A Genetic-Based Approach for Solving Optimal Power Flow Problem. | ||||
| MEJ- Mansoura Engineering Journal | ||||
| Article 10, Volume 29, Issue 2, June 2004, Page 12-26 PDF (229.56 K) | ||||
| Document Type: Research Studies | ||||
| DOI: 10.21608/bfemu.2020.133266 | ||||
 View on SCiNiTO | ||||
| Author | ||||
| Magdy Mohamed Ali El-Saadawi* | ||||
| Department of Electrical.,Power & Machines Faculty of Engineering.,El- Mansoura University., Mansoura., Egypt | ||||
| Abstract | ||||
| The optimal power flow (OPF) is an optimization problem, in which the utility strives to minimize its costs while satisfying all of its constraints. Artificial intelligence is used to help a hypothetical electric utility nieet its electric load economically. A genetic algorithm (GA) —a specific type of artificial intelligence—is employed to perform this optimization. In this paper, a genetic algorithm is used to solve the OPF problem. A new genetic chromosome is structured to represent the solutions. The new chromosome structure is chosen in such a way that it greatly reduce the number of times the algorithm must solve the load-flow equations. Since solving the load-flow equations is time-consuming, this speeds execution of the algorithm considerably : A computer program, written in Matlab environment, is developed to represent the proposed method. The program is applied to both the IEEE 30-bus test system, and the IEEE 118-bus test system to demonstrate its ability and its potential to be used with larger systems. Thus, the proposed algorithm is shown to be a valid tool to perform this optimization. | ||||
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