Exploring Building Energy Use Modeling

OBJECTIVE: The project objective was to analyze and test building energy use modeling software programs to find a quick and easy to use tool that can be implemented in the early stages of design. A list of programs was developed and narrowed down based on criteria important to architects in early design stages. Programs were tested and rated using a weighted criteria formula. Recommendations for capabilities and user interface of future energy modeling programs were made. This research is aimed at creating a methodology that makes it easier to analyze new energy modeling tools as they are developed in the coming years.https://pdxscholar.library.pdx.edu/research_based_design/1079/thumbnail.jp

Visualizing urban microclimate and quantifying its impact on building energy use in San Francisco

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 hourly weather data measured at 27 sites in San Francisco, aiming to provide insights into the urban microclimate and urban heat island effect in San Francisco and how they evolve during the recent decade. The 10-year weather data are used in building energy simulations to investigate its influence on energy use and electrical peak demand, which informs the city's policy making on building energy efficiency and resilience. The visualization feature is implemented in CityBES, an open web-based data and computing platform for urban building energy research

A Framework for Urban Building Energy Use Modeling

Reliable quantification of energy consumption by buildings plays a key role in development of sustainable cities. However, there are methodological uncertainties embedded in the most common urban scale energy use modeling methods and tools which affect the reliability of these tools and their applicability for decision-making purposes. This article presents a novel bottom- up data-driven framework for urban energy use modeling (UEUM) to help predict energy use more precisely through utilizing disaggregated data at building level, incorporating the actual urban spatial patterns, and testing different algorithms to propose an enhanced prediction model. This framework integrates the influential factors in the model including building characteristics; i.e., height, as an urban intensity metric, urban attributes; i.e., sprawl indices, that are captured in a multidimensional way representing compactness and connectivity of neighborhoods, and occupant characteristics. A case study on 800,000 buildings in seventy-seven neighborhoods in Chicago was used to test the framework. This framework has the potential to help better understand the existing urban energy use profiles and provides a more holistic image of urban energy use at multi-scales of building, block, neighborhood, and urban levels

Residential building energy use and HVAC system comparison study

The objective of this study was to evaluate alternative heating and cooling approaches for a non-typical residence including geothermal and radiant floor heating technology. The analysis included four main components: estimating the design heating and cooling loads of the home, developing alternative approaches for heating and cooling the residence, designing an hourly energy use and heating, ventilating, and air conditioning (HVAC) system performance simulation model for the home over a period of one year, and estimating economic factors for each alternative system. Four alternative approaches for conditioning the case study home were developed and evaluated. These alternatives include systems that utilize either a water-to-air ground-source geothermal heat pump or a liquid-propane gas furnace for the forced air conditioning and either an electric boiler, liquid propane boiler, or a water-to-water ground-source geothermal heat pump for hydronic heating. Using the design heating and cooling loads on the home, specific equipment for each alternative was selected. The hourly energy demand on the home was simulated considering conduction heat transfer through the structure, solar loads, infiltration effects, and internal gain. The HVAC system model estimates the hourly performance of each alternative system given the hourly demand on the home. In addition, the approximate monthly and annual costs associated with each system were determined. Typical Meteorological Year (TMY2) data was used to estimate hourly weather and solar conditions expected at the geographical location of the home over a one year period. The economics for each alternative approach was evaluated based on a life-cycle-cost analysis. All annual expenses and savings for each approach were estimated over the assumed life of each system. The present-value and payback-period for each system was determined and compared. It was found that the approach utilizing a ground-source geothermal heat pump and electric hydronic boiler would be the most economical

