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.
El-Saadawi, M. M. (2020). A Genetic-Based Approach for Solving Optimal Power Flow Problem.. MEJ- Mansoura Engineering Journal, 29(2), 12-26. doi: 10.21608/bfemu.2020.133266
MLA
Magdy Mohamed Ali El-Saadawi. "A Genetic-Based Approach for Solving Optimal Power Flow Problem.". MEJ- Mansoura Engineering Journal, 29, 2, 2020, 12-26. doi: 10.21608/bfemu.2020.133266
HARVARD
El-Saadawi, M. M. (2020). 'A Genetic-Based Approach for Solving Optimal Power Flow Problem.', MEJ- Mansoura Engineering Journal, 29(2), pp. 12-26. doi: 10.21608/bfemu.2020.133266
VANCOUVER
El-Saadawi, M. M. A Genetic-Based Approach for Solving Optimal Power Flow Problem.. MEJ- Mansoura Engineering Journal, 2020; 29(2): 12-26. doi: 10.21608/bfemu.2020.133266
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