Xuan Luo

• Master of Science
• Engineer at Lawrence Berkeley National Laboratory

We present unprecedented datasets of current and future projected weather files for building simulations in 15 major cities distributed across 10 climate zones worldwide. The datasets include ambient air temperature, relative humidity, atmospheric pressure, direct and diffuse solar irradiance, and wind speed at hourly resolution, which are essentia...

We present unprecedented datasets of current and future projected weather files for building simulations in 15 major cities distributed across 10 climate zones worldwide. The datasets include ambient air temperature, relative humidity, atmospheric pressure, direct and diffuse solar irradiance, and wind speed at hourly resolution, which are essentia...

Understanding and quantifying the interactions between urban microclimate and urban buildings is essential to improve urban environment and building performance. Previous studies used tool-or-application-specific data exchange mechanisms which cannot be generalized and adopted for other tools or applications. In this paper, we introduce a new flexi...

Understanding and quantifying the interactions between urban microclimate and urban buildings is essential to improve the urban environment and building performance, especially during heatwaves. Most previous studies used tool or application specific data exchange mechanisms that cannot be generalized for other tools or applications. In this paper,...

Cities consume 2/3 of global energy and consequently release a large amount of anthropogenic heat into urban environments, which are already vulnerable to extreme heat risk due to the compounding effects of urban heat island and the warming climate. In this study, we use detailed process-based building energy modeling of over 1.1 million buildings...

Urban microclimate exerts an increasing influence on urban buildings, energy, and sustainability. This study uses 10-year measured hourly weather data at 27 sites in San Francisco, California, to (1) analyze and visualize the urban microclimate patterns and urban heat island effect; (2) simulate annual energy use and peak electricity demand of typi...

More frequent and longer duration heat waves have been observed worldwide and are recognized as a serious threat to human health and the stability of electrical grids. Past studies have identified a positive feedback between heat waves and urban heat island effects. Anthropogenic heat emissions from buildings have a crucial impact on the urban envi...

Data centers in the United States consume about two percent of the nation’s electricity. Because heat gains from IT equipment drive cooling demand, data centers offer unique opportunities for energy savings. However, no prototype energy model for data centers is available in the suite of existing U.S. Department of Energy’s Commercial Prototype Bui...

For building energy simulation at an urban-scale, solar shading calculations can be significantly slow when a large number of shading surfaces are considered in the solar shading calculations, due to the computational complexity of the geometry calculations. We developed a new algorithm using the ray-tracing technique to pre-calculate the sunlit fr...

Heat emissions from buildings is a significant source of anthropogenic heat influencing the urban microclimate; however, they are usually oversimplified in urban climate and microclimate modeling. This study developed a bottom-up physics-based approach to calculate heat emissions from buildings to the ambient air and implemented the approach in Ene...

Thermal interactions through longwave radiation exchange between buildings, especially in a dense urban environment, can strongly influence a building’s energy use and environmental impact. However, these interactions are either neglected or oversimplified in urban building energy modeling. We developed a new feature in EnergyPlus to explicitly con...

Fueled by big data, powerful and affordable computing resources, and advanced algorithms, machine learning has been explored and applied to buildings research for the past decades and has demonstrated its potential to enhance building performance. This study systematically surveyed how machine learning has been applied at different stages of buildi...

Weather data at nearby airports are usually used in building energy simulation to estimate energy use in buildings or evaluate building design or retrofit options. However, due to urbanization and geography characteristics, local weather conditions can differ significantly from those at airports. This study presents the visualization of 10-year hou...

Buildings in cities consume up to 70% of all primary energy. To achieve cities’ energy and climate goals, it is necessary to reduce energy use and associated greenhouse gas emissions in buildings through energy conservation and efficiency improvements. Computational tools empowered with rich urban datasets can model performance of buildings at the...

Heat emissions from buildings to ambient air are a crucial component influencing the urban microclimate. However, existing literature has very limited coverage of such research. This study developed a bottom-up approach to calculating heat emissions from buildings to the ambient air and implemented it in EnergyPlus. Simulation results of heat emiss...

Understanding the thermal interactions between buildings and environment is one key factor in urban modeling and simulation, as they can strongly influence buildings' energy use, environmental impact and occupants' thermal comfort. We added a new feature to EnergyPlus in version 8.8.0, modifying the heat balance of the building's exterior surfaces...

Urban building energy modeling (UBEM) is becoming a proven tool to support energy efficiency programs for buildings in cities. Development of a city-scale dataset of the existing building stock is a critical step of UBEM to automatically generate energy models of urban buildings and simulate their performance. This study introduces data needs, data...

This study presents a novel computing technique for data exchange and coupling between a high-resolution weather simulation model and a building energy model, with a goal of evaluating the impact of urban weather boundary conditions on energy performance of urban buildings. The Weather Research and Forecasting (WRF) model is initialized with the op...

Buildings in San Francisco consumed 52% of total primary energy. Improving building energy efficiency is one of the key strategies cities are adopting towards their energy and climate goals. Urban building energy models (UBEM) can support city managers to evaluate and prioritize energy conservation measures for investment and to design effective in...

Many buildings already exist in an urban context, in close proximity to many other buildings of similar or larger size and in micro-climates (e.g., urban canyons and heat islands) created by this environment. As the world's population increasingly flows into cities, many more buildings will fit this description. Cities are collecting new data on ba...

Occupancy has significant impacts on building performance. However, in current building performance simulation programs, occupancy inputs are static and lack diversity, contributing to discrepancies between the simulated and actual building performance. This paper presents an Occupancy Simulator that simulates the stochastic behavior of occupant pr...

Weather has significant impacts on the thermal environment and energy use in buildings. Thus, accurate weather data are crucial for building performance evaluations. Traditionally, typical year data inputs are used to represent long-term weather data. However, there is no guarantee that a single year represents the changing climate well. In this st...

In current building performance simulation programs, occupant presence and interactions with building systems are over-simplified and less indicative of real world scenarios, contributing to the discrepancies between simulated and actual energy use in buildings. Simulation results are normally presented using various types of charts. However, using...

Occupancy is an important factor driving building performance. Static and homogeneous occupant schedules, commonly used in building performance simulation, contribute to issues such as performance gaps between simulated and measured energy use in buildings. Stochastic occupancy models have been recently developed and applied to better represent spa...

Traditionally, in building energy modeling (BEM) programs, occupancy inputs are deterministic and less indicative of real world scenarios, contributing to discrepancies between simulated and actual energy use in buildings. This paper presents an agent-based occupancy simulator, which models each occupant as an agent with specified movement events a...

The Occupancy Simulator is an App simulating occupant movement in a building using the Markov-chain model. The App takes high level input on occupants, spaces and events, then simulates occupant movement and generates occupant schedules for each space. The generated schedules capture diversity and stochastic nature of occupant activities. These sch...