1 citations · 1 across the 4 of their papers we have counts for
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Optimal design of solar-battery hybrid resources considering multi-market participation under weather and price uncertainty
Hikaru Hoshino, Taiyo Mantani, Eiko Furutani
The rapid growth of variable renewable energy has increased the need for flexible and efficiently coordinated energy resources. In this context, hybrid resources that combine renew…
Sizing of Battery Considering Renewable Energy Bidding Strategy with Reinforcement Learning
Taiyo Mantani, Hikaru Hoshino, Tomonari Kanazawa +1
This paper proposes a novel computationally efficient algorithm for optimal sizing of Battery Energy Storage Systems (BESS) considering renewable energy bidding strategies. Unlike…
A Reinforcement Learning-based Transmission Expansion Framework Considering Strategic Bidding in Electricity Markets
Tomonari Kanazawa, Hikaru Hoshino, Eiko Furutani
Transmission expansion planning in electricity markets is tightly coupled with the strategic bidding behaviors of generation companies. This paper proposes a Reinforcement Learning…
Probabilistic Reachability Analysis of Multi-scale Voltage Dynamics Using Reinforcement Learning
Naoki Hashima, Hikaru Hoshino, Luis David Pabón Ospina +1
Voltage stability in modern power systems involves coupled dynamics across multiple time scales. Conventional methods based on time-scale separation or static stability margins may…
Model Predictive Online Trajectory Planning for Adaptive Battery Discharging in Fuel Cell Vehicle
Katsuya Shigematsu, Hikaru Hoshino, Eiko Furutani
This paper presents an online trajectory planning approach for optimal coordination of Fuel Cell (FC) and battery in plug-in Hybrid Electric Vehicle (HEV). One of the main challeng…
Combined Plant and Control Co-design via Solutions of Hamilton-Jacobi-Bellman Equation Based on Physics-informed Learning
Kenjiro Nishimura, Hikaru Hoshino, Eiko Furutani
This paper addresses integrated design of engineering systems, where physical structure of the plant and controller design are optimized simultaneously. To cope with uncertainties…