Data processing and analytics for a power system with renewable generation

• Main Author: Tan, Bervyn Woo Seng
• Other Authors: Tang Yi
• Format: Final Year Project
• Language: English
• Published: 2019
• Subjects: DRNTU::Engineering::Electrical and electronic engineering::Power electronics
• Online Access: http://hdl.handle.net/10356/78125
• Institution: Nanyang Technological University

Due to the intermittent nature of solar photovoltaic power generation and its impact on the power system, there is a need to estimate solar photovoltaic (PV) output power to study and prepare the power system to handle this renewable form of energy. This project provides an efficient method to estimate solar PV output power via the forming of a mathematical model by curve fitting. This model can calculate and obtain power output fluctuations from the frequency data of the power system. A simulation model that represents a typical power system is formed for simple reference and understanding of the various components in the power system. The frequency of the power system is measured using a frequency disturbance recorder (FDR), which can accurately measure frequency data from up to 4 significant figures and obtain several data for easy reference. This frequency data is cured from any anomalies and missing data that may affect the accuracy of results obtained through the use of the linear interpolation method. By generating a code in MATLAB based on this model, the solar PV output fluctuations at any given time and day can be obtained and calculated efficiently. The variables controlled in this project is that the day and the time measured must be similar when selecting the frequency and load data for calculation.