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DOE OSTI2024

Tailor : Altering Skip Connections for Resource-Efficient Inference

Deep neural networks use skip connections to improve training convergence. However, these skip connections are costly in hardware, requiring extra buffers and increasing on- and off-chip memory utilization and bandwidth requirements. In this article, we show that skip connections can be optimized for hardware when tackled with a hardware-software codesign approach. We argue that while a network’s skip connections are needed for the network to learn, they can later be removed or shortened to provide a more hardware-efficient implementation with minimal to no accuracy loss. We introduceTailor, a codesign tool whose hardware-aware training algorithm gradually removes or shortens a fully trained network’s skip connections to lower the hardware cost.Tailorimproves resource utilization by up to 34% for block random access memories (BRAMs), 13% for flip-flops (FFs), and 16% for look-up tables (LUTs) for on-chip, dataflow-style architectures.Tailorincreases performance by 30% and reduces memory bandwidth by 45% for a two-dimensional processing element array architecture.

Computer Science↗

DOE OSTI2023

Integration of sensors through additive manufacturing leading to increased efficiencies of gas turbines for power generation and propulsion

To realize the full capability of additively manufactured components in complex energy systems, it is imperative to minimize early component failures during development phases and during operation. Traditional field feedback timelines and offline inspection protocols significantly reduce the design-manufacturing iteration times. To address this specific question, the project developed and demonstrated a method for the integration of sensors into complex components through additive manufacturing. The team used gas turbine engines as a platform, which meets the need of both power generation and propulsion and offer opportunities for cost reductions and efficiency increases. The innovation of this intelligent integration of sensors into complex components uniquely customized to address questions of integrity and durability for additively manufactured components. With real-time sensing data from additively manufactured components, turbine manufacturers will realize higher efficiencies, reduced component failures, and a 30-50% acceleration in product deployment of high efficiency gas turbine components due to a faster reduction in component risk assessment under actual operating conditions. This is a transformative shift towards a data-driven design and qualification of additively manufactured gas turbine components. To directly integrate sensors into additively manufactured components with all the complexities of actual hardware, powder bed fusion (direct metal laser sintering) and laser metal deposition technologies was developed. Validation took take place in two university laboratories both of which contain actual engine hardware and closely simulate a gas turbine prior to demonstrating the technology in a turbine development test. Indeed, two major technologies from this research cold impact turbine systems in the near future: (1) higher efficiency materials and designs enabled by additive manufacturing with 50% faster design to manufacturing cycle time, to enable faster time-to-market targets; and (2) integration of sensors into additively manufactured components enabling broad health and condition based prognostics for faster component and engine risk reduction.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2026

Noise-canceling quantum feedback: Non-Hermitian dynamics with applications to state preparation and magic state distillation

Time-continuous quantum measurement allows for the tracking of a quantum system in real time via sequences of short, and individually weak, measurement intervals. Such measurements are necessarily invasive, imparting backaction to the system, and allowing the observer to update their state estimate based on stochastic measurement outcomes. Feedback control then involves real-time interventions by an observer, conditioned on the time-continuous measurement signal that they receive. Here, we consider here diffusive quantum trajectories and focus on the “noise-canceling” subset of feedback protocols that aim to minimize the degree of stochasticity in the dynamics. We derive such a class of feedback operations, showing that under the idealized assumptions of pure states, unit measurement efficiency, and zero time delay in implementing feedback operations, perfectly noise-canceling feedback always exists. We consider the resulting noise-canceled dynamics generated by an effective non-Hermitian Hamiltonian; while non-Hermitian Hamiltonians from continuous monitoring generally describe rare dynamics (accessible by costly postselection), the use of noise-canceling feedback here leads to non-Hermitian dynamics that occur deterministically. We demonstrate this via examples of entangled state preparation and stabilization. We then illustrate the potential for the application of noise cancellation to boost success rates in magic state distillation protocols. We show that adding feedback based on noise cancellation into a time-continuous five-to-one distillation protocol leads to higher probabilities of successful distillation across a range of input errors and increases the threshold on input errors for which the protocol is effective. Our results highlight the efficacy of noise-canceling feedback-aided protocols for quantum state preparation and stabilization tasks.

