5 results on '"Leila Nikdel"'
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2. Datasets for occupancy profiles in apartment-style student housing for occupant behavior studies and application in building energy simulation
- Author
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Leila Nikdel, Alan E.S. Schay, Daqing Hou, and Susan E. Powers
- Subjects
Occupancy profiles ,Occupancy schedules ,Student housing ,Occupant behavior ,Building energy simulation ,Geo fence data ,Computer applications to medicine. Medical informatics ,R858-859.7 ,Science (General) ,Q1-390 - Abstract
Building energy simulation (BES) tools fail to capture diversity among occupants’ consumption behaviors by using simple and generic occupancy and load profiles, causing uncertainties in simulation predictions. Thus, generating actual occupancy profiles can lead to more accurate and reliable BES predictions. In this article, occupancy profiles for apartment-style student housing are presented from high-resolution monitored occupancy data. A geo-fencing app was designed and installed on the cellphones of 41 volunteer students living in student housing buildings on Clarkson University's campus. Occupants’ entering and exiting activities were recorded every minute from February 4 to May 10, 2018. Recorded events were sorted out for each individual by the date and time of day considering 1 for ‘entered’ events and 0 for ‘exited’ events to show the probability of presence at each time of day. Accounting for excluded days (234 days with errors and uncertainties), 1,096 daily occupancy observations were retained in the dataset. Two methods were used to analyze the dataset and derive weekday and weekend occupancy schedules. A simple averaging method and K-means clustering techniques were performed [1]. This article provides the input datasets that were used for analysis as well as the outputs of both methods. Occupancy schedules are presented separately for each day of a week, weekdays, and weekend days. To show differences in students’ occupancy patterns, occupancy schedules in 7 clusters for weekdays and 3 clusters for weekend days are provided. These datasets can be beneficial for modelers and researchers for either using provided occupancy schedules in BES tools or understanding occupant behaviors in student housing.
- Published
- 2021
- Full Text
- View/download PDF
3. Net Zero Energy Housing: An Empirical Analysis from Measured Data
- Author
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Leila Nikdel, Philip Agee, Georg Reichard, and Andrew McCoy
- Subjects
Mechanical Engineering ,Building and Construction ,Electrical and Electronic Engineering ,general_engineering ,Civil and Structural Engineering - Abstract
This study reports an empirical analysis of an all-electric, Net Zero Energy Housing (NZEH) development located in a mixed-humid climate zone (4A, Virginia, USA). Circuit-level energy monitors were used to measure energy consumption and energy production data (solar photovoltaic) at 1-hr intervals in six identical apartments over 24 months. The study employs a multi-step case study methodology to a) empirically evaluate energy consumption and production data, b) identify the temporal variability of energy consumption and production data at different time scales, c) understand the impact(s) of weather and human-building interaction on energy consumption and production, and d) synthesize the study’s “lessons learned” toward data-driven recommendations for future NZEH researchers and practitioners. The study found that the development’s net zero energy goal was achieved in three of six case units and that NZEH housing performance was more influenced by human-building interaction than weather variability. The analysis also found the solar photovoltaic (PV) performance to be reliable across the sampled units over the periods of measurement, suggesting that solar PV could be oversized as an approach to overcome verifiability in HBI and achieve NZEH performance goals.
- Published
- 2022
4. Multiple perspectives of the value of occupancy-based HVAC control systems
- Author
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Leila Nikdel, Stephen Bird, Kerop D. Janoyan, and Susan E. Powers
- Subjects
Environmental Engineering ,Occupancy ,business.industry ,020209 energy ,Geography, Planning and Development ,Fossil fuel ,0211 other engineering and technologies ,02 engineering and technology ,Building and Construction ,Environmental economics ,Thermostat ,law.invention ,Setpoint ,law ,Air conditioning ,Greenhouse gas ,021105 building & construction ,HVAC ,0202 electrical engineering, electronic engineering, information engineering ,Environmental science ,business ,Building envelope ,Civil and Structural Engineering - Abstract
Occupancy-based strategies for reducing energy used for heating, ventilating, and air conditioning (HVAC) benefit building owners and help meet state and federal energy and climate goals. However, this value has not previously been quantified beyond typical building owner energy savings. The objective of this research is to estimate the national-level potential added-value of occupancy-based HVAC controls in small office buildings relative to a constant setpoint or to programmable thermostats. Value is defined based on the building owner perspective (energy cost), as well as societal based perspectives of fossil fuels consumed and greenhouse gas, NOx and SOx emissions. A generic small office building with two different HVAC systems is simulated in EnergyPlus and applied to five climate zones representative of the United States. Specific building envelope, electricity supplies, utility costs and total area of small office buildings are adjusted for each climate zone. Results demonstrate that occupancy-based strategies for HVAC control are highly effective, yielding 22-50%and 47-87% reduction in electricity and natural gas use, respectively, compared to no thermostat control. Results vary substantially across climate zones and HVAC systems. With occupancy sensors installed in all small office buildings, the U.S. national savings would be 15 - 66 million GJ fossil fuel use, 0.9–3.7 million metric tons CO2e emissions, and 168 - 658 million dollars for utility cost.
- Published
- 2018
- Full Text
- View/download PDF
5. Data-driven Occupancy Profiles for Apartment-style Student Housing
- Author
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Leila Nikdel, Alan Schay, Daqing Hou, and Susan E. Powers
- Subjects
High probability ,Schedule ,ComputingMilieux_THECOMPUTINGPROFESSION ,Apartment ,Occupancy ,Computer science ,020209 energy ,Mechanical Engineering ,Cold climate ,education ,0211 other engineering and technologies ,02 engineering and technology ,Building and Construction ,Building design ,Data-driven ,Behavioral study ,ComputerApplications_GENERAL ,021105 building & construction ,Statistics ,0202 electrical engineering, electronic engineering, information engineering ,Electrical and Electronic Engineering ,Civil and Structural Engineering - Abstract
To support the need for a better understanding of occupant behaviors in buildings, we present occupancy profiles for apartment-style student housing from high-resolution monitored occupancy data. We illustrate differences between data-driven occupancy patterns and the widely-used reference occupancy schedule in Building America’s House Simulation Protocol. We evaluate the sensitivity of predicted savings associated with the installation of occupancy-based heating and cooling controls to differences in occupancy schedules. Results demonstrate a wide variety of occupancy patterns among students. Weekday occupancy schedules are influenced by students’ class schedules with the average probability that students are home mid-day twice that defined by the reference occupancy schedule. However, the differences between the reference and actual occupancy profiles have produced a small change (~3%) in the savings predicted for occupancy-based heating and cooling controls in a cold climate (4.3–7.7%). The potential savings was not sensitive to the variability among student occupancy schedules due to the high probability of occupancy for most hours of the day. Nonetheless, the variety of occupancy patterns among students reveals diversity in students’ behaviors. Better understanding of occupant behavior in buildings provides crucial information for demand and distribution management of electrical grids, behavioral studies, and occupant-centric building design.
- Published
- 2021
- Full Text
- View/download PDF
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