scholarly journals Closing the gap: an assessment of mixed-method data collection techniques in post occupancy evaluation

2021 ◽  
Author(s):  
Thomas Moore
Keyword(s):  
Data Collection ◽  
Mixed Method ◽  
High Performance ◽  
Energy Use ◽  
Predictive Performance ◽  
Practical Case ◽  
Performance Gap ◽  
Post Occupancy Evaluation ◽  
Energy Use Intensity ◽  
Performance Discrepancy

Demand for energy efficient buildings has supported an increase in predictive performance modeling. However, operation of buildings can often be different than predictive models, creating a collective performance discrepancy referred to as the “performance gap”. Post Occupancy Evaluation (POE) can close this gap by evaluating performance, and contrasting operational data to design intention. This POE demonstrates an identifiable performance gap in a practical case study on one high-performance building. Findings suggest the case building is not meeting anticipated energy consumption with a higher than predicted energy use intensity (EUI). Additional findings indicate a leaky building enclosure, significant thermal bridging, unrealistic simulation assumptions, acoustic disturbances, and occupant thermal comfort satisfaction. This POE demonstrates that mixed-method data collection provides more information than singular analyses when attempting to identify a performance gap. It is demonstrated that qualitative data collection techniques explain quantitative findings in analysis, informing understanding of performance gap causation.

scholarly journals Closing the gap: an assessment of mixed-method data collection techniques in post occupancy evaluation

2021 ◽  
Author(s):  
Thomas Moore
Keyword(s):  
Data Collection ◽  
Mixed Method ◽  
High Performance ◽  
Energy Use ◽  
Predictive Performance ◽  
Practical Case ◽  
Performance Gap ◽  
Post Occupancy Evaluation ◽  
Energy Use Intensity ◽  
Performance Discrepancy

Demand for energy efficient buildings has supported an increase in predictive performance modeling. However, operation of buildings can often be different than predictive models, creating a collective performance discrepancy referred to as the “performance gap”. Post Occupancy Evaluation (POE) can close this gap by evaluating performance, and contrasting operational data to design intention. This POE demonstrates an identifiable performance gap in a practical case study on one high-performance building. Findings suggest the case building is not meeting anticipated energy consumption with a higher than predicted energy use intensity (EUI). Additional findings indicate a leaky building enclosure, significant thermal bridging, unrealistic simulation assumptions, acoustic disturbances, and occupant thermal comfort satisfaction. This POE demonstrates that mixed-method data collection provides more information than singular analyses when attempting to identify a performance gap. It is demonstrated that qualitative data collection techniques explain quantitative findings in analysis, informing understanding of performance gap causation.

scholarly journals Evaluating Performance of Southern Ontario Buildings Using Submetering data and Whole Building Modeling Results

2021 ◽  
Author(s):  
Mark Adrian Turcato
Keyword(s):  
High Performance ◽  
Energy Use ◽  
Value Engineering ◽  
Data Sets ◽  
Performance Gap ◽  
Actual Performance ◽  
Energy Models ◽  
Building Modeling ◽  
Building Management ◽  
The Difference

The performance gap, the difference between how a building was intended to Perform and its actual performance, poses a challenge to successful high performance design. This research examines the application of submetering data and whole building energy models to evaluate the performance gap in buildings as related to energy consumption, and in specific energy use associated with receptacles and lighting. While difficulties in grappling with large amounts of data persist, results indicate that building management and occupancy issues can offer an explanation for a significant portion of differences between predicted and actual energy use. Experience working with these data sets also suggests that further efforts are required to demonstrate the value of submetering in order to ensure submetering systems are not compromised by the value engineering process.

scholarly journals Evaluating Performance of Southern Ontario Buildings Using Submetering data and Whole Building Modeling Results

2021 ◽  
Author(s):  
Mark Adrian Turcato
Keyword(s):  
High Performance ◽  
Energy Use ◽  
Value Engineering ◽  
Data Sets ◽  
Performance Gap ◽  
Actual Performance ◽  
Energy Models ◽  
Building Modeling ◽  
Building Management ◽  
The Difference

The performance gap, the difference between how a building was intended to Perform and its actual performance, poses a challenge to successful high performance design. This research examines the application of submetering data and whole building energy models to evaluate the performance gap in buildings as related to energy consumption, and in specific energy use associated with receptacles and lighting. While difficulties in grappling with large amounts of data persist, results indicate that building management and occupancy issues can offer an explanation for a significant portion of differences between predicted and actual energy use. Experience working with these data sets also suggests that further efforts are required to demonstrate the value of submetering in order to ensure submetering systems are not compromised by the value engineering process.

scholarly journals Assessment of the Potential of High-Performance Buildings to Achieve Zero Energy: A Case Study

