Short-Term Load Forecasting Using Application of Interval Type 2 Fuzzy Logic

This study investigates the development of Interval Type 2 Fuzzy Logic (IT2FL) for short-term load forecasting (STLF). Maintaining grid stability and assuring a steady supply of power is crucial, and hence the need for accurate STLF. The study's main objective is to assess IT2FL's accuracy and dependability by contrasting it with a benchmark Artificial Neural Network (ANN). The findings show that IT2FL performs quite effectively, producing load estimates that nearly match target values. Its ability to retain accuracy in a variety of settings and during periods of high load indicates its robustness. Comparative investigation demonstrates the possibility of IT2FL as a workable STLF solution. Even with more work to be done, IT2FL has the potential to fulfill the ever-evolving demands of the energy industry by providing reliable and accurate load forecasting.