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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A Green's Function Wind Turbine Induction Model That Incorporates Complex Inflow Conditions

ABSTRACT In this work, we develop a new analytical turbine induction model that can incorporate complex inflow conditions including cases where the wind velocity and temperature profiles can vary as functions of height. This induction model is derived from the linearized Navier–Stokes and leads to a second‐order ODE that can be solved using a Green's function formulation. The corresponding Green's function for several configurations are found including the infinite domain, semi‐infinite domain with ground plane, and a power law velocity inflow profile. The results of this approach are then compared with simulations of the turbine induction field using the AMR‐Wind CFD solver with a uniformly loaded actuator disk model. These comparisons show that the Green's function approach captures the centerline blockage, three‐dimensional blockage flow field, and streamwise velocity slow down, with very good agreement for lower thrust conditions and at larger distances away from rotor disk. The effects of shear on the turbine blockage were also compared using a power law inflow profile, and we show that this approach matches the CFD predictions for the cases considered.

17 WIND ENERGY↗
DOE OSTI2021

Sensitivity-Informed Bayesian Inference for Home PLC Network Models with Unknown Parameters

Bayesian inference is used to calibrate a bottom-up home PLC network model with unknown loads and wires at frequencies up to 30 MHz. A network topology with over 50 parameters is calibrated using global sensitivity analysis and transitional Markov Chain Monte Carlo (TMCMC). The sensitivity-informed Bayesian inference computes Sobol indices for each network parameter and applies TMCMC to calibrate the most sensitive parameters for a given network topology. A greedy random search with TMCMC is used to refine the discrete random variables of the network. This results in a model that can accurately compute the transfer function despite noisy training data and a high dimensional parameter space. The model is able to infer some parameters of the network used to produce the training data, and accurately computes the transfer function under extrapolative scenarios.

42 ENGINEERING↗
DOE OSTI2022

A New Perspective of Post-Weld Baking Effect on Al-Steel Resistance Spot Weld Properties through Machine Learning and Finite Element Modeling

The root cause of post-weld baking on the mechanical performance of Al-steel dissimilar resistance spot welds (RSWs) has been determined by machine learning (ML) and finite element modeling (FEM) in this study. A deep neural network (DNN) model was constructed to associate the spot weld performance with the joint attributes, stacking materials, and other conditions, using a comprehensive experimental dataset. The DNN model positively identified that the post-weld baking reduces the joint performance, and the extent of degradation depends on the thickness of stacking materials. A three-dimensional finite element (FE) model was then used to investigate the root cause and the mechanism of the baking effect. It revealed that the formation of high thermal stresses during baking, from the mismatch of thermal expansion between steel and Al alloy, causes damage and cracking of the brittle intermetallic compound (IMC) formed at the interface of the weld nugget during welding. This in turn reduces the joint performance by promoting undesirable interfacial fracture when the welds were subjected to externally applied loads. The FEM model further revealed that increase in structural stiffness, because of increase in steel sheet thickness, reduces the thermal stresses at the interface caused by the thermal expansion mismatch and consequently lessens the detrimental effect of post-weld baking on the joint performance.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Sensitivity of fatigue reliability in wind turbines: effects of design turbulence and the Wöhler exponent

Fatigue assessment of wind turbines involves three main sources of uncertainty: material resistance, load, and the damage accumulation model. Many studies focus on increasing the accuracy of fatigue load assessment to improve the fatigue reliability. Probabilistic modeling of the wind's turbulence standard deviation is an example of an approach used for this purpose. Editions 3 and 4 of the IEC standard for the design of wind energy generation systems (IEC 61400-1) suggest different probability distributions as alternatives for the representative turbulence in the normal turbulence model (NTM) of edition 1. There are debates on whether the suggested distributions provide conservative reliability levels, as the established design safety factors are calibrated based on the representative turbulence approach. The current study addresses the debate by comparing annual reliability based on different scenarios of NTM using a probabilistic approach. More importantly, it elaborates on the relative importance of load assessment accuracy in defining the fatigue reliability. Using the DTU 10 MW reference wind turbine and the first-order reliability method (FORM), we study the changes in the annual reliability level and its sensitivity to the three main random inputs. We perform the study considering the blade root flapwise and the tower base fore–aft moments, assuming different fatigue exponents in each load channel. The results show that integration over distributions of turbulence in each mean wind speed results in less conservative annual reliability levels than representative turbulence. The difference in the reliability levels varies according to turbulence distribution and the fatigue exponent. In the case of the tower base, the difference in the annual reliability index after 20 years can be up to 50 %. However, the model and material uncertainty have much higher effects on the reliability levels compared to load uncertainty. Knowledge about such differences in the reliability levels due to the choice of turbulence distribution is especially important, as it impacts the extent of lifetime extension through reliability reassessments.

