scholarly journals Advanced Cluster and Predictive Analysis Tool Development for Commercial Office Real Estate Energy Usage

2021 ◽  
Author(s):  
Carleen Lawson
Keyword(s):  
Energy Use ◽  
Data Gathering ◽  
Machine Learning Algorithms ◽  
Analysis Tool ◽  
Tool Development ◽  
Energy Usage ◽  
Future Data ◽  
Building Characteristics ◽  
Energy Benchmarking ◽  
Physical Features

From 2009-2015, REALPAC collected monthly energy usage and building characteristics for over 500 buildings in the 20 by ‘15 Energy Benchmarking Survey (REALPAC, 2009). While preliminary analysis had been completed on this dataset, this research undertook an in-depth statistical analysis of the data to identify trends and important variables. Eight machine learning algorithms were employed to predict energy usage as a function of previous energy use and select physical features. The dataset did not possess the appropriate variables to predict such usage accurately. Characteristics such as building system efficiency, construction assemblies, condition, compactness, and window to wall ratio are thus recommended for inclusion in future data-gathering initiatives. https://digital.library.ryerson.ca/islandora/object/RULA:8631/datastream/LAW_RSCR-4.80MB/view https://digital.library.ryerson.ca/islandora/object/RULA:8631/datastream/LAW-ExTa-428KB/view https://digital.library.ryerson.ca/islandora/object/RULA:8631/datastream/LAW-ExGa-5.62MB/view https://digital.library.ryerson.ca/islandora/object/RULA:8631/datastream/LAW-DATA-1.9MB/view

scholarly journals Advanced Cluster and Predictive Analysis Tool Development for Commercial Office Real Estate Energy Usage

2021 ◽  
Author(s):  
Carleen Lawson
Keyword(s):  
Energy Use ◽  
Data Gathering ◽  
Machine Learning Algorithms ◽  
Analysis Tool ◽  
Tool Development ◽  
Energy Usage ◽  
Future Data ◽  
Building Characteristics ◽  
Energy Benchmarking ◽  
Physical Features

From 2009-2015, REALPAC collected monthly energy usage and building characteristics for over 500 buildings in the 20 by ‘15 Energy Benchmarking Survey (REALPAC, 2009). While preliminary analysis had been completed on this dataset, this research undertook an in-depth statistical analysis of the data to identify trends and important variables. Eight machine learning algorithms were employed to predict energy usage as a function of previous energy use and select physical features. The dataset did not possess the appropriate variables to predict such usage accurately. Characteristics such as building system efficiency, construction assemblies, condition, compactness, and window to wall ratio are thus recommended for inclusion in future data-gathering initiatives. https://digital.library.ryerson.ca/islandora/object/RULA:8631/datastream/LAW_RSCR-4.80MB/view https://digital.library.ryerson.ca/islandora/object/RULA:8631/datastream/LAW-ExTa-428KB/view https://digital.library.ryerson.ca/islandora/object/RULA:8631/datastream/LAW-ExGa-5.62MB/view https://digital.library.ryerson.ca/islandora/object/RULA:8631/datastream/LAW-DATA-1.9MB/view

scholarly journals Towards the Development of Language Analysis Tools for the Written Latgalian Language

2020 ◽  
Author(s):  
Daiga Deksne ◽  
Anna Vulāne
Keyword(s):  
Web Service ◽  
Morphological Analysis ◽  
Written Language ◽  
Analysis Tool ◽  
Tool Development ◽  
Joint Effort ◽  
Analysis Tools ◽  
Language Analysis ◽  
Wide Range ◽  
Development Of Language

This paper reports on the development of spell checking and morphological analysis tools for Latgalian. The Latgalian written language is a historic variant of the Latvian language. There is a wide range of language analysis tools available for Latvian, whereas the Latgalian language lacks such tools. The work is done by the joint effort of linguists who work on morphologically marked lexicon creation and IT specialists who work on language tool development. For the creation of a morphological analysis tool, we reuse the FST technology used for the Latvian morphological analyzer. We create a spelling dictionary that can be used with the Hunspell engine. All tools are accessible via Web Service. For now, the Latgalian lexicon contains 13,139 lemmas marked by 105 inflection groups. The work of lexicon replenishment still continues.

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.

A Study on the Influence of Planar Mechanism Design on Energy Use During Controlled Movements

2018 ◽  
Author(s):  
David H. Myszka ◽  
Austin M. Fischer ◽  
Andrew P. Murray
Keyword(s):  
Degrees Of Freedom ◽  
Energy Use ◽  
Energy Savings ◽  
Degree Of Freedom ◽  
Energy Utilization ◽  
Energy Usage ◽  
Multiple Degrees Of Freedom ◽  
Low Degree ◽  
Robotic Devices ◽  
Actuator Control

This paper presents a study on the energy utilization of planar automation mechanisms that operate with controlled moves. Designers of factory automation for pick & place tasks often select multiple degree-of-freedom robotic devices. With multiple degrees-of-freedom, task flexibility is available, but many operations require little or no flexibility. The majority of research on the energy usage of these robot devices for pick & place tasks focuses on path planning. The study presented in this paper explores the energy savings in using low degree-of-freedom devices and the influence of design parameter selection. Energy predictor equations are developed and confirmed through experimentation. Various positioning mechanisms of differing dimensions are studied for trends in energy utilization. Lastly, an actuator control strategy is proposed for further reducing energy requirements. The study concludes that energy usage can be substantially decreased in pick & place applications by reducing the degrees of freedom of the device, implementing a prudent mechanism architecture, ideally selecting mechanism dimensions and optimally controlling the actuator(s).

