Maggiora, Sofia Margherita (2026) From Social Practices to Load Curves: A Bottom-Up Framework Based on Time-Use Data. Master's Research Project 1, Energy and Environmental Sciences.
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Abstract
Understanding residential electricity demand requires models that reflect how energy use emerges from everyday life. This research presents a bottom-up modelling framework that reconstructs household electricity load curves from time-use data using a social practice perspective. Rather than modelling appliances in isolation, electricity demand is treated as the outcome of daily routines and coordinated household activities. The model is based on Dutch time-use diaries, from which individual activity patterns are extracted and aggregated into a reduced set of household related practices. Individual behaviour is simulated using time-inhomogeneous semi-Markov chains, allowing the model to capture both time-dependent routines and realistic activity durations. Synthetic households are assembled by combining simulated individuals within socio-demographic cohorts defined by household composition and income group. Electricity demand is then generated by probabilistically assigning appliances and triggering their operation when corresponding practices occur. The framework produces high resolution daily load curves for different household types, income groups, and day types. Results show that household composition primarily shapes the temporal structure and simultaneity of demand, while income mainly influences demand magnitude through differences in appliance ownership and usage intensity. At the national level, aggregated demand profiles reproduce characteristic weekday evening peaks driven by food related practices and flatter weekend profiles associated with increased daytime presence. Although the model underestimates absolute annual consumption compared to official statistics, it successfully captures the behavioural structure of residential electricity demand. The results demonstrate the value of integrating social practice theory and time-use data for analysing the environmental implications of everyday household activities.
| Item Type: | Thesis (Master's Research Project 1) |
|---|---|
| Supervisor name: | Ruzzenenti, F. and Medjroubi, W. |
| Degree programme: | Energy and Environmental Sciences |
| Thesis type: | Master's Research Project 1 |
| Language: | English |
| Date Deposited: | 17 Feb 2026 10:04 |
| Last Modified: | 17 Feb 2026 10:04 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/37236 |
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