17 WIND ENERGY↗
DOE OSTI2015

Evaluation of Geometrically Nonlinear Reduced Order Models with Nonlinear Normal Modes

Several reduced-order modeling strategies have been developed to create low-order models of geometrically nonlinear structures from detailed finite element models, allowing one to compute the dynamic response of the structure at a dramatically reduced cost. But, the parameters of these reduced-order models are estimated by applying a series of static loads to the finite element model, and the quality of the reduced-order model can be highly sensitive to the amplitudes of the static load cases used and to the type/number of modes used in the basis. Our paper proposes to combine reduced-order modeling and numerical continuation to estimate the nonlinear normal modes of geometrically nonlinear finite element models. Not only does this make it possible to compute the nonlinear normal modes far more quickly than existing approaches, but the nonlinear normal modes are also shown to be an excellent metric by which the quality of the reduced-order model can be assessed. Hence, the second contribution of this work is to demonstrate how nonlinear normal modes can be used as a metric by which nonlinear reduced-order models can be compared. Moreover, various reduced-order models with hardening nonlinearities are compared for two different structures to demonstrate these concepts: a clamped–clamped beam model, and a more complicated finite element model of an exhaust panel cover.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Advanced Natural Gas Reciprocating Engine(s)

Energy independence and fuel savings are hallmarks of the nation’s energy strategy. The advancement of natural gas reciprocating engine power generation technology is critical to the nation’s future. A new engine platform that meets the efficiency, emissions, fuel flexibility, cost and reliability/maintainability targets will enable American manufacturers to have highly competitive products that provide substantial environmental and economic benefits in the US and in international markets. Along with Cummins and Waukesha, Caterpillar participated in a multiyear cooperative agreement with the Department of Energy to create a 50% efficiency natural gas powered reciprocating engine system with a 95% reduction in NOx emissions by the year 2013. This platform developed under this agreement will be a significant contributor to the US energy strategy and will enable gas engine technology to remain a highly competitive choice, meeting customer cost of electricity targets, and regulatory environmental standard. Engine development under the Advanced Reciprocating Engine System (ARES) program was divided into phases, with the ultimate goal being approached in a series of incremental steps. This incremental approach would promote the commercialization of ARES technologies as soon as they emerged from development and would provide a technical and commercial foundation of later-developing technologies. Demonstrations of the Phase I and Phase II technology were completed in 2004 and 2008, respectively. Program tasks in Phase III included component and system development and testing from 2009-2012. Two advanced ignition technology evaluations were investigated under the ARES program: laser ignition and distributed ignition (DIGN). In collaboration with Colorado State University (CSU), a laser ignition system was developed to provide ignition at lean burn and high boost conditions. Much work has been performed in Caterpillar’s DIGN program under the ARES program. This work has consisted of both modeling and single cylinder engine experiments to quantify DIGN performance. The air handling systems of natural gas engines dissipate a percentage of available energy as a result of both flow losses and turbomachinery inefficiencies. An analytical study was initiated to increase compressor efficiency by employing a 2-stage inter-cooled compressor. Caterpillar also studied a turbo-compound system that employs a power turbine to recover energy from the exhaust gases for improved engine efficiency. Several other component and system investigations were undertaken during the final phase of the program to reach the ultimate ARES goals. An intake valve actuation system was developed and tested to improve engine efficiency, durability and load acceptance. Analytical modeling and materials testing were performed to evaluate the performance of steel pistons and compacted graphite iron cylinder head. Effort was made to improve the detonation sensing system by studying and comparing the performance of different pressure sensors. To reduce unburned hydrocarbon emissions, different camshafts were designed and built to investigate the effect of exhaust valve opening timing and value overlap. 1-D & 3-D coupled simulation was used to study intake and exhaust manifold dynamics with the goal of reducing load in-balance between cylinders. Selective catalytic reduction with on-board reductant generation to reduce NOx emissions was also engine tested. An effective mean to successfully deploy ARES technologies into the energy markets is to deploy demonstration projects in the field. In 2010, NETL and Caterpillar agreed to include a new “opportunity fuel” deliverable and two field demonstrations in the ARES program. An Organic Rankine Cycle system was designed with production intent incorporating lessons learned from the Phase II demonstration. Unfortunately, business conditions caused Caterpillar to cancel this demonstration in 2011. Nonetheless, Caterpillar partnered with a local dealer to deploy an ARES class engine using syngas from a biomass gasifier as the DE-FC26-01CH11079 primary combustion fuel in Gleason, TN. Upon the successful start-up and commissioning of the demonstration unit, ownership of the system was transferred to the dealer. In order to further our understanding of syngas combustion, a fundamental combustion study on syngas combustion at high pressure and lean condition was conducted through the collaboration with University of Southern California. A Methane program was also developed to rate engine performance for various compositions of syngas using empirical data obtained at CSU. While much work remains in terms of extending and integrating these developments into commercial products, it is evident that engine manufacturers on our own or through private consortium efforts could not have overcome the financial hurdles to drive these improvements into reciprocating engine and system capabilities, helping maintain the natural gas reciprocating engine power generation technology as a strong option for electric power markets, both in the United States and worldwide.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

