scholarly journals An Integrated Energy Simulation Model for Buildings

Energies ◽  
2020 ◽  
Vol 13 (5) ◽  
pp. 1170 ◽  
Author(s):  
Nikolaos Kampelis ◽  
Georgios I. Papayiannis ◽  
Dionysia Kolokotsa ◽  
Georgios N. Galanis ◽  
Daniela Isidori ◽  
...  
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Building Energy ◽  
Energy Performance ◽  
Energy Modeling ◽  
Initial Model ◽  
Building Energy Modeling ◽  
Novel Approach ◽  
Efficiency Measures ◽  
Simulation Results

The operation of buildings is linked to approximately 36% of the global energy consumption, 40% of greenhouse gas emissions, and climate change. Assessing the energy consumption and efficiency of buildings is a complex task addressed by a variety of methods. Building energy modeling is among the dominant methodologies in evaluating the energy efficiency of buildings commonly applied for evaluating design and renovation energy efficiency measures. Although building energy modeling is a valuable tool, it is rarely the case that simulation results are assessed against the building’s actual energy performance. In this context, the simulation results of the HVAC energy consumption in the case of a smart industrial near-zero energy building are used to explore areas of uncertainty and deviation of the building energy model against measured data. Initial model results are improved based on a trial and error approach to minimize deviation based on key identified parameters. In addition, a novel approach based on functional shape modeling and Kalman filtering is developed and applied to further minimize systematic discrepancies. Results indicate a significant initial performance gap between the initial model and the actual energy consumption. The efficiency and the effectiveness of the developed integrated model is highlighted.

scholarly journals Integrating GIS-Based Point of Interest and Community Boundary Datasets for Urban Building Energy Modeling

Energies ◽  
2021 ◽  
Vol 14 (4) ◽  
pp. 1049
Author(s):  
Zhang Deng ◽  
Yixing Chen ◽  
Xiao Pan ◽  
Zhiwen Peng ◽  
Jingjing Yang
Keyword(s):  
Large Scale ◽  
Residential Buildings ◽  
Building Energy ◽  
Energy Performance ◽  
Energy Modeling ◽  
Office Buildings ◽  
Building Energy Modeling ◽  
Downtown Area ◽  
Point Of Interest

Urban building energy modeling (UBEM) is arousing interest in building energy modeling, which requires a large building dataset as an input. Building use is a critical parameter to infer archetype buildings for UBEM. This paper presented a case study to determine building use for city-scale buildings by integrating the Geographic Information System (GIS) based point-of-interest (POI) and community boundary datasets. A total of 68,966 building footprints, 281,767 POI data, and 3367 community boundaries were collected for Changsha, China. The primary building use was determined when a building was inside a community boundary (i.e., hospital or residential boundary) or the building contained POI data with main attributes (i.e., hotel or office building). Clustering analysis was used to divide buildings into sub-types for better energy performance evaluation. The method successfully identified building uses for 47,428 buildings among 68,966 building footprints, including 34,401 residential buildings, 1039 office buildings, 141 shopping malls, and 932 hotels. A validation process was carried out for 7895 buildings in the downtown area, which showed an overall accuracy rate of 86%. A UBEM case study for 243 office buildings in the downtown area was developed with the information identified from the POI and community boundary datasets. The proposed building use determination method can be easily applied to other cities. We will integrate the historical aerial imagery to determine the year of construction for a large scale of buildings in the future.

scholarly journals Application of Urban Scale Energy Modelling and Multi-Objective Optimization Techniques for Building Energy Renovation at District Scale

2021 ◽  
Vol 13 (20) ◽  
pp. 11554
Author(s):  
Fahad Haneef ◽  
Giovanni Pernigotto ◽  
Andrea Gasparella ◽  
Jérôme Henri Kämpf
Keyword(s):  
Energy Efficiency ◽  
Building Energy ◽  
Energy Performance ◽  
Building Envelope ◽  
Optimization Techniques ◽  
Multi Objective Optimization ◽  
Building Stock ◽  
Energy Efficiency Measures ◽  
Multi Objective ◽  
Efficiency Measures

