Analysis of Correlations between Energy Consumption, Structural Specifications and Climate-Induced Variables to increase Energy Efficiency in Households and Buildings through a Prediction Model

Abstract

In a world where the transition towards increasingly progressive renewable energy sources is of great importance moving towards sustainability for our planet and future generations, a large portion of mundane equipment and machinery will turn to the usage of electricity rather than fossil fuel as a resource. This does however pose some challenges to the infrastructure in place as it increases the strain on the power grid through the vastly increased demand for power, potentially outweighing the supply. The primary goal of this thesis is to find and analyze correlations between factors expected to have an impact on the energy efficiency of buildings and present a methodology and a model which could be applied to buildings in order to examine the effects of implementing a series of measures to a building’s structural envelope. This is done through the usage of advanced prediction/forecasting models for wind, measured data for temperature at specified locations, and an analysis of energy consumption over time at two locations, where the changes in energy efficiency before and after renovation at one location is used as a measuring stick to predicting post-renovation changes in energy efficiency at the other. The thesis shows a clear correlation between temperature, wind speeds and energy consumptions both before and after renovation, although post-renovation correlations are significantly lower in comparison to prior to renovation. Similarly, there is a significant decrease in energy consumption before and after renovation, although due to the unexpected usage of an alternate energy sources in form of fireplaces at one of the locations prior to renovation, the decrease is likely to be significantly more extreme than what the data suggests.