English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Stochastic person-based activity models play an important role in the prediction of the realistic time-series energy demand for residential buildings. These models generally use input parameters developed based on timeuse data. This paper evaluates how the adopted data preparation approach alters the variability in simulated activities among households. Four simulation cases were developed in the study, representing 1) clustering, 2) regression and 3) integrated approaches combining the first two. A comparison of the results indicates the integrated approach to be the most advantageous. Finally, a strategy to enhance heterogeneity in the simulated household activity for residential energy demand modelling is discussed.

Data Preparation to Address Heterogeneity in Time Use Data Based Activity Modelling