Nearly-zero energy buildings are now a standard for new constructions. However, the real challenge for a decarbonized society relies in the renovation of the existing building stock, selecting energy efficiency measures considering not only the energy performance but also the economic and sustainability ones. Even if the literature is full of examples coupling building energy simulation with multi-objective optimization for the identification of the best measures, the adoption of such approaches is still limited for district and urban scale simulation, often because of lack of complete data inputs and high computational requirements. In this research, a new methodology is proposed, combining the detailed geometric characterization of urban simulation tools with the simplification provided by “building archetype” modeling, in order to ensure the development of robust models for the multi-objective optimization of retrofit interventions at district scale. Using CitySim as an urban scale energy modeling tool, a residential district built in the 1990s in Bolzano, Italy, was studied. Different sets of renovation measures for the building envelope and three objectives —i.e., energy, economic and sustainability performances, were compared. Despite energy savings from 29 to 46%, energy efficiency measures applied just to the building envelope were found insufficient to meet the carbon neutrality goals without interventions to the system, in particular considering mechanical ventilation with heat recovery. Furthermore, public subsidization has been revealed to be necessary, since none of the proposed measures is able to pay back the initial investment for this case study.

scholarly journals A Study on Energy and Cost Efficiency for Existing Hotel Buildings in Turkey

2019 ◽  
Vol 111 ◽  
pp. 03037
Author(s):  
Merve Atmaca ◽  
Zerrin Yýlmaz
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Cost Efficiency ◽  
Building Energy ◽  
Energy Performance ◽  
Insulation Material ◽  
Negative Effects ◽  
Energy Needs ◽  
Global Cost ◽  
Optimum Solution

In Turkey, according to TUİK Sectoral Energy Consumption Statistics (2006), the hotel buildings with the highest share, constitute 35% of the total building energy consumption. Energy needs and consumption behaviours differ according to the typology of the building. Energy Performance of Buildings Directive (EPBD) has been adapted to the conditions of Turkey to increase energy and cost efficiency, to reduce the environmental and economic negative effects. The energy consumption and the global cost were investigated under different conditions in an existing hotel building. The paper is unique in its ability to deliver optimum solution through comparison by evaluating energy and cost efficiency at the same time considering sectoral, climatic, technological and economic national conditions when the literature research detailed in the present works about the problem is evaluated in detail. All findings have been compared simultaneously under different climate regions of seasonal and yearly working conditions of selected test hotel to obtain the energy and cost efficiency. Among the proposed improvement scenarios, the optimum scenario is determined in terms of cost and energy efficiency in S18 which has the highest energy efficiency. In this case, both insulation material type and thickness as well as glass type can be bent and through multiple measures can be achieved by 25.7% improvement for energy efficiency.

scholarly journals An Integrated Spatial Analysis Computer Environment for Urban-Building Energy in Cities

2018 ◽  
Vol 10 (11) ◽  
pp. 4235 ◽  
Author(s):  
Yu Sun ◽  
Elisabete Silva ◽  
Wei Tian ◽  
Ruchi Choudhary ◽  
Hong Leng
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Spatial Analysis ◽  
Building Energy ◽  
Energy Modeling ◽  
Integrated Analysis ◽  
Scale Efficiency ◽  
Building Energy Consumption ◽  
Multi Scale ◽  
Analysis Environment

In this paper, we developed a new integrated analysis environment in order to thoroughly analyses urban-building energy patterns, named IUBEA (integrated urban building energy analysis), which focuses on energy modeling and analysis of a city’s building stock to support district or city-scale efficiency programs. It is argued that cities and towns account for more than two-thirds of world energy consumption. Thus, this paper explores techniques to integrate a spatial analysis environment in the field of urban building energy assessment in cites to make full use of current spatial data relevant to urban-building energy consumption and energy efficiency policies. We illustrate how multi-scale sampling and analysis for energy consumption and simulate the energy-saving scenarios by taking as an example of Greater London. In the final part, is an application of an agent-based model (ABM) in IUBEA regarding behavioral and economic characteristics of building stocks in the context of building energy efficiency. This paper first describes the basic concept for this integrated spatial analysis environment IUBEA. Then, this paper discusses the main functions for this new environment in detail. The research serves a new paradigm of the multi-scale integrated analysis that can lead to an efficient energy model, which contributes the body of knowledge of energy modeling beyond the single building scale. Findings also proved that ABM is a feasible tool to tackle intellectual challenges in energy modeling. The final adoption example of Greater London demonstrated that the integrated analysis environment as a feasible tool for building energy consumption have unique advantages and wide applicability.

