The objective of this project is to minimize the voltage and frequency deviations, to attain a proper power flow between DC and AC buses. And to maintain a smooth mode transition between autonomous and grid connected modes.
In this project, a robust Iterative Learning Controller (ILC) operating under autonomous and grid connected modes with variable generation and loading conditions has been proposed for maintaining a stable voltage and frequency of a micro grid. The micro grid was modeled with solar, wind, fuel cell, battery, and load.
The simulation was carried out in MATLAB/Simulink and the results were compared with the performance of Proportional Integral Controller, Fuzzy Logic Controller, and Recurrent Neural Network Controller.
The performance indices, such as Integral of Time Absolute Error, Integral of Time Squared Error, standard deviation, percentage overshoot of DC bus voltage, and execution time of controller, were evaluated to validate the performance of the proposed controller. The results show that the proposed ILC is more effective in controlling voltage and frequency when compared to other controllers.
Keywords: Distributed Generation, Energy Management System, Solar PV system, wind energy conversion system, Iterative Learning Controller, Recurrent Neural Network.
NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Software Configuration:
Operating System : Windows 7/8/10
Application Software : Matlab/Simulink
Hardware Configuration:
RAM : 8 GB / 4 GB (Min)
Processor : I3 / I5(Mostly prefer)