Abstract
Energy flexibility from buildings is a key enabler of the flexible energy system required to integrate intermittent renewable energy sources. This systematic literature review investigates the factors influencing energy flexibility from the built environment and the uncertainties associated with its exploitation. It employed a structured methodology using over 140 relevant studies to identify and categorise the sources of uncertainty into aleatory and epistemic sources.
Stochastic elements, like weather and occupant behaviour, introduce aleatory uncertainty which challenges prediction capabilities. This can be managed through probabilistic modelling and adaptive controls. Epistemic uncertainty, driven by incomplete data, lack of knowledge and modelling assumptions, remains a barrier to accurate forecasting. The identified dominant factors were determined iteratively and comprise occupant behaviour, building characteristics, energy systems and controls, and externalities.
A framework was proposed in which uncertainties arising from the dominant factors can be categorised and mitigated for different stakeholders. Uncertainty can propagate through systems and controls, causing poor realisation of building energy flexibility. This can be managed via implementation of robust optimisation methods and real-time (15 min or shorter) data integration. Externalities such as market volatility and complex policy frameworks also pose risks to the economic viability of flexibility services. This review emphasises the need for improved data collection and advanced control as methods to mitigate uncertainty in flexibility quantification. Additionally, it highlights the critical role of diversity in mitigating uncertainty, and the importance of increasing building populations (i.e., 100 or more domestic dwellings) to enable scalable flexibility solutions.
Stochastic elements, like weather and occupant behaviour, introduce aleatory uncertainty which challenges prediction capabilities. This can be managed through probabilistic modelling and adaptive controls. Epistemic uncertainty, driven by incomplete data, lack of knowledge and modelling assumptions, remains a barrier to accurate forecasting. The identified dominant factors were determined iteratively and comprise occupant behaviour, building characteristics, energy systems and controls, and externalities.
A framework was proposed in which uncertainties arising from the dominant factors can be categorised and mitigated for different stakeholders. Uncertainty can propagate through systems and controls, causing poor realisation of building energy flexibility. This can be managed via implementation of robust optimisation methods and real-time (15 min or shorter) data integration. Externalities such as market volatility and complex policy frameworks also pose risks to the economic viability of flexibility services. This review emphasises the need for improved data collection and advanced control as methods to mitigate uncertainty in flexibility quantification. Additionally, it highlights the critical role of diversity in mitigating uncertainty, and the importance of increasing building populations (i.e., 100 or more domestic dwellings) to enable scalable flexibility solutions.
| Original language | English |
|---|---|
| Article number | 116157 |
| Journal | Energy and Buildings |
| Volume | 346 |
| Number of pages | 14 |
| ISSN | 0378-7788 |
| DOIs | |
| Publication status | Published - 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Building energy systems
- Building-grid interaction
- Dominant factors
- Energy flexibility
- Uncertainty mitigation
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