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Energy and Power System Optimization in GAMS (All levels)


 Energy and Power System Optimization in GAMS (All levels) 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.
4.5 (143 ratings)
8,280 students enrolled
Created by Dr. Alireza Soroudi .
Last updated 9/2019 
 
 Energy and Power System Optimization in GAMS (All levels)
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
Online Course CoupoNED
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