Zobrazeno 1 - 10
of 165
pro vyhledávání: '"Mukherjee, Sayak"'
Autor:
Mukherjee, Sayak, Hossain, Ramij Raja, Chatterjee, Kaustav, Kundu, Soumya, Kwon, Kyung-Bin, Nekkalapu, Sameer, Elizondo, Marcelo
This paper addresses the following fundamental research question: how does the integration of grid-forming inverters (GFMs) replacing conventional synchronous generators (SGs) impact the slow coherent eigen-structure and the low-frequency oscillatory
Externí odkaz:
http://arxiv.org/abs/2405.09675
Effective collaboration among heterogeneous clients in a decentralized setting is a rather unexplored avenue in the literature. To structurally address this, we introduce Model Agnostic Peer-to-peer Learning (coined as MAPL) a novel approach to simul
Externí odkaz:
http://arxiv.org/abs/2403.19792
Autor:
Ferdous, S M, Neff, Reece, Peng, Bo, Shuvo, Salman, Minutoli, Marco, Mukherjee, Sayak, Kowalski, Karol, Becchi, Michela, Halappanavar, Mahantesh
A coloring of a graph is an assignment of colors to vertices such that no two neighboring vertices have the same color. The need for memory-efficient coloring algorithms is motivated by their application in computing clique partitions of graphs arisi
Externí odkaz:
http://arxiv.org/abs/2401.06713
This paper develops a risk-aware controller for grid-forming inverters (GFMs) to minimize large frequency oscillations in GFM inverter-dominated power systems. To tackle the high variability from loads/renewables, we incorporate a mean-variance risk
Externí odkaz:
http://arxiv.org/abs/2312.10635
Autor:
Mukherjee, Sayak, Hossain, Ramij R., Mohiuddin, Sheik M., Liu, Yuan, Du, Wei, Adetola, Veronica, Jinsiwale, Rohit A., Huang, Qiuhua, Yin, Tianzhixi, Singhal, Ankit
Improving system-level resiliency of networked microgrids is an important aspect with increased population of inverter-based resources (IBRs). This paper (1) presents resilient control design in presence of adversarial cyber-events, and proposes a no
Externí odkaz:
http://arxiv.org/abs/2311.12264
Autor:
Rahman, Aowabin, Bhattacharya, Arnab, Ramachandran, Thiagarajan, Mukherjee, Sayak, Sharma, Himanshu, Fujimoto, Ted, Chatterjee, Samrat
Search and Rescue (SAR) missions in remote environments often employ autonomous multi-robot systems that learn, plan, and execute a combination of local single-robot control actions, group primitives, and global mission-oriented coordination and coll
Externí odkaz:
http://arxiv.org/abs/2212.10064
Autor:
Mukherjee, Sayak, Hossain, Ramij R., Liu, Yuan, Du, Wei, Adetola, Veronica, Mohiuddin, Sheik M., Huang, Qiuhua, Yin, Tianzhixi, Singhal, Ankit
This paper presents a novel federated reinforcement learning (Fed-RL) methodology to enhance the cyber resiliency of networked microgrids. We formulate a resilient reinforcement learning (RL) training setup which (a) generates episodic trajectories i
Externí odkaz:
http://arxiv.org/abs/2212.08973
Load frequency control (LFC) is a key factor to maintain the stable frequency in multi-area power systems. As the modern power systems evolve from centralized to distributed paradigm, LFC needs to consider the peer-to-peer (P2P) based scheme that con
Externí odkaz:
http://arxiv.org/abs/2209.12361
Networking of microgrids can provide the operational flexibility needed for the increasing number of DERs deployed at the distribution level and supporting end-use demand when there is loss of the bulk power system. But, networked microgrids are vuln
Externí odkaz:
http://arxiv.org/abs/2209.07385
We present a learning-based predictive control methodology using the differentiable programming framework with probabilistic Lyapunov-based stability guarantees. The neural Lyapunov differentiable predictive control (NLDPC) learns the policy by const
Externí odkaz:
http://arxiv.org/abs/2205.10728