The Review Robustness of FMPC-Based SMIB Dynamic Stability Control Using Load Cluster Pattern

Fluctuations in electrical load due to usage affect the stability of frequency and voltage values in the generating system. The study of electrical load forecasting is one solution to achieve dynamic stability of the generating system. However, optimization of electrical load dynamics modeling can be achieved through the formation of load cluster patterns. This paper proposes a test of an electrical load forecasting model based on hierarchical cluster grouping based on distance similarity to determine the number of clusters through an analytical descriptive approach. This research shows the robustness of the electrical load cluster pattern using Fuzzy Model Predictive Control. For a model with 7 clusters, an average increase in frequency performance of 11.75 percent, voltage of 8.44 percent, and output power of 13.99 percent was obtained. While the model with 4 clusters obtained an average increase in frequency performance of 16.21 percent, voltage of 5.45 percent, and output power of 14.78 percent.