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Taylor, Zachary T.

Publications and source records attributed to Taylor, Zachary T..

At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

National Cost-Effectiveness of the Residential Provisions of the 2018 IECC

As part of the U.S. Department of Energy Building Energy Codes Program's support for the development and implementation of model building energy codes and standards for new residential buildings, DOE analyzes each new edition of the International Energy Conservation Code to assess its cost effectiveness relative to the prior edition. This report estimates the incremental cost to comply with the 2018 IECC relative to the 2015 IECC, the associated energy savings, and the life-cycle cost savings.

2018 iecc↗
DOE OSTI2019

Assessing overall building energy performance of a large population of residential single-family homes using limited field data

The U.S. Department of Energy (DOE), through the Building Energy Codes Program (BECP), supports building energy code development and implementation processes to achieve the maximum practicable, cost-effective improvements in energy efficiency while providing safe, healthy buildings for occupants. Currently, there is a lack of statistically representative data that shows how energy codes are implemented in the field and the energy savings opportunities that exist. To address this gap, DOE initiated a research study targeted at new residential single-family homes in 8 states starting in the fall of 2014. The study comprises of a baseline phase to determine current levels of compliance with the key energy provisions of the residential building energy code, identify issues, and calculate potential energy savings from improved compliance; a second phase implementing education, training and outreach activities designed to increase targeted code compliance; and a post-study phase to measure the impact of the training and outreach activities compared to the baseline phase. Initial analyses determined the code requirements with the largest energy impact and the minimum number of observations required to detect statistically significant differences in energy use. Data was collected in the field during a single site visit to avoid bias from repeat visits. However, the single site visit principle prevented energy simulation of individual homes due to the lack of all required model inputs. To address this, energy simulation was conducted using Pacific Northwest National Laboratory’s prototype building models and employing bootstrap random sampling on the data collected from all homes visited. The modeled energy consumption using the observed field data was evaluated relative to that associated with the minimum code requirements and potential savings associated with improved compliance of select items were assessed. This paper discusses the methodology developed for this field study, and presents the results and findings from the baseline phase.

Xie, YuLong↗
DOE OSTI2019

Preliminary Energy Costs and Savings Estimates: 2018 IECC Residential Requirements

This report provides preliminary estimates of the incremental costs and savings associated with the residential provisions of the 2018 International Energy Conservation Code (IECC). The analysis is provided to the U.S. Department of Energy (DOE) to help quantify the costs and savings impacts of the latest published edition of the IECC, the 2018 IECC. The incremental cost of building to the 2018 IECC, relative to the 2015 IECC, ranges from $\$398$ to $\$1,071$ depending on the climate zone, and payback periods range from 0 (immediate) to 1.8 years, depending on the climate zone.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2018

Residential Heat Recovery Ventilation

Heat recovery ventilators (HRVs) save energy by recovering heat that would otherwise be exhausted as part of energy code-mandated mechanical ventilation systems. Residential HRVs can be life cycle cost effective depending on equipment/installation costs and the severity of the climate. This brief evaluates HRV cost effectiveness in the context of building energy codes to identify the climate zones in which a code might reasonably require residential HRVs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Residential Slab Component Calculations

Modern residential building energy codes provide a component tradeoff mechanism by which builders can trade reductions in the efficiency of some building components in trade for corresponding improvement in other components. One common tradeoff approach is based on maintaining a building "UA value," which represents the building envelope's overall thermal conductance. The building UA is the sum of individual component UA values, each of which is calculated as the product of the component's U-factor and area. Current codes, however, provide little guidance on including slab-on-grade components in the overall UA calculation. This brief provides information on calculating effective slab UA values and provides recommended text for building codes.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

The Building ENergy Demand (BEND) Model: A Comprehensive Composite Building Energy Modeling Framework

The Building ENergy Demand (BEND) model was developed at Pacific Northwest National Laboratory (PNNL) to simulate climate-dependent hourly building energy demand with the ability to disaggregate down to or aggregate up to any geographic area of interest, including counties, states, electric utility service territories, and census regions. The BEND modeling framework is designed to study the effects of climate change, economics, technology advancement, and various mitigation policies on aggregate building energy demand. To make the process computationally feasible, BEND reduces granularity in building characteristics and weather forcing while maintaining enough detail to minimize systematic differences (biases) between BEND results and data from the Energy Information Administration (EIA). Based on the Commercial Building Energy Consumption Survey (CBECS) and Residential Energy Consumption Survey (RECS) databases, BEND establishes a set of representative buildings with predefined sets of building types, sizes, and vintages. These representative buildings are defined for each of the four U.S. census regions and the five climate zones used by the EIA for building surveys (hereafter “EIA climate zones”). BEND’s representative buildings are based on a statistical analysis of the CBECS and RECS databases that infers detailed parameters such as construction type, thermal properties, internal loads, equipment and mechanical systems, and operation schedules from the high-level descriptors in those databases (building type, vintage, size, and location). The representative buildings are simplified and consolidated into a set of prototype buildings for the purpose of simulating building energy demand. Combining the prototype buildings with weather files from selected locations and years, BEND creates a set of simulation-ready building models to be run using the EnergyPlus simulation engine (EnergyPlus). The base spatial unit of each BEND simulation is a subregion that is the intersection of an International Energy Conservation Code climate zone, a census region, and an EIA climate zone; analysis for each spatial unit is influenced by the weather file BEND selects to represent the climate-similar area. The major simulation outputs of interest to BEND are hourly energy consumption values for each simulated year, possibly for multiple fuel types. Based on building-stock weights derived from the CBECS/RECS data, the hourly output streams are aggregated to a single, 8760-hour load profile for each of the major building categories—residential and commercial—with the possibility of segregating by fuel types. To correct for biases inherent in the use of a limited suite of representative buildings, BEND is calibrated against observational targets of total annual building energy consumption and hourly load profiles (including peak demand) obtained for the decision-relevant geographic scales of interest (e.g., total electric load data for individual balancing authorities available from EIA). Based on available data such as population distribution, BEND is able to aggregate both up and down scales, allowing the study of building energy demand over a range of spatial scales (e.g., states or counties within the Western Electricity Coordinating Council, Eastern Interconnection, or the entire U.S.) and/or subsets of building types (e.g., office buildings with particular size ranges).

24 POWER TRANSMISSION AND DISTRIBUTION↗