The application of NN technique to automatic generation control for the power system with three areas including SMES units

The study includes an application of layered neural network controller to study automatic generation control (AGC) problem of the power system, which contains superconducting magnetic energy storage (SMES) units. The effectiveness of SMES unit over frequency oscillations improvement against load perturbations in power system is well known. In addition, the proposed control scheme provides the steady state error of frequency and inadvertent interchange of tie-lines to be maintained in steady state values. The power system considered has three areas two of which including steam turbines while the other containing a hydro turbine, and all of them contain SMES units, in addition. In the power system each area with a steam turbine contains the non-linearity due to reheat effect of the steam turbine and all of the areas contain upper and lower constraints for generation rate. Only one neural network (NN) controller, which controls all the inputs of each area in the power system, is considered. In the NN controller, back propagation-through-time algorithm is used as neural network learning rule. The performance of the power system is simulated by using conventional integral controller and NN controller for the cases with or without SMES units in all areas, separately. By comparing the results for both cases, it can be seen that the performance of NN controller is better than conventional controllers.