CLIMATE IMPACT ON ENERGY DEMAND FOR SPACE HEATING IN ICELAND

A major impact of climate change is expected to materialize on energy demand for space heating and cooling needs in the residential sector. To quantify this impact, a set of regression models were tested to study the relation between residential energy demand for space heating in Iceland and explanatory variables such as Heating Degree Days and GDP per capita. Considering the nonstationarity of the time-series, three methods were studied to cope with this condition: Cointegration, differencing and detrending.The evaluation statistics of the three models for the validation period showed that the modified detrending approach is the most reliable method. It became obvious that including the seasonal dummy variables and AR component significantly improve the power of the model to predict monthly energy demand for residential space heating in Iceland. The developed model can be used to project climate related changes in demand for low-geothermal heat.

[1]  G. Franco,et al.  Climate change and electricity demand in California , 2008 .

[2]  A. Amato,et al.  Regional Energy Demand Responses To Climate Change: Methodology And Application To The Commonwealth Of Massachusetts , 2005 .

[3]  M. Ruth,et al.  Regional energy demand and adaptations to climate change: Methodology and application to the state of Maryland, USA , 2006 .

[4]  Julián Moral-Carcedo,et al.  Modelling the non-linear response of Spanish electricity demand to temperature variations , 2005 .

[5]  Development and the Impact of Climate Change on Energy Demand: Evidence from Brazil , 2010 .

[6]  Guohua Liu,et al.  Towards an Error Correction Model for dam monitoring data analysis based on Cointegration Theory , 2013 .

[7]  G. Yule Why do we Sometimes get Nonsense-Correlations between Time-Series?--A Study in Sampling and the Nature of Time-Series , 1926 .

[8]  L. Baxter,et al.  Global warming and electricity demand: A study of California , 1992 .

[9]  R. Engle,et al.  Modelling peak electricity demand , 1992 .

[10]  E. Mansur,et al.  Climate change adaptation: A study of fuel choice and consumption in the US energy sector , 2008 .

[11]  Jonathan G. Koomey,et al.  WHAT CAN HISTORY TEACH US? A Retrospective Examination of Long-Term Energy Forecasts for the United States* , 2002 .

[12]  Sašo Medved,et al.  Predicted changes in energy demands for heating and cooling due to climate change , 2010 .

[13]  John Peirson,et al.  Electricity load and temperature: issues in dynamic specification , 1994 .

[14]  Á. Pardo,et al.  Temperature and seasonality influences on Spanish electricity load , 2002 .

[15]  Kjell Vaage,et al.  HEATING TECHNOLOGY AND ENERGY USE, A DISCRETE/CONTINUOUS CHOICE APPROACH TO NORWEGIAN HOUSEHOLD ENERGY DEMAND , 2000 .

[16]  M. Auffhammer,et al.  Measuring climatic impacts on energy consumption: A review of the empirical literature , 2014 .

[17]  Donald W. Marquardt,et al.  Comment: You Should Standardize the Predictor Variables in Your Regression Models , 1980 .

[18]  Erkan Erdogdu Electricity Demand Analysis Using Cointegration and ARIMA Modelling: A case study of Turkey , 2007 .

[19]  John Peirson,et al.  Residential energy demand and the interaction of price and temperature: British experimental evidence , 1998 .

[20]  John Peirson,et al.  Non‐Linearities in Electricity Demand and Temperature: Parametric Versus Non‐Parametric Methods , 1997 .

[21]  The Impact of Climate Change on the United States Economy: The impact of global warming on US energy expenditures , 1999 .

[22]  R Aguiar,et al.  Climate change impacts on the thermal performance of Portuguese buildings. Results of the SIAM study , 2002 .

[23]  Hulya Sarak,et al.  The degree-day method to estimate the residential heating natural gas consumption in Turkey: a case study , 2003 .

[24]  T. Frank,et al.  Climate change impacts on building heating and cooling energy demand in Switzerland , 2005 .

[25]  Michael J. Scott,et al.  Effects of Climate Change on Commercial Building Energy Demand , 1994 .

[26]  Byung Sam Yoo,et al.  Seasonal integration and cointegration , 1990 .

[27]  Benjamin F. Hobbs,et al.  Artificial neural networks for short-term energy forecasting: Accuracy and economic value , 1998, Neurocomputing.

[28]  D. Sailor,et al.  Air conditioning market saturation and long-term response of residential cooling energy demand to climate change , 2003 .

[29]  M. J. OrtizBevia,et al.  The influence of meteorological variability on the mid-term evolution of the electricity load , 2014 .

[30]  James A. Dirks,et al.  Methodological Framework for Analysis of Buildings-Related Programs: The GPRA Metrics Effort , 2004 .

[31]  R. Sands,et al.  Climate Change Impacts on U.S. Commercial Building Energy Consumption: An Analysis Using Sample Survey Data , 1996 .

[32]  V. Bianco,et al.  Electricity consumption forecasting in Italy using linear regression models , 2009 .

[33]  Projecting Monthly Natural Gas Sales for Space Heating Using a Monthly Updated Model and Degree-days from Monthly Outlooks , 1994 .

[34]  D. Sailor Relating residential and commercial sector electricity loads to climate : evaluating state level sensitivities and vulnerabilities , 2001 .