Sustainable Infrastructure and South Mountain Village: Building Energy Use

abstract: This report examines the energy infrastructure in the South Mountain Village of Phoenix AZ. The report is in support of the Rio Grande 2.0 project being implemented by the City of Phoenix in conjunction with Arizona State University. The report focuses on a small section of the village, for which we create energy demand profiles, solar generation profiles, and solar + storage generation profiles. We utilize these profiles to demonstrate the impact that neighborhood solar will have on the grid. We additionally research SRP’s deployment of smart grid technologies and SRP’s plans for the future of their power system. The report examines the benefits, and challenges of microgrid development in South Mountain Village. We undertake this study to identify strategies that increase energy efficiency, that implement resilient and redundant systems in the existing energy grid, and that provide flexibility and adaptability to the community’s energy systems. Deploying these strategies will ensure the sustained provision of energy to the community in the event of catastrophic events. We demonstrate that the installation of rooftop solar photovoltaics on residential buildings in conjunction with battery storage systems proves more than sufficient to provide power to the residents of South Mountain Village. We explore the benefits and challenges for the development of smart grid infrastructure and microgrid networks in the village. We determine that the implementation of a smart grid and a parallel microgrid improves the resiliency of the Village’s energy systems. While SRP has managed to make progressive steps forward in implementing Smart Grid technologies, they can continue this progression by developing a unified communication system that is secure through cyber security measures to allow for reliable energy service to their customers. A hybrid development of smart grid and microgrid technologies in the village that employs rooftop solar photovoltaics and battery storage will provide community members with the resilient energy infrastructure they require in a future which entails multiplied risks of catastrophic events like increased heat waves and cyber attacks

Impact of solar shading geometry on building energy use in hot humid climates with special reference to Malaysia

External solar shading devices can substantially reduce the cooling load of buildings and large energy savings can be achieved. Hence, intercepting the radiant heat wave before penetrating to the internal environment through envelope openings is the main criterion in designing solar shading. In hot and humid climate, one draw back of using shading devices is the risk to reduce daylight level thus increases in use of artificial lighting. Therefore it is important to understand the magnitude of energy consumption for cooling and lighting when shading devices are adapted in order to analyze optimum shading as energy conservation option in high-rise office buildings. In other words, little is known about the relationship between energy use and external horizontal shading device geometry. In an attempt to elucidate these complex relationships, a simple experiment of an office room is carried out using dynamic computer simulation program eQUEST- 3 (DOE 2.2). The study indicated depth of the external horizontal overhang can be manipulated to obtain an optimum energy use in high-rise buildings. The results showed that correlation between overhang depth and energy is an important aspect compared to correlation between overhang depth with building cooling loads and daylight level, especially in tropical climate conditions

Estimation of the Relationship Between Remotely Sensed Anthropogenic Heat Discharge and Building Energy Use

This paper examined the relationship between remotely sensed anthropogenic heat discharge and energy use from residential and commercial buildings across multiple scales in the city of Indianapolis, Indiana, USA. The anthropogenic heat discharge was estimated with a remote sensing-based surface energy balance model, which was parameterized using land cover, land surface temperature, albedo, and meteorological data. The building energy use was estimated using a GIS-based building energy simulation model in conjunction with Department of Energy/Energy Information Administration survey data, the Assessor's parcel data, GIS floor areas data, and remote sensing-derived building height data. The spatial patterns of anthropogenic heat discharge and energy use from residential and commercial buildings were analyzed and compared. Quantitative relationships were evaluated across multiple scales from pixel aggregation to census block. The results indicate that anthropogenic heat discharge is consistent with building energy use in terms of the spatial pattern, and that building energy use accounts for a significant fraction of anthropogenic heat discharge. The research also implies that the relationship between anthropogenic heat discharge and building energy use is scale-dependent. The simultaneous estimation of anthropogenic heat discharge and building energy use via two independent methods improves the understanding of the surface energy balance in an urban landscape. The anthropogenic heat discharge derived from remote sensing and meteorological data may be able to serve as a spatial distribution proxy for spatially-resolved building energy use, and even for fossil-fuel CO2 emissions if additional factors are considered

Analysing building energy use using sub metering and external weather data

The Intergovernmental Panel on Climate Change and the McKinsey Greenhouse Gas abatement studies have highlighted reduction of building energy consumption as a primary cost-effective element in the abatement of Global Warming. Nevertheless, the energy investigation in most of our existing building stock remains at a novice level at best. Building sub-metering, by which we mean any secondary, hourly, metering (after the main) of various circuits, provides substantial information on when and where energy is used in specific buildings. Furthermore, combining this information with external weather data provides information beyond basic metering results. This paper discusses three case studies and explains how sub-metering, augmented by external solar and temperature data, benefits energy management and identified problems. It explains how different methods of analysing energy usage allowed: justifiable sizing of a solar photovoltaic system, with a calculated Cooling Degree Unit, identified the absence of savings from a proprietary chiller controller, and the energy variation due to user schedules and external conditions indicated anomalies in energy use. The advantages of wireless access are noted. Extracting information in graphical formats suggests better strategies to understand and control energy use