scholarly journals Extracting occupants’ energy-use patterns from Wi-Fi networks in office buildings

2019 ◽  
Vol 26 ◽  
pp. 100864 ◽  
Author(s):  
Hamed Nabizadeh Rafsanjani ◽  
Ali Ghahramani
Keyword(s):  
Energy Use ◽  
Office Buildings ◽  
Use Patterns

scholarly journals DETERMINING THE EFFECT OF BUILDING GEOMETRY ON ENERGY USE PATTERNS OF OFFICE BUILDINGS IN TORONTO

2014 ◽  
Vol 9 (2) ◽  
pp. 124-144 ◽  
Author(s):  
Tonima Ferdous ◽  
Mark Gorgolewski
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Energy Performance ◽  
Office Buildings ◽  
Design Parameters ◽  
Use Patterns ◽  
Aspect Ratios ◽  
Building Geometry ◽  
Shading Devices ◽  
Saving Measure

The project investigated the potential of building geometry to minimize energy consumption in office buildings. Five distinct geometries were modeled as mid-size office occupancies in the context of Toronto, Ontario, and examined with varied design parameters: window to wall ratio (WWR) and external static shading devices. IES VE software was used to predict the annual energy consumption of the five archetypes for 40 permutations. The outcome of this research showed that the variation of the total energy use from one shape to another was relatively small. WWR appeared to have a stronger impact on the energy pattern of a building than its shape. Overall, the energy performance of the archetypes were observed to conform to their individual building aspect ratios. The findings are thus expected to provide useful guidelines for architects on utilizing building geometry as an energy saving measure in the design of office buildings.

scholarly journals Energy and Greenhouse Gas Savings for LEED-Certified U.S. Office Buildings

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 749
Author(s):  
John H. Scofield ◽  
Susannah Brodnitz ◽  
Jakob Cornell ◽  
Tian Liang ◽  
Thomas Scofield
Keyword(s):  
Greenhouse Gas ◽  
Energy Use ◽  
Energy Savings ◽  
Electric Energy ◽  
Building Energy ◽  
Energy Performance ◽  
Office Buildings ◽  
Ghg Emission ◽  
Site Energy ◽  
New Construction

In this work, we present results from the largest study of measured, whole-building energy performance for commercial LEED-certified buildings, using 2016 energy use data that were obtained for 4417 commercial office buildings (114 million m2) from municipal energy benchmarking disclosures for 10 major U.S. cities. The properties included 551 buildings (31 million m2) that we identified as LEED-certified. Annual energy use and greenhouse gas (GHG) emission were compared between LEED and non-LEED offices on a city-by-city basis and in aggregate. In aggregate, LEED offices demonstrated 11% site energy savings but only 7% savings in source energy and GHG emission. LEED offices saved 26% in non-electric energy but demonstrated no significant savings in electric energy. LEED savings in GHG and source energy increased to 10% when compared with newer, non-LEED offices. We also compared the measured energy savings for individual buildings with their projected savings, as determined by LEED points awarded for energy optimization. This analysis uncovered minimal correlation, i.e., an R2 < 1% for New Construction (NC) and Core and Shell (CS), and 8% for Existing Euildings (EB). The total measured site energy savings for LEED-NC and LEED-CS was 11% lower than projected while the total measured source energy savings for LEED-EB was 81% lower than projected. Only LEED offices certified at the gold level demonstrated statistically significant savings in source energy and greenhouse gas emissions as compared with non-LEED offices.

Closed-Form Correlation of Buildings Energy Use With Key Design Parameters Calibrated Using a Genetic Algorithm

2011 ◽  
Vol 133 (4) ◽  
Author(s):  
Raed I. Bourisli ◽  
Adnan A. AlAnzi
Keyword(s):  
Genetic Algorithm ◽  
Closed Form ◽  
Energy Use ◽  
Building Design ◽  
Office Buildings ◽  
Design Parameters ◽  
Wide Range ◽  
Variable Function ◽  
Real Coded Genetic Algorithm ◽  
The Difference