Karmakar, Tathagata [University of California, Ber↗

DOE OSTI2021

Sonic Lift-off of GaAs-based Solar Cells with Reduced Surface Facets

Spalling has been proposed as a promising kerfless technique for slicing thin wafers and devices, enhancing the wafer yield from an ingot by reducing kerf-losses and enabling substrate reuse for the case of costly devices. The main challenge of spalling is to control the roughness and thickness variation of the spalled wafers that can be as high as 100% of the wafer thickness. Here, we have shown previously that the thickness variations are largely influenced by the interaction of the crack front with its own reflected waves. Herein we show that through Sonic Lift-off we can offer a modification to standard spalling technologies that minimizes the interaction of reflected waves with the crack front during lift-off of GaAs(100)-based solar cells. We show that the average surface facets amplitude can be reduced by 96% while obtaining a high quality bulk with no discernible residual strain as measured by PL. The resulting spalling depth can easily be tuned from 100 µm to less than 15µm. The electrical characterization of the Sonic lift-off cell shows no degradation of the VOC and a power conversion within 99% relative of a non-spalled baseline.

42 ENGINEERING↗

DOE OSTI2024

Manufacturing and Additive Design of Electric Machines by 3D Printing (MADE3D) (Final Technical Report)

As the U.S clean energy transition hinges on the growth of offshore wind, this is expected to be a major driver for innovations in manufacturing, material and design advancements to enable robust and cost-competitive wind turbines. The race to build larger and taller turbines rated 10 megawatts (MW) and beyond, has intensified pressure on OEMs in terms of logistics of handling and transporting large wind components, securing critical raw material as well as scaling up necessary domestic production infrastructure to meet the demand. There is increased interest in building lightweight, more efficient, and high-power dense drivetrains that will ease the burden on installation, minimize the raw material demand, increasing domestic sourceability. Despite good efficiency and reliability, existing drivetrain technologies such as direct-drive permanent magnet generators are heavy (> 300 tons), expensive, and often rely on large quantities of rare-earth permanent magnets (PMs), steel and copper.

17 WIND ENERGY↗

DOE OSTI2022

Calibration of cloud and aerosol related parameters for solar irradiance forecasts in WRF-solar

Model parameters are a major source of uncertainty in numerical weather prediction. Recently, the Weather Research and Forecasting model with Solar extensions (WRF-Solar) has been upgraded by enhancing the treatment of sub-grid scale cloud and aerosols with augmentations of a sub-grid scale cloud scheme (CLD3) and an upgraded aerosol-aware Thompson-Eidhammer scheme (TE14). However, the value of model parameters associated with these parameterizations are assigned based on limited measurements or theoretical calculations. Calibrating the most sensitive parameters has the potential to improve solar irradiance predictions. Here, we adopted a multiobjective surrogate-based optimization (SBO) framework to calibrate nine parameters used in CLD3 and TE14 that lead to the largest sensitivity in simulated irradiance. The normalized mean-absolute-error (NMAE) of global horizontal irradiance (GHI) and direct normal irradiance (DNI) are minimized by calibrating WRF-Solar over two regions including the Southern Great Plains (SGP) and Central California, in order to focus on parameter calibration under cloudy conditions with different aerosol loading. The results show that generalized linear model (GLM)-based surrogate models approximate physical models well, particularly when the third order and three-way interaction terms are considered. The SBO framework efficiently searches the parameter space for optimal solutions with less computational costs than directly calibrating the physical model. We first calibrate CLD3 parameters over the less-polluted SGP region. Optimized CLD3 parameters alone result in NMAE reduction by 14% for the site-mean and up to 33% for individual cases over the SGP region. With further calibration of TE14 parameters over the Central California during active fire periods, the optimized parameters lead to over 20% reductions of NMAE. Our investigation reveals, however, that optimizing TE14 has a limited impact on irradiance simulations under less-polluted conditions in the SGP.

