Paper Details

The Automatic Generation Control (AGC) process performs the task of adjusting system generation tomeet the demand for sustainable load control and regulation at the large system frequency changes. In most of theearlier work on the interconnected systems, line of junction bias control strategy has been widely accepted by the publicservices. In this method, Area Control Error (ACE) is calculated through feedback for each area and control action istaken to regulate ACE to zero. As well, the frequency and power are interchanged retained as large system requirement.The problems of monitoring the frequency of interconnected areas are more important than those isolated areas (simple).Intelligent control techniques provide a strong adherence to the evolution of the conditions and have the ability to makedecisions quickly by the treatment of the imprecise information. In this research work, the parameters of the fuzzycontrollers are very variable by an appropriate choice of the functions of members and the settings in the basis of rules.The effectiveness of the fuzzy controllers is tested on a double machine operation producing the system with AGC forseveral points of operation. The two different systems like hydro-thermal and thermal-thermal work based on differentfrequency conditions. These systems are Comparing for without and with fuzzy system for efficient output.

Atul Gandhi, Pankaj Kumar Mehta, “Evaluation of Artificial Intelligence Technique in Improving Automatic Generation Control”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 4, Issue 8, pp. 605-611, August 2017.