Reinforcement Learning-Based Stackelberg Game for Optimizing EV Utilization and Shared Energy Storage System Charging Price
強化学習型Stackelberg Gameに基づくEV利用と共有電池充電価格の最適化
- Delivery
- Available on this site
- Format
- Price
- Non-members (tax incl.)：￥1,100 Members (tax incl.)：￥880
- Publication code
- 20266007
- Paper/Info type
- Proceedings (Autumn)
No.94-26
- Pages
- 1-6(Total 6 p)
- Date of publication
- Oct 2026
- Publisher
- JSAE
- Language
- Japanese
- Event
- 2026 JSAE Annual Congress (Autumn)
Detailed Information
| Author(J) | 1) 大野 結人, 2) 稲垣 伸吉, 3) 鈴木 達也, 4) 中野 日加里 |
|---|---|
| Author(E) | 1) Yuito Ohno, 2) Shinkichi Inagaki, 3) Tatsuya Suzuki, 4) Hikari Nakano |
| Affiliation(J) | 1) 名古屋大学, 2) 南山大学, 3) 名古屋大学, 4) NUVVE JAPAN |
| Affiliation(E) | 1) Nagoya University, 2) Nanzan University, 3) Nagoya University, 4) NUVVE JAPAN |
| Abstract(J) | 太陽光発電の余剰電力活用に向け，地域コミュニティのEVと共有蓄電池を協調運用するエネルギーマネジメントシステムについて検討する．システムの運用手法を構築し，種々の観点から評価を行うことで，実用化に向けた有効性と今後の課題について議論する． Translation |
| Abstract(E) | This study investigates an energy management system that coordinates electric vehicles (EVs) and a shared battery within a local community for the effective utilization of surplus photovoltaic generation. We construct an operation method for the system and evaluate it from various perspectives, thereby discussing its effectiveness and remaining challenges toward practical implementation. |
