4 papers
Comparing Traditional and Reinforcement-Learning Methods for Energy Storage Control
Elinor Ginzburg, Itay Segev, Yoash Levron +1
We aim to better understand the tradeoffs between traditional and reinforcement learning (RL) approaches for energy storage management. More specifically, we wish to better underst…
Bi-Residual Neural Network based Synchronous Motor Electrical Faults Diagnosis: Intra-link Layer Design for High-frequency Features
Qianchao Wang, Leena Heistrene, Yoash Levron +2
In practical resource-constrained environments, efficiently extracting the potential high-frequency fault-critical information is an inherent problem. To overcome this problem, thi…
Leveraging Bitcoin Mining Machines in Demand-Response Mechanisms to Mitigate Ramping-Induced Transients
Elinor Ginzburg-Ganz, Ittay Eyal, Ram Machlev +4
We propose an extended demand response program, based on ancillary service for supplying flexible electricity demand. In our proposed scheme, we suggest a broader management model…
Storage placement policy for minimizing frequency deviation: A combinatorial optimization approach
Ram Machlev, Nilanjan Roy Chowdhury, Juri Belikov +1
As the share of renewable sources is increasing the need for multiple storage units appropriately sized and located is essential to achieve better inertial response. This work focu…