37 citations · 73 across the 21 of their papers we have counts for
21 papers
Ensuring Data Privacy in AC Optimal Power Flow with a Distributed Co-Simulation Framework
Xinliang Dai, Alexander Kocher, Jovana Kovačević +5
During the energy transition, the significance of collaborative management among institutions is rising, confronting challenges posed by data privacy concerns. Prevailing research…
Real-Time Coordination of Integrated Transmission and Distribution Systems: Flexibility Modeling and Distributed NMPC Scheduling
Xinliang Dai, Yi Guo, Yuning Jiang +3
This paper proposes a real-time distributed operational architecture to efficiently coordinate intergrated transmission and distribution systems (ITD). At the distribution system l…
A Generalized Stopping Criterion for Real-Time MPC with Guaranteed Stability
Kristína Fedorová, Yuning Jiang, Juraj Oravec +2
Most of the real-time implementations of the stabilizing optimal control actions suffer from the necessity to provide high computational effort. This paper presents a cutting-edge…
Data-Driven Robust Control Using Prediction Error Bounds Based on Perturbation Analysis
Baiwei Guo, Yuning Jiang, Colin N. Jones +1
For linear systems, many data-driven control methods rely on the behavioral framework, using historical data of the system to predict the future trajectories. However, measurement…
Bayesian Optimization of Expensive Nested Grey-Box Functions
Wenjie Xu, Yuning Jiang, Bratislav Svetozarevic +1
We consider the problem of optimizing a grey-box objective function, i.e., nested function composed of both black-box and white-box functions. A general formulation for such grey-b…
Advancing Distributed AC Optimal Power Flow for Integrated Transmission-Distribution Systems
Xinliang Dai, Junyi Zhai, Yuning Jiang +3
This paper introduces a distributed operational solution for coordinating integrated transmission-distribution (ITD) systems regarding data privacy. To tackle the nonconvex challen…
Hypergraph-Based Fast Distributed AC Power Flow Optimization
Xinliang Dai, Yingzhao Lian, Yuning Jiang +2
This paper presents a novel distributed approach for solving AC power flow (PF) problems. The optimization problem is reformulated into a distributed form using a communication str…
Adaptive Data-Driven Prediction in a Building Control Hierarchy: A Case Study of Demand Response in Switzerland
Jicheng Shi, Yingzhao Lian, Christophe Salzmann +1
By providing various services, such as Demand Response (DR), buildings can play a crucial role in the energy market due to their significant energy consumption. However, effectivel…
Primal-Dual Contextual Bayesian Optimization for Control System Online Optimization with Time-Average Constraints
Wenjie Xu, Yuning Jiang, Bratislav Svetozarevic +1
This paper studies the problem of online performance optimization of constrained closed-loop control systems, where both the objective and the constraints are unknown black-box fun…
PIQP: A Proximal Interior-Point Quadratic Programming Solver
Roland Schwan, Yuning Jiang, Daniel Kuhn +1
This paper presents PIQP, a high-performance toolkit for solving generic sparse quadratic programs (QP). Combining an infeasible Interior Point Method (IPM) with the Proximal Metho…
Physically Consistent Multiple-Step Data-Driven Predictions Using Physics-based Filters
Yingzhao Lian, Jicheng Shi, Colin N. Jones
(Extended Version) Data-driven control can facilitate the rapid development of controllers, offering an alternative to conventional approaches. In order to maintain consistency bet…
CONFIG: Constrained Efficient Global Optimization for Closed-Loop Control System Optimization with Unmodeled Constraints
Wenjie Xu, Yuning Jiang, Bratislav Svetozarevic +1
In this paper, the CONFIG algorithm, a simple and provably efficient constrained global optimization algorithm, is applied to optimize the closed-loop control performance of an unk…
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…
Computationally Efficient Reinforcement Learning: Targeted Exploration leveraging Simple Rules
Loris Di Natale, Bratislav Svetozarevic, Philipp Heer +1
Model-free Reinforcement Learning (RL) generally suffers from poor sample complexity, mostly due to the need to exhaustively explore the state-action space to find well-performing…
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…
Distributed data-driven predictive control for cooperatively smoothing mixed traffic flow
Jiawei Wang, Yingzhao Lian, Yuning Jiang +3
Cooperative control of connected and automated vehicles (CAVs) promises smoother traffic flow. In mixed traffic, where human-driven vehicles with unknown dynamics coexist, data-dri…
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…
Scheduling Delays and Curtailment for Household Appliances with Deterministic Load Profiles using MPC
Yingzhao Lian, Yuning Jiang, Colin N. Jones +1
Smart home appliances can time-shift and curtail their power demand to assist demand side management or allow operation with limited power, as in an off-grid application. This pape…
A Proximal-Point Lagrangian Based Parallelizable Nonconvex Solver for Bilinear Model Predictive Control
Yingzhao Lian, Yuning Jiang, Daniel F. Opila +1
Nonlinear model predictive control has been widely adopted to manipulate bilinear systems with dynamics that include products of the inputs and the states. These systems are ubiqui…
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…
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…