9 research outputs found
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Exploratory analysis of family-related activities during peak electricity periods
Price-based interventions (such as Time of Use tariffs) are designed to shift the timing of certain everyday activities to mitigate peak electricity demand. On the one hand, it is argued that timing activities outside the peak hours would decrease the demand, easing the stress on the grid. On the other hand, recent literature suggests that householders are more likely to ignore timing of activities - due to convenience or due to activities considered 'non-negotiable' during peak hours. One way to address this conundrum is to investigate how family-related activities during the peak times hang together and the extent to which they are performed together at a specific time of the day. The starting point of this research is that working hours and school times shape the dynamics of peak demand, leaving less time for families to do more during these time periods and also making it difficult to shift activities to other times of the day. We aim to explore the timing and sequences of activities, comparing how they vary at different temporal scales (e.g. workdays vis-Ă -vis school holidays). In conclusion, we argue that any effective shifting of family-related activities will need to look beyond the meter (such as de-synchronized effects of school holidays), potentially collecting information regarding both energy and non-energy data in order to understand the connection, coordination and organization between activities which constitute electricity demand
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Role of household activities in peak electricity demand and distributional effects of Time-of-Use tariffs
Introduction of Time-of-Use (ToU) tariffs have the potential to motivate consumers to flex their energy use and, by utilising their flexibility, support the reduction in peak electricity demand.
In return, lower peak demand could also reduce the system costs due to the reduced need for peaking generation and network reinforcement.
By their nature, ToU tariffs would penalise consumers with high consumption during peak periods and who are not able to exercise flexibility.
Therefore to ensure the affordability of energy bills it is important to understand the relationship between the timing of activities in the household and socio-demographic properties of the consumers.
This paper uses UK Time Use survey data to cluster households by their energy-related activities during the peak electricity demand periods, model the corresponding electricity demand and analyse the impact of ToU tariffs across several socio-demographic parameters.
Results show that similar patterns of energy related activities exist for the clusters with different socio-demographic parameters (e.g. family structure or income).
Findings also show that there is no single dominant socio-demographic parameter that defines the winners or losers from the introduction of ToU tariff
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Exploring socioeconomic and temporal characteristics of British and German residential energy demand
The British and German residential sectors account for similar fractions of national energy demand and carbon emissions. They also exhibit underlying differences in the building stock, fuel split, tenure and household load profiles. The temporal habits in British and German households are also quite different, which is challenging to measure due to the paucity of German smart meter data. This contribution takes this background as a starting point to explore some of the temporal and socioeconomic
characteristics of residential energy demand in Britain and Germany. The Centre for Renewable Energy Systems Technology (CREST) residential load profile generator is updated for the UK and extended to the German context and validated with standard load profiles, providing high levels of accuracy according standard normalized root-mean-squared error (NRMSE) measures. The paper then analyzes the energy-related activities of different socioeconomic household groups based on with National Time
Use Survey data from both countries. The analysis showed some clear differences between groups and countries, which are a reminder of the importance of non-energy policy (e.g. school hours) in determining peaks. As well as encountering useful insights into international differences in energy related behaviour, the results showed some key differences within specific socioeconomic groups, such as single persons, families with children, and pensioners. Further work will focus on extending the
German CREST model to include a German appliance stock, as well as allocating these appliances according to householdsâ socioeconomic characteristics. The definition of the groups themselves needs to be refined, perhaps to include multiple variables and based on clustering or similar techniques, and validation with smart meter data
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Making demand side response happen: A review of barriers in commercial and public organisations
The decarbonisation of electricity systems and the associated increase in variable generation sources requires an increase in power system flexibility. Demand side response (DSR) is widely viewed as a cost-effective source of flexibility, with considerable market potential. To date, the main DSR providers have been energy intensive firms. However, the expectation is that non-energy intensive consumers such as commercial firms and public sector organisations will also provide system flexibility. Despite its DSR potential, commercial and public organisations have received little attention in the literature. This paper helps address this gap by identifying and exploring barriers to the participation of large commercial firms and public sector organisations in DSR through a review of the academic and grey literature on DSR. Drawing on the literature on barriers to energy efficiency, we use concepts from orthodox and behavioural economics, organisational studies and social practice theory to frame our analysis. The article argues that barriers to participation in DSR exist at the level of the organisation and not only the site. For large commercial firms and public sector organisations, the combination of having small individual electricity loads and complex internal decision-making processes can hinder their uptake of DSR. The hidden costs of participation, issues of bounded rationality and what the energy is used for within different organisations also limit the firmsâ ability to participate in DSR
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Work-related practices: an analysis of their effect on the emergence of stable practices in daily activity schedules
Despite its âwordlessâ and hidden characteristics, it is within the everyday tasks, routines and rhythms that consumption takes place, from getting up every morning, having breakfast, going to work or school, having lunch, going home, having dinner, reading a book, surfing the internet, watching TV and probably doing similar things again and again. This study examines this routinized daily use of time of employed individuals based on the 2014-2015 UK Time Use Survey data. In doing this, we focus on individualâs day-to-day activities and how they are routinised or how they are formed into stabilised practices. Starting from the definition of stable practices we apply a relatively new method of social network analysis to visualize stable practices during workdays. We then analyse the cohesion between practices based on work hours and connections and coordination between practices. Our results suggest that work arrangements create stable practices that by themselves are stone pillars of daily routines. This implies that the removal (or âunlockingâ) of stable practices during these time periods could produce some â albeit marginal â decongestion of routinized activities
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COVID-19 lockdowns in the United Kingdom: Exploring the links between changes in time use, work patterns and energy-relevant activities
Restrictions on movement and the imposed social distancing and work-from-home rules due to the recent global
pandemic have sparked an interest in understanding changes in the timing, duration and sequencing of daily
activities. In this paper, we investigate how working from home during the various stages of COVID-19-induced
lockdowns in the United Kingdom influenced the timing of in-home, energy-related activities. We present findings
from the analysis of data collected during the first and second UK lockdowns using an online diary instrument
developed by the UK Centre for Time Use Research. Based on a weighted average index we show that there were
noticeable changes in the start times of energy-relevant activities between the pre- and mid-lockdown periods.
Both lockdowns showed a substantial variation in start times of laundering compared to the reference period. The
food preparation activities start times varied more during the second lockdown depending on the time of the day.
TV watching activities started later and lasted longer relative to the pre-pandemic reference period. We conclude
by discussing how we can account for the associations we have identified between changing energy-relevant
activities over the different phases of the lockdown periods
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Unpacking the modelling process for energy policy making
This article explores how the modeling of energy systems may lead to an undue closure of alternatives by generating an excess of certainty around some of the possible policy options. We retrospectively exemplify the problem with the case of the International Institute for Applied Systems Analysis (IIASA) global modeling in the 1980s. We discuss different methodologies for quality assessment that may help mitigate this issue, which include Numeral Unit Spread Assessment Pedigree (NUSAP), diagnostic diagrams, and sensitivity auditing (SAUD). We illustrate the potential of these reflexive modeling practices in energy policyâmaking with three additional cases: (i) the case of the energy system modeling environment (ESME) for the creation of UK energy policy; (ii) the negative emission technologies (NETs) uptake in integrated assessment models (IAMs); and (iii) the ecological footprint indicator. We encourage modelers to adopt these approaches to achieve more robust, defensible, and inclusive modeling activities in the field of energy research