The nonlinear behavior of generic tail fins for small wind turbines

This paper describes analysis and measurements of the yaw response of tail fins for small wind turbines. It is based on an extension of unsteady slender body theory (USBT) to cover non-slender fins and high angles of incidence, both of which make the theory nonlinear. We provide three main additions to the substantial literature on linearized USBT for tail fins. First, USBT is extended to high angles by modeling the nonlinear vortex dynamics. Second, the restriction to slender bodies is removed by modeling the chordwise load variation. Third, we consider the effect of time-varying wind speed. Further, the extended theory is compared to wind tunnel measurements of the yaw behavior of delta, elliptical, and rectangular tail fins without a rotor and nacelle. The fins were released from initial yaw angles of -40° and -80°; the latter is of sufficient magnitude to show the importance of the nonlinear yaw dynamics. Generally good agreement was found between the theory and measurements, and the theory was shown to be more accurate than a “polar” or quasi-steady model which uses only the lift and drag of a delta planform. Of the three planforms, the rectangular one showed the lowest accuracy in terms of frequency but the damping was accurately predicted. Overall, the results demonstrate the importance of nonlinearity in the response of a yawing tail fin, particularly for the higher aspect ratio fins at large yaw angles.

17 WIND ENERGY↗
DOE OSTI2020

Numerical Model Development of a Variable-Geometry Attenuator Wave Energy Converter: Preprint

Because the wave energy industry is still in its infancy, an optimal design for wave energy converters (WECs) has yet to be established; more work is needed to explore various cost reduction pathways. The primary cost-reduction pathway considered for this work is the optimization of the geometric profile on an attenuator WEC to maximize power production while, at the same time, minimizing capital expenditures through the use of variable-geometry modules. In this investigation, the variable geometry modules consist of inflatable bags placed on either side of a base central steel cylinder that would be inflated in low moderate sea states to maximize power capture and then deflated in moderate-extreme sea states to minimize wave loading. The numerical model and simulation of the attenuator WEC were developed and completed using WEC-Sim, which is an open-source code that is appropriate for use in evaluating the dynamic response of the different WEC models in operational seas. The power production estimates were obtained from the Wave Energy Prize (WEP) sea states, which are representative of U. S. deployment sites, to calculate the average climate capture width that is used in the WEP ACE calculation. Preliminary capital expenditure costs were obtained assuming the base central steel cylinder mass was equal to the fluid displaced mass, minus the mass of the variable-geometry bags. The additional weight required to offset the additional buoyancy from the variable-geometry bags was assumed to come from the addition of seawater ballast. The variable-geometry attenuator model was found to have a similar power capture efficiency as a fixed-body model, but is expected to have a lower characteristic capital expenditure given its more streamlined profile, which demonstrates that variable-geometry modules may provide a realistic cost-reduction pathway to help design a more cost-competitive WEC.

