Machine Learning

During my internship from May 2024 to August 2024 at Hubei State Grid Wuhan University of Technology Power Consulting Division, I had the opportunity to engage with cutting-edge technologies in digital grid solutions, intelligent energy, and extensive data operations. The company specializes in integrating digital technology into power grid solutions, providing intelligent energy, system integration, and comprehensive data analytics expertise. This internship allowed me to work on several impactful projects, significantly enhancing my technical and professional skills.

In modern power grid infrastructure projects, ensuring the quality of construction is critical to maintaining safety and operational stability. Traditional manual inspections face significant challenges due to weather conditions, terrain, and the complexity of the environment. To address these challenges, intelligent detection methods utilizing drones and AI-based algorithms are gaining traction. This article presents a novel approach for grid infrastructure quality detection using CBAM-ASFF-YOLOv4, which integrates Adaptive Spatial Feature Fusion (ASFF) and Convolutional Block Attention Module (CBAM) with YOLOv4 to improve detection accuracy and speed.

During my internship at the Tsinghua Sichuan Energy Internet Research Institute from August to December 2023, I had the opportunity to contribute to a highly technical project focused on power system analysis, specifically examining the impact of large-scale renewable energy integration on system inertia and frequency. This experience greatly enhanced my algorithm development, simulation, and technical communication skills. It provided a deeper understanding of the intersection between AI and energy systems.

During my first co-op at Chongqing University Electrical Engineering Lab from Janurary 2023 to April 2023, I had the opportunity to work on an exciting project involving energy consumption mode mining and exception identification of power users. My advisor is Professor Juan Yu. This experience gave me invaluable skills and insights that shaped my approach to machine learning and research. Here’s a detailed look at what I learned and accomplished during this co-op:

From March 2021 to November 2023, I had the privilege of being a member of the Electrical Engineering Lab at Chongqing University, where I worked on a research project advised by Professor Duo Liu aimed at identifying and predicting meteorologically sensitive loads in power supply station areas. This project involved the development of advanced machine learning models to analyze municipal grid power load data and forecast both long- and short-term power load curves. The experience significantly deepened my understanding of power systems. It reinforced my skills in applying machine learning to real-world energy problems.