A Bayesian Integration of End-Use Metering and Conditional-Demand Analysis

1995 ◽  
Vol 13 (3) ◽  
pp. 315 ◽  
Author(s):  
Cheng Hsiao ◽  
C. Mountain ◽  
Kathleen Ho Illman
Keyword(s):  
Demand Analysis ◽  
Bayesian Integration ◽  
Conditional Demand Analysis ◽  
End Use

Use of Nerual Networks for Modeling Energy Consumption in the Residential Sector

2010 ◽  
pp. 180-204
Author(s):  
Merih Aydinalp Koksal
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Residential Energy ◽  
Residential Energy Consumption ◽  
Residential Sector ◽  
Advantages And Disadvantages ◽  
Energy Consumption Model ◽  
Engineering Models ◽  
Conditional Demand Analysis ◽  
End Use

This chapter investigates the use of neural networks (NN) for modeling of residential energy consumption. Currently, engineering and conditional demand analysis (CDA) approaches are mainly used for residential energy modeling. The studies on the use of NN for residential energy consumption modeling are limited to estimating the energy use of individual or a group of buildings. Development of a national residential end-use energy consumption model using NN approach is presented in this chapter. The comparative evaluation of the results of the model shows NN approach can be used to accurately predict and categorize the energy consumption in the residential sector as well as the other two approaches. Based on the specific advantages and disadvantages of three models, developing a hybrid model consisting of NN and engineering models is suggested.

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