Economic Dispatch For Natural Gas-Electricity Networks

Apply Python & GAMS for Optimisation & Data Science to Electricity & Natural Gas Grids

What you'll learn

Learn how to model electricity-gas grids in Python and GAMS

All the code is explained line by line - great for beginners

The content is updated often - visit often to keep updated!

Download all the code!

Requirements

Ideal for beginners! Just have Python installed!

Description

- The course gets updated every 6-12 months. Visit often to download new material and watch new videos.- Course Overview: This course, "Economic Dispatch for Natural Gas-Electricity Networks," provides a comprehensive introduction to the modelling, formulation, and implementation of coupled energy systems. It focuses on the economic dispatch problem, where the goal is to minimise the cost of supplying energy while considering the physical and operational constraints of both electricity and natural gas networks. The course begins with an overview of the system and its mathematical formulation, followed by downloadable materials that include the model files in Python and GAMS. Students are introduced to a simplified yet realistic system where electricity and natural gas interact through common infrastructure, such as gas-fired power plants.In the implementation section, the course guides learners through the development of Python and GAMS-based models. This includes defining input data for both systems, setting up variables, and coding relevant constraints. Participants will solve and interpret the optimisation results using both platforms. The final section explores model extensions and summarises key takeaways. The course is ideal for students, researchers, and professionals in energy systems engineering who seek practical insights into integrated energy modelling and decision-making under economic criteria.

Overview

Section 1: Introduction

Lecture 1 Introduction and System Description

Lecture 2 Download The mathematical Formulation

Lecture 3 Download the Python file

Lecture 4 Download the GAMS file

Section 2: Python and GAMS implementation

Lecture 5 Python input data power system

Lecture 6 Python input gas system

Lecture 7 Variables

Lecture 8 Constraints for power system

Lecture 9 Constraints for natural gas

Lecture 10 Solving and understanding the solution in Python

Lecture 11 Modelling in GAMS

Lecture 12 Solving in GAMS

Lecture 13 Formulation

Section 3: Conclusions

Lecture 14 Extensions

Lecture 15 Overview

Energy Economists,Quant Developers,Software engineers with a focus on Energy,Energy Professionals