Optimization of Energy Consumption Using BIM-Based Building Energy Performance Analysis

2013 ◽  
Vol 281 ◽  
pp. 649-652 ◽  
Author(s):  
Dae Kyo Jung ◽  
Dong Hwan Lee ◽  
Joo Ho Shin ◽  
Byung Hun Song ◽  
Seung Hee Park
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Performance Analysis ◽  
Cooling System ◽  
Optimization Technique ◽  
Building Energy ◽  
Energy Performance ◽  
Information Modeling ◽  
Building Energy Performance ◽  
Heating And Cooling

Recently, the interest in increasing energy efficiency of building energy management system (BEMS) has become a high-priority and thus the related studies also increased. In particular, since the energy consumption in terms of heating and cooling system takes a large portion of the energy consumed in buildings, it is strongly required to enhance the energy efficiency through intelligent operation and/or management of HVAC (Heating, Ventilation and Air Conditioning) system. To tackle this issue, this study deals with the BIM (Building Information Modeling)-based energy performance analysis implemented in Energyplus. The BIM model constructed at Revit is updated at Design Builder, adding HVAC models and converted compatibly with the Energyplus environment. And then, the HVAC models are modified throughout the comparison between the energy consumption patterns and the real-time monitoring in-field data. In order to maximize the building energy performance, a genetic algorithm (GA)-based optimization technique is applied to the modified HVAC models. Throughout the proposed building energy simulation, finally, the best optimized HVAC control schedule for the target building can be obtained in the form of “supply air temperature schedule”.

scholarly journals Decarbonizing Local Mobility and Greenhouse Agriculture through Residential Building Energy Upgrades: A Case Study for Québec

Energies ◽  
2021 ◽  
Vol 14 (20) ◽  
pp. 6820
Author(s):  
James Bambara ◽  
Andreas K. Athienitis ◽  
Ursula Eicker
Keyword(s):  
Energy Efficiency ◽  
Ghg Emissions ◽  
Building Energy ◽  
Energy Performance ◽  
Low Energy ◽  
Resistance Heating ◽  
Electric Resistance ◽  
Efficiency Measures ◽  
Fresh Vegetables ◽  
Electric Resistance Heating

Electrification is an efficient way to decarbonize by replacing fossil fuels with low-emission power. In addition, energy efficiency measures can reduce consumption, making it easier to shift to a zero-carbon society. In Québec, upgrades to aging buildings that employ electric resistance heating offer a unique opportunity to free up large amounts of hydroelectricity that can serve to decarbonize heating in other buildings. However, another source of energy would be needed to electrify mobility because efficiency measures free up small amounts of electricity in summer compared to winter. This study reveals how building efficiency measures combined with solar electricity generation provide an energy profile that matches the requirements for decarbonizing both mobility and heating. The TRNSYS software was used to simulate the annual energy performance of an existing house and retrofitted/rebuilt low-energy houses equipped with a photovoltaic (PV) roof in Montreal, Québec, Canada (45.5° N). The electricity that is made available by upgrading the houses is mainly considered for powering battery and fuel cell electric vehicles (BEVs and FCEVs) and electrifying heating in greenhouses. The results indicate that retrofitting 16% or rebuilding 12% of single-detached homes in Québec can provide enough electricity to decarbonize heating energy use in existing greenhouses and to operate the new greenhouses required for growing all fresh vegetables locally. If all the single-detached houses that employ electric resistance heating are upgraded, 33.4 and 21.8 TWh year−1 of electricity would be available for decarbonization, equivalent to a 19% and 12% increase of the province’s electricity supply for the retrofitted or rebuilt houses, respectively. This is enough energy to convert 83–100% of personal vehicles to BEVs or 35–56% to FCEVs. Decarbonization using the electricity that is made available by upgrading to low-energy solar houses could reduce the province’s greenhouse gas (GHG) emissions by approximately 32% (26.5 MtCO2eq). The time required for the initial embodied GHG emissions to surpass the emissions avoided by electrification ranges from 3.4 to 11.2 years. Building energy efficiency retrofits/rebuilds combined with photovoltaics is a promising approach for Québec to maximize the decarbonization potential of its existing energy resources while providing local energy and food security.

scholarly journals A STUDY OF THE ENERGY EFFICIENCY RENOVATION ON PUBLIC HOUSING PROJECTS

2012 ◽  
Vol 7 (1) ◽  
pp. 192-212 ◽  
Author(s):  
Qian Chen ◽  
Qian Ma
Keyword(s):  
Energy Efficiency ◽  
Public Housing ◽  
Cost Effective ◽  
Building Energy ◽  
Energy Performance ◽  
High Energy ◽  
Efficiency Measures ◽  
The Government ◽  
Financial Burdens ◽  
Whole Building Energy Simulation

