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Li, Han

Publications and source records attributed to Li, Han.

45 records · Page 3
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DOE OSTI2020

AlphaBuilding - Synthetic Buildings Operation Dataset

This is a synthetic building operation dataset which includes HVAC, lighting, miscellaneous electric loads (MELs) system operating conditions, occupant counts, environmental parameters, end-use and whole-building energy consumptions at 10-minute intervals. The data is created with 1395 annual simulations using the U.S. DOE detailed medium-sized reference office building, and 30 years' historical weather data in three typical climates including Miami, San Francisco, and Chicago. Three energy efficiency levels of the building and systems are considered. Assumptions regarding occupant movements, occupants' diverse temperature preferences, lighting, and MELs are adopted to reflect realistic building operations. A semantic building metadata schema - BRICK, is used to store the building metadata. The dataset is saved in a 1.2 TB of compressed HDF5 file. This dataset can be used in various applications, including building energy and load shape benchmarking, energy model calibration, evaluation of occupant and weather variability and their influences on building performance, algorithm development and testing for thermal and energy load prediction, model predictive control, policy development for reinforcement learning based building controls.

AlphaBuilding↗
DOE OSTI2020

OpenStudio Occupant-centric KPIs Reporting Measure v1.0

This is an OpenStudio measure that calculates and reports the occupant-centric key performance indicators (KPIs) for evaluating building energy performance from occupant-centric perspectives. The measure automatically calculate the KPIs in the following categories: (1) visual & lighting, (2) thermal (3) air quality, and (4) others.

Hong, Tianzhen↗
DOE OSTI2020

Anomalous Behavior of 2D Janus Excitonic Layers under Extreme Pressures

Newly discovered 2D Janus transition metal dichalcogenides layers have gained much attention from a theory perspective owing to their unique atomic structure and exotic materials properties, but little to no experimental data are available on these materials. Here, experimental and theoretical studies establish the vibrational and optical behavior of 2D Janus S–W–Se and S–Mo–Se monolayers under high pressures for the first time. Chemical vapor deposition (CVD)-grown classical transition metal dichalcogenides (TMD) monolayers are first transferred onto van der Waals (vdW) mica substrates and converted to 2D Janus sheets by surface plasma technique, and then integrated into a 500 µm size diamond anvil cell for high-pressure studies. Overall, the results show that 2D Janus layers do not undergo phase transition up to 15 GPa, and in this pressure regime, their vibrational modes exhibit a nonmonotonic response to the applied pressures (dω/dP). Interestingly, these 2D Janus monolayers exhibit unique blueshift in photoluminescence (PL) upon compression, which is in contrast to many other traditional semiconductor materials. Overall theoretical simulations offer in-depth insights and reveal that the overall optical response is a result of competition between the ab-plane (blueshift) and c-axis (redshift) compression. The overall findings shed the very first light on how 2D Janus monolayers respond under extreme pressures and expand the fundamental understanding of these materials.

2D Janus monolayers↗
DOE OSTI2020

Generation and representation of synthetic smart meter data

Advanced energy algorithms running at big-data scale will be necessary to identify, realize, and verify energy savings to meet government and utility goals of building energy efficiency. Any algorithm must be well characterized and validated before it is trusted to run at these scales. Smart meter data from real buildings will ultimately be required for the development, testing, and validation of these energy algorithms and processes. However, for initial development and testing, smart meter data are difficult to work with due to privacy restrictions, noise from unknown sources, data accessibility, and other concerns which can complicate algorithm development and validation. This paper describes a new methodology to generate synthetic smart meter data of electricity use in buildings using detailed building energy modeling, which aims to capture the variability and stochastics of real energy use in buildings. The methodology can create datasets tailored to represent specific scenarios with known truth and controllable amounts of synthetic noise. Knowledge of ground truth also allows the development and validation of enhanced processes which leverage building metadata, such as building type or size (floor area), in addition to smart meter data. The methodology described in this paper includes the key influencing factors of real-world building energy use including weather data, occupant-driven loads, building operation and maintenance practices, and special events. Data formats to support workflows leveraging both synthetic meter data and associated metadata are proposed and discussed. Finally, example use cases of the synthetic meter data are described to illustrate potential applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

OpenStudio-Occupant-Variability-Gem v1.0

This gem contains methods to introduce occupant-related variability to extend core OpenStudio SDK. The goal of introducing the variability is to improve the assumptions related to stochastic occupant movement, occupant-related lighting and electric equipment, and thermostat set points schedules in traditional OpenStudio and EnergyPlus models.

Li, Han↗
DOE OSTI2020

OpenStudio System-level KPI Reporting Measure v1.0

This is a OpenStudio measure that calculates and reports the system-level key performance indicators (KPIs) for evaluating building energy performance at the system level. The systems are defined by the service it provides in commercial buildings, which include (1) lighting, (2) Miscellaneous Electric Loads (MELs), (3) Heating, Ventilation and Air Conditioning (HVAC), and (4) Service Water Heating (SWH).

Li, Han↗
DOE OSTI2020

OpenStudio-Variability-Gem v1.0

This gem contains methods to introduce variability to extend core OpenStudio SDK. The term "variability" refers to changes in building systems efficiency, operation, or controls, which are non-routine events.

Li, Han↗