Modeling and optimization of energy systems in GAMS

Modeling and optimization of energy systems in GAMS

 Lesson Planning

SSE-Course Credits: 7.5 Credits (Equivalent to YP: 60 –points) includes:

  • Lectures: SSE credit: 4.0
  • Assignments: SSE credit :1.0 (Group Base Activity)
  • Projects: SSE credit: 2.5(Group Base Activity)

Teachers and Course Manager

Course manager: Jafar Mahmoudi, PhD (Stockholm School of Energy)


Teacher: Amir Sabripoor



The basic language will be in English (could be translated to other languages based on request- using Google Translator).


10 weeks including lectures, project and assignments.

The purpose of this course

  • The goal of the course “Modelling and optimization of energy systems” is to present and apply techniques for the modelling and the thermo-economic optimization of industrial process and energy systems. The course covers the problem statement, the solving methods for the simulation and the single and multi-objective optimization problems. The course explain how collaboration in technical systems can increase energy efficiency through synergies.
  • This course provides a comprehensive methodology for modeling, assessment, improvement of any energy system with guidance, and practical examples that provide detailed insights for energy engineering, mechanical engineering, chemical engineering and researchers in the field of analysis and optimization of energy systems.
  • This course describes how the General Algebraic Modeling System (GAMS) can be used to solve various energy system and planning optimization problems. The course covers theoretical background as well as the application examples and test case studies.

In Modeling and optimization of energy systems in GAMS course you will learn:

  • How to formulate your problem and implement it in GAMS and make optimal decisions in your real-life problems
  • How to code efficiently, get familiarized with the techniques that will make your code scalable for large problems
  • How to design an action block with a clearly defined conversion goal
  • How to run sensitivity analysis in GAMS to predict the outcome of a decision if a situation turns out to be different compared to the key predictions.
  • For your convenience the course is broken into two sections:
  1. General GAMS coding (Pure GAMS, elements, loops, multi-objectives, conditional statements, Examples).
  2. Energy system GAMS coding (Static/dynamic economic/ environmental dispatch, AC/DC Optimal Power Flow (OPF), Storage modeling, demand response, Power system observability, …)
  • You will be walked through every step of GAMS coding with real-life case studies, actual experiments, and multiple examples from around different disciplines.
  • By the end of this course, you’ll be able to Code your own optimization problem in GAMS.

Course content and implementation

  1. Introduction to the concepts of energy modeling and optimization.
  2. Introduction to GAMS.
  3. The main parts of coding.
  4. Energy supply modeling.
  5. Energy modeling and optimization in thermal and combined cycle power plants.
  6. Energy modeling and optimization in renewable power plants.
  7. Energy modeling and optimization in the building.

Course books

  • Power System Optimization Modeling in GAMS, Dr. Alireza Soroudi, 2018.
  • Optimization of Energy Systems, Ibrahim Dincer, Marc A. Rosen, Pouria Ahmadi, 2017.
  • Modeling, Assessment, and Optimization of Energy Systems, Hoseyn Sayyaadi, 2020.


  • Written Examination (4.0 HP)
  • Exercises: 1.0 HP (might be included in the written exam or in a separate format)
  • Project: The examination form for project work (2.5 HP)

Rating step

  • Criteria for the grade “approved” (G)

To pass the course (grade G), the student needs to show that the course’s learning objectives are met at the basic level within 3 of the course’s main content and pass the exam.

  • Criteria for rating well approved” (VG)

For the grade ‘well approved’: Meet the requirements for G and show greater breadth at the basic level or greater depth at the advanced level in their knowledge and skills in all parts of main content through deep understanding and analysis of the questions on the exam.

  • The criteria for “Non-approved” (IG)

The student shows the inadequate results in relation to the requirements for this course.

Further work is required in order to meet the objectives of education and training.