14 SOLAR ENERGY↗

DOE OSTI2021

Improved Contacts for Tandem Cells with Enhanced Effciency Grown by D-HVPE

Dynamic hydride vapor phase epitaxy (D-HVPE) has provided a potential route towards lower cost material growth of III-V photovoltaic devices. A highly doped Ga0.5In0.5P emitter layer is grown in attempt to force passivation at the front of the cell to account for the absence of a suitable window layer in our reactor. Control over dopant diffusion in these materials is thus critical to achieving high-efficiency device performance. Here, we institute a two-step contact layer design that boosts tandem cell efficiencies by minimizing Se diffusion into the underlying emitter layer while still providing sufficiently low contact resistance. Short-circuit current in these devices improves to 8.9 mA/cm2 in an uncoated GaInP/GaAs cell, an improvement of 1.2 mA/cm2 over our previous best cell. Conversion efficiency with the new contact doping scheme is projected to be ~27% with the inclusion of a standard ARC layer.

27 ARPA - Advanced Research Projects Agency-Energy↗

DOE OSTI2020

VersaBuild: A Novel, Multi-scale, Versatile 3d Printer Concept

Our team has identified and attempted to solve a major challenge limiting the increased deployment of additive manufacturing in full-scale production environments. As engineers desire for greater flexibility of design grows, and as the diversity of properties achievable and materials usable in additive manufacturing increases, additive manufacturing becomes increasingly valuable and useful. However, the machines used to produce AM parts have largely stagnated in terms of configurability, technology, and design. We have conceptualized a system which enables a single machine to provide the functionality of multiple machines, with minimal operator changes. The gap that was identified by the team was the lack of a system that could accept user-configurable changes to the print resolution and printbed size. This would enable manufacturers flexibility in the size, quality, and quantity of parts produced in a facility of a given size. Significant floorspace savings could be achieved in a facility deploying our proposed solution due to the flexibility of the machine, lowering operational cost. Our envisioned design is similar in concept to a standard Delta robot, which is a three-armed robot that is used in many industrial applications. However, we intend for our design to have extensible delta arms that include position sensing, allowing for a greater range of motion and thus print volume while maintaining precise control over the printhead position. Some of the key risks associated with are system are caused by the novelty of the concept. Our system must undergo significant R&D and requires a fully integrated software, electrical, and mechanical system to be developed.

