MAXIMAL OPTIMAL BENEFITS OF DISTRIBUTED GENERATION USING GENETIC ALGORITHMS | ||||
| ERJ. Engineering Research Journal | ||||
| Article 8, Volume 31, Issue 1, January 2008, Page 59-68 PDF (291.28 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/erjm.2008.69503 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| A. A. Abou El-Ela1; S. M. Allam1; M. M. Shatla2 | ||||
| 1Electrical Engineering Department, Faculty of Engineering, Minoufiya University, Egypt | ||||
| 2West Delta Regional Control Center, Egyptian Electricity Transmission Co., Egypt | ||||
| Abstract | ||||
| As a result of the renewed interest for the distributed power generation (DG); meanly because of the constraints on the traditional power generation besides the great development in the DG technologies, increasing amounts of DG are being used. To accommodate this new type of generation, the existing network should be utilized and developed in an optimal manner. This paper presents an optimal proposed approach to determine the optimal sitting and sizing of DG with multi-system constraints to achieve a single or multi-objectives using genetic algorism (GA). The Linear Programming (LP) is used not only to confirm the optimization results obtained by GA but also to investigate the influences of varying ratings and locations of DG on the objective functions. The methodology is implemented and tested on a real section of the West Delta subtransmission network, as a part of Egypt network. Results are presented, demonstrating that the proper sitting and sizing of DG are important to improve the voltage profile, increase the spinning reserve, reduce the power flow in critical lines and reduce the system power losses | ||||
| Keywords | ||||
| Distributed power generation; Genetic Algorithm; Leaner programming; Voltage profile improvement; Spinning reserve increasing; Line loss reduction and Line flow reduction | ||||
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