Automatic Generation Control of Multi-Area Multi-Source Realistic System using GWO Algorithm

This paper presents the study of an application of an innovative search method founded on the concept of artificial intelligence. It focuses on the factors to be optimized that is nonlinear in Load Frequency Controller (LFC). To study the given purpose, a power system with multiple sources is considered. Area-1 has non-reheat thermal, hydro and wind plants while area-2 has non-reheat thermal, hydro and diesel power plants. System performance with boiler dynamics and governor dead band (GDB), governor rate constraint (GRC) was also considered. Gray Wolf Optimized algorithm (GWO) is used to identify the optimum controller factors to mineralize time-domain-objective-function. The outcome obtained from its compared and analyzed with recently publishing algorithm outcomes viz. differential evolution (DE) and teaching-learning optimization algorithm (TLBO) to demonstrate the relatively better and more efficient performance of given scheme of tuning PID by GWO. With this correlative study and analysis, the performance of the proposed GWO is proven and verified over diverse operational settings, and system parameters disparities.