50 EE - Wind and Water Power Program - Water (EE-4↗
DOE OSTI2020

Numerical Model Development of a Variable-Geometry Attenuator Wave Energy Converter

Because the wave energy industry is still in its infancy, an optimal design for wave energy converters (WECs) has yet to be established; more work is needed to explore various cost-reduction pathways. The primary cost-reduction pathway considered for this work is the optimization of the geometric profile on an attenuator WEC to maximize power production while, at the same time, minimizing capital expenditures through the use of variable-geometry modules. In this investigation, the variable-geometry modules consist of inflatable bags placed on either side of a base central steel cylinder that would be inflated in low-moderate sea states to maximize power capture and then deflated in moderate-extreme sea states to minimize wave loading. The numerical model and simulation of the attenuator WEC were developed and completed using WEC-Sim, which is an open-source code that is appropriate for use in evaluating the dynamic response of the different WEC models in operational seas. The power production estimates were obtained from the Wave Energy Prize (WEP) sea states, which are representative of U. S. deployment sites, to calculate the average climate capture width that is used in the WEP ACE calculation. Preliminary capital expenditure costs were obtained assuming the base central steel cylinder mass was equal to the fluid displaced mass, minus the mass of the variable-geometry bags. The additional weight required to offset the additional buoyancy from the variable-geometry bags was assumed to come from the addition of seawater ballast. The variable-geometry attenuator model was found to have a similar power capture efficiency as a fixed-body model, but is expected to have a lower characteristic capital expenditure given its more streamlined profile, which demonstrates that variable-geometry modules may provide a realistic cost-reduction pathway to help design a more cost-competitive WEC.

50 EE - Wind and Water Power Program - Water (EE-4↗
DOE OSTI2021

Deformation behavior of CP-titanium under strain path changes: Experiment and crystal plasticity modeling

The deformation behavior of commercially pure rolled titanium subjected to strain path changes is studied using experiments and a crystal plasticity model. Four different loading combinations are performed at room temperature to study the activation of slip, twinning, de-twinning and double-twinning in hexagonal closed packed titanium. The strain paths considered are: rolling direction compression (RDC) followed by normal direction compression (NDC), RDC followed by transverse direction compression (TDC), NDC followed by RDC, and NDC followed by TDC. An EBSD-based analysis of the distribution of boundary misorientation angles before and after reload was developed to analyze the evolution of {$10\bar{1}2$} tensile and {$11\bar{2}2$} compression twins. This analysis supports the model results concerning the treatment of twin reorientation. A de-twinning and double-twinning model accounting for back stress effects, an important feature of strain path changes, is implemented within the framework of the visco-plastic self-consistent (VPSC) model along with a dislocation density (DD) based hardening scheme. In the model, plasticity is accommodated by prismatic $\langle$a$\rangle$, basal $\langle$a$\rangle$ and pyramidal $\langle$c+a$\rangle$ slip modes, and {$10\bar{1}2$} tensile and {$11\bar{2}2$} compression twinning modes. The VPSC model predicts the evolution of twinning, de-twinning and double-twinning processes for both tensile and compression twinning modes under strain path change. The model predicts macroscopic stress-strain response, texture evolution, and twin volume fraction that are in agreement with experimental observations. The evolution of texture is investigated in detail by separately analyzing the twinned domains, rather than the evolution of the global texture.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Preparing Distribution Utilities for the Future - Unlocking Demand-Side Management Potential: A Novel Analytical Framework

The balance of supply and demand in the power systems has traditionally been served solely through generation and network capacity planning and operations. However, with increased requirements for flexibility due to the uptake in variable renewable generation sources such as wind and solar there is a need to increased demand-side flexibility. In addition, there are increased communications and flexibility capabilities emerging on the demand-side from the adoption of advanced metering infrastructures and smart meter deployment and intelligent loads such as smart thermostats and schedulable white goods (e.g. dishwashers and washing machines). Unlocking demand-side flexibility can bring system benefits from peak load reduction bringing about generation capacity and network upgrade deferral, to reducing demand and more efficient utilization of generation and network capacity. Unlocking demand-side flexibility is an evolving process for utilities and solutions must be tailored to each specific customer group. Demand-side management (DSM) is a broad set of tools that can include demand response (both dispatchable and non-dispatchable), energy efficiency and distributed energy resources and demand-side technologies. The National Renewable Energy Laboratory (NREL), in collaboration with BSES Rajdhani Power Ltd. (BRPL) and Deloitte, examined the potential of DSM in BRPL’s service territory, developing detailed information on customer classes and willingness to participate in DSM. The study developed modeling frameworks for load analysis and the analysis tools to assess the potential of time-of-use tariffs in motivating customers to reduce their peak period energy consumption. The study shows that BRPL customers, specifically their domestic customers, are willing to participate in DSM programs and that time-of-use pricing can help BRPL reduce their peak demand and help unlock demand-side flexibility.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

