research to include solar power generation and DC microgrids. He even built an off-grid house and has lived without purchasing electricity from the utility company for over eight years. Although he retired from Tohoku University in March 2024, he still continues his research on autonomous decentralized cooperative controlled microgrids at the International Research Institute of Disaster Science (IRIDeS), Tohoku University, from April onwards.

Title: Resilient DC Microgrid Enabled by Battery-Integrated DC-Bus

In residential areas, the electric power grid—an essential lifeline—must exhibit strong resilience against disasters and other disruptions. Microgrids based on Autonomous Distributed Cooperative Control (ADCC) demonstrate excellent recovery capabilities, enabling partial power supply even when parts of the grid are damaged by utilizing surviving segments. This inherent resilience makes ADCC-based microgrids particularly well-suited for residential communities. We propose an ADCC DC microgrid architecture featuring a battery-integrated DC bus, in which multiple small-scale batteries are distributed and directly connected to the DC bus. A physical testbed has been constructed, and comprehensive validation experiments are currently underway. In this presentation, we will discuss how integrating batteries into the DC bus enhances grid stability and simplifies control mechanisms.

Achara Pichetjamroen is an Assistant Professor at the Faculty of Electrical Engineering, Kasetsart University, Thailand, where she also serves as the Program Director for the AI and IoT Master's program. She received her Ph.D. in Engineering from Osaka University, Japan, in 2016. She also holds an M.Eng. from King Mongkut's Institute of Technology Ladkrabang (KMITL) in 2009 and a B.Eng. (First Class Honors) from the same institution in 2006. Her research interests include power electronics in power systems, with a focus on renewable energy integration and energy storage technologies.

Dr. Muhammad Waseem is an Assistant Professor in Business Analytics at Maynooth University’s School of Business. His research spans sustainable energy systems, AI/ML, and data-driven decision support, with a focus on demand response, prosumer flexibility, EV integration, and digital-twin–enabled optimization for communities and microgrids. Previously, he was a Marie Skłodowska-Curie Research Fellow at Maynooth University (IVI/Lero, SYMECO project) and a Postdoctoral Fellow at The Hong Kong Polytechnic University, with earlier research and teaching roles linked to Zhejiang University and UET Taxila.
Dr. Waseem has authored and co-authored papers across IEEE, Elsevier, and IET venues and has presented at international conferences including AUPEC, UPEC, KPEC, and iSPEC. His recognitions include an Academic Research Excellence Award at Zhejiang University and inclusion among the 2024 “Top 2% Scientists” in the energy field. He regularly serves as a reviewer for leading journals and collaborates with industry and public-sector partners to translate research into deployable solutions that enhance resilience, reduce emissions, and support community energy transitions.

Title: Forecast → Optimize → Trade: Data-Driven Community Energy under Dynamic Tariffs

Short-term PV/load forecasting feeds an optimization layer for battery energy storage (BESS), and finally a market layer where homes trade power under dynamic tariffs. I’ll show why a Bi-Directional LSTM outperforms other tested architectures for forecasting, how a MILP scheduler translates predictions into charge/discharge actions, and how a simple auction with slot-level dynamic prices turns surplus into earnings. We’ll discuss comfort/resilience via SOC management, evidence that cumulative earnings can exceed costs, and why dynamic tariffs boost exports and raise average SOC across households.