The F-Factor Optimization Algorithm for Energy Storage

The F-Factor Optimization Algorithm for Energy Storage

The F-Factor Optimization Algorithm for Energy Storage

The F-Factor Optimization Algorithm for Energy Storage

 The F-Factor Optimization Algorithm for Energy Storage

A Mathematical Optimization model for Energy Storage to reduce the peak load in electricity grids

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What you'll learn
  • Use this code at Checkout. You get a Discount & you get our course "Quantitative Careers" for free : E862387445113FCE8525
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  • Contents: Learn the "F-Factor" algorithm for the optimal control of Energy Storage. First-ever online!
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We build an optimization model that simulates the operation of Energy Storage in electricity grids so that Energy Storage can reduce the peak electricity demand.

This operation is known as "security contribution of Energy Storage".

We measure this contribution using different metrics. One such metric is the 'F-Factor'.
We go through the F-Factor algorithm in detail, including extensive sensitivity analyses.

The model is detailed. We consider all the important Energy Storage parameters such as Energy Capacity, Power Capability, Charging Efficiency etc.

We make plots and test assumptions.

We conduct sensitivity analyses and understand the behaviour of the Energy Storage parameters. 

The algorithm has been used to consult clients in the real-world marketplace. It is not just an academic exercise. It is not a theoretical model. It has been applied to the real-world marketplace. it has been tried and tested in the real world.

Instructor support:

If you have questions then send a private message here on Udemy.
Or, send a message on the Website www. quantalg .com (without space).

Either way, it is certain that your questions will be replied to by the Instructor within hours.

I am the CEO of Quantalg, a boutique firm focusing on the development of Quantitative Algorithms for Finance and Energy, always using the most up-to-date resources. 

I have a PhD in Optimization & Data Science from Imperial College London.
I also have an MEng (Masters of Engineering).
For more visit: www. quantalg .com

Who this course is for:
  • Quantitative Finance professionals
  • Quantitative Energy professionals
  • Students & Academics
  • Portfolio Managers & Economists
  • Data Scientists & Software Engineers

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