arXiv subjects

Ruizhi Yu

Publications and source records attributed to Ruizhi Yu.

6 recordsLinked to original sources

arXiv2026

Click-to-Ask: An AI Live Streaming Assistant with Offline Copywriting and Online Interactive QA

Live streaming commerce has become a prominent form of broadcasting in the modern era. To facilitate more efficient and convenient product promotions for streamers, we present Click-to-Ask, an AI-driven assistant for live streaming commerce with complementary offline and online components. The offline module processes diverse multimodal product information, transforming complex inputs into structured product data and generating compliant promotional copywriting. During live broadcasts, the online module enables real-time responses to viewer inquiries by allowing streamers to click on questions and leveraging both the structured product information generated by the offline module and an event-level historical memory maintained in a streaming architecture. This system significantly reduces the time needed for promotional preparation, enhances content engagement, and enables prompt interaction with audience inquiries, ultimately improving the effectiveness of live streaming commerce. On our collected dataset of TikTok live stream frames, the proposed method achieves a Question Recognition Accuracy of 0.913 and a Response Quality score of 0.876, demonstrating considerable potential for practical application. The video demonstration can be viewed here: https://www.youtube.com/shorts/mWIXK-SWhiE.

cs.CV↗

arXiv2025

Dynamic Energy Flow Analysis of Integrated Electricity and Gas Systems: A Semi-Analytical Approach

Ensuring the safe and reliable operation of integrated electricity and gas systems (IEGS) requires dynamic energy flow (DEF) simulation tools that achieve high accuracy and computational efficiency. However, the inherent strong nonlinearity of gas dynamics and its bidirectional coupling with power grids impose significant challenges on conventional numerical algorithms, particularly in computational efficiency and accuracy. Considering this, we propose a novel non-iterative semi-analytical algorithm based on differential transformation (DT) for DEF simulation of IEGS. First, we introduce a semi-discrete difference method to convert the partial differential algebraic equations of the DEF model into ordinary differential algebraic equations to resort to the DT. Particularly, by employing spatial central difference and numerical boundary extrapolation, we effectively avoid the singularity issue of the DT coefficient matrix. Second, we propose a DT-based semi-analytical solution method, which can yield the solution of the DEF model by recursion. Finally, simulation results demonstrate the superiority of the proposed method.

eess.SY↗

arXiv2024

Quantify Gas-to-Power Fault Propagation Speed:A Semi-Implicit Simulation Approach

Relying heavily on the secure supply of natural gas, the modern clean electric power systems are prone to the gas disturbances induced by the inherent rupture and leakage faults. For the first time, this paper studies the cross-system propagation speed of these faults using a simulation-based approach. Firstly, we establish the differential algebraic equation models of the rupture and leakage faults respectively. The boundary conditions at the fault locations are derived using the method of characteristics. Secondly, we propose utilizing a semi-implicit approach to perform post-fault simulations. The approach, based on the stiffly-accurate Rosenbrock scheme, possesses the implicit numerical stability and explicit computation burdens. Therefore, the high-dimensional and multi-time-scale stiff models can be solved in an efficient and robust way. Thirdly, to accurately locate the simulation events, which can not be predicted a priori, we propose a critical-time-location strategy based on the continuous Runge-Kutta approach. In case studies, we verified the accuracy and the efficiency superiority of the proposed simulation approach. The impacts of gas faults on gas and power dynamics were investigated by simulation, where the critical events were identified accurately. We found that the fault propagation speed mainly depends on the fault position and is influenced by the pipe frictions. The bi-directional coupling between gas and power may lead to cascading failures.

eess.SY↗

arXiv2024

Nonlinear PDE Constrained Optimal Dispatch of Gas and Power: A Global Linearization Approach

The coordinated dispatch of power and gas in the electricity-gas integrated energy system (EG-IES) is fundamental for ensuring operational security. However, the gas dynamics in the natural gas system (NGS) are governed by the nonlinear partial differential equations (PDE), making the dispatch problem of the EG-IES a complicated optimization model constrained by nonlinear PDE. To address it, we propose a globally linearized gas network model based on the Koopman operator theory, avoiding the commonly used local linearization and spatial discretization. Particularly, we propose a data-driven Koopman operator approximation approach for the globally linearized gas network model based on the extended dynamic mode decomposition, in which a physics-informed stability constraint is derived and embedded to improve the generalization ability and accuracy of the model. Based on this, we develop an optimal dispatch model for the EG-IES that first considers the nonlinear gas dynamics in the NGS. The case study verifies the effectiveness of this work. Simulation results reveal that the commonly used locally linearized gas network model fails to accurately capture the dynamic characteristics of NGS, bringing potential security threats to the system.

eess.SY↗

arXiv2023

Semi-implicit Continuous Newton Method for Power Flow Analysis

As an effective emulator of ill-conditioned power flow, continuous Newton methods (CNMs) have been extensively investigated using explicit and implicit numerical integration algorithms. Explicit CNMs are prone to non-convergence issues due to their limited stable region, while implicit CNMs introduce additional iteration-loops of nonlinear equations. Faced with this, we propose a semi-implicit version of CNM. We formulate the power flow equations as a set of differential algebraic equations (DAEs), and solve the DAEs with the stiffly accurate Rosenbrock type method (SARM). The proposed method succeeds the numerical robustness from the implicit CNM framework while prevents the iterative solution of nonlinear systems, hence revealing higher convergence speed and computation efficiency. A new 4-stage 3rd-order hyper-stable SARM, together with a 2nd-order embedded formula to control the step size, is constructed to further accelerate convergence by tuning the damping factor. Case studies on ill-conditioned systems verified the alleged performance. An algorithm extension for MATPOWER is made available on Github for benchmarking.

eess.SY↗

arXiv2021

Non-iterative Calculation of Quasi-Dynamic Energy Flow in the Heat and Electricity Integrated Energy Systems

Quasi-dynamic energy flow calculation is an indispensable tool for the heat and electricity integrated energy system (HE-IES) analysis. One solves the nonlinear partial differential algebraic equations to obtain thermal, hydraulic and electric variations. However, mainstream iteration solvers face the challenges of inefficiency and bad robustness. For one thing, the frequent update and factorization of Jacobian matrices utilize high CPU time. For another, the per-step iteration numbers grow exponentially as the system loading level creeps up. This paper presents a novel non-iterative algorithm for the quasi-dynamic energy flow calculation. The kernel of the proposed algorithm is to transform these nonlinear equations into linear recursive ones, by solving which, we obtain explicit closed-form solutions of unknown variables. In each step, the proposed algorithm requires only one matrix factorization and fixed times of arithmetic operations regardless of the loading levels, so that it achieves small and consistent per-step time costs. A semi-discrete scheme is used in PDE solution to avoid dissipative and dispersive errors that are often overlooked in previous literature. To ensure convergence, we also propose to control the temporal step sizes adaptively by estimating the simulation errors. Case studies showed that the proposed method manifested efficient and robust time performance compared with the iterative algorithms, and meanwhile preserved high accuracy.

eess.SY↗