Load Frequency Control in Interconnected Power System by Nonlinear Term and Uncertainty Considerations by Using of Harmony Search Optimization Algorithm and Fuzzy-Neural Network

Load frequency control is one of the most important issues in the power systems that many researches have been done for improving this problem until now, but most of the researches have not considered the power system model that is close to reality and nonlinear factors such as generation rate constraints, governor dead-band, boiler dynamic and time delays. Also because of the power system dynamic changes continuously, the uncertainty is undeniable in the system. In this article by consideration of these nonlinear effects and uncertainty, first the PI control factors are found by using the harmony search algorithm then by consideration of the uncertainty, optimized factors for PI controller are found each time and by forming a table that determines inputs and outputs for fuzzy-neural network, the designing and training of the fuzzy-neural network is done that has capability of controller coefficients regulation in various dynamics of system and presence of uncertainty. The proposed method by a fuzzy controller that is designed based on certified knowledge, has been compared and shown that has a very good performance such as lower settling time, higher speed, better damping, and steady-state error equal to 0.