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Journal ArticleDOI

Spatial distribution of urban building energy consumption by end use

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TLDR
In this article, the authors 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.
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This article is published in Energy and Buildings.The article was published on 2012-02-01. It has received 380 citations till now. The article focuses on the topics: Energy consumption & Energy accounting.

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Citations
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Journal ArticleDOI

Urban building energy modeling – A review of a nascent field

TL;DR: In this paper, a review of emerging simulation methods and implementation workflows for bottom-up urban building energy models (UBEM) is presented, as well as an outlook for future developments.
Journal ArticleDOI

Forecasting energy consumption of multi-family residential buildings using support vector regression: Investigating the impact of temporal and spatial monitoring granularity on performance accuracy

TL;DR: In this paper, a sensor-based forecasting model using Support Vector Regression (SVR), a commonly used machine learning technique, was applied to an empirical data-set from a multi-family residential building in Manhattan.
Journal ArticleDOI

Determinants of residential electricity consumption: Using smart meter data to examine the effect of climate, building characteristics, appliance stock, and occupants' behavior

TL;DR: In this article, structural and behavioral determinants of residential electricity consumption were examined by developing separate models for daily maximum (peak) and minimum (idle) consumption, and they applied their method on a data set of 1628 households' electricity consumption.
Journal ArticleDOI

A review of data-driven approaches for prediction and classification of building energy consumption

TL;DR: The conclusions drawn in this review could facilitate future micro-scale changes of energy use for a particular building through the appropriate retrofit and the inclusion of renewable energy technologies and paves an avenue to explore potential in macro-scale energy-reduction with consideration of customer demands.

Urban building energy modeling – A review of a nascent field

TL;DR: In this article, a review of emerging simulation methods and implementation workflows for bottom-up urban building energy models (UBEM) is presented, as well as an outlook for future developments.
References
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Journal ArticleDOI

Modeling of end-use energy consumption in the residential sector: A review of modeling techniques

TL;DR: In this paper, the authors provide an up-to-date review of the various modeling techniques used for modeling residential sector energy consumption, focusing on the strengths, shortcomings and purposes.
Journal ArticleDOI

Predicting electricity energy consumption: A comparison of regression analysis, decision tree and neural networks

TL;DR: This study presents three modeling techniques for the prediction of electricity energy consumption: decision tree and neural networks are considered, and model selection is based on the square root of average squared error.
Journal ArticleDOI

Using building energy simulation and geospatial modeling techniques to determine high resolution building sector energy consumption profiles

TL;DR: In this paper, a technique is presented for estimating hourly and seasonal energy consumption profiles in the building sector at spatial scales down to the individual taxlot or parcel, which combines annual building energy simulations for city-specific prototypical buildings and commonly available geospatial data.
Book

Energy, planning, and urban form

TL;DR: In this paper, the authors argue that energy considerations should be integrated into the land-use planning program and argue that the relationship between energy systems and spatial structure of society has been a subject of growing interest since the energy crisis of the 1970s.
Journal ArticleDOI

Modelling the electricity consumption of cities: effect of urban density

TL;DR: In this article, the authors present a statistical model that establishes a relationship between the annual electricity consumption per capita and some variables which characterize a sample of Canadian cities, which are related to urban density, demography and meteorological data as well as economic activities and energy context.
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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.