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This article answers four questions posed by Facility Executive Magazine regarding the new 2016 edition of ASHRAE Standard 90.1. The discussion centers on new lighting power limits, lighting controls, and the new simulation based performance path in the standard.
Insulating glass unit (IGU) degradation has been studied extensively. However, there is limited understanding of how present durability evaluation standards relate to product lifetime. Furthermore, there is debate on how to quantify performance of installed windows over time to better understand degradation processes. More knowledge on these topics is required to link durability evaluation to product lifetime projections based on energy performance. Energy models provide helpful estimations of total annual building energy consumption. However, most models are based on “as installed” performance of envelope components and fail to account for performance degradation. This can lead to an underestimation of building lifetime energy consumption. A better understanding of the relationship between durability and energy performance can inform integration of degradation dynamics into energy modeling software. This will improve lifetime building energy consumption estimations as well as inform appropriate retrofit strategies and timing. This paper reviews current durability literature, various standards for window performance ratings and weathering methods, existing in situ IGU energy performance measurement techniques, and whole-building energy effects. The challenges and disparities among various studies are analyzed and discussed. The authors hope that further work in this area will lead to the development of improved in situ test methods to assess IGU degradation in the field and link this knowledge to improved energy performance modeling approaches.
Different data pipelines and statistical methods are applied to photovoltaic (PV) performance datasets to quantify the performance loss rate (PLR). Since the real values of PLR are unknown, a variety of unvalidated values are reported. As such, the PV industry commonly assumes PLR based on statistically extracted ranges from the literature. However, the accuracy and uncertainty of PLR depend on several parameters including seasonality, local climatic conditions, and the response of a particular PV technology. In addition, the specific data pipeline and statistical method used affect the accuracy and uncertainty. To provide insights, a framework of (≈200 million) synthetic simulations of PV performance datasets using data from different climates is developed. Time series with known PLR and data quality are synthesized, and large parametric studies are conducted to examine the accuracy and uncertainty of different statistical approaches over the contiguous US, with an emphasis on the publicly available and “standardized” library, RdTools . In the results, it is confirmed that PLRs from RdTools are unbiased on average, but the accuracy and uncertainty of individual PLR estimates vary with climate zone, data quality, PV technology, and choice of analysis workflow. Best practices and improvement recommendations based on the findings of this study are provided.
One of the most important aspects that need to be addressed to increase solar energy penetration is the power ramp-rate control. In weak grids such as the one found in Puerto Rico, it is important to smooth power fluctuations caused by the intermittence of passing clouds. In this work, a novel power ramp-rate control strategy is proposed. Additionally, a comparison with some of the most common power ramp-rate control methods is performed using a proposed model and real solar radiation data from the Coto Laurel photovoltaic power plant located in Ponce, Puerto Rico. The proposed model was validated using one-year real data from Coto Laurel. The power ramp-rate control methods were compared in real-time simulations using the OP5700 from Opal-RT Technologies considering power ramp rate fluctuations, power ramp-rate violations, fluctuations in the state-of-charge, among other indicators. Moreover, the proposed power ramp-rate control strategy, called predictive dynamic smoothing was explained and compared. Results indicate that the predictive dynamic smoothing produced a considerably reduced Levelized Cost of Storage compared to other power ramp-rate control methods and provided a higher lifetime expectancy for lithium batteries.
In this work we benchmark the performance of various methods for obtaining pressure-dependent phenomenological rate coefficients against direct numerical simulations and propose a new method called simulation least-squares.
The accurate quantification of the performance loss rate of photovoltaic systems is critical for project economics. Following the current research activities in the photovoltaic performance and reliability field, this work presents a comparative assessment between common change point methods for performance loss rate estimation of fielded photovoltaic installations. An extensive testing campaign was thus performed to evaluate time series analysis approaches for performance loss rate evaluation of photovoltaic systems. Historical electrical data from eleven photovoltaic systems installed in Nicosia, Cyprus, and the locations’ meteorological measurements over a period of 8 years were used for this investigation. The application of change point detection algorithms on the constructed monthly photovoltaic performance ratio series revealed that the obtained trend might not always be linear. Specifically, thin film photovoltaic systems showed nonlinear behavior, while nonlinearities were also detected for some crystalline silicon photovoltaic systems. When applying several change point techniques, different numbers and locations of changes were detected, resulting in different performance loss rate values (varying by up to 0.85%/year even for the same number of change points). The results highlighted the importance of the application of nonlinear techniques and the need to extract a robust nonlinear model for detecting significant changes in time series data and estimating accurately the performance loss rate of photovoltaic installations.
