Thank you for allowing me here, in your group. It is a pleasure to be here. I might be a bit away from the scientists. However, energy is a business as any other, and therefore, we can´t hide behind the "better future" phrases. The main interest of the market players is either to earn or save money. And that´s exactly where my mission starts.

The attached plot shows the level of electricity in Africa. How best can it increase? using smart grids? micrograms?

A new report on battery storage has been published. It is about the global growth in energy storage. As a subscriber you can download the full report, and view all previous ones. Below, you will find the sources used to compile this report, along with my own commentary. Please note that while sources like the Financial Times, Wall Street Journal, and The Economist are behind paywalls, you do not need to subscribe to them. Your Skool subscription provides access to the most important energy economics articles from these publications, which I have curated and explained in simple language. Why read these reports? Developing deep expertise in the energy sector is essential when writing effective code (Data Science / Machine Learning for Energy Economics) but also, for handling professional conversations with clients and colleagues with competence (display expertise). You can access all reports by clicking on 'Classroom' and navigating to Section 6.2. You can find all the reports by clicking 'Classroom' and then go to section 6.2. ------------------------------- KEY MESSAGES -------------------- Battery storage refers to the large batteries that are connected to power grids, to electric vehicles, etc. Batteries are also in small electronic devices. But the main growth is happening in the large batteries connected to power grids. This is because 3 things happen at the same time: electricity demand increases + battery cost reduces + electricity generation unpredictability increases (due to more and more renewables connecting). These 3 factors have been driving the growth in Battery installations globally. Read all the details in the new report . To download it, click Classroom and then find the section 6.2. Sources for this report: [1] Financial Times: https://www.ft.com/content/874fb936-86de-4fa5-95a1-92afb46e2538 [2]: McKinsey: https://www.mckinsey.com/features/mckinsey-center-for-future-mobility/our-insights/the-hidden-trends-in-battery-supply-and-demand-a-regional-analysis

Batteries are becoming one of the most important technologies of the 21st century. The world is becoming very dependent on China for Batteries. See the plot , which is attached below. Find the full report in the Classroom --> section 6.2 for more analysis on this issue. ----- Below, you will find the sources used to compile this report, along with my own commentary. Please note that while sources like the Financial Times, Wall Street Journal, and The Economist are behind paywalls, you do not need to subscribe to them. Your Skool subscription provides access to the most important energy economics articles from these publications, which I have curated and explained in simple language. Why read these reports? Developing deep expertise in the energy sector is essential when writing effective code (Data Science / Machine Learning for Energy Economics) but also, for handling professional conversations with clients and colleagues with competence (display expertise). You can access all reports by clicking on 'Classroom' and navigating to Section 6.2. Sources: [1]: Financial Times: https://www.ft.com/content/874fb936-86de-4fa5-95a1-92afb46e2538 [2]: The Economist: https://www.economist.com/business/2025/05/20/chinas-battery-giant-eyes-world-domination? [3]: The Wall Street Journal: https://www.wsj.com/world/china/china-slaps-export-curbs-on-ev-battery-technology-56b0e041? [4]: Forbes: https://www.forbes.com/sites/heatherfarmbrough/2025/03/31/why-the-oecd-says-green-tech-is-different/

In Energy Economics/ Finance the CDF of the standard normal distribution is very popular. It appears in many economic models. If a model involves risk, probability, (like strike prices), the CDF is usually the tool doing the calculation. No need to know all the details e.g. mathematical formulas etc. We just need to interpret it. Also in our code we need to implement it. You can copy-paste it from this file (attached) into any model you develop that includes the CDF. Specifically this is the CDF of the standard normal distribution. CDF = Cumulative Distribution Function. The word "Cumulative" means "accumulating" or "summing up". Attached is a Python file (.ipynb for Jupyter notebook) that implements the Cumulative Distribution Function (CDF) for the standard normal distribution in Python, in two ways. The video explains all we need to know about the CDF for energy economics. Such a question is very frequent in interviews. E.g. to explain what the CDF is, and how to implement it in Python.