OVERVIEW OF PREDICTION MODELS FOR BUILDINGS ENERGY EFFICIENCY

The purpose of the paper is to provide an overview of existing models that deal with energy efficiency for buildings. The research aims to scientifically contribute the realization of European Commission directives about reducing greenhouse gas emissions, increasing energy efficiency and using 20% of energy consumption from renewable energy resources until 2020. There are Strategies of energy development as well as National plans of energy efficiency in Croatia and in other EU countries, which quantify and control the objectives of reducing immediate energy consumption. However, the data on energy efficiency have not been analyzed enough for the purpose of efficient management of energy consumption and cost reduction, while there is a lack of research that use machine learning methods to more precisely detect interdependence among variables, prediction of payback period and other analytics. In this paper, the methodology used in previous research as well as the choice of variables used to model energy efficiency of buildings is analyzed. The advantages and limitations of previous approaches are identified which can serve as a baseline for future research in providing more efficient models.