4 papers
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…