Comparison of dynamic urban building energy models (UBEM): Sigmoid energy signature and physical modelling approach

Nageler, Peter Josef; Koch, Andreas; Mauthner, Franz; Leusbrock, Ingo; Mach, Thomas; Hochenauer, Christoph; Heimrath, Richard

doi:10.1016/j.enbuild.2018.09.034

Cited by 51 publications

(19 citation statements)

References 35 publications

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“…Due to concerns about climate change and energy security, photovoltaic (PV) solar technology is one of the most promising sources of renewable energy. It has been widely discussed that photovoltaic solar technology will be one of the major sources for future energy because of its long-term benefits [1,2]. Photovoltaic solar technology is clean, quiet, and helps protect against climate change and pollution.…”

Section: Introductionmentioning

confidence: 99%

Factors Affecting Photovoltaic Solar Technology Usage Intention among Households in Malaysia: Model Integration and Empirical Validation

et al. 2021

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The objective of this research is to identify the antecedents affecting the behavioural intentions of local housing residences in using photovoltaic (PV) solar technology in their houses. An integrated model of behavioural intention to use PV solar technology is tested in this research. This study combined the theory of reason action (TRA), technology acceptance model (TAM), theory of planned behaviour (TPB) and diffusion of innovation (DOI) theory. Additional factors, including cost, awareness, and government initiatives, are also included in this model. The proposed model findings are based on empirical data from a sample of 382 residences in Malaysia. This study postulates that the intent to use PV solar technology is predicted by trialability, compatibility, perceived ease of use, relative advantage, observability, perceived behavioural control, attitude, subjective norms, cost, government initiatives, and level of awareness towards photovoltaic technology. The integrated model achieves 54% variance explained for usage intention of PV solar technology among housing residences in Malaysia. The findings suggest an integrated model for the acceptance intention of PV solar technology, which can assist stakeholders in planning, evaluating, and executing PV solar technology.

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Section: Introductionmentioning

confidence: 99%

Factors Affecting Photovoltaic Solar Technology Usage Intention among Households in Malaysia: Model Integration and Empirical Validation

et al. 2021

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“…In their opinion, classic BEM is not appropriated to simulate a lot of building at the same time due to their high computational time and/or required parameters. (Nageler et al, 2018) presents a study with 34 buildings modelling by means of classic BEM and data driven method. They show that this is technically feasible.…”

Section: 3384/ecp19157129mentioning

confidence: 99%

Dynamic Simulation of Residential Buildings Supporting the Development of Flexible Control in District Heating Systems

Aoun¹,

Bavière²,

Vallée³

et al. 2019

Linköping Electronic Conference Proceedings

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Load shifting, peak shaving and night-time setback are key demand-side management measures to make the operation of District Heating Systems (DHSs) more flexible and efficient. These goals can be achieved through appropriate control strategies exploiting the building's and space heating system's thermal inertia. To ease the development of such an advanced controller, we programmed a detailed dynamic Modelica simulator representative of French multi-stories radiator-heated residential buildings. We parametrized the simulator to vary the factors influencing the flexibility potential of a building (e.g. envelope properties, additional internal mass such as partition walls and furniture, the heating system…). This helped us designing a reduced-order building model relevant to our application and setting up a robust identification method for its parameters. We finally used the detailed simulator to test an optimal space-heating controller, thereby allowing many incremental improvements without jeopardizing endusers thermal comfort. This simulation work paves the way to considering the actual implementation of our advanced controller on a real building.

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“…In this scenario, energy in cities must be better managed, and the cities' design must be optimized [4]. Thus, numerous urban building energy modeling (UBEM) methodologies and tools have been developed [5]. They provide users with the energy demand of the building stock, comprehending benchmarking analyses, scenarios evaluation, peak loads and energy patterns analysis, and other peculiar analyses [6].…”

Section: Introductionmentioning

confidence: 99%

Urban building energy modeling (UBEM) tools: A state-of-the-art review of bottom-up physics-based approaches

Ferrando

Causone

Hong

et al. 2020

Sustainable Cities and Society

199

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Regulations corroborate the importance of retrofitting existing building stocks or constructing new energy-efficient districts. There is, thus, a need for modeling tools to evaluate energy scenarios to better manage and design cities, and numerous methodologies and tools have been developed. Among them, Urban Building Energy Modelling (UBEM) tools allow the energy simulation of buildings at large scales. Choosing an appropriate UBEM tool, balancing the level of complexity, accuracy, usability, and computing needs, remains a challenge for users. The review focuses on the main bottom-up physics-based UBEM tools, comparing them from a user-oriented perspective. Five categories are used: (i) the required inputs, (ii) the reported outputs, (iii) the exploited workflow, (iv) the applicability of each tool, and (v) the potential users. Moreover, a critical discussion is proposed, focusing on interests and trends in research and development. The results highlighted major differences between UBEM tools that must be considered to choose the proper one for an application. Barriers of adoption of UBEM tools include the needs of a standardized ontology, a common threedimensional city model, a standard procedure to collect data, and a standard set of test cases. This feeds into future development of UBEM tools to support cities' sustainability goals.

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Comparison of dynamic urban building energy models (UBEM): Sigmoid energy signature and physical modelling approach

Cited by 51 publications

References 35 publications

Factors Affecting Photovoltaic Solar Technology Usage Intention among Households in Malaysia: Model Integration and Empirical Validation

Factors Affecting Photovoltaic Solar Technology Usage Intention among Households in Malaysia: Model Integration and Empirical Validation

Dynamic Simulation of Residential Buildings Supporting the Development of Flexible Control in District Heating Systems

Urban building energy modeling (UBEM) tools: A state-of-the-art review of bottom-up physics-based approaches

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