42 ENGINEERING↗

DOE OSTI2022

Port of New York and New Jersey Drayage Electrification Analysis

The National Renewable Energy Laboratory (NREL) evaluated the potential for drayage electrification in the Port of New York and New Jersey (PoNYNJ), with a focus on operators: Harbor Freight Transport (HF), Safeway Trucking (SWT), and International Motor Freight Inc (IMF). This report summarizes the data collection and electrification evaluation of all three drayage operators, includes detailed operational data, and identifies the performance requirements for battery electric tractors (BETs) and corresponding infrastructure operated within the context of PoNYNJ drayage operation. This report also details a methodology to evaluate opportunities, strategies, and challenges associated with future expansions of BETs in meeting PANYNJ emissions goals. The Port Authority has established a goal of achieving Net Zero carbon emissions by 2050 across all facilities, including from tenant and stakeholder sources such as drayage trucks. NREL used real-world performance data collected on the three PoNYNJ drayage operations, along with modeling and analysis tools to compare BET to diesel trucks. From March to July 2021, NREL collected 1Hz vehicle and engine data from 46 drayage trucks at the three operators totaling nearly 121,000 miles of operation, providing enough information to assess vehicle operations for electrification potential. A Future Automotive Systems Technology Simulator (FASTSim) electric truck powertrain model was validated using PoNYNJ data and scenarios were run to evaluate drayage truck electrification requirements over the real-world cycles. The first scenario examined BET viability with minimal changes to existing operations. This assumes the trucks charge when stopped for two hours or longer, have a functional battery size of 375 kWh, and can charge at 270 kilowatts (kW) average which are the specification of the commercially available Freightliner eCascadia. The second scenario looked at what operational, charging infrastructure, and BET technology changes would be needed to fully electrify. Finally, detailed analysis was run on charging rate structure to understand operational costs to the fleets. The studied drayage trucks averaged 5.1 MPG, spent roughly 9% of their energy at idle, and drove an average of 140 miles per day with a maximum daily distance of 573 miles. The FASTSim model results indicate a comparable BET would use 417 kWh of energy per day on average accounting for cargo weight, which is close to the full usable capacity of the eCascadia currently available on the market. Based on the daily average operating data, partial fleet electrification is possible with current technology. However, some specific days of operation would require over 1,600 kWh of energy due to longer distances traveled by the trucks and more intense operation. Trucks used for long distance and intense operation cannot be readily electrified with current technology without operational changes. Full adoption of BETs could reduce CO 2 emissions from these fleets by roughly 75% today, eliminating 76 metric tons of CO 2 (MTCO 2 ) per vehicle each year, which equates to 24,100 MTCO 2 per year for all three operators. Commercially available direct current fast chargers (DCFC) have charge rates up to 350 kW. Based on the average daily modeled energy use for each operator, current industrial rate structures, and the assumption of 350 kW peak charging, full drayage electrification would increase electricity consumption. In addition, peak demand usage would increase with unmanaged charging along with cost of electricity having a direct impact on cost per mile for electric vehicles. The resulting cost per mile for BETs along with comparable cost per mile for conventional diesel trucks are also examined at $\$$4.00 per gallon of diesel. It will be important for PANYNJ and the drayage operators within the PoNYNJ to consider these load impacts to their existing electrical infrastructure and devise operational strategies that avoid coincident charging of vehicles to mitigate demand charges. Despite these electricity cost increases, savings from reductions in diesel consumption will help offset the costs of this increased electricity consumption. However, prices of both electricity and diesel are subject to change based on various factors meaning the realized savings will vary over time. This shows BETs could be cost-competitive on an energy cost per mile basis for all scenarios while diesel is above $\$$3.00/gal. Further, if diesel prices dropped to the 15-year low of $2.33/gal, it would still be cost competitive to operate the EVs with electricity costs of 16.3 ¢/kWh or less.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2024

TEAMER - Field Demonstration of MarineSitu’s Marine Energy Monitoring Tools - CRADA 664 (Abstract)

In order to effectively monitor for marine life around marine energy devices and thus minimize the risk of collision, multiple sensors working in coordination and augmented with around-the-clock automated monitoring algorithms need to be installed in challenging high-energy tidal and wave environments. Such systems are often too expensive for widespread adoption, or lack sufficient sensors or smarts to enable around-the-clock, real-time monitoring without human involvement. MarineSitu has been working to tackle this problem by developing a low-cost, combined sonar and stereo camera sensor array with connected real-time AI-based algorithms for automatically detecting marine life in these marine energy suitable environments. In this TEAMER project with Pacific Northwest National Lab (PNNL), MarineSitu will be testing this novel sensor system for the first time in the high-energy tidal channel environment at PNNL’s Marine and Coastal Research Lab. Throughout this deployment, MarineSitu will be monitoring their system and running analytics on the sensor’s data in real-time. Meanwhile, PNNL Data Scientists and Ocean Engineers, will be evaluating the system’s effectiveness and ease of use both as a tool for plug-and-play environmental monitoring and novel environmental monitoring research. In doing so, the team will improve MarineSitu’s system and software, produce insightful data products, and develop novel visualizations and AI algorithms for combining and analyzing the data produced by systems like MarineSitu’s.

