Generation control of interconnected power systems using computational intelligence techniques

Basic power systems are steadily growing and have become large and more complex with interconnections to neighbouring systems. A novel approach is presented for steady-state analysis of generation control, incorporating load and generation characteristics, which gives nearly exact practical solution for large interconnected power systems during normal operating conditions and under disturbance. It also assists planning and operation engineers to observe the steady-state behaviour of a network disturbances, such as loss of generation and loss of load. Adopting decoupled Newton-Raphson method, steady-state frequency deviation (DeltaF) and tie-line error (DeltaP_tie)are estimated for the disturbance. In the paper, the knowledge of frequency deviation and tie-line error are handled to produce the required change in generation using both a fuzzy-logic controller and an artificial-neural-network controller separately.