On data-driven energy flexibility quantification: A framework and case study

Li, Han; Hong, Tianzhen

doi:10.1016/j.enbuild.2023.113381

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On data-driven energy flexibility quantification: A framework and case study

Li, Han·Hong, Tianzhen

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Abstract

Building energy flexibility is an important resource for a sustainable and resilient power grid, and an important measure to reduce utility costs for building owners. Quantifying energy flexibility for existing buildings can provide critical insights in optimizing their operation. Data-driven methods for building energy modeling and analytics are gaining popularity due to the increasingly available sensor and meter infrastructure, affordable computational resources, and advanced modeling algorithms. However, their application in quantifying the energy flexibility of real buildings is still limited due to the heterogeneous data types and limited data availability. Here, this study proposes a framework for building-level data-driven energy flexibility quantification that considers different levels of data availability and use cases. Two case studies with real building data collected at different scales were conducted to demonstrate the proposed framework for different purposes.

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32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION Building Dataset Data-Driven Methods Demand Flexibility Energy Flexibility Grid-interactive Efficient Buildings

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Li, Han, Hong, Tianzhen. 2023-07-17. On data-driven energy flexibility quantification: A framework and case study. https://doi.org/10.1016/j.enbuild.2023.113381

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