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A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "G: Energy and Buildings".

Deadline for manuscript submissions: closed (30 November 2023) | Viewed by 4510

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Special Issue Editor

Dr. Jian Yao

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Guest Editor

Research Center for Green Building Technology, Ningbo University, Ningbo 315211, China
Interests: solar shading devices; daylighting; occupants’ behavior

Special Issue Information

Dear Colleagues,

Building energy simulation is widely adopted to predict/estimate building energy performance for various aims, such as evaluating the energy performance of a new building project or the energy-saving potential of a renovated building. An accurate simulation of building energy performance is key to conducting building-energy-related analysis. In building energy simulation, various assumptions on modeling, environmental conditions, building operation, etc. need to be made for simplifying the simulation process. Schedule-based simple assumptions on occupant behavior, building modeling, and operation might over-/underestimate actual building energy demand. An in-depth understanding of the impact of various modeling assumptions on building energy performance is critical to develop advanced and accurate modeling and simulating techniques. The focus of this Special Issue is on the measurement, modeling, and simulation of various energy-related modeling assumptions (such as occupant behavior and building operation) and their implications on actual building energy performance.

The topics of interest include (but are not limited to):

Energy-related occupant behavior in buildings;
Building energy analysis;
Monitoring, modeling, and simulation of energy systems;
Uncertainty and sensitivity analysis of building energy performance;
Building energy optimization;
Building envelope modeling;
Building cooling, heating, lighting demands;
Building climate;
Building thermal comfort.

Dr. Jian Yao
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

building energy modeling and simulation
building energy performance
building occupant behavior
building energy optimization

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Published Papers (3 papers)

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Research

18 pages, 2630 KiB

Open AccessArticle

Sensitivity Analysis and Multi-Objective Optimization of Skylight Design in the Early Design Stage

by Yuan Fang, Soolyeon Cho, Yanyu Wang and Luya He

Energies 2024, 17(1), 219; https://doi.org/10.3390/en17010219 - 31 Dec 2023

Cited by 1 | Viewed by 1066

Abstract

Building geometry design decisions are important for energy efficiency and daylight performance. Sensitivity analysis, coupled with optimization, is an important approach to investigate and optimize building geometry in the early design stage. Incorporating skylights is an important daylighting strategy in commercial buildings; however, skylight-to-floor ratio (SFR) is often the only design variable evaluated in precedent studies. More design variables related to skylight geometry, clerestory geometry, skylight material, and building geometry need to be evaluated. This study investigates the skylight design of a 2000-square-meter commercial building. Eighteen design variables are evaluated according to their influence on building energy and daylight performance. One-at-a-time (OAT), linear regression, and Morris sensitivity analysis approaches are utilized to identify the most influential variables. Seven of the twelve building geometry variables and two of the six building material variables are considered as important. Then, a multi-objective optimization with genetic algorithms is processed to find out the optimal design solution. The three objectives are energy use intensity (EUI), daylight autonomy (DA), and daylight uniformity (DU). After the optimization, five candidate design options are picked from the Pareto front. Discussions are made on the features of these designs, and one design is selected as the optimal solution. Full article

(This article belongs to the Special Issue Advances in Building Energy Modeling and Simulation)

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46 pages, 2040 KiB

Open AccessArticle

A Modeling Toolkit for Comparing AC and DC Electrical Distribution Efficiency in Buildings

by Avpreet Othee, James Cale, Arthur Santos, Stephen Frank, Daniel Zimmerle, Omkar Ghatpande, Gerald Duggan and Daniel Gerber

Energies 2023, 16(7), 3001; https://doi.org/10.3390/en16073001 - 25 Mar 2023

Cited by 3 | Viewed by 1387

Abstract

Recently, there has been considerable research interest in the potential for DC distribution systems in buildings instead of the traditional AC distribution systems. Due to the need for performing power conversions between DC and AC electricity, DC distribution may provide electrical efficiency advantages in some systems. To support comparative evaluations of AC-only, DC-only, and hybrid AC/DC distribution systems in buildings, a new modeling toolkit called the Building Electrical Efficiency Analysis Model (BEEAM) was developed and is described in this paper. To account for harmonics in currents or voltages arising from nonlinear devices, the toolkit implements harmonic power flow, along with nonlinear device behavioral descriptions derived from empirical measurements. This paper describes the framework, network equations, device representations, and an implementation of the toolkit in an open source software package, including a component library and graphical interface for creating circuits. Simulations of electrical behavior and device and system efficiencies using the toolkit are compared with experimental measurements of a small office environment in a variety of operating and load configurations. A detailed analysis of uncertainty estimation is also provided. Key findings were that a comparison of predicted versus measured efficiencies and power losses in the validation testbed using the initial toolkit implementation predicted device- and system-level efficiencies with reasonably good accuracy under both balanced and unbalanced AC scenarios. An uncertainty analysis also revealed that the maximum estimated error for system efficiency across all scenarios was 3%, and measured and modeled system efficiency agreed within the experimental uncertainty in approximately half of the scenarios. Based on the correspondence between simulation and measurement, the toolkit is proposed by the authors as a potentially useful tool for comparing efficiency in AC, DC, and hybrid AC/DC distribution systems in buildings. Full article

(This article belongs to the Special Issue Advances in Building Energy Modeling and Simulation)

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25 pages, 7560 KiB

Open AccessArticle

Energy Performance of Occupant Behaviors on Windows: A Green Building Based Study

by Kaixiang Cheng, Jian Yao and Rongyue Zheng

Energies 2023, 16(5), 2209; https://doi.org/10.3390/en16052209 - 24 Feb 2023

Cited by 6 | Viewed by 1324

Abstract

In this paper, the window-opening behavior in a three-star green building with an operation mark in Ningbo was investigated. Four single offices facing south were selected, and the measurement lasted 20–40 days in the cooling season. An analysis of the relationship between window use and environmental factors was assessed by monitoring the occupancy state, the window action and window state, the time, and the temperature and humidity. A statistical analysis method was conducted to reveal the similarities and differences in window use among different occupants. The main findings were as follows: The window adjustment behaviors of different people vary significantly. In terms of adjustment time, there are two modes of behaviors. In addition, the occupancy state had a great impact on window action. Moreover, some people prefer to open the windows in the morning and close the windows at departure time, However, some of them prefer to open the windows at departure time and close the windows at the arrival time. Some irrational window opening behaviors were found in this research. Through correlation analysis, it was shown that the longer time the occupants were in the office, the higher window-opening duration and window-opening frequency would be. If the window was closed at arrival time, the total opening duration of window was significantly reduced. Also, window opening duration and closing duration are proportional to each other. With the help of principal component analysis (PCA) of the 12 features that affected window adjustment, the correlation between the window opening behaviors and the features could be clearly illustrated. A stochastic model of window-opening behavior based on logistics regression and uncertainty analysis was used in this paper. The cooling energy consumption of the stochastic model is 99.9% higher than the energy consumption generated by a fixed number of air changes, and the average energy consumption exceeds the fixed value by more than 21%. The findings of this study have certain guiding significance for promoting energy conservation by occupants’ behaviors in green buildings in this region. Full article

(This article belongs to the Special Issue Advances in Building Energy Modeling and Simulation)

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