Objectives/Scope: StimuFrac (US Patents 9,873,828 B2 and 9,447,315 B2), a CO2-reactive polymer aqueous solution [polyallylamine (PAA) 1wt% in water] combined with CO2, can be used as a less water-intensive fracturing fluid for enhanced geothermal systems (EGS). Our previous results show that in hot dry rock (HDR), PAA/CO2 fracturing fluids outperformed other fluids such as water, CO2, and CO2/water in generating large fractures with less fluid consumed. The objective of this work is to study the effect of initial water saturation of rock on the performance of StimuFrac fluid in ½ foot cubic rock samples and under representative EGS pressure/temperature conditions using cyclic and constant flow rate injection strategies. The fracturing results are compared with results using different fracturing fluids in terms of controlling fracture propagation rates, fracture hydraulic conductivity, breakdown pressures and volumes of fluids required. Methods/Procedures/Process: In all tests, water was initially injected into the rock to increase the water saturation before the fracturing processes to simulate actual geothermal reservoir conditions. For the cyclic injection, one complete cycle consisted of (1) a PAA slug (or water slug) injection followed by (2) CO2 injection to initiate the fracture. In the second step of the first cycle, the pressure of CO2 is increased until a maximum pressure is reached (fracture is initiated at this moment), and then the injection of CO2 is allowed for another 30 seconds to propagate the fracture. Then, the two-step cycle of PAA followed by CO2 injection (up to 2-4 mL/min) was continued. For the constant flow rate injection strategies, the initial water saturation was increased by injecting water at 1000 psi and 200°C for three days. After that, an initial slug of water, CO2, or PAA was injected and then fracturing was initiated and propagated by injecting CO2 at a constant flow rate. Applications/Significance/Novelty: The results of this study suggest that water saturation, especially near the wellbore region, will significantly affect the fracturing fluid transmission into the rock porous media by changing the relative permeability of CO2 or water, thus affecting the fracture initiation and propagation. In this study, fracturing with cyclic injection or constant flow rate injection methods were performed using three different kinds of fluids systems. These fluids are water, CO2, or CO2 with PAA. Splitting the rock samples in half after fracturing reveals that the fracture propagation is significantly limited under these high water saturated conditions compared to dry initial conditions: The fractures propagate less than 1/3 length of the distance from the wellbore to rock surface, and in some cases no fracture is generated. This may be caused by the fact that leak-off is dominating the fracturing process and the injected fluid flow rate is not high enough to overcome the leak-off even under high flow rate injection conditions. Additionally, CO2 could be leaking off into the wellbore annulus and this may be making it more difficult to generate pressure gradients away from the near-wellbore region.
Abstract The IEA PVPS Task 13 group, experts who focus on photovoltaic performance, operation, and reliability from several leading R&D centers, universities, and industrial companies, is developing a framework for the calculation of performance loss rates of a large number of commercial and research photovoltaic (PV) power plants and their related weather data coming across various climatic zones. The general steps to calculate the performance loss rate are (i) input data cleaning and grading; (ii) data filtering; (iii) performance metric selection, corrections, and aggregation; and finally, (iv) application of a statistical modeling method to determine the performance loss rate value. In this study, several high‐quality power and irradiance datasets have been shared, and the participants of the study were asked to calculate the performance loss rate of each individual system using their preferred methodologies. The data are used for benchmarking activities and to define capabilities and uncertainties of all the various methods. The combination of data filtering, metrics (performance ratio or power based), and statistical modeling methods are benchmarked in terms of (i) their deviation from the average value and (ii) their uncertainty, standard error, and confidence intervals. It was observed that careful data filtering is an essential foundation for reliable performance loss rate calculations. Furthermore, the selection of the calculation steps filter/metric/statistical method is highly dependent on one another, and the steps should not be assessed individually.
