Yuning Jiang

Federated learning (FL), as an emerging edge artificial intelligence paradigm, enables many edge devices to collaboratively train a global model without sharing their private data. To enhance the training efficiency of FL, various algorithms have been prop ...

2022

Distributionally Robust Joint Chance-Constrained Dispatch for Integrated Transmission-Distribution Systems via Distributed Optimization

This paper focuses on the distributionally robust dispatch for integrated transmission-distribution (ITD) systems via distributed optimization. Existing distributed algorithms usually require synchronization of all subproblems, which could be hard to scale ...

2022

Distributed adjustable robust optimal power-gas flow considering wind power uncertainty

The rapid uptake of natural gas-fired units in energy systems poses significant challenges in coordinating the electricity and gas systems. Besides, the uncertainty caused by integrated renewable energy such as wind power raises more requirements on the ro ...

2022

Advancing Distributed AC Optimal Power Flow for Integrated Transmission-Distribution Systems

This paper introduces a distributed operational solution for integrated transmission-distribution (ITD) system management. A fundamental challenge in designing distributed approaches for AC optimal power flow (OPF) problems in ITD systems is the nonconvexi ...

IEEE COMPUTER SOC2025

Microservice Deployment for Satellite Edge AI Inference via Deep Reinforcement Learning

Artificial intelligence (AI) is critical in evolving 5G and developing 6G networks, running on edge devices, and solving resource management challenges. The burgeoning number of edge devices draws attention to the potential of low-earth orbit (LEO) satelli ...

Institute of Electrical and Electronics Engineers Inc.2024

A Distributionally Robust Model Predictive Control for Static and Dynamic Uncertainties in Smart Grids

The integration of various power sources, including renewables and electric vehicles, into smart grids is expanding, introducing uncertainties that can result in issues like voltage imbalances, load fluctuations, and power losses. These challenges negative ...

2024

Decentralized coordination between active distribution network and multi-microgrids through a fast decentralized adjustable robust operation framework

Due to the autonomous characteristic and heterogeneity of the individual agents in active distribution network (ADN) with multi-microgrids (MMG), this paper proposes a fully decentralized adjustable robust operation framework achieving the coordinated oper ...

ELSEVIER2023

Hypergraph-Based Fast Distributed AC Power Flow Optimization

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 structure corresponding to a hypergraph, by which complex relationships between ...

IEEE2023

Microservice Migration in Hybrid Satellite-Terrestrial Networks for Autonomous Vehicles

Autonomous vehicles (AVs) have the potential to enhance road safety, reduce fuel consumption, and alleviate traffic congestion. However, the computational demands of processing large volumes of sensory data for tasks like motion planning and trajectory for ...

2025

A Peer-to-peer Joint Energy and Reserve Market Considering Renewable Generation Uncertainty: a Generalized Nash Equilibrium Approach

Yuning Jiang, Lu Wang

Peer-to-peer energy trading enhances distribution network resilience by reducing energy demand from central power plants and enabling distributed energy resources to support critical loads after extreme events. However, adequate reserves from main grids ar ...

WILEY2024

Self-triggered Control with Energy Harvesting Sensor Nodes

Distributed embedded systems are pervasive components jointly operating in a wide range of applications. Moving toward energy harvesting powered systems enables their long-term, sustainable, scalable, and maintenance-free operation. When these systems are ...

ASSOC COMPUTING MACHINERY2023

Joint Energy Management for Distributed Energy Harvesting Systems

Employing energy harvesting to power the Internet of Things supports their long-term, self-sustainable, and maintenance-free operation. These energy harvesting systems have an energy management subsystem to orchestrate the flow of energy and optimize their ...

Association for Computing Machinery2021

One-Bit Byzantine-Tolerant Distributed Learning via Over-The-Air Computation

Distributed learning has become a promising computational parallelism paradigm that enables a wide scope of intelligent applications from the Internet of Things (IoT) to autonomous driving and the healthcare industry. This paper studies distributed learnin ...

2024

Robust Resource-Aware Self-Triggered Model Predictive Control

The wide adoption of wireless devices in the Internet of Things requires controllers that are able to operate with limited resources, such as battery life. Operating these devices robustly in an uncertain environment, while managing available resources, in ...

2022

Federated Linear Bandit Learning via Over-the-air Computation

Yuning Jiang, Xin Liu

In this paper, we investigate federated contextual linear bandit learning within a wireless system that comprises a server and multiple devices. Each device interacts with the environment, selects an action based on the received reward, and sends model upd ...

IEEE2023

Over-the-Air Computation via Reconfigurable Intelligent Surface

Wei Chen, Yuning Jiang

Over-the-air computation (AirComp) is a disruptive technique for fast wireless data aggregation in Internet of Things (IoT) networks via exploiting the waveform superposition property of multiple-access channels. However, the performance of AirComp is bott ...

2021

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

The increasing application of voltage source converter (VSC) based high voltage direct current (VSC-HVDC) technology in power grids has raised the importance of incorporating DC grids and converters into the existing transmission network. This poses signif ...

IEEE Institute of Electrical and Electronics Engineers2022

Relaxed Recentered Log-Barrier Function based Nonlinear Model Predictive Control

This paper investigates the use of relaxed recentered logarithmic barrier functions in the context of nonlinear model predictive control. These functions are a variation of the regular log-barrier functions that are introduced in the objective function of ...

IEEE2023

Asynchronous decentralized adjustable robust operation for multi-area integrated electricity-gas systems considering wind power uncertainty

Modern energy infrastructure has evolved into an integrated electricity and natural gas systems (IEGS), which often encompasses multiple geographically-diverse energy areas. This paper focuses on the decentralized adjustable robust operation problem for mu ...

2022

Parallel MPC for Linear Systems With State and Input Constraints