Energy systems analysis and planning

Course code: MEC5059Z

Course convenors: Adrian Stone and Mamahloko Senatla (Energy systems analysis and planning group at ERC), and

Course dates: The course usually runs from June- August each year, with lectures taking place in a two week block during June/July.

Course objectives

The aim of the course is to acquaint students with the tools for solving problems in the world of energy planning and analysis. Students will be presented with the framework for energy modelling and analysis, including the various modelling approaches for assisting decision-makers and policy makers with energy planning. An understanding of the fundamentals of the modelling process allows students to develop skills for critically evaluating model output in view of model limitations and assumptions, and to develop proficiency in model design and application. Students will also be trained in methods for deriving the appropriate input drivers used in energy system modelling, and gain practical experience in the use of energy modelling software tools.

This course will be of benefit to all who have an interest in developing their analytical skills, particularly in the field of energy systems analysis.  Applicants from a wide range of disciplines would be welcome. This is a masters level course and it is advisable that students have a tertiary qualification, and at least one year of university level mathematics.

Key elements of the course include the following

  • Rationale for modelling energy systems
  • Background tools: Time value of money, net present values, variable and fixed costs, Useful and final energy and unit conversion
  • Introduction to modelling and decision analysis
  • Model design, data requirements, driver analysis and sectoral disaggregation
  • Energy Demand Analysis: Trend analysis, end-use method and econometric approach
  • Reference Energy System (RES)
  • Integrated Energy Planning
  • Electricity sector expansion planning, reliability and availability factors
  • Techniques for solving problems under uncertainties
  • Levelised costs and screening curves
  • Introduction to MCDA, application of MCDA in energy planning
  • Classification of energy models: top-down, bottom up and hybrid models
  • Translation of model output into policy
  • Case studies from industry (usually guest lecturers)


The course consists of pre-reading and 2 sets of lectures, with 5 consecutive full days in the first set and 3 consecutive days in the second set.  Included in these sessions are individual and group assignments and presentations. An exam will take place at the after the course (optional for CPD students).

Course Assessment

Short Assignment – 10%, Exam – 25% and Long Assignment – 65%.