Device-independent metrics for explicit, a priori measurement of energy flexibility
Author:
Affiliation:
1. Aalborg University, Denmark
Funder
Danish Industry Foundation
Innovation and Networks Executive Agency
Executive Agency for Small and Medium-sized Enterprises
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3632775.3661965
Reference23 articles.
1. [1] 2022. https://pod-point.com/guides/vehicles/tesla/2022/model-s
2. Jonas Brusokas Torben Bach Pedersen Laurynas Siksnys Dalin Zhang and Kaixuan Chen. 2021. HeatFlex: Machine learning based data-driven flexibility prediction for individual heat pumps. In e-Energy.
3. F. Carlucci K. Negendahl and F. Fiorito. 2023. Energy flexibility of building systems in future scenarios: optimization of the control strategy of a dynamic shading system and definition of a new energy flexibility metric. Energy and Buildings (2023).
4. An Empirical Energy Demand Flexibility Metric for Residential Properties
5. Roel De Coninck and Lieve Helsen. 2016. Quantification of flexibility in buildings by cost curves – Methodology and application. Applied Energy (2016).
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