This work aims at developing a closed-form correlation between key building design variables and its energy use. The results can be utilized during the initial design stages to assess the different building shapes and designs according to their expected energy use. Prototypical, 20-floor office buildings were used. The relative compactness, footprint area, projection factor, and window-to-wall ratio were changed and the resulting buildings performances were simulated. In total, 729 different office buildings were developed and simulated in order to provide the training cases for optimizing the correlation’s coefficients. Simulations were done using the VisualDOE TM software with a Typical Meteorological Year data file, Kuwait City, Kuwait. A real-coded genetic algorithm (GA) was used to optimize the coefficients of a proposed function that relates the energy use of a building to its four key parameters. The figure of merit was the difference in the ratio of the annual energy use of a building normalized by that of a reference building. The objective was to minimize the difference between the simulated results and the four-variable function trying to predict them. Results show that the real-coded GA was able to come up with a function that estimates the thermal performance of a proposed design with an accuracy of around 96%, based on the number of buildings tested. The goodness of fit, roughly represented by R2, ranged from 0.950 to 0.994. In terms of the effects of the various parameters, the area was found to have the smallest role among the design parameters. It was also found that the accuracy of the function suffers the most when high window-to-wall ratios are combined with low projection factors. In such cases, the energy use develops a potential optimum compactness. The proposed function (and methodology) will be a great tool for designers to inexpensively explore a wide range of alternatives and assess them in terms of their energy use efficiency. It will also be of great use to municipality officials and building codes authors.

scholarly journals Domestic versus foreign energy use: an analysis for four European countries

2021 ◽  
Author(s):  
José A. Camacho ◽  
Lucas da Silva Almeida ◽  
Mercedes Rodríguez ◽  
Jesús Molina
Keyword(s):  
Czech Republic ◽  
Total Energy ◽  
Energy Use ◽  
Energy Intensity ◽  
Value Chains ◽  
The Czech Republic ◽  
Preliminary Step ◽  
Use Patterns ◽  
Domestic Use ◽  
Energy Intensities

AbstractIn order to adequately assess energy policies and set clear objectives, a key preliminary step is to know the energy use patterns of the different countries. This paper estimates the evolution of the total energy use over the period 1995–2015 in four European Union (EU) countries, the Czech Republic, Hungary, Italy, and Spain, representative of two different energy patterns, the “Southern” one and the “Eastern” one. For doing so, we employ a Multi-Regional Input Output (MRIO) model. In difference with previous studies, in addition to differentiate between domestic and foreign use we distinguish whether this energy is produced domestically or abroad. The results obtained show a certain convergence in energy intensity across the four countries examined because of the radical transformations experienced by the Czech Republic and Hungary. Nonetheless, energy intensities are still substantially higher in Eastern than in Southern countries which confirms that the first group of countries have still a long road to go, especially regarding the incentives that their industries have to use energy efficiently. Taking our decomposition of total energy use, the reductions in total energy use were mainly caused by a high decrease in the importance of the domestic use of energy produced domestically. At the same time, a growing importance of the role played by the energy produced abroad was observed. These trends confirm the great importance of global value chains and the steady internalization of energy use. This methodology could be further applied to other countries.

The Use of BIM Technology in Analyzing Building Energy and EconomicFeasibility of Solar Panel

2021 ◽  
Vol 5 (2) ◽  
Author(s):  
Muhammadiya Rifqi ◽  
Heni Fitriani ◽  
Puteri Kusuma Wardhani
Keyword(s):  
Power Plants ◽  
Energy Use ◽  
Electrical Energy ◽  
Building Energy ◽  
Economic Feasibility ◽  
Information Modeling ◽  
Office Buildings ◽  
Design Stage ◽  
Solar Panels ◽  
Building Information

Buildings contribute more than 40% of world energy consumption, so it is feared that it will cause energy problems in thefuture, especially in the construction sector. One solution to reducing this problem is by analyzing energy use at the initialdesign stage and utilizing solar energy as one of the solar power plants (PLTS) in office buildings. To analyze the use ofenergy in buildings, Building Information Modeling (BIM) was used. The purpose of this research is to analyze the annualenergy level of office buildings in Palembang using BIM software, namely Autodesk Revit. The number of solar panels aswell as the amount of energy were also identified using web-based software (HelioScope) resulting the economic feasibilityas indicated by the installation of solar panels as a component of PV mini-grid. The results showed that the use of BIMtechnology in analyzing building energy can provide a detailed description of the building model at the design stage. Revitanalysis indicates that the building consumed electrical energy per year for about 3,647,713 kWh with a roof area of 1,657m2. In addition, based on the HelioScope analysis, the use of renewable energy from the installation of PLTS was 152,900kWh/year. Meanwhile, for economic feasibility analysis, the installation of PLTS in office buildings can provide a positive NetPresent Value (NPV), indicating a feasible project.

