EG2420 Monte Carlo Simulation Theory and Project 7.5 credits

Teori och projekt i Monte Carlo-simulering

Monte Carlo methods comprises a number of different methods for solving complicated mathematical problems using sample surveys. Applications of Monte Carlo methods can be found in many fields, from opinion polls to simulations of technical systems. The focus of this course is going to be on the latter.

The methods that are taught are general, although many examples in the course are from simulation of electricity markets. However, students do not need to have any previous knowledge of electricity markets to follow these examples.

  • Education cycle

    Second cycle
  • Main field of study

    Electrical Engineering
  • Grading scale

    A, B, C, D, E, FX, F

Course offerings

Autumn 19 for programme students

Autumn 18 for programme students

Intended learning outcomes

To pass the course, the students should show that they are able to

• apply method for random number generation, simple sampling and variance reduction techniques,

• formulatem models appropriate for Monte Carlo simulation and design suitable simulation methods,

• analyse suggested simulation methods and provide constructive critisism.

Course main content

Theory and examples are presented during the lectures and are then applied by the students in a number of home assignments, which are to be solved using appropriate software (for example Matlab). The course will include the following topics:

  • general probability theory
  • random variables
  • random number generation
  • simple sampling
  • complementary random numbers
  • dagger sampling
  • control variates
  • correlated sampling
  • stratified sampling
  • importance sampling

Disposition

Lessons, seminars, project assignment

Eligibility

• SF1625 Calculus in one variable (or equivalent)

• SF1626 Calculus in several variables (or equivalent)

• MJ1520 Statistics and risk assessment or SF1901 Probability theory and statistics (or equivalent)

• English B/English 6 (or equivalent)

Recommended prerequisites

SF1811 or SF1861 Optimization (or equivalent)

Literature

M. Amelin, Monte Carlo Methods in Engineering, course compendium

Examination

  • PRO1 - Project Work 1, 4.0, grading scale: A, B, C, D, E, FX, F
  • TEN1 - Examination, 3.5, grading scale: P, F

The final grade is equal to the grade of the project assignment.

Requirements for final grade

Each part of the examination must be passed.

Offered by

EECS/Electrical Energy Engineering

Examiner

Mikael Amelin <amelin@kth.se>

Version

Course syllabus valid from: Spring 2019.
Examination information valid from: Spring 2019.