2019 ◽  
Vol 9 (4) ◽  
pp. 775 ◽  
Author(s):  
Dan Wang ◽  
Xiufeng Pang ◽  
Wei Wang ◽  
Zewei Qi ◽  
Jin Li ◽  
...  
Keyword(s):  
High Performance ◽  
Energy Use ◽  
Cost Effective ◽  
Energy Performance ◽  
Photovoltaic System ◽  
Occupant Behavior ◽  
Zero Energy ◽  
Performance Targets ◽  
Energy Use Intensity ◽  
High Performance Buildings

Buildings that are designed with aggressive energy performance targets are defined broadly in this study as high-performance buildings. As the technology advances, some of these buildings have the potential to become zero-energy ready through the adoption of cost-effective measures, such as retro-commissioning and occupant behavior techniques. This study demonstrated the viability of an office building to achieve the zero-energy goal and intended to engage the owners of similar facilities. The case building was designed as a very low-energy building with an energy use intensity (EUI) goal of 42 kWh/(m2 a), and the actual EUI was 23.9 kWh/(m2 a). The calibrated simulation approach was employed in the study, and the results indicated that the case building can achieve the zero-energy goal by optimizing the controls of the HVAC (Heating, Ventilation and Air Conditioning) system, changing the occupant behavior and improving the performance of the photovoltaic system.

scholarly journals Statistical and machine learning models for optimizing energy in parallel applications

2019 ◽  
Vol 33 (6) ◽  
pp. 1079-1097 ◽  
Author(s):  
Mark Endrei ◽  
Chao Jin ◽  
Minh Ngoc Dinh ◽  
David Abramson ◽  
Heidi Poxon ◽  
...  
Keyword(s):  
Machine Learning ◽  
Energy Efficiency ◽  
High Performance ◽  
Large Scale ◽  
Energy Use ◽  
Parallel Applications ◽  
Learning Models ◽  
Trade Off ◽  
Time Required ◽  
Machine Learning Models

Rising power costs and constraints are driving a growing focus on the energy efficiency of high performance computing systems. The unique characteristics of a particular system and workload and their effect on performance and energy efficiency are typically difficult for application users to assess and to control. Settings for optimum performance and energy efficiency can also diverge, so we need to identify trade-off options that guide a suitable balance between energy use and performance. We present statistical and machine learning models that only require a small number of runs to make accurate Pareto-optimal trade-off predictions using parameters that users can control. We study model training and validation using several parallel kernels and more complex workloads, including Algebraic Multigrid (AMG), Large-scale Atomic Molecular Massively Parallel Simulator, and Livermore Unstructured Lagrangian Explicit Shock Hydrodynamics. We demonstrate that we can train the models using as few as 12 runs, with prediction error of less than 10%. Our AMG results identify trade-off options that provide up to 45% improvement in energy efficiency for around 10% performance loss. We reduce the sample measurement time required for AMG by 90%, from 13 h to 74 min.

scholarly journals Loneliness Among the Elderly in Rural Contexts: A Mixed-Method Study Protocol

2021 ◽  
Vol 20 ◽  
pp. 160940692199686
Author(s):  
Borja Rivero Jiménez ◽  
David Conde-Caballero ◽  
Lorenzo Mariano Juárez
Keyword(s):  
Data Collection ◽  
Mixed Method ◽  
Rural Areas ◽  
Population Group ◽  
The Elderly ◽  
Interaction Patterns ◽  
Structured Interviews ◽  
Strict Adherence ◽  
Data Collection And Analysis ◽  
Technological Tools

Loneliness among the elderly has become a pressing issue in Western societies. In the Spanish context, the problem of the so-called “empty” Spain disproportionately affects this population group—elderly individuals living in rural areas with low population density, and therefore at higher risk of social exclusion and isolation. We introduce here a mixed-method, quantitative-qualitative research protocol, triangulated with technological tools, designed to improve both data acquisition and subsequent data analysis and interpretation. This study will take place in a rural locality in the Extremadura region (Spain), chosen according to a particular socio-demographic profile. The De Jong Gierveld Loneliness Scale will be used on a cohort of 80 people over 65 years old. Within this cohort, a smaller sample of 20–30 individuals will be selected for semi-structured interviews about their beliefs and experiences of loneliness. Finally, data gathered from technological tools (smartbands, Bluetooth sensors) will allow us to monitor social interactions and to map daily loneliness/interaction patterns. Data will be triangulated by analyzing and comparing the empirical material gathered through these different methods and tools. Strict adherence to ethical standards for data protection and handling will be essential through data collection and analysis. As well as providing insights into the phenomenon of loneliness in old age, the use of different methods and tools for data collection will provide the basis for an epistemological reflection on the scope and limits of each one of these methods.