Highlights: • Li{sub 2}SiO{sub 3}-modified LiNi{sub 0.5}Mn{sub 1.5}O{sub 4} with well-defined octahedral morphology have been controllably obtained. • The combination of the modification of fast ions conductor and solid state method will be an optional method. • The cyclic performance and rate capability of LiNi{sub 0.5}Mn{sub 1.5}O{sub 4}-based materials have been significantly improved. - Abstract: A simple solid state method was utilized to synthesize excellent spinel Li{sub 2}SiO{sub 3}-modified LiNi{sub 0.5}Mn{sub 1.5}O{sub 4} cathodes. Dual-modification of coating and doping of fast-ion conductor Li{sub 2}SiO{sub 3} leads to stable crystal structure and additional three-dimensional (3-D) channels for Li{sup +}-ion diffusion, and protects the electrode surface from electrolyte attack. The Li{sub 2}SiO{sub 3}-modified material possesses coexistence of ordered P4{sub 3}32 and disordered Fd-3m phases. As a result of improved structure, morphology and conductivity, the Li{sub 2}SiO{sub 3}-modified LiNi{sub 0.5}Mn{sub 1.5}O{sub 4} shows more superior cyclic performance, rate capability and high temperature stability than the pristine: capacity retention of 95.17% at 0.1 C after 100 cycles vs. that of 79.23%; rate capability of 130–89.1 mAh g{sup −1} at 0.1–10 C vs. that of 120–57.6 mAh g{sup −1}; and high temperature capacity retention of 99.42% at 0.1 C vs. that of 79.59%. Our study provides a facile approach to stabilize crystal structure, optimize morphology and conductivity, and thus enhance electrochemical performance of LiNi{sub 0.5}Mn{sub 1.5}O{sub 4}-based materials.
The Enrico Fermi Atomic Power Plant Unit 1 (Fermi-1) was a sodium-cooled fast breeder reactor located in Monroe County, Michigan. The reactor was powered by a core of enriched uranium metal alloy driver fuel, which was enveloped by an axial and radial blanket material consisting of depleted uranium metal alloyed with 3 wt.% molybdenum. There are 406 axial and 559 radial irradiated sodium-bonded Fermi-1 blanket assemblies in storage at INL, totaling 34 metric tons of heavy metal. Disposal of the Fermi-1 blanket material directly into a geological repository is prohibited due to the reactive characteristic of its bond sodium. A melt drain evaporate (MEDE) process can effectively remove bond sodium from Fermi-1 blanket material. Consequently, planning is underway to apply a MEDE process to treat the 34 metric tons of heavy metal of irradiated Fermi-1 blanket material. Given the irradiated Fermi-1 blanket material’s relatively low power history and 50+ years of decay, it can be treated in a shielded glovebox. To assess the requisite shielding, the dose rates of the Fermi-1 blanket elements in various process configurations are needed. The method to perform the dose rate calculations is to first generate an average source term and associated photon source spectra for the Fermi-1 blanket material in SCALE and then use the associated photon spectra to calculate dose rates using MCNP6.2 in seven representative geometries. Dose rates in rem/h were calculated on contact (1 cm from outer geometry surface), 30 cm away from outer geometry surface, and 1 m from outer geometry surface at axial heights spanning the length of the blanket material within the geometry. The maximum average dose rate for the single Fermi-1 radial blanket element is ~0.60 rem/h, for the Fermi-1 radial blanket assembly ~1.10 rem/h, for the single Fermi-1 axial blanket element ~0.5 rem/h, for the Fermi-1 axial blanket assembly ~1.01 rem/h, for the MEDE can ~ 0.98 rem/h, for the Fermi Storage Canister ~ 0.83 rem/h, and for the MEDE cans in the DOE Standard Canister ~0.51 rem/h. Based on these maximum average values, the bounding dose rates are assumed to be 3× the average dose rates calculated for the axial blanket material and 7.6× the average dose rates calculated for the radial blanket material, based on the distribution of Fermi-1 blanket material assembly burnup.
This paper presents a Bayesian approach using Metropolis-Hastings Markov Chain Monte Carlo algorithm and applies this method for daily river flow rate forecast and uncertainty quantification for Zhujiachuan River using data collected from Qiaotoubao Gage Station and other 13 gage stations in Zhujiachuan watershed in China. The proposed method is also compared with the conventional maximum likelihood estimation (MLE) for parameter estimation and quantification of associated uncertainties. While the Bayesian method performs similarly in estimating the mean value of daily flow rate, it performs over the conventional MLE method on uncertainty quantification, providing relatively narrower reliable interval than the MLE confidence interval and thus more precise estimation by using the related information from regional gage stations. As a result, the Bayesian MCMC method might be more favorable in the uncertainty analysis and risk management.