A Study on the Power Consumption Patterns of General Hospital Buildings

2015 ◽  
Vol 1092-1093 ◽  
pp. 573-577
Author(s):  
Myung Kil Yeo ◽  
Kang Guk Lee ◽  
Won Hwa Hong
Keyword(s):  
Power Consumption ◽  
General Hospital ◽  
Power Supply ◽  
Energy Use ◽  
Consumption Patterns ◽  
Basic Data ◽  
Energy Usage ◽  
General Hospitals ◽  
Usage Patterns ◽  
Save Energy

The most important part of energy use in hospital buildings is to identify its usage patterns and maintain power supply even in blackout situations, rather than to save energy. This paper presents the power energy usage patterns of general hospitals as basic data for the establishment of countermeasures in blackout situations.

Analysis of Electrical Energy Savings From Daylighting Through Skylights

Solar Energy ◽  
2005 ◽  
Author(s):  
Abdelkarim Nemri ◽  
Moncef Krarti
Keyword(s):  
Energy Use ◽  
Energy Savings ◽  
Simulation Analysis ◽  
Control Strategies ◽  
Electrical Energy ◽  
Office Building ◽  
Analysis Tool ◽  
Energy Saving Potential ◽  
Lighting Energy ◽  
The Impact

This paper provides a simplified analysis tool to assess the energy saving potential of daylighting for commercial buildings through skylights. Specifically, the impact of daylighting is investigated for various fenestration opening sizes, glazing types, control strategies, and geographic locations. A top floor of a prototypical office building has been considered in the analysis. The results obtained for the office building can be applied to other types of buildings such as retails stores, schools, and warehouses. Based on the simulation analysis results, it was determined that skylight to floor ratio more than 0.3 does not affect significantly the lighting energy savings. An optimum value of skylight to floor area ratio was found to be 0.2 to minimize the annual total building energy use.

Standing the Test of Time: Signals and Noise From Environmental Assessments of Energy Technologies

2007 ◽  
Vol 1041 ◽  
Author(s):  
Björn A. Sandén
Keyword(s):  
Large Scale ◽  
Energy Use ◽  
Data Gathering ◽  
Point Of View ◽  
Technology Choice ◽  
Methodological Choices ◽  
Energy Technologies ◽  
Time Signals ◽  
Current Production

AbstractThe point of view taken here is that systems analysis is a kind of learning process, not data gathering, not decision making, but the production and effective communication of arguments relevant in a particular context. This idea, that the intended application of the result of an assessment has consequences for methodological choices, is beginning to spread in the LCA research community. One problem is that standard LCA methodology is developed to answer questions about environmental impacts of the current production and use of one unit of a product or minor product or process changes. When this methodology, unchanged, is used to provide answers to questions about strategic technology choice, i.e. not decisions that aim at improving a process within an existing technological environment, but with the long-term goal of changing large-scale technological systems, the result could be of little value or misleading. In many cases, LCAs produce more noise than knowledge. This observation seems to be of particular importance for LCAs of energy technologies and for how energy use is treated in all kinds of LCAs. Here, it is suggested that a better understanding of some critical methodological issues related to time, universality, cause-effect relationships, technical maturity and system innovation, could result in better studies that reveal fundamental environmental issues related to the objects of study and reduce the noise from irrelevant information. Examples are given from the technology fields of solar cells, fuel cells, batteries, renewable transport fuels and carbon nanoparticles.

Sustainability and cost assessment of coastal vacation homes for energy retrofits

2017 ◽  
Vol 7 (2) ◽  
pp. 185-198 ◽  
Author(s):  
Kamalesh Panthi ◽  
Kanchan Das ◽  
Tarek Abdel-Salam
Keyword(s):  
Energy Use ◽  
Energy Savings ◽  
Residential Buildings ◽  
Building Envelope ◽  
Energy Usage ◽  
Water Heater ◽  
Content Type ◽  
Modeling Software ◽  
Energy Use Intensity

Purpose Vacation rental homes, in general, have different energy usage characteristics than traditional residential homes mainly because of the occupancy pattern that changes on a weekly basis. These homes, predominantly larger in size, offer a greater scope for energy savings also because of the wasteful habits of their seasonal occupants. The purpose of this paper is to investigate the causes of energy inefficiencies prevalent in these homes so that appropriate retrofit choices can be offered to homeowners. Design/methodology/approach This research presents a case study of a vacation rental home whose energy consumption was investigated in depth and energy inefficiencies identified through modeling using energy modeling software, eQUEST. Simulations were performed to identify viable retrofit scenarios. Findings While improvement in the building envelope such as providing shades/overhangs on the windows, reducing infiltration and increasing insulation of the exterior wall did not show promising results for savings on energy cost, other improvements such as use of highly efficient lamps, tank-less water heater system and occupancy sensors showed viable investment options with shorter payback periods. It was also found that energy use intensity of sampled houses was about half of the average of US residential buildings, which could primarily be attributed to the seasonal nature of occupancy of these houses. Originality/value There is a dearth of literature pertaining to energy efficiency-related retrofits of coastal vacation homes. This research fills that gap to some extent by addressing this issue with an ultimate aim of assisting homeowners in retrofit decision-making.

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