Analysis of real-life power quality sags

• Main Author: Chuang, Wesley Paul Da
• Other Authors: Wong Kin Shun, Terence
• Format: Final Year Project
• Language: English
• Published: 2019
• Subjects: DRNTU::Engineering::Computer science and engineering::Information systems::Information interfaces and presentation
• Online Access: http://hdl.handle.net/10356/78255
• Institution: Nanyang Technological University

In recent years, the electrical power industry has been faced with various challenges, especially to operate in a cost-efficient manner. The gap in this industry presents an opportunity for markets to implement a new system to address the impending issues – Smart Grid System. The project will be focusing on real-life power quality sags as these findings are essential indicators of real-time power quality performance. These findings have a significant impact on the Smart Grid system as they provide a basis for testing of different approaches in the system. In the dataset provided to study power quality sags, there is currently a large amount of raw data available. However, these data will be only be useful through data visualization, as users will be able to sieve out trends and patterns to propose insightful recommendations backed by evidence. Jupyter notebook was used to facilitate data visualization through the project, as it allowed for the study of vital information such as peak, maximum, minimum and average voltage with python programming language. Apart from data visualization, the study also utilized big data analytics (BDA) for actionable insights.