![economic-dispatch-for-electricity-grids,-in-python-and-gams-free-course-coupon-[100%-off]](https://i0.wp.com/diypriceless.com/courses/wp-content/uploads/2024/06/8476-economic-dispatch-for-electricity-grids-in-python-and-gams-free-course-coupon-100-off.jpg?resize=750%2C422&ssl=1 "Economic Dispatch for Electricity Grids, in Python and GAMS Free Course Coupon [100% Off] 1")
What
You’ll Learn
You’ll Learn
- Learn how to model the operation of power stations
- such as thermal power stations and renewables (e.g. wind farms).
- Learn how to model thexa0Energy Storage in electricity grids.
- Learn how to develop the Economic Dispatch model that finds which power stations must produce the electricity needed at the smallest cost.
- How to calculate the Economic value of Energy Storage.
- Learn how to develop optimization models using Python
- Pyomo and GAMS; these are languages for developing optimization models.
- Learn how to develop a model for Wind Farms (Renewabes).
- Learn how to model Carbon Dioxide (CO2) constraints to measure the CO2 emissions resulting from electricity generation.
- You will learn important concepts about Electricity grids such as the per-unit system for electricity grids
- DC power flow and Reliability Test Systems
- You will learn important Operations-Research concepts such as Convexity
- Linearity
- Solvers
- Optimal solution,
- You can download all the code in Python/Pyomo and GAMS.
- The code & videos are updated regularly. This means that the code will never feel old to you. We update it typically every 6-12 months.
- No need to have prior knowledge of economics
- energy or coding. The videos teach the code and theory step-by-step. We start from scratch!
- The Instructor is very responsive! You can send direct messages to the Instructor and get a reply within yours!
Requirements
- No prerequisites are needed. The videos teach the code and theory step-by-step. We start from scratch! No need to know economics / energy / coding.
Description
SOFTWARE ENGINEERING FOR ECONOMICS
The Economics Platform is an education consultancy that teaches how to develop economic and finance models in Python, step by step, starting from scratch.
As you develop these models, you also learn their theory, without having to do any prior preparation.
WHAT CAREER OPTIONS YOU CAN PURSUE
The skills that you will develop will be useful if you currently work or aim to find employment in the wider area of economics, such as an economist, quantitative developer, software engineer, data scientist, financial analyst, risk analyst, investment analyst, financial consultant, research scientist, business analyst, and statistician.
WHAT YOU WILL LEARN IN THIS COURSE
You will learn how to develop optimization models in Python, Pyomo and GAMS which focus on the economics of electricity grids, energy storage, renewables, and CO2 emissions. You will include all this in an economic study known as ‘Economic Dispatch’.
No Prior Knowledge is necessary.
CODE
You can download all the code, in both Python and in GAMS.
The code receives frequent updates. So return here to download them (every 5-6 months).
SUPPORT
You can reach out to us via Direct Message anytime. You can expect a reply within hours. We are all the time here!
More courses
Visit our platform to find all our online courses and to join our live classes for a more interactive experience. You can also join our newsletter, follow us on X and watch our videos on YouTube.
EXPERTS
We are a team of expert economists from academia and consultancies, led by Dr. S. Gianelos. We guarantee you will have the best learning experience with us.
Who this course is for:
- Economists who want to work in Energy projects.
- Data Scientists who want to apply their skills in Economics and Energy.
- Students who want to work in Economics and Energy.
- Researchers in Economics & Energy.
- Portfolio managers dealing with Energy Assets.
- Software Engineers who want to develop code related to Economics and Energy.
- Operations Research engineers who want to develop Optimization models for Economics and Energy.
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Infos:
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