Course

An Introduction to Energy Demand Simulation with MAED

Courses

This publication was produced as part of CCG's FlatPack initiative and provides learning materials for an introductory course on using the MAED tool to build and analyse energy demand case studies. It includes editable lecture slides, hands-on exercises, sample learning objectives, and a suggested course timetable.

FlatPack aims to integrate open source energy and financial modelling tools into higher education courses (BSc, MSc, PhD) in universities across the world. This material is adaptable to various contexts and proficiency levels.

In this introductory course, students will explore the conceptual foundations of energy demand modelling, including the differences between bottom-up and top-down approaches, and between simulation and optimisation techniques. Through hands-on use of MAED, students will learn how to interpret national energy balances, calibrate models to reflect real-world data, and understand how energy demand evolves across key sectors such as households, services, industry, and transport.

Updated at 2026-02-13 Created at 2026-02-13
Authors
  • Fynn Kiley
    Affiliation: Imperial College London
    ORCID: 0009000451721921
  • IAEA
  • Mamud Musah
    Affiliation: University of Energy and Natural Resources
    ORCID: 0009000359100452
Acknowledgement
This material has been produced under the Climate Compatible Growth (CCG) programme, with contributions from the International Atomic Energy Agency (IAEA), which brings together leading research organizations and is led out of the STEER centre, Loughborough University. CCG is funded by UK aid from the UK government. However, the views expressed herein do not necessarily reflect the UK government's official policies.
Cite as
Kiley, F., IAEA, Musah,M. (2025) An Introduction to Energy Demand Simulation with MAED. Climate Compatible Growth Teaching Kit Website. Climate Compatible Growth.

Courses

MAED Course Core Documents

File 1 contains an outline of the course, its learning objectives, duration, example assessment methods, and the IT requirements. In File 2, an example timetable is provided that breaks the course into three different blocks and suggests time allocations. File 3 provides a reading list containing key publications, the MAED manual, and other related interesting publications.

Lecture files
1. Course Outline and Syllabus.docx2. Timetable.docx3. Reading List.docx

MAED Week 1

Week 1 lectures introduce the SDGs, energy planning in mineral, and an introduction to the MAED methodology. They also discus other energy modelling techniques and the structure of the energy chain. The Hands-On exercises guide users through installing the UI and setting up the structure of the model.

Lecture files

MAED Week 2

Week 2 lectures introduce the MAED-D module and looks more closely at the theory behind the industrial and household sector modelling. The Hands-On exercises guide users through finishing setting up the model, inputting data, and introduces base year reconstruction (model calibration).

Lecture files

MAED Week 4

In Week 4, the focus shifts to MAED-EL with an introduction to the theory behind the model and a closer look at electricity demand curves. Students are coached through setting up a model and inputting data.

Lecture files

MAED Week 5

Week 5 finishes the introduction to MAED-EL by guiding students through its structure and analysing results.

Lecture files

MAED Week 7

Week 7 finishes the theoretical portion of the course by looking in depth at the equations used in the services and transport sectors as well as how to construct scenarios and reconstructing the base year in the manufacturing sub-sector.

Lecture files

MAED Week 6

Week 6 takes a closer look at the equations used in the industrial and household sectors and guides students step by step through reconstructing the base year for the Agriculture, Construction, and Mining sub-sectors.

Lecture files

MAED Week 3

Week 3 lectures cover the transport and service sectors as well as how to ensure data consistency and that the data is processed for input to the tool. The Hands-On exercise shows users how to input data for scenarios.

Lecture files