Due to an increase in the production of various industries, the employment of automated systems, and  the consequent use of numerous appliances on both the sending end and the receiving end of the power system, the world's energy consumption has been rising quite quickly in recent decades. As a result, maintaining the quality of the power is crucial for maintaining stability. The greatest problem in the current electrical power system without compromising the quality and flow of power is penetration of such sources to generate electricity due to variations in the availability of natural resources. Maintaining a strong, dependable, and exceptionally smart generation, distribution, and transmission infrastructure is crucial. In order to preserve consistent quality & flow of electricity with its stability, this paper presents many power quality difficulties & tasks in the penetration of renewable energy resources with solutions. The article outlines the methods put in place on the power system to reduce power quality issues. 
 

This study offers an adaptive neuro-fuzzy controller (NFC) for a wind energy conversion system (WECS) based on a doubly fed induction generator (DFIG) that may run in standalone mode. The adaptivenetwork-based fuzzy inference system (ANFIS) architecture is the foundation upon which the NFC is built since it offers the singular benefit of rapid convergence while integrating the resilience of fuzzy logic and flexibility of neural network algorithm. The load side converter (LSC) control of ANFIS is intended for the independent operation of DFIG-WECS. By keeping output voltage consistent, the suggested approach shows increased dynamic performance under conditions of fluctuating wind speed and load. Due to the precise control of the LSC, the supply frequency to the load is kept consistent even while the turbine rotation changes with changing wind speed. The rotor side converter's proportional-integral (PI) control maintains the flux alignment. The simulation outcomes demonstrate the controller's exceptional performance through its effective management of supply frequency and load-voltage under variations in wind speed and demand load power. 
 

This paper focuses on the development of ANN based MPPT interfaced Permanent magnet synchronous generator (PMSG) for wind energy conversion system (WECS). It focuses on design and modeling aspects of the completely different elements of the WECS like the fundamental model of ANN based MPPT controller, MLI, wind turbine, optimum maximum power point tracking system utilizing MATLAB/Simulink. Major object is to extract the maximum energy from the wind which confirms a highest efficiency of developed system. The thesis shows the model of wind turbine together with the model of PMSG. The ANN based mostly MPPT approach used right here is predicated on Perturbation and observation (P&O). To complete the process of modeling and simulation the platform of MATLAB/Simulink is utilized. Developed ANN are most efficient technique compared to conventional methods. It achieves maximum power with more stability, precision and better performance with good dynamic response under variable wind speed conditions. It exhibits the enhancements for the developed system and control action for balance/unbalanced steady state in addition to transient, dynamic response circumstances.