Electricity Demand Analysis using Data Science
What you'll learn
- How to actually use Data Science to gain insights about Energy Storage
- Modelling key concepts of electricity demand: load factors, normalization, peakiness, plots
- Specialized electricity demand analyses - sector analyses
- Duration curves - residual, load duration, decomposition
- Data analysis on electricity demand - pivot tables, updates
- Country-level electricity demand analyses
- Part of the giannelos dot com official certificate for high-tech projects.
- The only prerequisite is to take the first course of the "giannelos dot com" program , which is the course "Data Science Code that appears all the time at workplace".
What is the course about:
This course teaches how to use Data Science in order to get insights about Electricity Demand.
First, we explore fundamental concepts about electricity demand such as the load factors, normalization, peakiness as well as how to accurately plot the electricity demand.
We then mention a special case of demand analysis done with electricity grids.
Furthermore, we model electricity demand duration curves: net load, residual load duration curve, and decomposition.
We also conduct data analysis on electricity demand datasets as well as calculate the total annual energy demand of a country.
I am a research fellow and I lead industry projects related to energy investments using mathematical optimisation and data science. Specialized in the Data Science aspect of the Green Energy transition, focused on algorithmic design and optimisation methods, using economic principles.
Doctor of Philosophy (PhD) in Analytics & Mathematical Optimization applied to Energy Investments, from Imperial College London , and Master of Engineering (M. Eng.) degree in Power System Analysis (Electricity) and Economics .
To Himalaya Bir Shrestha, senior energy system analyst, who has been contributing to the development of Python scripts for this course and who regularly posts on medium.
No pre-requisites and no experience required.
Every detail is explained, so that you won't have to search online, or guess. In the end you will feel confident in your knowledge and skills.
We start from scratch, so that you do not need to have done any preparatory work in advance at all. Just follow what is shown on screen, because we go slowly and understand everything in detail.
Who this course is for:
- Members of the highly googled giannelos dot com program
- Investment Bankers
- Academics, PhD Students, MSc Students, Undergrads
- Postgraduate and PhD students.
- Data Scientists
- Energy professionals (investment planning, power system analysis)
- Software Engineers
- Finance professionals
Dr. Giannelos is a Research Scientist at Imperial College London leading Mathematical Optimization & Data Science projects at the intersection of Energy, Finance, and Data Science (Optimization, Machine Learning). He holds a Doctor of Philosophy (Ph.D.) in Mathematical Optimization applied to Energy Investments and Economics, from Imperial College London. He is also the founder of the research-scientist dot com program.