4.7 Article

Demand-side flexibility in a residential district: What are the main sources of uncertainty?

Journal

ENERGY AND BUILDINGS
Volume 255, Issue -, Pages -

Publisher

ELSEVIER SCIENCE SA
DOI: 10.1016/j.enbuild.2021.111595

Keywords

Urban building energy modeling; Bottom-up; District; Space heating; Demand-response; Sensitivity analysis; Occupant behavior; Probabilistic district characterization

Funding

  1. French National Research Agency, CLEF project [ANR-17-CE22-0005-01]

Ask authors/readers for more resources

With the increasing share of intermittent renewable energy sources, demand-side flexibility will be crucial in the future. This study explores an indirect control strategy at the district scale to achieve flexibility by adjusting the dwelling thermostat. The analysis identifies influential factors such as occupant behavior, event duration, and district characteristics.
With the increasing share of intermittent renewable energy sources in the energy mix, demand-side flexibility is likely to play a key role in the future. For buildings, flexibility is defined as the ability to shift their energy consumption away from peak periods i.e. high-demand periods of the electrical network. In France, these episodes occur mainly during the wintertime due to the significant demand for space heating. To achieve flexibility objectives, we explore an indirect control strategy at district scale by adjusting the dwelling thermostat during peak periods. The study is conducted over 337 dwellings in order to better predict the load curve by taking advantage of the aggregation effect. Three main research questions are addressed in relation to the assessment of flexibility potential: (i) the effect of aggregation, (ii) the identification of the most influencing factors, including occupant behavior, and (iii) the quantification of uncertainties. Using an urban building energy modeling tool populated with various national data sources (building envelope, energy class of equipment, etc), we perform a sensitivity analysis on 22 parameters representing the geometry, the appliances, the building characteristics, the occupants, and the grid. The output indicator is the average power shifted during the flexibility (or demand response) event. From this analysis, 7 parameters appear as being the most influential. A regression analysis on these parameters is performed, depending on both the duration of the event and the typology of district. The results show that the duration of the flexibility event and the occupant pre-selected temperature change are the most influential parameters. It results to approximately +/- 90 W of uncertainty on an average potential of 290 W of shiftable power per household in a recent district. Furthermore, the occupants are highlighted as making a significant contribution to flexibility. Finally, we observed that the thermal properties investigated with the study of an old fabric district play a key role. Low thermal performance means high heating consumption and increased flexibility potential, but a similar relative uncertainty. (C) 2021 Elsevier B.V. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available