A DECISION TREE-BASED CLASSIFICATION APPROACH TO RULE EXTRACTION FOR SECURITY ANALYSIS

2006 ◽  
Vol 05 (01) ◽  
pp. 227-240 ◽  
Author(s):  
N. REN ◽  
M. ZARGHAM ◽  
S. RAHIMI
Keyword(s):  
Decision Tree ◽  
High Performance ◽  
Security Analysis ◽  
Predictive Performance ◽  
Classification Model ◽  
Stock Selection ◽  
Selection Rules ◽  
Stock Portfolios ◽  
Decision Tree Classification ◽  
C4.5 Decision Tree

Stock selection rules are extensively utilized as the guideline to construct high performance stock portfolios. However, the predictive performance of the rules developed by some economic experts in the past has decreased dramatically for the current stock market. In this paper, C4.5 decision tree classification method was adopted to construct a model for stock prediction based on the fundamental stock data, from which a set of stock selection rules was derived. The experimental results showed that the generated rules have exceptional predictive performance. Moreover, it also demonstrated that the C4.5 decision tree classification model can work efficiently on the high noise stock data domain.

Solar-Driven Sorption Chillers for Residential Space Cooling: A Review of Recent Developments and Possible Applications in Canada

2015 ◽  
Author(s):  
Daniel Bowie ◽  
Cynthia A. Cruickshank
Keyword(s):  
High Performance ◽  
Energy Use ◽  
Peak Load ◽  
Internal Heat ◽  
Electricity Grid ◽  
Residential Sector ◽  
Absorption Chillers ◽  
Space Cooling ◽  
Recent Developments ◽  
Advanced Cycles

Energy use for space cooling has increased by 156% from 1990 to 2010 in the Canadian residential sector. In many parts of the country, the increasing use of electrically driven air-conditioners has begun to shift the peak load on the electricity grid from the coldest days of winter to the hottest days of summer. Many of Canada’s major electric utilities providers rely on fossil fuels to generate the additional capacity needed to meet the peak demand, resulting in significant greenhouse gas emissions. Solar-driven sorption chillers remain one of the possible solutions for shaving the peak loads experienced by the electricity grid. This paper presents a review of the recent developments in the research of adsorption and absorption chillers, as well as a comparison of the two technologies based on the latest published experimental results found in the literature. Adsorption chillers continue to evolve in their design, including the use of new consolidated and composite adsorbents, the integration of coated adsorbers into internal heat exchangers, and newly developed advanced cycles for heat and mass recovery. While the physical design of adsorption chillers continues to be advanced, the development of absorption chillers for solar cooling applications has largely been focused on optimizing the system as a whole through improved control strategies and the implementation of newly developed high performance solar collectors. Finally, the paper aims to assess the current state of development of solar-driven sorption chillers to provide insight into their applicability in the Canadian residential sector, as well as the remaining challenges facing this technology.

People or Systems: Does Productivity Enhancement Matter More than Energy Management in LEED Certified Buildings?

2021 ◽  
Vol 13 (24) ◽  
pp. 13863
Author(s):  
Yana Akhtyrska ◽  
Franz Fuerst
Keyword(s):  
Energy Consumption ◽  
Energy Management ◽  
Energy Use ◽  
Management Practices ◽  
Energy Savings ◽  
Occupant Comfort ◽  
Energy Use Intensity ◽  
Using Data ◽  
Advanced Metering ◽  
The Impact

This study examines the impact of energy management and productivity-enhancing measures, implemented as part of LEED Existing Buildings Operations and Management (EBOM) certification, on source energy use intensity and rental premiums of office spaces using data on four major US markets. Energy management practices, comprised of commissioning and advanced metering, may reduce energy usage. Conversely, improving air quality and occupant comfort in an effort to increase worker productivity may in turn lead to higher overall energy consumption. The willingness to pay for these features in rental office buildings is hypothesised to depend not only on the extent to which productivity gains enhance the profits of a commercial tenant but also on the lease arrangements for passing any energy savings to the tenant. We apply a difference-in-differences method at a LEED EBOM certification group level and a multi-level modelling approach with a panel data structure. The results indicate that energy management and indoor environment practices have the expected effect on energy consumption as described above. However, the magnitude of the achieved rental premiums appears to be independent of the lease type.

Developing High Performance GaP/Si Heterojunction Solar Cells

10.3791/58292 ◽  
2018 ◽  
Author(s):  
Chaomin Zhang ◽  
Ehsan Vadiee ◽  
Som Dahal ◽  
Richard R. King ◽  
Christiana B. Honsberg
Keyword(s):  
Solar Cells ◽  
High Performance ◽  
Performance Gap ◽  
Heterojunction Solar Cells
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