6 citations · 25 across the 18 of their papers we have counts for
21 papers
CarbonChat: Large Language Model-Based Corporate Carbon Emission Analysis and Climate Knowledge Q&A System
Zhixuan Cao, Ming Han, Jingtao Wang +1
As the impact of global climate change intensifies, corporate carbon emissions have become a focal point of global attention. In response to issues such as the lag in climate chang…
Enhancing LLMs for Power System Simulations: A Feedback-driven Multi-agent Framework
Mengshuo Jia, Zeyu Cui, Gabriela Hug
The integration of experimental technologies with large language models (LLMs) is transforming scientific research. It positions AI as a versatile research assistant rather than a…
Zero and Few Shot Load Forecasting with Large Language Models
Wenlong Liao, Chengrui Zhang, Zhe Yang +4
Deep learning models have shown strong performance in load forecasting, but they generally require large amounts of data for model training before being applied to new scenarios, w…
Data-driven Power Flow Linearization: Theory
Mengshuo Jia, Gabriela Hug, Ning Zhang +3
This two-part tutorial dives into the field of data-driven power flow linearization (DPFL), a domain gaining increased attention. DPFL stands out for its higher approximation accur…
Data-driven Power Flow Linearization: Simulation
Mengshuo Jia, Gabriela Hug, Ning Zhang +3
Building on the theoretical insights of Part I, this paper, as the second part of the tutorial, dives deeper into data-driven power flow linearization (DPFL), focusing on comprehen…
Enabling Large Language Models to Perform Power System Simulations with Previously Unseen Tools: A Case of Daline
Mengshuo Jia, Zeyu Cui, Gabriela Hug
The integration of experiment technologies with large language models (LLMs) is transforming scientific research, offering AI capabilities beyond specialized problem-solving to bec…
Toward Value-oriented Renewable Energy Forecasting: An Iterative Learning Approach
Yufan Zhang, Mengshuo Jia, Honglin Wen +2
Energy forecasting is an essential task in power system operations. Operators usually issue forecasts and leverage them to schedule energy dispatch ahead of time. However, forecast…
The Design of By-product Hydrogen Supply Chain Considering Large-scale Storage and Chemical Plants: A Game Theory Perspective
Qianni Cao, Boda Li, Mengshuo Jia +1
Hydrogen, an essential resource in the decarbonized economy, is commonly produced as a by-product of chemical plants. To promote the use of by-product hydrogen, this paper proposes…
Control-aware Probabilistic Load Flow for Transmission Systems: An Analytical Method
Mengshuo Jia, Qianni Cao, Chen Shen +1
Probabilistic load flow (PLF) calculation, as a fundamental tool to analyze transmission system behavior, has been studied for decades. Despite a variety of available methods, exis…
Chance-constrained OPF: A Distributed Method with Confidentiality Preservation
Mengshuo Jia, Gabriela Hug, Yifan Su +1
Given the increased percentage of wind power in power systems, chance-constrained optimal power flow (CC-OPF) calculation, as a means to take wind power uncertainty into account wi…
A fault detection scheme for PV panels in large scale PV stations with complex installation conditions
Qianni Cao, Chen Shen, Mengshuo Jia
Faults in photovoltaic (PV) systems can seriously affect the efficiency, energy yield as well as the security of the entire PV plant, if not detected and corrected quickly. Therefo…
Convergence Analysis of Dual Decomposition Algorithm in Distributed Optimization: Asynchrony and Inexactness
Yifan Su, Zhaojian Wang, Ming Cao +2
Dual decomposition is widely utilized in distributed optimization of multi-agent systems. In practice, the dual decomposition algorithm is desired to admit an asynchronous implemen…
Iterative Decomposition of Joint Chance Constraints in OPF
Mengshuo Jia, Gabriela Hug, Chen Shen
In chance-constrained OPF models, joint chance constraints (JCCs) offer a stronger guarantee on security compared to single chance constraints (SCCs). Using Boole's inequality or i…
Privacy-preserving Distributed Probabilistic Load Flow
Mengshuo Jia, Yi Wang, Chen Shen +1
Probabilistic load flow (PLF) allows to evaluate uncertainties introduced by renewable energy sources on system operation. Ideally, the PLF calculation is implemented for an entire…
Privacy-Preserving Distributed Clustering for Electrical Load Profiling
Mengshuo Jia, Yi Wang, Chen Shen +1
Electrical load profiling supports retailers and distribution network operators in having a better understanding of the consumption behavior of consumers. However, traditional clus…
Distributed Generalized Nash Equilibrium Seeking for Energy Sharing Games
Zhaojian Wang, Feng Liu, Zhiyuan Ma +4
With the proliferation of distributed generators and energy storage systems, traditional passive consumers in power systems have been gradually evolving into the so-called "prosume…
A Distributed Incremental Update Scheme for Probability Distribution of Wind Power Forecast Error
Mengshuo Jia, Chen Shen, Zhaojian Wang
Due to the uncertainty of distributed wind generations (DWGs), a better understanding of the probability distributions (PD) of their wind power forecast errors (WPFEs) can help mar…
Privacy-Preserving Probabilistic Forecasting for Temporal-spatial Correlated Wind Farms
Mengshuo Jia, Chen Shen, Zhiwen Wang +1
Adopting Secure scalar product and Secure sum techniques, we propose a privacy-preserving method to build the joint and conditional probability distribution functions of multiple w…
A Distributed Probabilistic Modeling Algorithm for the Aggregated Power Forecast Error of Multiple Newly Built Wind Farms
Mengshuo Jia, Chen Shen, Zhiwen Wang
The extensive penetration of wind farms (WFs) presents challenges to the operation of distribution networks (DNs). Building a probability distribution of the aggregated wind power…
Privacy-Preserving Distributed Parameter Estimation for Probability Distribution of Wind Power Forecast Error
Mengshuo Jia, Shaowei Huang, Zhiwen Wang +1
Building the conditional probability distribution of wind power forecast errors benefits both wind farms (WFs) and independent system operators (ISOs). Establishing the joint proba…
Discussion of Parameters Setting for A Distributed Probabilistic Modeling Algorithm
Mengshuo Jia, Chen Shen, Zhiwen Wang
This manuscript provides additional case analysis for the parameters setting of the distributed probabilistic modeling algorithm for the aggregated wind power forecast error.