A platform for research: civil engineering, architecture and urbanism
Spatial distribution of urban building energy consumption by end use
Highlights ► Develops a model to estimate urban building sector annual energy end-use intensities. ► Intensities calculated using a robust multivariate linear regression. ► Calibrated using ZIP code level data for electricity and fuel use. ► End-use ratios derived from residential and commercial building consumption surveys. ► Results in map of building energy consumption by end use for New York City.
Abstract The current energy distribution infrastructure in many urban areas either cannot support anticipated future energy use or would require significant rehabilitation even if current use were maintained. Understanding the dynamics of local energy use is an important precondition of understanding how to remedy this situation. This paper builds a model to estimate the building sector energy end-use intensity (kwh/m2 floor area) for space heating, domestic hot water, electricity for space cooling and electricity for non-space cooling applications in New York City. The model assumes that such end use is primarily dependent on building function, whether residential, educational or office for example, and not on construction type or the age of the building. The modeled intensities are calibrated using ZIP code level electricity and fuel use data reported by the New York City Mayor's Office of Long-Term Planning and Sustainability. The end-use ratios were derived from the Residential and Commercial Building Energy Consumption Survey's Public Use Microdata. The results provide the ability to estimate the end-use energy consumption of each tax lot in New York City. The resulting spatially explicit energy consumption can be a valuable tool for determining cost-effectiveness and policies for implementing energy efficiency and renewable energy programs.
Spatial distribution of urban building energy consumption by end use
Highlights ► Develops a model to estimate urban building sector annual energy end-use intensities. ► Intensities calculated using a robust multivariate linear regression. ► Calibrated using ZIP code level data for electricity and fuel use. ► End-use ratios derived from residential and commercial building consumption surveys. ► Results in map of building energy consumption by end use for New York City.
Abstract The current energy distribution infrastructure in many urban areas either cannot support anticipated future energy use or would require significant rehabilitation even if current use were maintained. Understanding the dynamics of local energy use is an important precondition of understanding how to remedy this situation. This paper builds a model to estimate the building sector energy end-use intensity (kwh/m2 floor area) for space heating, domestic hot water, electricity for space cooling and electricity for non-space cooling applications in New York City. The model assumes that such end use is primarily dependent on building function, whether residential, educational or office for example, and not on construction type or the age of the building. The modeled intensities are calibrated using ZIP code level electricity and fuel use data reported by the New York City Mayor's Office of Long-Term Planning and Sustainability. The end-use ratios were derived from the Residential and Commercial Building Energy Consumption Survey's Public Use Microdata. The results provide the ability to estimate the end-use energy consumption of each tax lot in New York City. The resulting spatially explicit energy consumption can be a valuable tool for determining cost-effectiveness and policies for implementing energy efficiency and renewable energy programs.
Spatial distribution of urban building energy consumption by end use
Howard, B. (author) / Parshall, L. (author) / Thompson, J. (author) / Hammer, S. (author) / Dickinson, J. (author) / Modi, V. (author)
Energy and Buildings ; 45 ; 141-151
2011-10-31
11 pages
Article (Journal)
Electronic Resource
English
Spatial distribution of urban building energy consumption by end use
Online Contents | 2012
|British Library Conference Proceedings | 2019
|Editorial Special Issue: Building Energy Consumption and Urban Energy Planning
DOAJ | 2022
|