16 TIDAL AND WAVE POWER↗

DOE OSTI2025

TEAMER – Field Demonstration of MarineSitu’s Marine Energy Monitoring (Abstract)

16 TIDAL AND WAVE POWER↗

DOE OSTI2021

Radial storage efficiency for CO 2 injection: Quantifying effectiveness of local flow control methods

Basin-scale geologic carbon sequestration will require hundreds of injection wells, each of which has costs related to property rights and regulatory requirements that correlate with the areal size of the carbon dioxide plume. These surface-footprint-related issues motivate maximizing storage efficiency radially away from each well. Radial storage efficiency (RSE) is defined here as the ratio of the volumetrically weighted carbon dioxide free-phase saturation within a given radius away from the injection well to the available pore space within that same radius. Maximizing RSE effectively minimizes the radial extent of the CO 2 plume. Optimizing RSE around individual wells requires local flow control injection strategies that can increase the uniformity of the filling of pore space around the well over the entire length of the perforated injection interval despite differences in local formation transmissivity. The goal of uniform filling of the storage reservoir starting from the well outward is to maximize carbon dioxide sweep and trapping locally outward from the well in all of the layers of the storage region before buoyancy forces predominate and drive carbon dioxide upward where it will spread laterally under lower-permeability layers. Example simulations of carbon dioxide injection into a layered storage system with and without local flow control are presented to show the advantage of uniformly filling all layers and how RSE can be used to quantify storage efficiency for the two different injection approaches. Published 2021. This article is a U.S. Government work and is in the public domain in the USA.

03 NATURAL GAS↗

DOE OSTI2024

A multiphase flow model of water droplets dielectrophoretic-induced air dehumidification phenomena

Air humidity in indoor spaces plays a critical role in human comfort and health. Dehumidification systems are used for building humidity controls, but they can take significant energy consumption, especially in geographic locations with high outdoor humidity and warm climates. Consequently, there is a growing demand for innovative dehumidification processes that consume minimal energy. Dielectrophoretic air dehumidification represents one such promising approach. However, it has not garnered significant attention due to the absence of engineering models and simulation tools capable of evaluating its performance and limitations at large-scale airflows. A new numerical multiphase CFD model, which is also experimentally validated, is developed in a customized Reacting Foam solver based on OpenFOAM® version 9. The newly developed model seeks to decrease substantial energy consumption and lower costs by leveraging the dielectrophoretic phenomenon to regulate moisture levels in the air. The solver integrates a hybrid Eulerian-Lagrangian framework to track the droplet's trajectory and growth rate while solving the continuum equations for the moist air. An electrospray produces electrically charged droplets, which grow during their in-flight trajectories as water vapor condenses onto their surfaces. The role of electrostatic forces in promoting vapor condensation within a high-gradient electrical field is investigated, and the dielectrophoretic vapor nucleation process on charged water droplets is discussed. The CFD model was validated against results from the literature and from proof-of-concept experiments conducted by the authors, which showed a 2 % air dehumidification with a single electrospray and airflow rate of 5 cubic feet per minute. The simulation results indicated that augmenting the number of electrically charged spray droplets increased the dehumidification of the air to 25 %. The initial mean droplet diameter, the orientation of the injector and relative humidity significantly influence the assessment of dehumidification. As a result, scaling up this approach to larger airflow volumes is identified as a potential future research direction.

42 ENGINEERING↗

DOE OSTI2024

Low-chromophore lignin isolation from natural biomass with polyol-based deep eutectic solvents

When attempting to obtain light-color lignin from lignocellulosic biomass or industrial lignin, the available options based on chemical or morphological modification suffer from low yield, high cost, and lack of availability at the required scales. In this study, we adopted a polyhydric-alcohol-based deep eutectic solvent (PA-DES) to directly extract light-color lignin from natural biomass, which is even whiter than native cellulolytic enzyme lignin (CEL). The isolated lignin possessed a high recovery yield (97.36%), regular micro-spherical morphology, enriched β-ether linkage of 58/100Ar, low phenolic hydroxyl content of 1.25 mmol g -1 , minimal carbonyl content of 0.70 mmol g -1 , and less condensed structures, thus yielding a lower content of chromophores. Further, this lignin showed excellent sunscreen effects, which could enhance the SPF of a commercial sunscreen from 15 to 40 with only 5 wt% addition. This study can provide essential guidance for the scale-up production of light-color lignin and obtaining near-complete digestible cellulose for further saccharification.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Paired Hydro-Battery Hybrid System Operations Using MIQP Based Multi-Objective Optimization

