Forecasting Residential Electricity Consumption in Southeastern Brazil Using Type-2 Interval Fuzzy Inference Systems

Abstract

Electricity consumption in the residential sector has increased over the last few decades [1]. With the introduction of new technologies, different types of loads have been used and consumer behaviour has changed. Therefore, it is extremely important to improve electricity consumption models for residential units to incorporate changes in consumer habits and uncertainties [2]. This article proposes the use of an Interval Type-2 Fuzzy Inference System (IT2FIS) to estimate the electricity consumption of residential units, taking into account aspects of consumer behaviour, climatic conditions and socio-economic aspects. The database used to evaluate the models contains 2073 hourly consumption samples, obtained from the 2019 Survey of Ownership and Usage Habits of Electrical Equipment in the Residential Class, carried out by the Programa Nacional de Conservação de Energia Elétrica - Procel [41]. The models were implemented using the Pyhton programming language. The results were evaluated using Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Mean Square Error (MSE) and Root Mean Square Error (RMSE). The results obtained were satisfactory and demonstrate that IT2FIS models can correlate human behavioural aspects, social and economic factors, and climatic conditions in order to estimate hourly electricity consumption in the residential sector.