Multiobjective design of load frequency control using genetic algorithms

Recently, several modern control theory designs like H∞ have been applied to the load–frequency control (LFC) problem optimization technique. However, the importance and difficulties in the selection of weighting functions of these approaches and the pole-zero cancellation phenomenon associated with it produces closed loop poles. In addition, the order of the H∞-based controllers is as high as that of the plant. This gives rise to complex structure of such controllers and reduces their applicability. Also conventional LFC systems that use classical or trial-and-error approaches to tune the PI controller parameters are more difficult and time-consuming to design.In this paper the decentralized LFC synthesis is formulated as a multiobjective optimization problem (MOP) and is solved using genetic algorithms (GAs) to design well-tuned PI controllers in multi-area power systems. The proposed control scheme has been applied to the LFC problem in a three-area power system network and the 10-machine New England test system respectively and shows desirable performance.