A Fuzzy Logic Model for Short-Term Load Forecasting in the Libyan Power Network

Abstract

Short-term load forecasting is an essential system for predicting electricity demand, with a lead time ranging from one hour to one month. This is crucial for effectively scheduling and operating the power system. Achieving high forecasting accuracy is of utmost importance, requiring a thorough analysis of load characteristics and the identification of key factors influencing demand. In electricity markets, factors such as season, day type, weather, and electricity prices have intricate relationships with system load. This study focuses on conducting short-term load forecasting for the Libyan electric grid using a fuzzy logic technique. Input variables for the fuzzy logic include temperature, humidity, and the previous day's peak load. The design and simulation of the fuzzy logic system are implemented using MATLAB SIMULINK software. The results demonstrate that weather factors significantly impact the electric system's load. The model's error margin ranges between +3.67% and -3.75%. Additionally, the study concludes that the fuzzy logic method is easy for forecasters to understand due to its use of simple "IF-THEN" statements.