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# GWO Optimized LFC controller for PV Wind Thermal Power system

## GWO Optimized LFC controller for PV Wind Thermal Power system

Introduction:

Welcome, viewers, to LMI Solution! In today's session, we'll explore the implementation of a Grey Wolf Optimized Load Frequency Controller integrated with a thermal power system and renewable energy sources. This concept is derived from a reference paper that focuses on the integration of variable energy into thermal systems for effective load frequency control. The approach considers a two-area system, connecting a thermal system in Area 1 and a wind system in Area 2. The controllers employed include a P I D controller for enhanced automation.

### System Description:

Controller Structure:

• The controller structure involves a PID controller with two derivative parts. The parameters of this controller are tuned through a software optimization process.

System Areas:

• Area 1 is connected to a thermal system, while Area 2 is connected to a wind system.

Objective Function:

• The objective function for optimization is defined as the integration of absolute error multiplied by time, particularly focusing on integral time multiplied by absolute error (ITA). This function guides the optimization process to find optimal values for controller parameters.

### MATLAB Implementation:

Variable Optimization:

• The MATLAB script incorporates the optimization process using the Grey Wolf Algorithm to find optimal values for controller parameters. The optimization targets the integral time multiplied by absolute error (ITA).

Simulation:

• After optimization, the obtained optimal parameters are used in the Load Frequency Controller (LFC) model. The simulation results showcase the effectiveness of the Grey Wolf Optimized controller in handling load frequency control with renewable energy integration.

### Conclusion:

The Grey Wolf Optimized Load Frequency Controller, integrated with thermal and renewable energy systems, provides an efficient approach to enhance load frequency control. By optimizing controller parameters using the Grey Wolf Algorithm, the system achieves optimal performance. The MATLAB simulation results reflect the successful integration of renewable energy into the thermal power system.

### Future Considerations:

Future studies can explore the adaptability of this approach to larger power systems and investigate the impact of varying renewable energy inputs.

In conclusion, the Grey Wolf Optimized Load Frequency Controller presents a promising solution for improved load frequency control in power systems incorporating renewable energy. Thank you for watching our video, and be sure to subscribe to our channel for more insightful content. Stay tuned for upcoming videos!