Economics Of Energy Storage Using Data Science

Using Data Science to gain insights about Energy Storage
What you'll learn
This is a very brief online course. I plan to add more videos soon! Please bear with me!
Python & Excel examples of key parameters of energy storage
Efficiency, Power Capability, Duration and Energy Storage
Energy Storage is the most promising Energy Technology
Python modelling of Energy Storage for parameter optimisation
Requirements
No prerequisites
Description
What is the course аbout:The course teaches key parameters of Energy Storage using Data Science. Energy Storage is a valuable energy infrastructure asset that has significant scope for growth. Parameters such as Energy Capacity, Energy Efficiency, Energy Power Capability and duration, are shown in excel and Python.This is an introductory course, with more videos coming up soon. Who:I am a research fellow at Imperial College London, and I have been part of high-tech projects at the intersection of Academia & Industry for over 10 years, prior to, during & after my Ph.D. I am also the founder of the giannelos dot com program in data science.Doctor of Philosophy (Ph.D.) in Analytics & Mathematical Optimization applied to Energy Investments, from Imperial College London, and Masters of Engineering (M. Eng.) in Power Systems and Economics. Important:Prerequisites: The course Data Science Code that appears all the time at Workplace.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 explain everything in detail.
Overview
Section 1: Data Analysis on Energy Storage
Lecture 1 Energy Storage Capacity using Python
Lecture 2 Total storage capacity and efficiency
Section 2: Bonus
Lecture 3 Extras
Enterpreneurs,Economists,Quants,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
Screenshots


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