Handling uncertainty in housing stock models

Booth, A.T.; Choudhary, Ruchi; Spiegelhalter, David

doi:10.1016/j.buildenv.2011.08.016

Cited by 141 publications

(82 citation statements)

References 28 publications

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“…The limitations of existing building stock models can be categorized into five areas (Booth et al 2012):…”

Section: Uncertainty Issues In Existing Building Stock Modelsmentioning

confidence: 99%

“…Booth et al (2012) discussed three sources that can cause uncertainties in building stock models: the first is uncertainty from the model accuracy, that is, how adequately the model represents the true process of energy in a building. Second, it arises from different building characteristics according to various building types.…”

Section: Stochastic Building Energy Models For Individual Buildingsmentioning

confidence: 99%

“…To consider the uncertainty of building stock models, Booth et al (2012) (Lee et al 2011) as an energy simulation tool because of the speed of the calculation and ability to assess the impact of technological interventions. The overall process is similar to Heo's method (Heo 2011;Heo et al 2012) for individual buildings.…”

Section: Stochastic Building Energy Models For Individual Buildingsmentioning

confidence: 99%

“…4) to quantify the energy use for supermarket at the city scale, the authors also used the Bayesian calibration framework based on Kennedy and O'Hagan (2001), and the process of building simulation and calibration by Heo et al (2012) and Booth et al (2012). They stated that the previous application of a probabilistic approach was only limited to calibrate the model parameters to a single resolution of simulation output (e.g., monthly energy consumption).…”

Section: Stochastic Building Energy Models For Individual Buildingsmentioning

confidence: 99%

“…The normative model (e.g. EPSCT (Lee et al 2011)) was employed in several studies (Heo 2011;Zhao 2012;Heo et al 2012;Booth et al 2012;Kim et al 2013). A simple hourly method based on RC network used in CEN-ISO 13790 was employed to calibrate and optimize the unknown parameters (Jacob et al 2010;Pavlak et al 2013;Henze et al 2014).…”

Section: Computational Timementioning

confidence: 99%

See 4 more Smart Citations

Review on stochastic modeling methods for building stock energy prediction

Lim

Zhai

2017

Build. Simul.

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Increasing risks of energy security and greenhouse gas emission due to the growing urbanization trend have prompted the need for urban energy demand prediction and management, in which the building energy consumption is the main cause. This paper reviews the recent advances and state-of-the-art in modeling building stock energy consumption, including both the top-down and bottom-up approaches. The study compares and summarizes the strengths and weaknesses of each primary method. Specific focus has been paid to the bottom-up stochastic engineering modeling methods, which hold sound quantitative theory bases as well as considering uncertain reality conditions. Stochastic building stock energy models account for the uncertainties that are the main limitation in existing building stock models. Discussions are provided regarding the process in the current stochastic building stock energy model. Challenges and possible future directions are examined for the improvement of stochastic building stock energy model.

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“…The limitations of existing building stock models can be categorized into five areas (Booth et al 2012):…”

Section: Uncertainty Issues In Existing Building Stock Modelsmentioning

confidence: 99%

Section: Stochastic Building Energy Models For Individual Buildingsmentioning

confidence: 99%