H. Hashimoto

Deep Reinforcement Learning for Joint Bidding and Pricing of Load Serving Entity /Author=Xu, Hanchen; Sun, Hongbo; Nikovski, Daniel N.; Kitamura, Shoichi; Mori, Kazuyuki; Hashimoto, Hiroyuki /CreationDate=January 8, 2020 /Subject=Artificial Intelligence, Data Analytics, Electric Systems, Machine Lea

D. Nikovski, Hanchen Xu, Hongbo Sun, 2020 .

Fast Market Clearing Algorithms

Hiroyuki Hashimoto, Arvind U. Raghunathan, Frank E. Curtis, 2018 .

Accelerating convergence to competitive equilibrium in electricity markets

Hiroyuki Hashimoto, Arvind U. Raghunathan, Frank E. Curtis, 2016, 2016 IEEE Power and Energy Society General Meeting (PESGM).

Illegitimate Trade Detection for Electricity Energy Markets

D. Nikovski, Hongbo Sun, K. Mori, 2020, 2020 International Conference on Smart Grids and Energy Systems (SGES).

Long‐Term Generation Scheduling Method with Constrained Numbers of Unit Commitment and Fuel Constraints on Thermal Units

Hiroyuki Hashimoto, Junichi Takahashi, Hideaki Hirano, 2014 .

Deep Reinforcement Learning for Joint Bidding and Pricing of Load Serving Entity

Hanchen Xu, Daniel Nikovski, Hongbo Sun, 2019, IEEE Transactions on Smart Grid.

An integrated approach to dynamic security assessment and control of power systems

Boming Zhang, H. Taoka, Yiwei Zhang, 2000, PowerCon 2000. 2000 International Conference on Power System Technology. Proceedings (Cat. No.00EX409).

Economic benefits comparison between point‐to‐point and multi‐terminal VSC HVDC systems with large‐scale wind farms

Yoshio Izui, Sang-Won Kim, Tomihiro Takano, 2018, IEEJ Transactions on Electrical and Electronic Engineering.

Economic benefit evaluation of multi-terminal VSC HVDC systems with wind farms based on security-constrained optimal power flow

Akihiko Yokoyama, Yoshio Izui, Tomihiro Takano, 2017, 2017 IEEE Manchester PowerTech.