Evaluation and monitring of energy consumption patterns using statistical modeling and simulation

Author

Khalid, Qasim ; Langhe, Roland

fYear

2010

fDate

18-19 Oct. 2010

Firstpage

124

Lastpage

127

Abstract

Regression models have been defined with the help of case studies, carried out for residential and commercial buildings in Sweden, for energy consumption patterns and predictions. Regression models are used as an input to Monte Carlo simulation technique to carry out energy predictions and future energy demand and supply patterns. Model is developed on the basis of historical data for four years: 2006 to 2009. Aim is to analyze the regression models for long term forecasting of monthly energy consumption patterns. The predicted models can assist the companies for making decisions of energy demand/supply plans.

Keywords

Monte Carlo methods; decision making; load forecasting; power system planning; regression analysis; supply and demand; Monte Carlo simulation; decision making; energy consumption pattern monitoring; energy demand-supply planning; monthly energy consumption forecasting; statistical regression modeling; Buildings; Energy consumption; Monte Carlo methods; Power demand; Predictive models; Sensitivity; Temperature sensors; Energy consumption patterns; Modeling and Simulation; Non-linear regression; Regression models;

fLanguage

English

Publisher

ieee

Conference_Titel

Emerging Technologies (ICET), 2010 6th International Conference on

Conference_Location

Islamabad

Print_ISBN

978-1-4244-8057-9

Type

conf

DOI

10.1109/ICET.2010.5638367

Filename

5638367