Quantifying and simulating the weather forecast uncertainty for advanced building control

Zheng, Wanfu; Zabala, Laura; Febres, Jesus; Blum, David; Wang, Zhe

doi:10.1080/19401493.2025.2453537

Title: Quantifying and simulating the weather forecast uncertainty for advanced building control

Journal Article · 27 January 2025 · Journal of Building Performance Simulation

DOI: https://doi.org/10.1080/19401493.2025.2453537 · OSTI ID:2525900

Zheng, Wanfu ^[1]; Zabala, Laura ^[2]; Febres, Jesus ^[3];

^[4];

^[1]

Hong Kong University of Science and Technology (HKUST) (Hong Kong)
Basque Foundation for Science, Bilbao (Spain)
R2M Solution, Bilbao (Spain)
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Weather forecast uncertainty is unavoidable despite technological advancements. Accurately quantifying and modelling this uncertainty is essential for developing and comparing advanced building controllers. In this study, we present a structured approach using a first-order autoregressive model (AR(1)) to model uncertainty in ambient temperature and global solar irradiation (GHI) forecasts. We analyzed weather data from four cities and employed Jensen–Shannon divergence (JSD) to evaluate the similarity between synthetic and actual forecast errors. The average JSD values for temperature are 0.027 (Berkeley), 0.021 (Leuven), 0.018 (Berlin), and 0.008 (Oslo), and for GHI, the average JSD values are 0.016 (Berkeley), 0.058 (Leuven), and 0.013 (Berlin). The low JSD values indicate a high similarity between the synthetic and real forecast error distributions. Further, our approach successfully generates synthetic weather forecasts that mirror the statistical properties of actual forecasts. The implementation of our method for uncertain forecast generation is being added to the BOPTEST framework.

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Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Energy Efficiency Office. Building Technologies Office

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 2525900

Journal Information:: Journal of Building Performance Simulation, Journal Name: Journal of Building Performance Simulation Journal Issue: 4 Vol. 18; ISSN 1940-1493

Publisher:: Taylor & FrancisCopyright Statement

Country of Publication:: United States

Language:: English

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Title: Quantifying and simulating the weather forecast uncertainty for advanced building control

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