A New Approach for Modeling of Residential Energy Consumption
A National Neural Network Model for Residential End-use Energy Consumption
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Energy use and associated greenhouse gas emissions,and their potential effects on the global climatechange have been the worldwide concern particularlyafter the Kyoto Protocol. Improving the energyefficiency is one of the most effective ways toreduce energy use and associated emissions,especially for the residential sector. Since energyefficiency improvements have complex interrelatedeffects on the household energy use, detailedmathematical models are required to evaluate theireffects on residential energy use. This bookinvestigates the use of Neural Network (NN) approachfor modeling residenti...
Energy use and associated greenhouse gas emissions,
and their potential effects on the global climate
change have been the worldwide concern particularly
after the Kyoto Protocol. Improving the energy
efficiency is one of the most effective ways to
reduce energy use and associated emissions,
especially for the residential sector. Since energy
efficiency improvements have complex interrelated
effects on the household energy use, detailed
mathematical models are required to evaluate their
effects on residential energy use. This book
investigates the use of Neural Network (NN) approach
for modeling residential end-use energy consumption
at the national level. In addition to the NN model, a
statistical residential end-use model is also
developed. A comparison of the estimates of the NN
model with those of the statistical and an
engineering model developed earlier using the same
database shows that the NN model has a higher
prediction performance and ability to characterize
the residential end-use energy consumption than other
models. The NN Model is able to estimate the impact
of socio-economic factors and energy saving measures
on residential end-use energy consumption successfully.
and their potential effects on the global climate
change have been the worldwide concern particularly
after the Kyoto Protocol. Improving the energy
efficiency is one of the most effective ways to
reduce energy use and associated emissions,
especially for the residential sector. Since energy
efficiency improvements have complex interrelated
effects on the household energy use, detailed
mathematical models are required to evaluate their
effects on residential energy use. This book
investigates the use of Neural Network (NN) approach
for modeling residential end-use energy consumption
at the national level. In addition to the NN model, a
statistical residential end-use model is also
developed. A comparison of the estimates of the NN
model with those of the statistical and an
engineering model developed earlier using the same
database shows that the NN model has a higher
prediction performance and ability to characterize
the residential end-use energy consumption than other
models. The NN Model is able to estimate the impact
of socio-economic factors and energy saving measures
on residential end-use energy consumption successfully.
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