scholarly journals Feature Identification for Non-Intrusively Extracting Occupant Energy-Use Information in Office Buildings

2019 ◽  
Vol 1 (1) ◽  
Author(s):  
Hamed Nabizadeh Rafsanjani
Keyword(s):  
Capital Investment ◽  
Energy Use ◽  
Low Cost ◽  
Specific Energy Consumption ◽  
Cost Effective ◽  
Office Buildings ◽  
Specific Power ◽  
Feature Identification ◽  
Load Monitoring ◽  
Energy Consuming

Detailed energy-use information of office buildings’ occupants is necessary to implement proper simulation/intervention techniques. However, acquiring accurate occupant-specific energy consumption in office buildings at low cost is currently a challenging task since existing intrusive load monitoring (ILM) technologies require a large capital investment to provide high-resolution electricity usage data for individual occupants. On the other hand, non-intrusive load monitoring (NILM) approaches have been proven as more cost effective and flexible approaches to provide energy-use information of individual appliances. Therefore, extending the concept of NILM to individual occupants would be beneficial. This paper proposes two occupancy-related energy-consuming features, delay interval and magnitude of power changes and evaluates their significances for extracting occupant-specific power changes in a non-intrusive manner. The proposed features were examined through implementing a logistic regression model as a predictor on aggregate energy load data collected from an office building. Hypotheses tests also confirmed that both features are statistically significant to non-intrusively derive individual occupants’ energy-use information. As the main contribution of this study, these features could be utilized in developing sophisticated NILM-based approaches to monitor individual occupant energy-consuming behavior.  

scholarly journals The Performance Gap in Energy-Efficient Office Buildings: How the Occupants Can Help?

Energies ◽  
2020 ◽  
Vol 13 (6) ◽  
pp. 1480 ◽  
Author(s):  
Qadeer Ali ◽  
Muhammad Jamaluddin Thaheem ◽  
Fahim Ullah ◽  
Samad M. E. Sepasgozar
Keyword(s):  
Energy Efficient ◽  
Behavioral Interventions ◽  
Energy Use ◽  
Energy Savings ◽  
Energy Performance ◽  
Office Buildings ◽  
Occupant Behavior ◽  
Energy Usage ◽  
Performance Gap ◽  
Energy Efficient Buildings

Rising demand and limited production of electricity are instrumental in spreading the awareness of cautious energy use, leading to the global demand for energy-efficient buildings. This compels the construction industry to smartly design and effectively construct these buildings to ensure energy performance as per design expectations. However, the research tells a different tale: energy-efficient buildings have performance issues. Among several reasons behind the energy performance gap, occupant behavior is critical. The occupant behavior is dynamic and changes over time under formal and informal influences, but the traditional energy simulation programs assume it as static throughout the occupancy. Effective behavioral interventions can lead to optimized energy use. To find out the energy-saving potential based on simulated modified behavior, this study gathers primary building and occupant data from three energy-efficient office buildings in major cities of Pakistan and categorizes the occupants into high, medium, and low energy consumers. Additionally, agent-based modeling simulates the change in occupant behavior under the direct and indirect interventions over a three-year period. Finally, energy savings are quantified to highlight a 25.4% potential over the simulation period. This is a unique attempt at quantifying the potential impact on energy usage due to behavior modification which will help facility managers to plan and execute necessary interventions and software experts to develop effective tools to model the dynamic usage behavior. This will also help policymakers in devising subtle but effective behavior training strategies to reduce energy usage. Such behavioral retrofitting comes at a much lower cost than the physical or technological retrofit options to achieve the same purpose and this study establishes the foundation for it.

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