Improvement The DFIG Active Power with Variable Speed Wind using Particle Swarm Optimization
The Wind Energy Conversion System (WECS) has become very popular and more attractive to study the possibility of replacing the conventional power source by renewable energy. This paper is focusing on the modeling and analysis of (DFIG) in Matlab/Smulink with constant and variable speed wind. Three...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
University of Diyala
2016-06-01
|
| Series: | Diyala Journal of Engineering Sciences |
| Subjects: | |
| Online Access: | https://djes.info/index.php/djes/article/view/270 |
| _version_ | 1828354081398194176 |
|---|---|
| author | Siraj Manhal Hameed |
| author_facet | Siraj Manhal Hameed |
| author_sort | Siraj Manhal Hameed |
| collection | DOAJ |
| description |
The Wind Energy Conversion System (WECS) has become very popular and more attractive to study the possibility of replacing the conventional power source by renewable energy. This paper is focusing on the modeling and analysis of (DFIG) in Matlab/Smulink with constant and variable speed wind. Three test systems are considered and implemented. The first system is studied with constant wind speed using sinusoidal pulse width modulation (SPWM) to control the switching of two level three phase back to back converters. The second system is investigated also with constant wind speed but using space vector pulse width modulation (SVPWM). The two systems have been simulated and the results shows the effect of each type of pulse width modulation.
Two fault conditions are subjected to the second system, single line to ground fault at phase A (in 33KV line), programmable fault (three phase voltage drop to 0.5pu) at the Grid bus (132KV bus). Then the system recovery at the steady-state under faults is shown.
For the third system the input was the variable speed wind, the simulation results illustrate that when the input is variable wind speed the generated power will be reduced and the system behavior unstable, therefore, the control circuit is needed for the optimization to reduce the losses of the generated power; this optimization can be made by tuning the controllers gains with new suitable values, so the optimization is made by using Particle Swarm Optimization (PSO).
The new optimal values improved the system behavior, and illustrated the possibility of operation with variable wind speed.
|
| first_indexed | 2024-04-14T02:18:16Z |
| format | Article |
| id | doaj.art-fc043c2650d045919bddcde263daaadf |
| institution | Directory Open Access Journal |
| issn | 1999-8716 2616-6909 |
| language | English |
| last_indexed | 2024-04-14T02:18:16Z |
| publishDate | 2016-06-01 |
| publisher | University of Diyala |
| record_format | Article |
| series | Diyala Journal of Engineering Sciences |
| spelling | doaj.art-fc043c2650d045919bddcde263daaadf2022-12-22T02:18:07ZengUniversity of DiyalaDiyala Journal of Engineering Sciences1999-87162616-69092016-06-019210.24237/djes.2016.09205Improvement The DFIG Active Power with Variable Speed Wind using Particle Swarm OptimizationSiraj Manhal Hameed The Wind Energy Conversion System (WECS) has become very popular and more attractive to study the possibility of replacing the conventional power source by renewable energy. This paper is focusing on the modeling and analysis of (DFIG) in Matlab/Smulink with constant and variable speed wind. Three test systems are considered and implemented. The first system is studied with constant wind speed using sinusoidal pulse width modulation (SPWM) to control the switching of two level three phase back to back converters. The second system is investigated also with constant wind speed but using space vector pulse width modulation (SVPWM). The two systems have been simulated and the results shows the effect of each type of pulse width modulation. Two fault conditions are subjected to the second system, single line to ground fault at phase A (in 33KV line), programmable fault (three phase voltage drop to 0.5pu) at the Grid bus (132KV bus). Then the system recovery at the steady-state under faults is shown. For the third system the input was the variable speed wind, the simulation results illustrate that when the input is variable wind speed the generated power will be reduced and the system behavior unstable, therefore, the control circuit is needed for the optimization to reduce the losses of the generated power; this optimization can be made by tuning the controllers gains with new suitable values, so the optimization is made by using Particle Swarm Optimization (PSO). The new optimal values improved the system behavior, and illustrated the possibility of operation with variable wind speed. https://djes.info/index.php/djes/article/view/270WindTurbine GeneratorDoubly Fed Induction Generator (DFIG)Variable Wind SpeedParticle Swarm Optimization (PSO) |
| spellingShingle | Siraj Manhal Hameed Improvement The DFIG Active Power with Variable Speed Wind using Particle Swarm Optimization Diyala Journal of Engineering Sciences Wind Turbine Generator Doubly Fed Induction Generator (DFIG) Variable Wind Speed Particle Swarm Optimization (PSO) |
| title | Improvement The DFIG Active Power with Variable Speed Wind using Particle Swarm Optimization |
| title_full | Improvement The DFIG Active Power with Variable Speed Wind using Particle Swarm Optimization |
| title_fullStr | Improvement The DFIG Active Power with Variable Speed Wind using Particle Swarm Optimization |
| title_full_unstemmed | Improvement The DFIG Active Power with Variable Speed Wind using Particle Swarm Optimization |
| title_short | Improvement The DFIG Active Power with Variable Speed Wind using Particle Swarm Optimization |
| title_sort | improvement the dfig active power with variable speed wind using particle swarm optimization |
| topic | Wind Turbine Generator Doubly Fed Induction Generator (DFIG) Variable Wind Speed Particle Swarm Optimization (PSO) |
| url | https://djes.info/index.php/djes/article/view/270 |
| work_keys_str_mv | AT sirajmanhalhameed improvementthedfigactivepowerwithvariablespeedwindusingparticleswarmoptimization |