A Novel Approach to Load Frequency Control Incorporating Renewable Energy and Automatic Voltage Regulator Optimized by Teaching-Learning-Based Optimization

The traditional method of generating power from fossil fuels leads to environmental damage more over these are non-renewable substances and are on the verge of extinction. Keeping these issues in mind there is incorporation of renewable energy sources (RES) such as wind turbine generation (WTG) and Photovoltaic (PV) in distribution system. The penetration of RES is pushed the standalone microgrid towards due to its intermittent nature leading to voltage and frequency fluctuations and affecting grid stability and reliability. To mitigate the impact caused by load fluctuation and the inherent variability of RES output, the paper proposes an optimized Tilt Integral Derivative (TID) controller. During iterative optimization, a weighted objective function is employed to robust stability and disturbance attenuation performances and to harmonize tracking error. Then the TID controller is determined by a metaheuristic Teaching-Learning-based optimization (TLBO) algorithm. The proposed control method is studied for a single-area microgrid system. The system consists of different generating units such as Diesel Engine Generator (DEG), Micro Turbine (MT), and Fuel Cell (FC), along with energy storage systems such as Flywheel Energy Storage (FES) and Batter Energy Storage (BES). Further, the system is incorporated with an Automatic Voltage Regulator (AVR) for enhanced stability, improved power quality, and overall grid stability.