Energy Efficient Homes: The Social and Spatial Patterns of Residential
Energy Efficiency in England
- URL: http://arxiv.org/abs/2302.09628v1
- Date: Sun, 19 Feb 2023 17:11:05 GMT
- Title: Energy Efficient Homes: The Social and Spatial Patterns of Residential
Energy Efficiency in England
- Authors: Boyana Buyuklieva, Adam Dennett, Nick Bailey and Jeremy Morley
- Abstract summary: Poor energy efficiency of homes is a major problem with urgent environmental and social implications.
Housing in the UK relies heavily on fossil fuels for energy supply and has some of the lowest energy efficiency in Europe.
We explore spatial variations in energy efficiency across England using data from Energy Performance Certificates.
- Score: 0.45880283710344055
- License: http://creativecommons.org/licenses/by-sa/4.0/
- Abstract: Poor energy efficiency of homes is a major problem with urgent environmental
and social implications. Housing in the UK relies heavily on fossil fuels for
energy supply and has some of the lowest energy efficiency in Europe. We
explore spatial variations in energy efficiency across England using data from
Energy Performance Certificates (EPCs), which cover approximately half of the
residential stock (14M homes between 2008-22). We examine variations between
authorities after accounting for the composition of the housing stock in terms
of its fixed characteristics of property type, building age and size. We
explore variations in terms of geographical and social context (region,
urban-rural and deprivation), which gives a picture of the scale of the
challenge each faces. We also examine variations in relation to the more
readily upgraded factors, such as glazing types, and in relation to local
participation in improvement programmes which gives some insight into local
actions or progress achieved.
Related papers
- Investigation of the Impact of Economic and Social Factors on Energy Demand through Natural Language Processing [0.48338156051969644]
This study was carried out in five regions of the UK and Ireland.
It considers multiple horizons from 1 to 30 days.
It also considers economic variables such as GDP, unemployment and inflation.
arXiv Detail & Related papers (2024-06-09T16:25:14Z) - Climate-sensitive Urban Planning through Optimization of Tree Placements [55.11389516857789]
Climate change is increasing the intensity and frequency of many extreme weather events, including heatwaves.
Among the most promising strategies is harnessing the benefits of urban trees in shading and cooling pedestrian-level environments.
Physical simulations can estimate the radiative and thermal impact of trees on human thermal comfort but induce high computational costs.
We employ neural networks to simulate the point-wise mean radiant temperatures--a driving factor of outdoor human thermal comfort--across various time scales.
arXiv Detail & Related papers (2023-10-09T13:07:23Z) - Benchmarks and Custom Package for Energy Forecasting [55.460452605056894]
Energy forecasting aims to minimize the cost of subsequent tasks such as power grid dispatch.
In this paper, we collected large-scale load datasets and released a new renewable energy dataset.
We conducted extensive experiments with 21 forecasting methods in these energy datasets at different levels under 11 evaluation metrics.
arXiv Detail & Related papers (2023-07-14T06:50:02Z) - High-resolution synthetic residential energy use profiles for the United
States [12.699816591560712]
We release a large-scale, synthetic, residential energy-use dataset for the residential sector across the contiguous United States.
The data comprises of hourly energy use profiles for synthetic households, disaggregated into Thermostatically Controlled Loads (TCL) and appliance use.
arXiv Detail & Related papers (2022-10-14T20:55:10Z) - Estimating Building Energy Efficiency From Street View Imagery, Aerial
Imagery, and Land Surface Temperature Data [0.0]
This work proposes a new method which can estimate a building's energy efficiency using purely remotely sensed data.
We find that in the binary setting of distinguishing efficient from inefficient buildings, our end-to-end deep learning model achieves a macro-averaged F1-score of 62.06%.
arXiv Detail & Related papers (2022-06-05T21:04:20Z) - Intelligent Energy Management Systems -- A Review [0.0]
People consume electricity in order to use home/work appliances and devices and also reach certain levels of comfort while working or being at home.
Confronting such a problem efficiently will affect both the environment and our society.
Monitoring energy consumption in real-time, changing energy wastage behavior of occupants and using automations with incorporated energy savings scenarios are ways to decrease global energy footprint.
arXiv Detail & Related papers (2022-05-16T20:10:20Z) - Localisation determines the optimal noise rate for quantum transport [68.8204255655161]
Localisation and the optimal dephasing rate in 1D chains are studied.
A simple power law captures the interplay between size-dependent and size-independent responses.
Relationship continues to apply at intermediate and high temperature but breaks down in the low temperature limit.
arXiv Detail & Related papers (2021-06-23T17:52:16Z) - Investigating Underlying Drivers of Variability in Residential Energy
Usage Patterns with Daily Load Shape Clustering of Smart Meter Data [53.51471969978107]
Large-scale deployment of smart meters has motivated increasing studies to explore disaggregated daily load patterns.
This paper aims to shed light on the mechanisms by which electricity consumption patterns exhibit variability.
arXiv Detail & Related papers (2021-02-16T16:56:27Z) - WattScale: A Data-driven Approach for Energy Efficiency Analytics of
Buildings at Scale [2.771897351607068]
Buildings consume over 40% of the total energy in modern societies.
We present textttWattScale, a data-driven approach to identify the least energy-efficient buildings.
arXiv Detail & Related papers (2020-07-02T20:45:33Z) - Entropy as a measure of attractiveness and socioeconomic complexity in
Rio de Janeiro metropolitan area [52.77024349608834]
We use a mobile phone dataset and an entropy-based metric to measure the attractiveness of a location.
The results show that the attractiveness of a given location measured by entropy is an important descriptor of the socioeconomic status of the location.
arXiv Detail & Related papers (2020-03-23T15:58:56Z) - Towards a Peer-to-Peer Energy Market: an Overview [68.8204255655161]
This work focuses on the electric power market, comparing the status quo with the recent trend towards the increase in distributed self-generation capabilities by prosumers.
We introduce a potential multi-layered architecture for a Peer-to-Peer (P2P) energy market, discussing the fundamental aspects of local production and local consumption as part of a microgrid.
To give a full picture to the reader, we also scrutinise relevant elements of energy trading, such as Smart Contract and grid stability.
arXiv Detail & Related papers (2020-03-02T20:32:10Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.