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At least 451 records · Page 25

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DOE OSTI2021

Detailed Evaluation of Electric Demand Load Shifting Potential of Heat Pump Water Heaters

Future utilities will emphasize home appliances to reduce greenhouse gas emissions while providing electric load shifting and demand profile management. Heat pump water heaters (HPWH) have demonstrated the ability to cut water heating energy by more than 65% compared with conventional electric resistance waters (ERWH). Laboratory research was conducted on the load shifting potential of grid-connected heat pump water heaters (HPWH), compared to ERWHs. Testing applied different CTA-2045 command designs. Highly-controlled laboratory experiments were conducted on one ERWH and four HPWHs, including a prototype incorporating the new CTA-2045-B protocol feature allowing ‘advanced’ load up above the tank setpoint. The prototype unit with the B-protocol increased tank temperature by 15oF (8.3C) under the advanced load up providing an increase of 1.8 kWh of storage for a 50-gallon (189 liter) tank. The prototype includes a built-in mixing valve to meet anti-scalding codes. With the load-shaping ability of CTA-2045-B, utilities might be able to store excess renewable energy in connected tanks when renewable wind and solar resource production is high. Tests were performed under baseline conditions (no load shift) and under several load-shifting schemes, including load up and advanced load up, ahead of shed commands. Grid-connected HPWHs reduced peak demand by as much as 0.5 kW, depending on tank volume, time of day, control scheme, and draw profile.

heat pump water heater, Demand flexibility, load s↗

DOE OSTI2022

2020 Solar Decathlon Education Partner: Cooperative Research and Development (Final Report, CRADA Number CRD-19-00802)

The U.S. Department of Energy Solar Decathlon (DOE/SD) is a collegiate competition, comprising 10 contests, that challenges student teams to design and build highly efficient and innovative buildings powered by renewable energy. The winners will be those teams that best blend architectural and engineering excellence with innovation, market potential, building efficiency, and smart energy production. The DOE/SD is comprised of two Challenges--Design Challenge (annual, in April of each year at NREL in Golden, Colo.) and Build Challenge (biennial, held next in June/July 2020 in Washington D.C.). NREL provides competition management for DOE/SD. For over 35 years, EEBA has provided the most trusted resources for building science information and education in the construction industry. EEBA delivers turn-key educational resources and events designed to transform residential construction practices through high performance design, marketing, materials, and technologies. NREL and EEBA establish this CRADA to enable the success of the DOE/SD program in managing sponsorship funds and creating a professional education program. EEBA acted as an Education Partner to DOE/SD, which included: 1) accepting and dispersing sponsorship funds for DOE/SD; and 2) providing professional development content.

14 SOLAR ENERGY↗

DOE OSTI2021

Deep Analysis Net with Causal Embedding for Coal-fired Power Plant Fault Detection and Diagnosis (DANCE4CFDD)

Fault detection and diagnosis is critical to power plant operation to ensure attaining high reliability while reducing operation cost. As more renewable power is introduced to the power grid, traditional fossil power plants take on the extra burden of excessive load cycling to compensate the generation variability from renewable power. Such load cycling will pose more reliability challenges to power plant operation. There are a number of challenges faced by today’s asset health management system in coal- fired (or gas) power plants: 1) high-dimensional nonlinear interaction among multiple time series measurements; 2) high measurement variance induced by operational conditions/modes; 3) variation among asset types and plant configurations; and 4) a small number of faulty events to learn from. To cope with these challenges, today’s fielded asset health management systems rely heavily on manual efforts from domain experts and hand-crafted features or rules based on domain knowledge. Despite its role in plant reliability, such a practice is costly and hinders its scalability and sustainability, particularly when a plant undergoes modifications. The objective of this project is to develop a novel end-to-end AI learning system that is trainable (i.e., the AI representation of a complex system behavior can be directly learned from properly labeled data) for accurate fault detection and root cause analysis. The ability to create a fault detection model directly from time series could alleviate the efforts associated with today’s asset management solution development. In the course of this project, we have achieved the following: Created an AI model development environment incorporating state-of-the-art neural network architectures for rapid model development and evaluation; Developed novel learning strategies for training of fault detection model; Developed special-purpose neural network architecture embedded with variable association graph aiming for better interpretability; Developed a learning strategy to leverage a small number of faulty events for enhanced fault detection capability; Conducted detailed experimental study based on public benchmark datasets and demonstrated the effectiveness of the proposed solution; and Validated the developed system with data from both a coal-fired plant boiler dynamic simulation model and real-world coal-fired power plant covering multiple asset and fault types. Overall, the project attained a technology readiness level of TRL 5 from TRL 2 at the beginning of the project.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2025

