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Hybrid swarm evolutionary programming for optimal distributed generation in distribution system | ||
| International Journal of Nonlinear Analysis and Applications | ||
| دوره 12، Special Issue، اسفند 2021، صفحه 1075-1090 اصل مقاله (507.33 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22075/ijnaa.2021.5570 | ||
| نویسندگان | ||
| Siti Rafidah Abdul Rahim* 1؛ Yeap Chuan Liang1؛ Muhamad Hatta Hussain1؛ Ismail Musirin2؛ Syahrul Ashikin Azmi1؛ Azralmukmin Azmi1 | ||
| 1Faculty of Electrical Engineering Technology, Universiti Malaysia Perlis, Perlis, Malaysia | ||
| 2School of Electrical Engineering, College of Engineering, Universiti Teknologi MARA, Shah Alam, Selangor, Malaysia | ||
| تاریخ دریافت: 27 خرداد 1400، تاریخ پذیرش: 21 شهریور 1400 | ||
| چکیده | ||
| This paper discusses the incorporation of the Hybrid Swarm Evolutionary Programming (SEP) for optimal distributed generation (DG) in the distribution system. High load demand will result in unstable control power distribution due to power transmission loss. The compensation process can be implemented by installing a compensation device to prevent this from happening. It is required the optimal sizing and location for the devices to achieve the objective and this can be done by using an optimization technique. Thus, this project aims to develop a hybrid computational intelligence technique is called hybrid SEP for loss minimization. The proposed method embedded the element of Particle Swarm Optimization (PSO) into traditional Evolutionary Programming (EP) to improve precision of traditional EP algorithm. The purpose of this study is to investigate the maximum benefits of DG integration to be gained. The proposed techniques are validated on IEEE-69 bus radial system with multiple units of DG. The results showed that the most effective type of DG inject to IEEE-69 bus radial system is with DG Type III, with 95% of active power loss reduction and the best on voltage profile improvement. Hybrid SEP shows superior to EP in term of loss minimization. | ||
| کلیدواژه‌ها | ||
| Distributed generation؛ Evolutionary programming؛ Hybrid Swarm evolutionary programming | ||
| مراجع | ||
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