Abstract MXenes are a class of two‐dimensional (2D) transition metal carbides, nitrides and carbonitrides that have shown promise for high‐rate pseudocapacitive energy storage. However, the effects that irreversible oxidation have on the surface chemistry and electrochemical properties of MXenes are still not understood. Here we report on a controlled anodic oxidation method which improves the rate performance of titanium carbide MXene (Ti 3 C 2 T x , T x refers to ‐F, =O, ‐Cl and ‐OH) electrodes in acidic electrolytes. The capacitance retention at 2000 mV s −1 (with respect to the lowest scan rate of 5 mV s −1 ) increases gradually from 38 % to 66 % by tuning the degree of anodic oxidation. At the same time, a loss in the redox behavior of Ti 3 C 2 T x is evident at high anodic potentials after oxidation. Several analysis methods are employed to reveal changes in the structure and surface chemistry while simultaneously introducing defects, without compromising electrochemically active sites, are key factors for improving the rate performance of Ti 3 C 2 T x . This study demonstrates improvement of the electrochemical performance of MXene electrodes by performing a controlled anodic oxidation.
MXenes are a class of two-dimensional (2D) transition metal carbides, nitrides and carbonitrides that have shown promise for high-rate pseudocapacitive energy storage. However, the effects that irreversible oxidation have on the surface chemistry and electrochemical properties of MXenes are still not understood. In this work, we report on a controlled anodic oxidation method which improves the rate performance of titanium carbide MXene (Ti 3 C 2 T x , T x refers to -F, =O, -Cl and -OH) electrodes in acidic electrolytes. The capacitance retention at 2000 mV s -1 (with respect to the lowest scan rate of 5 mV s -1 ) increases gradually from 38% to 66% by tuning the degree of anodic oxidation. At the same time, a loss in the redox behavior of Ti 3 C 2 T x is evident at high anodic potentials after oxidation. Several analysis methods are employed to reveal changes in the structure and surface chemistry while simultaneously introducing defects, without compromising electrochemically active sites, are key factors for improving the rate performance of Ti 3 C 2 T x . This study demonstrates improvement of the electrochemical performance of MXene electrodes by performing a controlled anodic oxidation.
The economic return on investment of a commercial photovoltaic system depends greatly on its performance over the long term and, hence, its degradation rate. Many methods have been proposed for assessing system degradation rates from outdoor performance data. However, comparing reported values from one analyst and research group to another requires a common baseline of performance; consistency between methods and analysts can be a challenge. An interlaboratory study was conducted involving different volunteer analysts reporting on the same photovoltaic performance data using different methodologies. Initial variability of the reported degradation rates was so high that analysts could not come to a consensus whether a system degraded or not. More consistent values are received when written guidance is provided to each analyst. Further improvements in analyst variance was accomplished by using the free open-source software RdTools, allowing a reduction in variance between analysts by more than two orders of magnitude over the first round, where multiple analysis methods are allowed. This article highlights many pitfalls in conducting 'routine' degradation analysis, and it addresses some of the factors that must be considered when comparing degradation results reported by different analysts or methods.
Microbial cell factories have been extensively engineered to produce free fatty acids (FFAs) as key components of crucial nutrients, soaps, industrial chemicals, and fuels. However, our ability to control the composition of microbially synthesized FFAs is still limited, particularly, for producing medium‐chain fatty acids (MCFAs). This is mainly due to the lack of high‐throughput approaches for FFA analysis to engineer enzymes with desirable product specificity. Here we report a mass spectrometry (MS)‐based method for rapid profiling of MCFAs in Saccharomyces cerevisiae by using membrane lipids as a proxy. In particular, matrix‐assisted laser desorption/ionization time‐of‐flight (MALDI‐ToF) MS was used to detect shorter acyl chain phosphatidylcholines from membrane lipids and a higher m/z peak ratio at 730 and 758 was used as an indication for improved MCFA production. This colony‐based method can be performed at a rate of ~2 s per sample, representing a substantial improvement over gas chromatography‐MS (typically >30 min per sample) as the gold standard method for FFA detection. To demonstrate the power of this method, we performed site‐saturation mutagenesis of the yeast fatty acid synthase and identified nine missense mutations that resulted in improved MCFA production relative to the wild‐type strain. Colony‐based MALDI‐ToF MS screening provides an effective approach for engineering microbial fatty acid compositions in a high‐throughput manner.
