OPTIMAL DISTRIBUTED GENERATION PLACEMENT AND SIZING TO REDUCE ACTIVE POWER LOSS USING GA AND ACO ALGORITHM | ||||
| Journal of Al-Azhar University Engineering Sector | ||||
| Article 26, Volume 14, Issue 52, July 2019, Page 909-925 PDF (3.77 MB) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/auej.2019.43459 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| Yousef Y Zakaria1; Noha H El-Amary1; R A Swief2; Amr Ibrahim2 | ||||
| 1Power andMachines 1Engineering Department , Faculty of Engineering, Arab Academy for Science, Technology& Maritime Transport, Cairo, gypt. | ||||
| 2Electrical Power andMachines 1Engineering Department, Faculty of Engineering, Ain Shams University, Cairo, Egypt | ||||
| Abstract | ||||
| In this paper, Genetic Algorithm (GA) and Ant colony Algorithm (ACO) optimization techniques are proposed to find optimal sizing and location for distributed generation in electrical networks. The objective function of the work relies upon a linearized model to compute the active power losses as a function of power generators. This strategy based on a strong coupling between active power and power flow taking into consideration the voltage angles. With the end goal to exhibit the adequacy of the proposed method, the proposed strategy is applied on IEEE 30-bus standard systems. Different maximum penetration level capacity of DG units with three ranges such as, 10%, 20% and 30% of maximum power load and various possible places of DG units among several types of DG (active, reactive or active and reactive power) are considered. Results show that the optimization tools employing GA and ACO are effective in reducing active power losses and cost loss by finding the optimal placement and sizing of DG units. | ||||
| Keywords | ||||
| Genetic Algorithm; Distributed generation; Planning Of DG; Optimum Allocation Of DG; Genetic algorithm (GA); Ant Colony Algorithm (ACO) | ||||
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