Voltage control of switched reluctance generator using grasshopper optimization algorithm
This paper presents a terminal voltage control approach of a Switched Reluctance Generator (SRG) based wind turbine generating systems. The control process is employed using a closed loop stimulated by the error between the reference voltage and the generator output voltage due to load and wind spee...
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| Main Authors: | , , , |
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| Format: | EJournal Article |
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Institute of Advanced Engineering and Science,
2020-03-01.
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| LEADER | 02473 am a22003013u 4500 | ||
|---|---|---|---|
| 001 | IJPEDS_19601_12974 | ||
| 042 | |a dc | ||
| 100 | 1 | 0 | |a Bahy, Mohamed |e author |
| 100 | 1 | 0 | |e contributor |
| 700 | 1 | 0 | |a Nada, Adel S. |e author |
| 700 | 1 | 0 | |a Elbanna, Sayed H. |e author |
| 700 | 1 | 0 | |a Shanab, Mohamed A. M. |e author |
| 245 | 0 | 0 | |a Voltage control of switched reluctance generator using grasshopper optimization algorithm |
| 260 | |b Institute of Advanced Engineering and Science, |c 2020-03-01. | ||
| 500 | |a https://ijpeds.iaescore.com/index.php/IJPEDS/article/view/19601 | ||
| 520 | |a This paper presents a terminal voltage control approach of a Switched Reluctance Generator (SRG) based wind turbine generating systems. The control process is employed using a closed loop stimulated by the error between the reference voltage and the generator output voltage due to load and wind speed variation. This error feeds the tuned Proportional Integral controller (PI).Tuning of PI controller by conventional analysis methods is difficult by the existence of a significant non-linearity. A novel strategy method is presented here to determine optimum PI controller parameters of voltage control of SRG using Grasshopper Optimization Algorithm (GOA). This proposed approach is a simple and effective algorithm that is able to solve many optimization problems. The simplicity of algorithm provides high quality tuning of optimal PI controller parameters. The integral of time weighted squared error (ITSE) is used as the performance of the proposed GOA-PI controller. The effectiveness of the proposed strategy is tested with the three-phase 12/8 structure SRG. Outcomes indicate the supremacy of GOA over Whale Optimization Algorithm (WOA) and Particle Swarm Optimization (PSO) in terms of control performance measures. | ||
| 540 | |a Copyright (c) 2019 Institute of Advanced Engineering and Science | ||
| 540 | |a http://creativecommons.org/licenses/by-sa/4.0 | ||
| 546 | |a eng | ||
| 655 | 7 | |a info:eu-repo/semantics/article |2 local | |
| 655 | 7 | |a info:eu-repo/semantics/publishedVersion |2 local | |
| 655 | 7 | |2 local | |
| 786 | 0 | |n International Journal of Power Electronics and Drive Systems (IJPEDS); Vol 11, No 1: March 2020; 75-85 | |
| 786 | 0 | |n 2722-256X | |
| 786 | 0 | |n 2088-8694 | |
| 786 | 0 | |n 10.11591/ijpeds.v11.i1 | |
| 787 | 0 | |n https://ijpeds.iaescore.com/index.php/IJPEDS/article/view/19601/12974 | |
| 856 | 4 | 1 | |u https://ijpeds.iaescore.com/index.php/IJPEDS/article/view/19601/12974 |z Get Fulltext |