A genetic-based approach for solving optimal power flow problem

Abstract EN

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 meet 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