Energy and Power System Optimization in GAMS (All levels)
4.5 (87 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
4,661 students enrolled

Energy and Power System Optimization in GAMS (All levels)

OPF, ED, DED, UC, PMU , Planning and more! Learn the Fundamentals of Optimization with dozens of Example
4.5 (87 ratings)
Course Ratings are calculated from individual students’ ratings and a variety of other signals, like age of rating and reliability, to ensure that they reflect course quality fairly and accurately.
4,661 students enrolled
Last updated 1/2019
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This course includes
  • 5 hours on-demand video
  • 24 downloadable resources
  • 2 Practice Tests
  • Full lifetime access
  • Access on mobile and TV
  • Assignments
  • Certificate of Completion
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What you'll learn
  • GAMS installation
  • Model any kind of optimisation (LP, QCP, NLP, MILP,MIQCP, MINLP)

  • Multi-Objective Optimization

  • Solve Economic dispatch problem
  • Solve Dynamic Economic dispatch problem
  • Solve Dynamic Economic dispatch scheduling and Energy storage systems problem
  • Unit commitment
  • Solve Optimal DC power flow problem
  • Solve Optimal AC power flow problem
  • Optimal PMU allocation
Requirements
  • Familier with mathematical modeling
  • You don't need to have extensive knowledge of programming
  • We will teach you whatever you need
Description

The developed course is suitable for you even if you have no background in power system. The first part of the course is devoted to general optimization problems in GAMS.

General GAMS coding

In this course you will learn how to use GAMS for solving power system optimization problems.

  • First of all you will learn how to install GAMS on your machine.

  • What is optimization ? What is the objective function ? What is the constraint ? 

  • You understand the meaning of different errors and the way you should debug them

  • How to read/write from/to an Excel file

  • Multi-Objective optimization in GAMS 

  • Conditional statements

  • Loop expressions

Power system GAMS coding

In this course you will learn how to use GAMS for solving

  • Economic dispatch problem

  • Dynamic economic dispatch

  • DC Optimal power flow (OPF)

  • AC Optimal power flow (OPF)

  • Security Constrained DC-OPF (N-1)

  • Unit commitment

  • Energy storage systems scheduling

  • PMU allocation

Who this course is for:
  • Any discipline that requires optimization and decision making
  • Power system academics or industry people
  • Beginner students in power system operation and planning
  • PhD/MSc students in power system operation and planning
  • PhD/MSc students in energy system optimisation
  • Power system utility researcher
Course content
Expand all 32 lectures 05:08:59
+ Introduction
15 lectures 02:11:46

This video explains how to install GAMS on a windows machine

Preview 06:15

In this lesson, you will get familiar with the general structure of each GAMS code

Preview 04:56
  • What is set ?

  • How to deal with sets in GAMS ? 

  • Syntax ? 

Sets in GAMS
04:55
  • What is Scalar?

  • How to deal with Scalars in GAMS ? 

  • Syntax ? 

Scalars in GAMS
01:50
  • What is parameter?

  • How to deal with Parameters in GAMS ? 

  • Syntax ? 

Parameters in GAMS
02:41
  • What is Table?

  • How to deal with Tables in GAMS ? 

  • Syntax ? 

Table in GAMS
01:26
  • Real variables

  • Binary variables

  • Integer variables 

  • SOS1

  • SOS2

  • Semicont

  • SemiInt

How to define lower and upper bounds for variables ?

Variables in GAMS
06:14

How to define equations in GAMS?

What is the syntax ?

Equations in GAMS
04:36
  • What kind of optimisation models can be solved in GAMS ? 

  • What is my model type ? 

Model definition in GAMS
14:32

How to select the right solver for my model in GAMS?

Preview 03:10

In this session you will learn how to code a linear programming problem in GAMS 

Preview 09:30

ssd

Example 1 LP
1 question
Example 2 LP
1 question
Solve the Dual of the LP examples
Dual of the primal LP
1 question

Mixed integrer programming in transportation problem is discussed here

Mixed integer quadratic programming
07:51
Suppose we have two Binary variables (x,y) , how can we linearize the following equation? Z=XY
Linearize the multiplication of two binary variables
2 questions

Conditional Expressions, Assignments and Equations


 

Conditional statements in GAMS
32:52

How to define a model in loops in GAMS environment? 

LOOP in GAMS
16:20

In this lecture you will learn:

  • What is the optimisation and decision making ?

  • What is an objective function ?

  • What is a constraint ? 

  • What is multi-objective optimisation ?

  • What is Pareto optimal front ?

  • How to code a Pareto optimal front in GAMS ?

Multiobjective Optimisation in GAMS
14:38
+ Some problems solved in GAMS
7 lectures 42:38

In a given circle find a rectangle of maximal area.

In a given circle find a rectangle of maximal area.
02:49

In a given sphere find a cylinder of maximal volume

Cylinder in a Sphere
02:40

“A woman at a point A on the shore of a circular lake with radius 2 mi wants to arrive at the point C diametrically opposite A on the other side of the lake in the shortest possible time (see the figure). She can walk at the rate of 4 mi/h and row a boat at 2 mi/h. For what value of the angle θ shown in the figure will she minimize her travel time?“

Travel time minimisation
03:36

A and B are two given points on the same side of a line ℓ. Find a point D on ℓ such that the sum of the distances form A to D and from D to B is a minimum.

Herons Problem
03:02

(Steiner) In the plane of a triangle, find a point such that the sum of its distances to the vertices of the triangle is minimal.

Preview 03:15

In this lecture you will learn how to code in GAMS for finding the shortest paths between nodes in a graph, which may represent, for example, road networks.


Shortest path via LP
19:21

The travelling salesman problem (TSP) asks the following question: "Given a list of cities and the distances between each pair of cities, what is the shortest possible route that visits each city and returns to the origin city?"

Each city should be met only once

Every city should be visited


Traveling Sales Person (TSP)
07:55
+ Power system optimization
10 lectures 02:07:35

In this video you will learn how to find and have access to Power system optimization library in GAMS website.

Preview 04:42

https://www.amazon.com/Power-System-Optimization-Modeling-GAMS/dp/3319623494/ref=sr_1_2?ie=UTF8&qid=1523040637&sr=8-2&keywords=soroudi


Economic Dispatch problem modelling in GAMS
10:20
What is the impact ?
Increase the demand value and see the impact
2 questions

Add a new generating unit and investigate the impact on total operating cost

What is the impact of adding a new generating unit ?
2 questions

In this lesson you will learn how to use the GAMS for solving the Dynamic economic dispatch problem

Dynamic Economic Dispatch
08:47

Can you model the DR in DED ? 

Demand response modelling in DED
1 question
Dynamic Economic Dispatch with Storage
08:38

DC Optimal power flow modelling will be discussed

DC-OPF
10:06
2 bus Code
1 question

Find the highest loaded line

Line loading
1 question

The AC -OPF takes into account the non-linear KVL-KCL constraints and tries to determine the optimal generating schedules of units

AC-OPF
23:45

In this lecture you will learn how to calculate the LMP in GAMS

Locational Marginal Price (LMP)
18:21

Security constrained optimal power flow is modelled in this lecture. The N-1 contingencies can cause overloading the remaining lines.

Security Constrained DC-OPF (N-1)
18:55

The unit commitment problem is explained in this lecturer

Unit commitment
17:49

This session provides a solution for increasing the power system observability by allocation of Phasor Measurement Units (PMU) problem in GAMS. The PMU is able to measure the voltage phasor at the connection bus and also it measures the current phasor of any branch connected to the bus hosting the PMU.

PMU allocation
06:12