Using BEopt (EnergyPlus) with energy audits and surveys to predict actual residential energy usage

Rhodes, Joshua D.; Gorman, William; Upshaw, Charles R.; Webber, Michael E.

doi:10.1016/j.enbuild.2014.10.076

Cited by 49 publications

(19 citation statements)

References 36 publications

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“…Results of this paper show that the average actual energy use varied by 5-7% of the predicted energy use, but at individual buildings level the deviation could be as high as 60% higher or lower. Large variations were also found in previous studies [7][8][9][10][11][13][14][15][16][17][18][19], which shows that it is difficult to choose an appropriate safety factor in energy use predictions. However, more data on actual energy use would help deduce realistic input data to be used in energy simulation models.…”

Section: Discussionsupporting

confidence: 58%

“…Branco et al [9] reported that actual energy use of low-energy multi-family buildings in Switzerland was 50% higher than predicted. Rhodes et al [10] found that the actual energy of individual single-family houses in Austin, USA could vary by 28% of the predicted energy use. A German study reported that the measured energy use was on average 30% lower than the predicted use [11].…”

Section: Objectivesmentioning

confidence: 99%

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Energy use and CO2 emission of new residential buildings built under specific requirements – The case of Växjö municipality, Sweden

Mahapatra

2015

Applied Energy

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Section: Discussionsupporting

confidence: 58%

Section: Objectivesmentioning

confidence: 99%

Energy use and CO2 emission of new residential buildings built under specific requirements – The case of Växjö municipality, Sweden

Mahapatra

2015

Applied Energy

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“…The output taken from the model is the total building cooling load (the amount of thermal energy that is removed from the space) for every hour time interval, which is then fed into the air conditioning and TES system model. Benchmarking BEopt with measured home electricity data has shown that while individual comparisons of energy use can differ significantly (both higher and lower), on average the modeling is reasonably accurate (within approximately 3%) at estimating electricity use [53].…”

Section: Modeling the House Thermal Loadmentioning

confidence: 97%

Modeling electric load and water consumption impacts from an integrated thermal energy and rainwater storage system for residential buildings in Texas

2017

Self Cite

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h i g h l i g h t sHydronic integrated rainwater thermal storage (ITHERST) system concept presented. ITHERST system modeled to assess peak electric load shifting and water savings. Case study shows 75% peak load reduction and 9% increase in energy consumption. Potable rainwater collection could provide $50-90% of water used for case study. a b s t r a c tThe United States' built environment is a significant direct and indirect consumer of energy and water. In Texas, and other parts of the Southern and Western US, air conditioning loads, particularly from residential buildings, contribute significantly to the peak electricity load on the grid, straining transmission. In parallel, water resources in these regions are strained by growing populations and shrinking supplies. One potential method to address both of these issues is to develop integrated thermal energy and auxiliary water (e.g. rainwater, greywater, etc.) storage and management systems that reduce peak load and freshwater consumption. This analysis focuses on a proposed integrated thermal energy and rainwater storage (ITHERST) system that is incorporated into a residential air-source chiller/heat pump with hydronic distribution. This paper describes a step-wise hourly thermodynamic model of the thermal storage system to assess on-peak performance, and a daily volume-balance model of auxiliary water collection and consumption to assess water savings potential. While the model is generalized, this analysis uses a case study of a single family home in Austin, Texas to illustrate its capabilities. The results indicate this ITHERST system could reduce on-peak air conditioning electric power demand by over 75%, with increased overall electric energy consumption of approximately 7-9%, when optimally sized. Additionally, the modeled rainwater collection reduced municipal water consumption by approximately 53-89%, depending on the system size.

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“…Simulations of building energy use can give insights into how energy efficiency retrofits and operational changes can influence a building's total and temporal energy use [20]. Rhodes et al [21] determined model accuracy by considering 54 homes in Austin, TX, that are part of a smart grid demonstration project. Lee et al [22] investigated retrofit tools both in the public domain as well as in the private sector to better understand the diverse approaches currently in use to evaluate retrofit methods, measures, interoperability, target audiences, as well as interface types and accessibility.…”

Section: Building Energy Retrofit In Hot-humid Climatementioning

confidence: 99%

A Multi-Facet Retrofit Approach to Improve Energy Efficiency of Existing Class of Single-Family Residential Buildings in Hot-Humid Climate Zones

2020

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Targeting existing residential buildings for retrofit improvement presents significant prospects for global reduction of energy-usage and carbon footprints. Energy consumption of the existing single-family building in the hot-humid climate zone needs to be targeted for improvement due to their potential energy-savings and sizeable market share. This paper proposes and evaluates energy savings and cost-effectiveness of a whole building retrofit package for single-family residential buildings built between 1950 and 1970. The study outlined a survey conducted using the clustering data mining technique on Florida Single-Family Residential (SFR) homes to determine the essence of the building envelope, patterns of construction, and Heating, Ventilation, and Air-Conditioning (HVAC) systems. The evaluation of the energy efficiency measures (EEMs) effectiveness is performed utilizing Autodesk Revit and a Six-Step modeled framework. This framework consists of baseline model development, validation of the model with an actual case study building, identification of potential EMMs, evaluation of EEMs individually and incorporating the selected EMMs into retrofit package and maximizing the energy-saving and cost-effectiveness of the proposed retrofit package. The study develops proposed retrofit improvement package detailing replacement & improvement EEMs, implementation cost, annual energy savings (kWh), cost-saving ($), and payback period (years) for each individual EEM as well as the combined/total energy improvement package. The paper further explored the usage of solar photovoltaics (PV) energy generation options to offset the remaining energy-use after the implementation of the proposed retrofit package.

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Using BEopt (EnergyPlus) with energy audits and surveys to predict actual residential energy usage

Cited by 49 publications

References 36 publications

Energy use and CO2 emission of new residential buildings built under specific requirements – The case of Växjö municipality, Sweden

Energy use and CO2 emission of new residential buildings built under specific requirements – The case of Växjö municipality, Sweden

Modeling electric load and water consumption impacts from an integrated thermal energy and rainwater storage system for residential buildings in Texas

A Multi-Facet Retrofit Approach to Improve Energy Efficiency of Existing Class of Single-Family Residential Buildings in Hot-Humid Climate Zones

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