Implementation Of AGC In PSAT For Optimal Use In Smart Grid

With the development of Smart Grids worldwide, efforts have been focused on opti-mizing the role of Smart Grid in the present electrical system. Since non-renewable energy resources are limited, the focus has shifted to integration of renewable energy resources such as wind to the smart grid. This imposes greater challenges since these renewable energy resources are intermittent in nature and vary constantly. To deal with this challenge, the new centre of attraction is AGC.Automatic Generation Control (AGC) has been used to keep a balance between gen-eration and demand. With power output of renewable energy resources constantly varying, the focus has been to design an efficient AGC to maintain the balance. The main function of AGC is to adjust the active power generation of generators so as to keep the frequency constant. AGC has been implemented in some softwares but not in PSAT.PSAT is the MATLAB toolbox designed to perform simulations of electric power systems. It can perform various functions such as Small Signal Stability Analysis, Time Domain Simulations, Continuation Power Flow, Optimal Power Flow and Simple Power Flow. But it lacks the functionality of AGC. This research presents AGC implementation on PSAT using neural networks and PID controller. The goal is to optimize PSAT by adding extra functionalities to it. The AGC design is implemented on IEEE14-bus system on PSAT. The results show successful ad-dition of AGC to PSAT library. The AGC design helps to control the frequency, has high performance and can be extended to other power systems.