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Sohn, Michael D.

Publications and source records attributed to Sohn, Michael D..

47 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Characterization of demand response in the commercial, industrial, and residential sectors in the United States

The goal of our study is to provide an overview of demand response (DR) technologies, including standards and end uses, in the United States and describe resource characteristics and the attributes of 14 specific DR resources in the U.S. commercial, residential, and industrial sectors. The attributes reviewed for the end uses being considered are response frequency, response time, the need for and impacts of energy pre- or recharge, the cost of enabling a resource to respond to a load-curtailment signal, and the magnitude of load curtailment in a given resource. We also describe controls and communications technologies that can enable end uses to participate in DR programs. The characterization was initially developed as a foundational work to quantify hourly availability of DR resources from the selected end uses followed by a multi-laboratory effort that quantified DR's value within the Western Interconnection.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2014

Uncertainty Estimation Improves Energy Measurement and Verification Procedures

Implementing energy conservation measures in buildings can reduce energy costs and environmental impacts, but such measures cost money to implement so intelligent investment strategies require the ability to quantify the energy savings by comparing actual energy used to how much energy would have been used in absence of the conservation measures (known as the baseline energy use). Methods exist for predicting baseline energy use, but a limitation of most statistical methods reported in the literature is inadequate quantification of the uncertainty in baseline energy use predictions. However, estimation of uncertainty is essential for weighing the risks of investing in retrofits. Most commercial buildings have, or soon will have, electricity meters capable of providing data at short time intervals. These data provide new opportunities to quantify uncertainty in baseline predictions, and to do so after shorter measurement durations than are traditionally used. In this paper, we show that uncertainty estimation provides greater measurement and verification (M&V) information and helps to overcome some of the difficulties with deciding how much data is needed to develop baseline models and to confirm energy savings. We also show that cross-validation is an effective method for computing uncertainty. In so doing, we extend a simple regression-based method of predicting energy use using short-interval meter data. We demonstrate the methods by predicting energy use in 17 real commercial buildings. We discuss the benefits of uncertainty estimates which can provide actionable decision making information for investing in energy conservation measures.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Tracking Contributions to Human Body Burden of Environmental Chemicals by Correlating Environmental Measurements with Biomarkers

The work addresses current knowledge gaps regarding causes for correlations between environmental and biomarker measurements and explores the underappreciated role of variability in disaggregating exposure attributes that contribute to biomarker levels. Our simulation-based study considers variability in environmental and food measurements, the relative contribution of various exposure sources (indoors and food), and the biological half-life of a compound, on the resulting correlations between biomarker and environmental measurements. For two hypothetical compounds whose half-lives are on the order of days for one and years for the other, we generate synthetic daily environmental concentrations and food exposures with different day-to-day and population variability as well as different amounts of home- and food-based exposure. Assuming that the total intake results only from home-based exposure and food ingestion, we estimate timedependent biomarker concentrations using a one-compartment pharmacokinetic model. Box plots of modeled R 2 values indicate that although the R 2 correlation between wipe and biological (e.g., serum) measurements is within the same range for the two compounds, the relative contribution of the home exposure to the total exposure could differ by up to 20%, thus providing the relative indication of their contribution to body burden. The novel method introduced in this paper provides insights for evaluating scenarios or experiments where sample, exposure, and compound variability must be weighed in order to interpret associations between exposure data.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Grid Integration of Aggregated Demand Response, Part 1: Load Availability Profiles and Constraints for the Western Interconnection

Demand response (DR) has the potential to improve electric grid reliability and reduce system operation costs. However, including DR in grid modeling can be difficult due to its variable and non-traditional response characteristics, compared to traditional generation. Therefore, efforts to value the participation of DR in procurement of grid services have been limited. In this report, we present methods and tools for predicting demand response availability profiles, representing their capability to participate in capacity, energy, and ancillary services. With the addition of response characteristics mimicking those of generation, the resulting profiles will help in the valuation of the participation of demand response through production cost modeling, which informs infrastructure and investment planning.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2013

How many replicate tests do I need?$-$ Variability of cookstove performance and emissions has implications for obtaining useful results

Almost half of the world’s population still cooks on biomass cookstoves of poor efficiency and primitive design, such as three stone fires (TSF). Emissions from biomass cookstoves contribute to adverse health effects and climate change. A number of “improved cookstoves” with higher energy efficiency and lower emissions have been designed and promoted across the world. During the design development, and for selection of a stove for dissemination, the stove performance and emissions are commonly evaluated, communicated and compared using the arithmetic average of replicate tests made using a standardized laboratory-based test, commonly the water boiling test (WBT). However, published literature shows different WBT results reported from different laboratories for the same stove technology. Also, there is no agreement in the literature on how many replicate tests should be performed to ensure “significance” in the reported average performance. This matter has not received attention in the rapidly growing literature on stoves, and yet is crucial for estimating and communicating the performance of a stove, and for comparing the performance between stoves. We present results of statistical analyses using data from a number of replicate tests of performance and emission of the Berkeley-Darfur Stove (BDS) and the TSF under well-controlled laboratory conditions. We observed moderate variability in the test results for the TSF and BDS when measuring several characteristics. Here we focus on two as illustrative: time-to-boil and PM2.5 (particulate matter less than or equal to 2.5 micrometers in diameter) emissions. We demonstrate that interpretation of the results comparing these stoves could be misleading if only a small number of replicates had been conducted. We then describe a practical approach, useful to both stove testers and designers, to assess the number of replicates needed to obtain useful data. Caution should be exercised in attaching high credibility to results based on only a few replicates of cookstove performance and emissions. Stove designers, testers, program implementers and decision makers should all benefit from improved awareness of the importance of adequate number of replicates required to produce practically useful test data.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2012

Computing Toxic Load for Shelter-in-Place Analysis Using Joint Urban 2003

Toxic load is a metric used to quantify acute effects from inhalation exposures. The toxic load to individuals depends on the fluctuations of chemical concentrations because the exposureresponse relationship is often nonlinear. To study the effects of concentration fluctuations on toxic load, we analyzed concentration data from the Joint Urban 2003 series of city-scale tracer gas studies. We summarized the outdoor concentrations measured by fast-response gas analyzers and computed outdoor toxic load. We then analyzed the amount of tracer gas that entered a 16- story office building and compared indoor and outdoor toxic loads. We show that the time aggregation used to compute toxic load is a source of uncertainty in hazard assessments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2012

Siting Samplers to Minimize Expected Time to Detection

We present a probabilistic approach to designing an indoor sampler network for detecting an accidental or intentional chemical or biological release, and demonstrate it for a real building. In an earlier paper, Sohn and Lorenzetti(1) developed a proof of concept algorithm that assumed samplers could return measurements only slowly (on the order of hours). This led to optimal detect to treat architectures, which maximize the probability of detecting a release. This paper develops a more general approach, and applies it to samplers that can return measurements relatively quickly (in minutes). This leads to optimal detect to warn architectures, which minimize the expected time to detection. Using a model of a real, large, commercial building, we demonstrate the approach by optimizing networks against uncertain release locations, source terms, and sampler characteristics. Finally, we speculate on rules of thumb for general sampler placement.

99 GENERAL AND MISCELLANEOUS↗