End-Use Savings Shapes: Public Dataset Release for Residential Round 1 [Slides]

The End-Use Load Profiles project created a public database of 900,000 individual building end-use load profiles. Load profiles were modeled to represent the U.S. building stock as it was in 2018, as nearly as possible based on the best available data. The End-Use Savings Shapes follow-on project adds measure impact profiles for energy efficiency and electrification packages to the public dataset. This presentation details the public dataset release on September 20, 2022.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

Predictive Scheduling for Electric Vehicles Considering Uncertainty of Load and User Behaviors

Un-coordinated Electric Vehicle (EV) charging can create unexpected load in local distribution grid, which may degrade the power quality and system reliability. The uncertainty of EV load, user behaviors and other baseload in distribution grid, is one of challenges that impedes optimal control for EV charging problem. Previous researches did not fully solve this problem due to lack of real-world EV charging data and proper stochastic model to describe these behaviors. In this paper, we propose a new predictive EV scheduling algorithm (PESA) inspired by Model Predictive Control (MPC), which includes a dynamic load estimation module and a predictive optimization module. The user-related EV load and base load are dynamically estimated based on the historical data. At each time interval, the predictive optimization program will be computed for optimal schedules given the estimated parameters. Only the first element from the algorithm outputs will be implemented according to MPC paradigm. Current-multiplexing function in each Electric Vehicle Supply Equipment (EVSE) is considered and accordingly a virtual load is modeled to handle the uncertainties of future EV energy demands. This system is validated by the real-world EV charging data collected on UCLA campus and the experimental results indicate that our proposed model not only reduces load variation up to 40% but also maintains a high level of robustness. Finally, IEC 61850 standard is utilized to standardize the data models involved, which brings significance to more reliable and large-scale implementation.

Wang, Bin↗
DOE OSTI2018

Numerical parameter optimizations of the Ignition and Growth model for a HMX plastic bonded explosive

We present here a novel method for optimizing parameters of the Ignition and Growth (I&G) reactive flow model for high explosives. The I&G model predicts the shock initiation response of explosives subjected to dynamic loading. However, calibrating the model is a time-consuming process because it has several parameters, typically requires multiple data sets, and there are no direct correlations between parameters and data. In this study, we couple a scalable optimization algorithm to simulations of shock initiation experiments in the multi-physics code ALE3D. We develop four I&G model parameter sets for the HMX (1,3,5,7-tetranitro-1,3,5,7-tetrazocane)-based explosive LX-07 [90 wt. % HMX, 10 wt. % Viton A] based on minimizing the difference between calculations and measurements at the embedded pressure gauges in 1D gun shock experiments. Our study shows that a cost function based on both shock time of arrival and pressure pulse shape demonstrates the best agreement with experimental data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A Privacy-Aware Federated Learning Framework for Distributed Energy Resource Analytics in Constrained Environments

To be resilient against extreme weather events, the rural communities in Puerto Rico are leveraging distributed energy resources (DER). However, computing frameworks sup-porting the grid in critical decision-making are still largely centralized. Sensitive consumer data are transmitted over the Internet or cellular networks to a secondary or tertiary node. It guarantees better situational awareness at the cost of a wider attack surface, jeopardizing user privacy, as more DER come online. Cloud, Edge, and Fog computing all require data aggregation at some level. This paper introduces a privacy-aware federated learning framework that leverages the Fog model by pushing analytics all the way to the DER and load assets. These local models train on individual asset data and transmit only learned parameters (such as weights) over secure communications to a global decision-maker. By abstracting personally identifiable consumer data without impacting decision optimality, this framework better aligns with distributed power generation paradigm.

