| 000 | 01995cam a2200337 a 4500 | ||
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| 003 | EG-GiCUC | ||
| 005 | 20250223031727.0 | ||
| 008 | 170529s2016 ua f m 000 0 eng d | ||
| 040 |
_aEG-GiCUC _beng _cEG-GiCUC |
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| 041 | 0 | _aeng | |
| 049 | _aDeposite | ||
| 097 | _aM.Sc | ||
| 099 | _aCai01.13.07.M.Sc.2016.Ah.T | ||
| 100 | 0 | _aAhmed Moussa Fakhry Moussa | |
| 245 | 1 | 0 |
_aTwo area load frequency control based on evolutionary computational techniques / _cAhmed Moussa Fakhry Moussa ; Supervised Mohamed A. Moustafa , Mohamed E. Ammar |
| 246 | 1 | 5 | _aالتحكم فى تردد حمل لمنطقتين إعتماداً على تقنيات حسابية تطورية |
| 260 |
_aCairo : _bAhmed Moussa Fakhry Moussa , _c2016 |
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| 300 |
_a65 P. ; _c30cm |
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| 502 | _aThesis (M.Sc.) - Cairo University - Faculty of Engineering - Department of Electrical Power and Machines | ||
| 520 | _aThe two area load frequency control (TALFC) is used to manage the shared active power between a two generation areas. The PID controller is used to improve the performance of the two area controllers. The particle swarm optimization technique and its modified techniques are one of the evolutionary computational techniques that could be used to set the PID parameters. The artificial Immune System (AIS) could be in optimization and it will be used in this paper for tuning the PID controller through using the clonal selection. Finally, the obtained results will be discussed after applying the algorithms on the TALFC. The obtained results are highly encouraging | ||
| 530 | _aIssued also as CD | ||
| 653 | 4 | _aEvolutionary computational techniques | |
| 653 | 4 | _aParticle Swarm Optimization (PSO) | |
| 653 | 4 | _aProportional-integral-derivative (PID) | |
| 700 | 0 |
_aMohamed Ahmed Moustafa Hassan , _eSupervisor |
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| 700 | 0 |
_aMohamed Elsayed Ammar , _eSupervisor |
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| 856 | _uhttp://172.23.153.220/th.pdf | ||
| 905 |
_aNazla _eRevisor |
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| 905 |
_aSamia _eCataloger |
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| 942 |
_2ddc _cTH |
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_c61035 _d61035 |
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