4.7 Article

Residential energy flexibility characterization using non-intrusive load monitoring

Journal

SUSTAINABLE CITIES AND SOCIETY
Volume 75, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.scs.2021.103321

Keywords

Event detection; Energy flexibility; Non-intrusive load monitoring

Funding

  1. European Commission through H2020 project Finest Twins grant [856602]
  2. EEA Financial Mechanism Baltic [EMP474]
  3. Estonian Centre of Excellence in Zero Energy and Resource Efficient Smart Buildings and Districts ZEBE - European Regional Development Fund [2014-2020.4.01.15-0016]
  4. Norway Research Program in Estonia [EMP474]

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This paper proposes a novel two-stage non-intrusive characterization method for building energy flexibility (EF), which increases accuracy by considering consumer usage behavior without adding complexity to the system. This method can help aggregators utilize the available EF of buildings to flatten demand consumption.
To accelerate progress in building sustainability as well as to aid balance supply and demand in the presence of renewable energy generation, a tailored characterization method for the energy flexibility (EF) of buildings is needed. In this paper, a novel two-stage non-intrusive EF characterization method is proposed. In the first stage, unlike the previous studies in which an individual meter is installed on appliances to extract their consumption pattern, a novel unsupervised event-matching non-intrusive load monitoring method is utilized which is time and cost-effective. Moreover, previous research characterize the EF considering as early and as late as possible appliances' start-time. However, the usage behavior of consumers affects the start-time of appliances. To tackle this issue, in the second stage of the proposed method, the usage behavior of consumers is taken into account for the EF characterization. The proposed method is verified in an individual building level and aggregated level including 50 residential buildings. The obtained results show that the proposed usage behavior-oriented method, characterizes the available aggregated EF with higher accuracy, without adding complexity to the system. These results can be used by aggregators to harness the available EF of buildings to flatten demand consumption by incentivizing potential consumers.

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