Comparison of neural network, conditional demand analysis, and engineering approaches for modeling end-use energy consumption in the residential sector

2008 ◽  
Vol 85 (4) ◽  
pp. 271-296 ◽  
Author(s):  
Merih Aydinalp-Koksal ◽  
V. Ismet Ugursal
Keyword(s):  
Neural Network ◽  
Energy Consumption ◽  
Demand Analysis ◽  
Residential Sector ◽  
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.

Analysis of Energy Use and Related Carbon Emissions in Beijing and Shanghai

2013 ◽  
Vol 291-294 ◽  
pp. 1365-1369
Author(s):  
Jing Zhang ◽  
Ru Guo
Keyword(s):  
Energy Consumption ◽  
Carbon Emissions ◽  
Power Plants ◽  
Energy Use ◽  
Thermal Power ◽  
Energy System ◽  
Rapid Urbanization ◽  
Residential Sector ◽  
Secondary Industry ◽  
End Use

Most Chinese cities are experiencing rapid urbanization and economic growth. It is needed to explore how a city’s energy system evolves and how it can be altered to reduce carbon emissions. This paper analyzed energy consumption and related CO2 emissions in Beijing and Shanghai. A rapid growth in energy consumption during the last two decades is evident. Shanghai presents higher energy intensity than Beijing, mainly due to the larger share of the secondary industry in economy. Energy consumption by the residential sector is higher in Beijing, despite a larger population in Shanghai. The CO2 emissions by the end-use energy in 2010 are 152 and 259 million ton in Beijing and Shanghai, respectively. Electricity usage presents an important share of energy consumption and CO2 emissions. Thus, development of renewable energy for electricity generation and improvement of the technologies in thermal power plants are important to reduce the future carbon emissions.

scholarly journals Energy Scenarios of Household Sector In Panauti Municipality For Sustainable Development and Energy Security

2019 ◽  
Vol 5 ◽  
pp. 89-100
Author(s):  
Pramila Dhaubanjar ◽  
Amrit Man Nakarmi ◽  
Sushil B. Bajracharya
Keyword(s):  
Energy Consumption ◽  
Total Energy ◽  
Energy Security ◽  
Energy Demand ◽  
Animal Feed ◽  
Secondary Data ◽  
Total Energy Consumption ◽  
Residential Sector ◽  
Per Capita ◽  
End Use

This study aims to analyse energy scenarios of residential sector in Panauti Municipality for sustainable energy development and energy security. This study was done by conducting a questionnaire survey, and was supported by secondary data from various sources. Data analysis was carried out with the help of excel and LEAP software. From the results, total energy consumption of Panauti Municipality is 147 TJ in year 2016 with per capita is 4.72GJ and per capita emission 82kg. The main fuel for consumption in residential sector is firewood with share 44% then followed by LPG with 26% of total energy. Cooking is the most energy intensive end-use, accounting 60% of total energy consumption, followed by animal feed preparation 28%. It was seen that total electrification in all end-use can reduce energy demand by 57% and 35% respectively in AEL and SUD scenario and saved fuel import cost about NRs.235 million. in year 2050. Using nationally available electricity ensures energy security and has co-benefit of emission reduction.

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