Sundararajan, Aditya↗
DOE OSTI2012

Limit Load and Buckling Analysis for Assessing Hanford Single-Shell Tank Dome Structural Integrity - 12278

The U.S. Department of Energy, Office of River Protection has commissioned a structural analysis of record for the Hanford single shell tanks to assess their structural integrity. The analysis used finite element techniques to predict the tank response to the historical thermal and operating loads. The analysis also addressed the potential tank response to a postulated design basis earthquake. The combined response to static and seismic loads was then evaluated against the design requirements of American Concrete Institute standard, ACI-349-06, for nuclear safety-related concrete structures. Further analysis was conducted to estimate the plastic limit load and the elastic-plastic buckling capacity of the tanks. The limit load and buckling analyses estimate the margin between the applied loads and the limiting load capacities of the tank structure. The potential for additional dome loads from waste retrieval equipment and the addition of large dome penetrations to accommodate retrieval equipment has generated additional interest in the limit load and buckling analyses. This paper summarizes the structural analysis methods that were used to evaluate the limit load and buckling of the single shell tanks. This paper summarizes the structural analysis methods that were used to evaluate the limit load and buckling limit states of the underground single shell tanks at the Hanford site. The limit loads were calculated using nonlinear finite element models that capture the progressive deformation and damage to the concrete as it approaches the limit load. Both uniform and concentrated loads over the tank dome were considered, and the analysis shows how adding a penetration in the center of the tank would affect the limit loads. For uniform surface loads, the penetration does not affect the limit load because concrete crushing and rebar yielding initiates first at the top of the wall, away from the penetration. For concentrated loads, crushing initiates at the center of the dome, so the penetration does reduce the concentrated limit load somewhat. However, the safety factors comparing the limit loads to the maximum allowable applied loads remain well above the required value of 3.0. The buckling analysis method accounts for the geometric imperfections, concrete creep, cracking and reinforcements, and concrete plasticity in determining the allowable buckling load limits. The method was demonstrated in this paper for the evaluation of a tank before and after a penetration is added in the dome center. Finite element buckling models were used to accurately calculate the linear critical buckling loads. The models showed that adding the penetration reduces the linear critical buckling load by only 2.5%. Bounding cases also showed that the possible range of soil support on the walls does not significantly affect the dome buckling loads. Buckling models of the full 360 deg. dome also showed that the dome is more resistant to buckling when the load is offset than when it is positioned over the center. These limit load and buckling analysis methods are being used at the Hanford site to assess the tank loads that can be safely applied during future waste retrieval activities. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2011

Optimizing Energy Savings from Direct-DC in U.S. Residential Buildings

An increasing number of energy efficient appliances operate on direct current (DC) internally, offering the potential to use DC from renewable energy systems directly and avoiding the losses inherent in converting power to alternating current (AC) and back. This paper investigates that potential for net-metered residences with on-site photovoltaics (PV) by modeling the net power draw of the ‘direct-DC house’ with respect to today’s typical configuration, assuming identical DC-internal loads. Power draws were modeled for houses in 14 U.S. cities, using hourly, simulated PV-system output and residential loads. The latter were adjusted to reflect a 33% load reduction, representative of the most efficient DC-internal technology, based on an analysis of 32 electricity end-uses. The model tested the effect of climate, electric vehicle (EV) loads, electricity storage, and load shifting on electricity savings; a sensitivity analysis was conducted to determine how future changes in the efficiencies of power system components might affect savings potential. Based on this work, we estimate that net-metered PV residences could save 5% of their total electricity load for houses without storage and 14% for houses with storage. Based on residential PV penetration projections for year 2035 obtained from the National Energy Modeling System (2.7% for the reference case and 11.2% for the extended policy case), direct-DC could save the nation 10 trillion Btu (without storage) or 40 trillion Btu (with storage). Shifting the cooling load by two hours earlier in the day (pre-cooling) has negligible benefits for energy savings. Direct-DC provides no energy savings benefits for EV charging, to the extent that charging occurs at night. However, if charging occurred during the day, for example with employees charging while at work, the benefits would be large. Direct-DC energy savings are sensitive to power system and appliance conversion efficiencies but are not significantly influenced by climate. While direct-DC for residential applications will most likely arise as a spin-off of developments in the commercial sector—because of lower barriers to market entry and larger energy benefits resulting from the higher coincidence between load and insolation—this paper demonstrates that there are substantial benefits in the residential sector as well. Among residential applications, space cooling derives the largest energy savings from being delivered by a direct-DC system. It is the largest load for the average residence on a national basis and is particularly so in high-load regions. It is also the load with highest solar coincidence.

14 SOLAR ENERGY↗