arXiv subjects

Shijie Cheng

Publications and source records attributed to Shijie Cheng.

5 recordsLinked to original sources

arXiv2025

Audio-Visual World Models: Learning Physically Grounded Multisensory Dynamics

World models simulate environmental dynamics to enable embodied agents to plan and reason about future states. While real-world perception is inherently multimodal, existing approaches focus primarily on visual observations, leaving crucial spatial and temporal acoustic cues underexplored. In this work, we present a unified formulation of Audio-Visual World Models (AVWM), casting multimodal environment simulation under action control as a partially observable Markov decision process with synchronized audio-visual observations. As a foundational benchmark, we construct AVW-4k, comprising 30 hours of action-annotated binaural audio-visual trajectories across 76 indoor environments. To capture these physically grounded multisensory dynamics, we propose AV-CDiT (Audio-Visual Conditional Diffusion Transformer), featuring a novel modality expert architecture that balances visual and auditory learning, optimized via a three-stage training strategy. Extensive experiments demonstrate that AV-CDiT achieves high-fidelity prediction across both visual and auditory modalities. Furthermore, we validate its practical utility in embodied navigation, showing that AVWM significantly enhances a pretrained agent in continuous audio-visual navigation tasks.

cs.MM↗

arXiv2025

A Unified Theory for Transient Synchronization Stability Analysis of Renewable Dominated Power Systems

The change of electric power generation - from synchronous generator (SG) to converter - is generally regarded as the second revolution of power system. Different from rotor swing of SG in traditional grids mainly described by the swing equation (SE), the converter dynamics plays an indispensable role in modern renewable dominated power systems (RDPS). The high complexity of the RDPS, including spatial large-scale, nonlinearity, multi-time-scale, and even sequential switching, prevents us from fully understanding its dynamics and assessing its transient stability under large disturbance. Here, a variety of transient switching mechanism models of renewable devices relying on wind or solar energies under low-voltage ride-through are established and unified, which can be perfectly described by a generalized swing equation (GSE) under parameter changes for switching dynamics. The GSE focusing on the dominant phase-locking loop dynamics is similar to the SE. Mainly relying on the mechanical equivalence and the energy conservative principle, a substantially improved equal-area criterion method is proposed. Based on this method, even for large-scale renewable fields, the calculation errors for the critical clearing time are only about 1%. This elegant nonlinear-dynamics-based approach establishes a unified theory including modelling and analysis for the RDPS transient dynamics.

eess.SY↗

arXiv2025

Knowledge-data fusion framework for frequency security assessment in low-inertia power systems

The integration of renewable energy via power electronics is transforming power grids into low-inertia systems, heightening the risks of frequency insecurity and widespread outages. Therefore, frequency security assessment (FSA) methods are urgently needed to ensure the reliable system operation. Recently, knowledge-data fusion models attempt to address the limitations of knowledge-driven (accuracy) and data-driven (generalization) FSA methods. However, current methods remain confined to shallow knowledge-data integration due to challenges in representing heterogeneous knowledge and establishing interactive mechanisms. Here, by classifing FSA domain knowledge into physics-guided and physics-constrained categories, we propose a guided learning-constrained network (GL-CN) framework, which deeply integrates domain knowledge across both network architecture and training process. In this framework, a data-driven model with dual input channels combining graph convolutional networks (GCN) and multilayer perceptrons (MLP) is proposed to extract both nodal and system-level power system features. Furthermore, guided learning enhances model generalization through data augmentation in pre-training utilizing physics-guided knowledge, while constrained network encodes physics-constrained knowledge into the network architecture and loss function to ensure physics-consistent and robust predictions. Validated on Yunnan Provincial Power Grid in China, our method reduces FSA time from days to seconds compared to traditional simulation, achieving 98% accuracy, robustness against 39.0% knowledge error, and generalization for 40%-60% renewable penetration. This provides a solid solution for mitigating blackouts caused by frequency insecurity and offers a generalizable paradigm for broader cross-domain problems.

eess.SY↗

arXiv2023

A Soft Coordination Method of Heterogeneous Devices in Distribution System Voltage Control

With the continuous increase of photovoltaic (PV) penetration, the voltage control interactions between newly installed PV inverters and previously deployed on-load tap-changer (OLTC) transformers become ever more significant. To achieve coordinated voltage regulation, current methods often rely on a decision-making algorithm to fully take over the control of all devices, requiring OLTC to give up its existing tap switching logic and execute corresponding upgrades. Aiming at bridging this gap, a soft coordination framework is proposed in this paper. Specifically, the decision-making commands are only applied on inverters, and OLTC that retains its own operation rule will be indirectly controlled by the changed system voltage, which is a result of appropriately adjusting inverters' Var output. The proposed method achieves the soft coordination by establishing a modified actor-critic algorithm to train a proxy model of inverters. The well-trained proxy model can properly adjust inverters' Var output to "softly" coordinate OLTC's tap operations, which finally attains coordinated voltage regulation and line loss minimization. Simulation results verify the superiority of our proposed method over traditional ones in coordinating heterogeneous devices for voltage control.

eess.SY↗

arXiv2020

Network-Constrained Transactive Control for Multi- Microgrids-based Distribution Networks with SOPs

Different from most transactive control studies only focusing on economic aspect, this paper develops a novel network-constrained transactive control (NTC) framework that can address both economic and secure issues for a multi-microgrids-based distribution network considering uncertainties. In particular, we innovatively integrate a transactive energy market with the novel power-electronics device (i.e., soft open point) based AC power flow regulation technique to improve economic benefits for individual microgrids and meanwhile ensure the security of the entire distribution network. In this framework, a dynamic two-timescale NTC model consisting of slow-timescale pre-scheduling and real-time scheduling stages is formulated to work against multiple system uncertainties. Moreover, the original bilevel game problems are transformed into single-level mixed-integer second-order cone programming problems through KKT conditions, duality, linearization and relaxation techniques to avoid iterations of transitional methods, so as to improve computational efficiency. Finally, numerical simulations on a modified 33-bus test system with 3 MGs verify the effectiveness of the proposed framework.

math.OC↗