While the energy efficiency of commercial buildings, schools, and private homes has received increasing attention, the energy performance of public housing has long been neglected. The high energy usage and resulting utility costs associated with such subsidized houses have added great financial burdens to the government and tenants. Therefore, improving public housing's energy performance becomes an important task. This paper presents a comparative study that mainly investigates the effectiveness of energy efficiency measures (EEMs) recently implemented in the Columbus Metropolitan Housing Authority's green renovation projects. Whole building energy simulation results show that due to budget constraints, the limited EEMs put into place would only result in a marginal (7.6%) improvement to the renovated building's energy performance prior to renovation. Another 38.5% reduction would be needed, using the performance requirement of the current building energy code as a reference. Based on these findings, this research offers some insights into more cost-effective energy efficiency upgrades that can help reduce public housing's energy consumption and green renovation costs.

Correlation Study on User Satisfaction from Adaptive Behavior and Energy Consumption in Office Buildings

2014 ◽  
Vol 70 (7) ◽  
Author(s):  
Ali Keyvanfar ◽  
Arezou Shafaghat ◽  
Mohd Zaimi Abd Majid ◽  
Hasanuddin Lamit ◽  
Kherun Nita Ali
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Adaptive Behavior ◽  
User Satisfaction ◽  
Building Design ◽  
Building Energy ◽  
Energy Performance ◽  
Assessment Tools ◽  
Sustainable Building ◽  
Building Assessment

Sustainable Building Assessment Tools have not yet measured the association between user satisfaction with adaptive behavior and energy efficiency. The current research aims to rectify this problem by testing the hypothesis that user satisfaction with adaptive behavior affects building energy consumption. To test the hypothesis, the staff’s overall satisfaction with adaptive behavior in response to tenant energy-efficiency features was used as the independent variable, while office unit energy consumption was used as the dependent variable. A set of conceptual variables and measured variables were identified for both the dependent and independent variables. A total of nine possible combinations of measured variables were investigated through a survey fielded in ten office units. The survey analysis determined that the building users are not satisfied with the tenant energy efficiency features and that they may adapt the indoor environment cooling and lighting qualities. An expert input study was conducted to validate the results with respect to the hypothesis. Seven experts who had experience in building assessments were invited to participate in the input study. Grounded group decision making analysis method confirmed the hypothesis testing results. The research results indicated that user adaptive behaviors directly affect building energy performance. Sustainable Building Assessment Tool developers along with energy efficient building design consultants and contractors could make use of these research findings.

Exploring and verifying BIM-based energy simulation for building operations

2020 ◽  
Vol 27 (8) ◽  
pp. 1679-1702
Author(s):  
Hong Xian Li ◽  
Zhiliang Ma ◽  
Hexu Liu ◽  
Jun Wang ◽  
Mohamed Al-Hussein ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Building Energy ◽  
Energy Performance ◽  
Energy Simulation ◽  
Information Modeling ◽  
Building Energy Simulation ◽  
Content Type ◽  
Simulation Tools ◽  
Building Information ◽  
Simulation Results

PurposeThe operational phase of a building's lifecycle is receiving increasing attention, as it consumes an enormous amount of energy and results in tremendous detrimental impacts on the environment. While energy simulation can be applied as a tool to evaluate the energy performance of a building in operation, the emergence of Building Information Modeling (BIM) technology is expected to facilitate the evaluation process with predefined and enriched building information. However, such an approach has been confronted by the challenge of interoperability issues among the related application software, including the BIM tools and energy simulation tools, and the results of simulation have been seldom verified due to the unavailability of corresponding experimental data. This study aims to explore the interoperability between the commonly used energy simulation and BIM tools and verifies the simulation approach by undertaking a case study.Design/methodology/approachWith Autodesk Revit and EnergyPlus selected as the commonly used BIM and energy simulation tools, respectively, a valid technical framework of transferring building information between two tools is proposed, and the interoperability issues that occur during the data transfer are studied. The proposed framework is then employed to simulate the energy consumption of a single-family house, and sensitivity analysis and analysis on such parameters as schedule are conducted for building operations to showcase its applicability.FindingsThe simulation results are compared with monitored data and the results from another simulation tool, HOT2000; the comparison reveals that EnergyPlus and HOT2000 predict the total energy consumption with a difference from the monitoring data of 8.0 and 7.1%, respectively.Practical implicationsThis research shows how to efficiently use BIM to support building energy simulation. Relevant stakeholders can learn from this research to avoid data loss during BIM model transformation.Originality/valueThis research explores the application of BIM for building energy simulation, compares the simulation results among different tools and validates simulation results using monitored data.

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