Microbial cell factories have been extensively engineered to produce free fatty acids (FFAs), key components of crucial nutrients, soaps, industrial chemicals, and fuels. Yet, our ability to control the specificity of microbially synthesized FFAs is still limited for medium-chain fatty acids (MCFAs), which is mainly due to lack of high-throughput approaches for FFA analysis. Here we report a mass spectrometry (MS)-based method for rapid profiling of MCFAs in Saccharomyces cerevisiae by using membrane lipids as a proxy. Specially, matrix-assisted laser desorption/ionization time-of-flight (MALDI-ToF) MS was used to detect shorter acyl chain phosphatidylcholines from membrane lipids and the m/z peak ratio at 730 and 758 was used as an index for improved MCFA production. This yeast colony-based method can be performed at a rate of ~2 second per sample, which is much faster than the gold standard gas chromatography (GC)-MS (typically > 30 min per sample). To demonstrate the power of this method, we performed site-saturation mutagenesis of the yeast fatty acid synthase and identified 9 mutants that resulted in improved MCFA production relative to the wild-type strain. This colony-based MALDI-ToF MS screening method offers an alternative way for engineering microbial fatty acid compositions in a high-throughput manner.
We consider a problem of detecting a low-level radiation source using a network of Gamma spectral sensors placed on the periphery of a monitored region. We propose a computationally light-weight, correlation-based method which is primarily intended for systems with limited computing capacity. Sensor measurements are combined at the fusion by first generating decisions at each time step and then taking their majority vote within a time widow. At each time step, decisions are generated using two strategies: (i) SUM method based on a threshold decision on a correlation statistic derived from measurements from all sensors, and (ii) OR method based on logical-OR of threshold decisions based on correlations statistics of individual sensor measurements. We derive analytical performance bounds for false alarm rates of SUM and OR methods, and show that their performance is enhanced by the temporal smoothing of majority vote within a time window. Using measurements from a test campaign, we generate a border monitoring scenario with twelve 2"x2" NaI Gamma sensors deployed on the periphery of 42m x 42m outdoor region. A Cs-137 source is moved in a straight-line across this region, starting several meters outside and finally moving away from it. We illustrate the performance of both correlation-based detection methods, and compare their performances with each other and with a particle filter method. Overall, under small false-alarm conditions, the OR fusion is found to produce better detection performance.
Purpose: To test the validity of a windowless extrapolation chamber used to measure surface dose rate from planar ophthalmic applicators and to compare different Monte Carlo based codes for deriving correction factors. Methods: Dose rate measurements were performed using a windowless, planar extrapolation chamber with a {sup 90}Sr/{sup 90}Y Tracerlab RA-1 ophthalmic applicator previously calibrated at the National Institute of Standards and Technology (NIST). Capacitance measurements were performed to estimate the initial air gap width between the source face and collecting electrode. Current was measured as a function of air gap, and Bragg-Gray cavity theory was used to calculate the absorbed dose rate to water. To determine correction factors for backscatter, divergence, and attenuation from the Mylar entrance window found in the NIST extrapolation chamber, both EGSnrc Monte Carlo user code and Monte Carlo N-Particle Transport Code (MCNP) were utilized. Simulation results were compared with experimental current readings from the windowless extrapolation chamber as a function of air gap. Additionally, measured dose rate values were compared with the expected result from the NIST source calibration to test the validity of the windowless chamber design. Results: Better agreement was seen between EGSnrc simulated dose results and experimental current readings at very small air gaps (<100 µm) for the windowless extrapolation chamber, while MCNP results demonstrated divergence at these small gap widths. Three separate dose rate measurements were performed with the RA-1 applicator. The average observed difference from the expected result based on the NIST calibration was −1.88% with a statistical standard deviation of 0.39% (k=1). Conclusion: EGSnrc user code will be used during future work to derive correction factors for extrapolation chamber measurements. Additionally, experiment results suggest that an entrance window is not needed in order for an extrapolation chamber to provide accurate dose rate measurements for a planar ophthalmic applicator.