Eoghan McKenna

Diagramming social practice theory: An interdisciplinary experiment exploring practices as networks

Achieving a transition to a low-carbon energy system is now widely recognised as a key challenge facing humanity. To date, the vast majority of research addressing this challenge has been conducted within the disciplines of science, engineering and economics utilising quantitative and modelling techniques. However, there is growing awareness that meeting energy challenges requires fundamentally sociotechnical solutions and that the social sciences have an important role to play. This is an interdisciplinary challenge but, to date, there remain very few explorations of, or reflections on, interdisciplinary energy research in practice. This paper seeks to change that by reporting on an interdisciplinary experiment to build new models of energy demand on the basis of cutting-edge social science understandings. The process encouraged the social scientists to communicate their ideas more simply, whilst allowing engineers to think critically about the embedded assumptions in their models in relation to society and social change. To do this, the paper uses a particular set of theoretical approaches to energy use behaviour known collectively as social practice theory – and explores the potential of more quantitative forms of network analysis to provide a formal framework by means of which to diagram and visualise practices. The aim of this is to gain insight into the relationships between the elements of a practice, so increasing the ultimate understanding of how practices operate. Graphs of practice networks are populated based on new empirical data drawn from a survey of different types (or variants) of laundry practice. The resulting practice networks are analysed to reveal characteristics of elements and variants of practice, such as which elements could be considered core to the practice, or how elements between variants overlap, or can be shared. This promises insights into energy intensity, flexibility and the rootedness of practices (i.e. how entrenched/established they are) and so opens up new questions and possibilities for intervention. The novelty of this approach is that it allows practice data to be represented graphically using a quantitative format without being overly reductive. Its usefulness is that it is readily applied to large datasets, provides the capacity to interpret social practices in new ways and serves to open up potential links with energy modelling. More broadly, a significant dimension of novelty has been the interdisciplinary approach, radically different to that normally seen in energy research. This paper is relevant to a broad audience of social scientists and engineers interested in integrating social practices with energy engineering.

Demand response behaviour of domestic consumers with photovoltaic systems in the UK: an exploratory analysis of an internet discussion forum

BackgroundDomestic consumers with photovoltaic (PV) systems in the UK can benefit financially by time-shifting their electricity demand to coincide with the output of the PV. This behaviour is a form of demand response and can provide insights into demand response behaviour more generally. This paper investigates whether people with PV in the UK engage in demand response, what appliances are used, and whether benefitting from free, self-produced electricity appears to influence their behaviour.MethodsTo achieve this, the approach presented here consists of an exploratory text analysis of an internet discussion forum frequented by consumers with PV in the UK.ResultsData was gathered on 105 forum participants with PV, of which 45 mentioned engaging in demand response, for example by changing cooking or cleaning practices. Washing machines, dishwashers and electric space and water heaters were the most commonly used appliances for demand response. Six participants engaged in demand response and yet received no direct financial benefit from this behaviour, while 14 participants specifically mentioned the influence of free electricity.ConclusionsThe results illustrate novel demand response behaviour compared to previous studies and indicate that while price may be an effective initiator for demand response, there are additional factors beyond price that can enhance responses. The discussion considers the application of these factors to the development of innovative demand tariffs for low-carbon futures.

Short-run impact of electricity storage on CO2 emissions in power systems with high penetrations of wind power: A case-study of Ireland:

This article studies the impact on CO2 emissions of electrical storage systems in power systems with high penetrations of wind generation. Using the Irish All-Island power system as a case-study, data on the observed dispatch of each large generator for the years 2008 to 2012 was used to estimate a marginal emissions factor of 0.547 kgCO2/kWh. Selected storage operation scenarios were used to estimate storage emissions factors – the carbon emissions impact associated with each unit of storage energy used. The results show that carbon emissions increase in the short-run for all storage technologies when consistently operated in ‘peak shaving and trough filling’ modes, and indicate that this should also be true for the GB and US power systems. Carbon emissions increase when storage is operated in ‘wind balancing’ mode, but reduce when storage is operated to reduce wind power curtailment, as in this case wind power operates on the margin. For power systems where wind is curtailed to maintain system stability, the results show that energy storage technologies that provide synthetic inertia achieve considerably greater carbon reductions. The results highlight a tension for policy makers and investors in storage, as scenarios based on the operation of storage for economic gains increase emissions, while those that decrease emissions are unlikely to be economically favourable. While some scenarios indicate storage increases emissions in the short-run, these should be considered alongside long-run assessments, which indicate that energy storage is essential to the secure operation of a fossil fuel-free grid.

Time-step analysis of the DECC 2050 calculator pathways

An hour-by-hour time-step analysis is presented of United Kingdom electricity grid balancing in low-carbon energy pathways from the DECC 2050 Calculator. The detailed modelling uses the future energy scenario assessment (FESA) tool, which uses real weather data and real electricity demand data from year 2001 to model future supply and demand profiles, suitably adjusted to reflect technology uptakes. The paper describes the linking of the DECC 2050 Calculator with FESA and many of the detailed considerations within the modelling. The calculation of net demand (total demand less intermittent renewables and inflexible portions of other electricity generation) reveals the magnitude and duration of peaks and troughs throughout the year and this allows quantification of required peaking plant, energy storage, demand response or a combination of these. The results indicate that the grid balancing challenge is much greater than is apparent from the DECC 2050 Calculator, with significant excess power from renewables and less flexible generators needing to be exported or curtailed, and, at other times of the year, a significant amount of additional conventional generation being required. FESA also indicates significantly lower capacity factors for despatchable generators than indicated in the DECC 2050 Calculator. The results underline the value of energy storage and flexible demand, particularly in the high-renewables pathways, but also that much of that storage and flexibility needs to be available for days or even weeks rather than hours.