Zobrazeno 1 - 10
of 30
pro vyhledávání: '"Bose, Shourya"'
Accurate short-term energy consumption forecasting for commercial buildings is crucial for smart grid operations. While smart meters and deep learning models enable forecasting using past data from multiple buildings, data heterogeneity from diverse
Externí odkaz:
http://arxiv.org/abs/2411.14421
The advent of smart meters has enabled pervasive collection of energy consumption data for training short-term load forecasting models. In response to privacy concerns, federated learning (FL) has been proposed as a privacy-preserving approach for tr
Externí odkaz:
http://arxiv.org/abs/2404.01517
This paper introduces a novel data-driven constraint screening approach aimed at accelerating the solution of convexified AC optimal power flow (C-OPF) by eliminating non-binding constraints. Our constraint screening process leverages a novel mixture
Externí odkaz:
http://arxiv.org/abs/2312.07276
The widespread adoption of smart meters provides access to detailed and localized load consumption data, suitable for training building-level load forecasting models. To mitigate privacy concerns stemming from model-induced data leakage, federated le
Externí odkaz:
http://arxiv.org/abs/2312.00036
Autor:
Bose, Shourya, Kim, Kibaek
The advent of smart meters has enabled pervasive collection of energy consumption data for training short-term load forecasting (STLF) models. In response to privacy concerns, federated learning (FL) has been proposed as a privacy-preserving approach
Externí odkaz:
http://arxiv.org/abs/2309.13194
The optimal power flow (OPF) problem is an important mathematical program that aims at obtaining the best operating point of an electric power grid. The optimization problem typically minimizes the total generation cost subject to certain physical co
Externí odkaz:
http://arxiv.org/abs/2305.00400
Publikováno v:
IEEE Global Communications Conference (GLOBECOM) 2022
Non-convex AC optimal power flow (AC-OPF) is a fundamental optimization problem in power system analysis. The computational complexity of conventional solvers is typically high and not suitable for large-scale networks in real-time operation. Hence,
Externí odkaz:
http://arxiv.org/abs/2212.03977
Autor:
Bose, Shourya
In this note we prove that the optimum value of a second-order cone program (SOCP) is convex in the right hand side (RHS) parameter.
Comment: Result found to be not novel
Comment: Result found to be not novel
Externí odkaz:
http://arxiv.org/abs/2208.13941
Mobile energy storage systems (MESS) offer great operational flexibility to enhance the resiliency of distribution systems in an emergency condition. The optimal placement and sizing of those units are pivotal for quickly restoring the curtailed load
Externí odkaz:
http://arxiv.org/abs/2205.11992
Autor:
Bose, Shourya, Zhang, Yu
Distributed energy storage systems (ESSs) can be efficiently leveraged for load restoration (LR) for a microgrid (MG) in island mode. When the ESSs are owned by third parties rather than the MG operator (MGO), the ESS operating setpoints may be consi
Externí odkaz:
http://arxiv.org/abs/2204.13897