Tuning of LFC in Multi-source Electrical Power Systems Implementing Novel Nature Inspired MFO Algorithm Based Controller Parameter

摘要

Moth Flame Optimization (MFO) is one of the latest metaheuristic optimization algorithms used in this paper for finding the PID optimal controller parameters in Automatic Generation Control (AGC) of single area with hydroelectric, thermal and gas hybrid power generation units. The optimizer inspires the navigation method of moths in nature which is called as the transverse orientation. The effectiveness of this algorithm is compared with the recent published TLBO and DE optimization algorithm applied in the same field to obtain the controller parameters. The controller performance of the controller's performance is compared with other objective functions. Responses such as like overshoot of frequency output, power deviation of the tie line and time of settling are compared by changing the system parameters and load. It is observed that the system become comparatively more stable with the use of the proposed controller. The performance is found to be better in comparison to that of TLBO and Differential Evolution algorithm-based feedback controller with change in parameters of the system and loading.