Dear Professor Akilan,
My final project is to optimize grid scheduling by using reinforcement learning methods for the rapid increase in the installed capacity of photovoltaic power generation and the number of electric vehicle charging stations.
In order to complete this project, I plan to complete it in steps: firstly, I will complete the prediction of photovoltaic power generation and charging power of charging stations by using the machine learning method, and in this step, I can get the data of photovoltaic power generation capacity and power generation from the previous work unit, as well as the data related to the charging piles' installed capacity and the charging volume, and complete the two theses on the prediction of the photovoltaic power generation and charging piles' charging data, respectively; the second step is based on the prediction results of the first step. On the basis of the prediction results completed in the first step, the optimization of power system scheduling is completed using reinforcement learning methods, and the same plan is to analyze and optimize photovoltaic power generation and charging stations charging respectively, forming two papers; the final goal is to complete the optimization of power grid scheduling combining photovoltaic power generation and charging stations charging.
To accomplish this vision, in the near future I would like to start by completing a project and publishing a paper on the prediction of PV power generation forecasts using machine learning.
Currently, I have in mind the data needed are the local light intensity and weather conditions, and the daily PV power curve.
Now I have contacted my colleague in my previous workplace and got some of the PV power data, and I would like to analyze the prediction based on the data of Yantai city. I think I can get the weather data from the official weather data, but I still need to learn more about how to find useful data and how to process the data scientifically.
Sincerely, Senye Zhang