Hybridizing a hydropower plant with a battery energy storage system is often a very expensive decision. So to make the case for feasibility of hybridization the cost benefit analysis must be comprehensive. Most literature found on this subject only uses one out of many different available value streams to carry out a feasibility analysis. To that end, in this study we propose a multi-objective optimization formulation and a mixed-integer quadratic programming optimization engine that considers multiple different value streams and optimizes hydro-battery hybrid system paired operations to maximize revenue generated from energy arbitrage while simultaneously minimizing the total hydro turbine mileage thus reducing turbine starts and stops and improving turbines life all while following all environmental constraints and not violating any limitations either regulatory or preferential (i.e., to support recreational activities like white water rafting, etc.). In this study we also implemented the developed optimization methodology to a real-world case study of Bagnell dam hydropower facility (8 units totaling 240 MW rated power capacity) which is owned and operated by our industry partner Ameren Energy Inc. The case study outcomes shows that by hybridizing the Bagnell dam hydropower facility with a 60 MW x 2-hr battery energy storage system, the annual benefits can be increased over \$6 million while reducing the annual mileage averaged per turbine and number of start/stops by over 98\% and 85\% respectively.

Chalishazar, Vishvas H.↗

DOE OSTI2022

A Process with Decoupled Absorber Kinetics and Solvent Regeneration through Membrane Dewatering and In-Column Heat Transfer (Final Report)

This report summarizes the work conducted on project DE-FE0031604 where University of Kentucky Center for Applied Energy (UK CAER) has validated its intensified CO 2 capture process through substantial enhancements to the kinetics of the absorption process and energy reductions by absorber temperature profile modification, dewatering and heat integration technologies for achieving significant capital and operating cost reductions. To address DOE’s objective of improving post-combustion CO 2 capture technology and reducing associated cost, UK CAER employed an intensified process which combined three key aspects targeted at overcoming inherent limitations or barriers in the conventional CO 2 capture and desorption process. The process designed to be independent of the type of solvent used, included (1) the use of 3-D printed two-channel structured packing material to control the temperature profile and increase the CO 2 absorption rate in the absorber, (2) a zeolite membrane dewatering unit for dewatering of the carbon-rich solvent to decouple solvent concentration needs for CO 2 absorption and desorption, and (3) a rich-split feed with two-phase flow heat transfer prior to the stripper that provided a secondary point of vapor generation to provide energy savings in steam extraction and solvent regeneration. The project was executed over two budget periods. This involved testing of individual process components which included the advanced heat transfer packing and the dewatering membrane on UK CAER’s 30 liter per minute (L/min) CO 2 (3” Column) capture bench unit with simulated flue gas in the first budget period. Subsequent scaled-up testing of these components together with the split-feed configuration were also tested in UK CAER’s 0.1 MWth CO 2 capture unit with coal-derived flue gas in the second-budget period. Long term studies were done during this period to assess process and solvent performance over extended duration. Project partners Lawrence Livermore National Laboratory (LLNL) and Media & Process Technology (MPT) led the development efforts for the advanced packing material and dewatering membrane respectively. Data from the long term testing was used as input for an environmental, health and safety (EH&S) assessment for the process and scaled technology performed by ALL4 LLC. Trimeric Corporation also completed a techno-economic analysis (TEA) for the UK CAER technology which was compared to the DOE reference Case B12B. Tests on the 3” column capture unit showed that the advanced heat transfer packing could be used to lower the bulge temperature in the absorber, and this was also proven in the scaled testing in the 0.1 MWth CO 2 capture unit. The bulge temperature could be lowered by >10 °C, changing the temperature profile in the absorber, and showed potential to enhance absorption with the ability to tailor the profile to provide conditions suitable for a solvent’s properties and kinetics. Conditions for short term evaluation of a 19” zeolite dewatering membrane on the 3” column capture unit yielded desirable fluxes and sustained rejection rates of >80%. However, for the scaled testing of six membrane modules consisting of 21 parts of 31-inch-long membrane tubes in each bundle (surface area 0.3 m 2 ), over a more extended duration, similar rejection rates could not be achieved. With the split-feed of the rich stream to the stripper, improved heat recovery minimized waste heat exiting the top of the stripper. The stripper exhaust temperatures could be reduced by >10 °C; reducing the amount of water vaporization contributed to lowering the regeneration energy by ~ 15%. The energy benefit could be sustained from the long term monitoring of the solvent performance. The solvent properties were not significantly impacted over the long-term operations. The benefits of the UK CAER process demonstrated experimentally were mostly validated from the TEA comparing a commercial scale application of the technology to DOE reference Case B12B. The cost of CO 2 capture for the UK CAER technology was estimated to be ~$34.97/tonne of CO 2 captured; a reduction of 23% compared to Case B12B. The increase in cost of electricity was also shown to be 16% lower than that of Case B12B. The total parasitic demand was also shown to be 11% lower. The key drivers for the benefits are a result of the process intensification approaches employed in the UK CAER technology for enhanced solvent performance, effective heat recovery and improved energy performance. The EH&S assessment did not find any major environmental concerns or barriers to the full scale implementation of the technology.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2021

