activity
20232026
most citedNetworked Multiagent Safe Reinforcement Learning for Low-carbon Demand Management in Distribution Network

40 citations · 43 across the 5 of their papers we have counts for

collaborators

5 papers

eess.SY2026

Stochastic Model Predictive Control under AC Power-Flow Constraints Using Generative Learning

Jie Zhu, Yinliang Xu, Guan Wang

This paper proposes an end-to-end generative framework for efficiently solving multi-period and multi-scenario stochastic model predictive control (SMPC) problems under nonlinear A…

eess.SY2026

Real-Time Neural Distributed Energy Resources Dispatch with Feasibility Guarantees

Jie Zhu, Yinliang Xu, Hongbin Sun

The growing penetration of renewable energy necessitates high-frequency real-time scheduling. While neural network-based surrogates enable computationally efficient scheduling, str…

eess.SY2024

Distribution Locational Marginal Emission for Carbon Alleviation in Distribution Networks: Formulation, Calculation, and Implication

Linwei Sang, Yinliang Xu, Hongbin Sun +2

Regulating the proper carbon-aware intervention policy is one of the keys to emission alleviation in the distribution network, whose basis lies in effectively attributing the emiss…

eess.SY2023★ 40 cited

Networked Multiagent Safe Reinforcement Learning for Low-carbon Demand Management in Distribution Network

Jichen Zhang, Linwei Sang, Yinliang Xu +1

This paper proposes a multiagent based bi-level operation framework for the low-carbon demand management in distribution networks considering the carbon emission allowance on the d…

math.OC2023★ 3 cited

Bi-level Mixed-Integer Nonlinear Optimization for Pelagic Island Microgrid Group Energy Management Considering Uncertainty

Jichen Zhang, Xuan Wei, Yinliang Xu

To realize the safe, economical and low-carbon operation of the pelagic island microgrid group, this paper develops a bi-level energy management framework in a joint energy-reserve…