7 Search Results

This work presents a mechanistic modeling approach for simulating methane emissions from triethylene glycol (TEG) dehydrators used in oil & gas (O&G) operations. The model was developed as a modular component of the Mechanistic Air Emissions Simulator (MAES) tool, incorporating species-specific absorption and emission dynamics through two-level, second-order polynomial regression (PR) models trained on ProMax simulation data: (1) species-level regression models that track the transfer rates of individual gas species within the dehydrator unit streams, and (2) outlet flow stream regression models that predict the fraction of inlet gas distributed among the outlet streams of the dehydrator unit. These behaviorsmore » were characterized over a range of glycol circulation ratios, wet gas pressures, and temperatures. The model was validated using root mean square error (RMSE) analysis. The species-level PR achieved low root mean square error (RMSE) values (<0.03) for light hydrocarbon species across all dehydrator components, ranging from 0.0009 for methane to 0.029 for normal pentane. Similarly, the outlet-level PR yielded RMSE values below 0.002 for the dry gas fraction, 0.001 for the flash tank fraction, and 0.002 for the still vent fraction, demonstrating strong agreement between predicted and reference ProMax values. When deployed at field facilities, the model significantly improved MAES-simulated dehydrator emissions, revealing that gas-assisted glycol pump emissions are the dominant contributors to both dehydrator-level and site-level methane emissions under uncontrolled conditions. Further analysis of the 154 dehydrator units reported by operators under the AMI 2024 project showed that 54 units (31%) used gas-driven glycol pumps, of which 6 units (11%) operated with uncontrolled flash tanks, and 22 units (40.7%) were identified as potentially oversized. Of the six dehydrator units with uncontrolled gas-assisted pumps, pump emissions accounted for 90.25% of total dehydrator emissions and 63.10% of total site-level emissions. These findings highlight substantial opportunities for emissions mitigation through equipment upgrades.« less

This article presents an experimental validation of a co-simulation architecture for simultaneously modeling whole-building energy performance and detailed building electrical distribution system performance. The co-simulation architecture consists of a whole-building energy model (EnergyPlus®) embedded within a Modelica-based building electrical distribution system library called the Building Electrical Efficiency Analysis Model (BEEAM) using the Functional Mock-up Interface standard. We validate the model using experimental data collected at a full-scale test cell within Lawrence Berkeley National Laboratory’s FLEXLAB® facility. In conclusion, we show that the co-simulation model accurately predicts the electrical, mechanical, and thermal performance of the test cell for typical loads withmore » both an AC and a DC electrical distribution topology.« less

Wave energy is a vast and largely untapped resource with the potential to contribute significantly to global energy production. A new wave energy technology has been developed by an Australian company, Wave Swell Energy Ltd., consisting of a unique unidirectional axial turbine version of the well-established oscillating water column (OWC) concept. A full-scale prototype of the technology, the UniWave200, was deployed for grid-connected testing near the coastline of King Island, Tasmania, from 2021 to 2022. Data collected during the pilot project were analyzed by the US Department of Energy's Pacific Northwest National Laboratory (PNNL). The results of this analysis indicatemore » the full-process wave-to-grid energy conversion efficiency, based on the combined capture width ratio (CWR) and power take-off (PTO) efficiency, to be on the order of 45% for significant wave heights above 1 m.« less

Methane is a powerful greenhouse gas with a 25 times higher 100-year warming potential than carbon dioxide and is a target for mitigation to achieve climate goals. To control and curb methane emissions, estimates are required from the sources and sectors which are typically generated using bottom-up methods. However, recent studies have shown that national and international bottom-up approaches can significantly underestimate emissions. In this study, we present three bottom-up approaches used to estimate methane emissions from all emission sectors in the Denver-Julesburg basin, CO, USA. Our data show emissions generated from all three methods are lower than historic measurements.more » A Tier 1/2 approach using IPCC emission factors estimated 2022 methane emissions of 358 Gg (0.8% of produced methane lost by the energy sector), while a Tier 3 EPA-based approach estimated emissions of 269 Gg (0.2%). Using emission factors informed by contemporary and region-specific measurement studies, emissions of 212 Gg (0.2%) were calculated. The largest difference in emissions estimates were a result of using the Mechanistic Air Emissions Simulator (MAES) for the production and transport of oil and gas in the DJ basin. The MAES accounts for changes to regulatory practice in the DJ basin, which include comprehensive requirements for compressors, pneumatics, equipment leaks, and fugitive emissions, which were implemented to reduce emissions starting in 2014. The measurement revealed that normalized gas loss is predicted to have been reduced by a factor of 20 when compared to 10-year-old normalization loss measurements and a factor of 10 less than a nearby oil and production area (Delaware basin, TX); however, we suggest that more measurements should be made to ensure that the long-tail emission distribution has been captured by the modeling. This study suggests that regulations implemented by the Colorado Department of Public Health and Environment could have reduced emissions by a factor of 20, but contemporary regional measurements should be made to ensure these bottom-up calculations are realistic.« less