Distributed ADMM Using Private Blockchain for Power Flow Optimization in Distribution Network With Coupled and Mixed-Integer Constraints

The optimization problem for scheduling distributed energy resources (DERs) and battery energy storage systems (BESS) integrated with the power grid is important to minimize energy consumption from conventional sources in response to demand. Conventionally this optimization problem is solved in a centralized manner, limiting the size of the problem that can be solved and creating a high communication overhead because all the data is transferred to the central controller. These limitations are addressed by the proposed distributed consensus-based alternating direction method of multiplier (DC-ADMM) optimization algorithm, which decomposes the optimization problem into subproblems with private cost function and constraints. The distribution feeder is partitioned into low coupling subnetworks/regions, which solves the private subproblem locally and exchanges information with the neighboring regions to reach consensus. The relaxation strategy is employed for mixed-integer and coupled constraints introduced in the optimal power flow (OPF) problem by stationary and transportable BESS because DC-ADMM convergence is only guaranteed for strict convex problems. The information exchange and synchronization between subnetworks/regions are vital for distributed optimization. In this work, both of these aspects are addressed by the blockchain. The smart contract deployed on the blockchain network acts as a mediator for secure data exchange and synchronization in distributed computation. The blockchain-based distributed optimization problem’s effectiveness is tested for a 0.5-MW laboratory microgrid for one hour ahead and day-ahead for the IEEE 123-bus and EPRI J1 test feeders, and results are compared with a centralized solution.

25 ENERGY STORAGE↗

DOE OSTI2020

Effect of reacting gas flowrates and hydration on the carbonation of anion exchange membrane fuel cells in the presence of CO 2

Anion exchange membrane fuel cells (AEMFCs) have been widely touted as a low-cost alternative to existing proton exchange membrane fuel cells. However, one of the limitations of this technology has been the severe performance penalty related to the introduction of CO 2 to the cell – typically in the air cathode feed. Introduction of CO 2 into AEMFCs results in cell carbonation, which imparts thermodynamic, kinetic and Ohmic overpotentials that can add up to hundreds of millivolts. Therefore, it is important to find strategies and operational protocols for AEMFCs that minimize these overpotentials. In this paper, we reserach the impacts of the anode and cathode flowrate, as well as the cell hydration level, on the extent of cell carbonation and cell polarization. Key findings include: (1) decreasing the cathode flowrate generally decreases the total CO 2 -related voltage loss while changing the anode flowrate has a minimal effect; (2) increasing cell hydration helps to mitigate the performance loss in the presence of CO 2 ; and (3) operational combinations are found that significantly reduce the CO 2 penalty compared to the present literature.

25 ENERGY STORAGE↗