Gab-SSDS: An AI-Based Similar Days Selection Method for Load Forecast

The important, while mostly underestimated, step in the process of short-term load forecasting–STLF is selection similar days. Similar days are identified based on numerous factors, such as weather, time, electricity prices, geographical conditions and consumers’ types. However, those factors influence differently within different circumstances conditions. To investigate optimise process, a new forecasting method, named Genetic algorithm-based–smart method–Gab-SSDS, has been proposed. presented approach implements genetic algorithm selecting days, used input parameters for STLF. Unlike other methods that use only to engine, authors suggest additional phase identify individual impact forecasted load. Several experiments were executed method’s effectiveness, forecast accuracy proposed how using can improve traditional an artificial neural network. paper reports experimental results, which affirm method potential increase