most citedDistributed Optimal Power Flow for VSC-MTDC Meshed AC/DC Grids Using ALADIN

37 citations · 42 across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG20221 cited

Physically Consistent Neural ODEs for Learning Multi-Physics Systems

Muhammad Zakwan, Loris Di Natale, Bratislav Svetozarevic +3

Despite the immense success of neural networks in modeling system dynamics from data, they often remain physics-agnostic black boxes. In the particular case of physical systems, th…

eess.SY2022

Uncertainty-aware Flexibility Envelope Prediction in Buildings with Controller-agnostic Battery Models

Paul Scharnhorst, Baptiste Schubnel, Rafael E. Carrillo +2

Buildings are a promising source of flexibility for the application of demand response. In this work, we introduce a novel battery model formulation to capture the state evolution…

math.OC20224 cited

Lower Bounds on the Worst-Case Complexity of Efficient Global Optimization

Wenjie Xu, Yuning Jiang, Emilio T. Maddalena +1

Efficient global optimization is a widely used method for optimizing expensive black-box functions such as tuning hyperparameter, and designing new material, etc. Despite its popul…

cs.IT2022

Over-the-Air Federated Learning via Second-Order Optimization

Peng Yang, Yuning Jiang, Ting Wang +3

Federated learning (FL) is a promising learning paradigm that can tackle the increasingly prominent isolated data islands problem while keeping users' data locally with privacy and…

math.OC202237 cited

Distributed Optimal Power Flow for VSC-MTDC Meshed AC/DC Grids Using ALADIN

Junyi Zhai, Xinliang Dai, Yuning Jiang +4

The increasing application of voltage source converter (VSC) high voltage direct current (VSC-HVDC) technology in power grids has raised the importance of incorporating DC grids an…