Recently, there has been considerable research interest in the potential for DC distribution systems in buildings instead of the traditional AC distribution systems. Due to the need for performing power conversions between DC and AC electricity, DC distribution may provide electrical efficiency advantages in some systems. To support comparative evaluations of AC-only, DC-only, and hybrid AC/DC distribution systems in buildings, a new modeling toolkit called the Building Electrical Efficiency Analysis Model (BEEAM) was developed and is described in this paper. To account for harmonics in currents or voltages arising from nonlinear devices, the toolkit implements harmonic power flow, along withmore » nonlinear device behavioral descriptions derived from empirical measurements. This paper describes the framework, network equations, device representations, and an implementation of the toolkit in an open source software package, including a component library and graphical interface for creating circuits. Simulations of electrical behavior and device and system efficiencies using the toolkit are compared with experimental measurements of a small office environment in a variety of operating and load configurations. A detailed analysis of uncertainty estimation is also provided. Key findings were that a comparison of predicted versus measured efficiencies and power losses in the validation testbed using the initial toolkit implementation predicted device- and system-level efficiencies with reasonably good accuracy under both balanced and unbalanced AC scenarios. An uncertainty analysis also revealed that the maximum estimated error for system efficiency across all scenarios was 3%, and measured and modeled system efficiency agreed within the experimental uncertainty in approximately half of the scenarios. Based on the correspondence between simulation and measurement, the toolkit is proposed by the authors as a potentially useful tool for comparing efficiency in AC, DC, and hybrid AC/DC distribution systems in buildings.« less

Advances in power electronics and their use in Miscellaneous Electric Loads (MELs) in buildings have resulted in increased interest in using low-voltage direct current (DC) power distribution as a replacement for the standard alternating current (AC) power distribution in buildings. Both systems require an endpoint converter to convert the distribution system voltage to the MELs voltage requirements. This study focused on the efficiency of these endpoint converters by testing pairs of AC/DC and DC/DC power converters powering the same load profile. In contrast to prior studies, which estimated losses based on data sheet efficiency and rated loads, in this study,more » we used part load data derived from real-world time-series load measurements of MELs and experimentally characterized efficiency curves for all converters. The measurements performed for this study showed no systematic efficiency advantage for commercially available DC/DC endpoint converters relative to comparable, commercially available AC/DC endpoint converters. For the eight appliances analyzed with the pair of converters tested, in 50%, the weighted energy efficiency of the DC/DC converter was higher, while, for the other 50%, the AC/DC converter was. Additionally, the measurements indicated that the common assumption of using either data sheet efficiency values or efficiency at full load may result in substantial mis-estimates of the system efficiency.« less

An increase of non-linear loads, primarily from power electronics, has substantially increased current harmonics in commercial buildings, which contributes to decreased transformer efficiency / lifespan and poor power quality. This study uses recorded power consumption data from common miscellaneous electric loads (MELs) seen in offices, combined with detailed characterizations of example MELs, to simulate harmonic cancellation within building circuits. Typically, harmonic cancellation studies assume that AC converters operate across their rated power range. However, this study finds that common MELs operate below 40% of rated power the majority of the time when not quiescent; 89% of sampled devices never operatedmore » above 60% of rated power. Simulations using these more realistic power levels indicate current-harmonic cancellation (3rd to 13th harmonic) is significantly lower than that predicted when using full-range power assumptions, resulting in minor errors for low-order harmonics and larger errors for higher order harmonics. Furthermore, increased MELs load diversity increases harmonic cancellation, but insufficiently to eliminate errors. In contrast, blending lighting loads with MELs on the secondaries of distribution transformers improves harmonic cancellation to near those predicted by traditional methods. These results indicate that realistic power levels, as well as better characterization of harmonics from typical MELs, should be used to estimate harmonic cancellation.« less