Long-term Forecasting Heat Use in Sweden's Residential Sector using Genetic Algorithms and Neural Network

Abstract

In this study, the parameters of population, gross domestic product (GDP), heat price, U-value, and temperature have been used to predict heat consumption for Sweden till 2050. It should be noted that the heat consumption has been considered for multi-family houses. Most multi-family houses (MFH) get their primary heat from district heating (DH). A literature analysis of various models and variables has been conducted to enhance comprehension of forecasting and its process. The majority of earlier research has focused on electricity or energy rather than heat. The aim of this study is to create a model (linear and non-linear) from 1993 to 2019 with a minimum error as possible, and then use the genetic algorithm (GA) and neural network (NN) to predict Sweden's heat consumption till 205