Network and Generator Constrained Economic Dispatch Using Real and Binary Coded Genetic Algorithms

The efficient and optimum economic operations of electric power generation systems have always occupied an important position in the electric power industry. This involves allocation of the total load between the available generating units in such a way that the total cost of operation is kept at a minimum. Network constrained economic dispatch have been applied to obtain optimal fuel cost while satisfying transmission line power flow limits. Similarly generator constrained economic dispatch schedules the outputs of generating units to meet the demand at minimum cost considering the prohibited zones. This paper proposes different types of Genetic Algorithms such as Binary Coded GA, Real Coded GA and Directional Search GA for solving the classical economic dispatch problem. The purpose of Network Constrained Economic Dispatch (NC-ED) and Generator Constrained Economic Dispatch is to minimize the operating fuel cost while satisfying load demand and operational constraints. As such, a Heuristic Algorithm is developed in this paper to adjust the generation output of a unit in order to avoid unit operation in the prohibited zones