Dynamic Model Development of a Wind Power Plant Using Neural Net Method to Forecast Wind Power Output (CRADA Final Report)

This project is intended to model wind power plant based on monitored data at the wind power plant. This project will promote the university research in Renewable Energy area and trains the future highly qualified engineers. The dynamic model will be based on neural net model with the input from the two met towers (12 inputs), and the number of turbines in operation (one input). The overall input will be 13 inputs to drive the simulations. The output power at the point of interconnection will be used to tune the neural net weight coefficients. Two neural net concepts will be investigated (the back propagation neural net and the dynamic recurrent neural net with feedback).

17 WIND ENERGY↗

DOE OSTI2025

A high-throughput experimentation platform for data-driven discovery in electrochemistry

Automating electrochemical analyses combined with artificial intelligence is poised to accelerate discoveries in renewable energy sciences and technologies. This study presents an automated high-throughput electrochemical characterization (AHTech) platform as a cost-effective and versatile tool for rapidly assessing liquid analytes. The Python-controlled platform combines a liquid handling robot, potentiostat, and customizable microelectrode bundles for diverse, reproducible electrochemical measurements in microtiter plates, minimizing chemical consumption and manual effort. To showcase the capability of AHTech, we screened a library of 180 small molecules as electrolyte additives for aqueous zinc metal batteries, generating data for training machine learning models to predict Coulombic efficiencies. Key molecular features governing additive performance were elucidated using Shapley Additive exPlanations and Spearman’s correlation, pinpointing high-performance candidates like cis-4-hydroxy-d-proline, which achieved an average Coulombic efficiency of 99.52% over 200 cycles. The workflow established herein is highly adaptable, offering a powerful framework for accelerating the exploration and optimization of extensive chemical spaces across diverse energy storage and conversion fields.

Lin, Dian-Zhao [Johns Hopkins University, Baltimor↗

DOE OSTI2021

Developing Southeast Asia Solar Resource Data to Support the Clean Energy Transition in the Region

This fact sheet describes the development and release of a high-fidelity solar time series data set for the entire Southeast Asia region, which can be used to drive energy sector investment, support enabling policies to support solar energy market expansion, and inform prospecting, renewable energy auctions, target-setting, grid integration and other high impact decisions, ranging from the micro to macro scale, to accelerate renewable energy deployment throughout SE Asia. This data is available on the enhanced and expanded RE Data Explorer (RE Explorer) platform.

Advanced Energy Partnership for Asia↗

DOE OSTI2024

Development of Tailored Hydrocarbon-Based Pentablock Copolymer Membranes for Sodium-Polysulfide Flow Batteries

Long-duration energy storage (LDES) technologies are pivotal for the adoption of renewables like wind and solar. Non-aqueous redox flow batteries (NARFBs) with a sodium-polysulfide hybrid system feature high energy density independent of power density, yet face challenges with polysulfide shuttling. This study investigates a hydrocarbon-based penta-block copolymer membrane, Nexar, to mitigate crossover effects by balancing TFSI conversion and their crosslink density. The membranes are annealed to induce crosslinking for reducing electrolyte uptake and enhancing mechanical stability while demonstrating excellent ionic conductivity. The hydrocarbon-based membranes address environmental concerns associated with perfluoroalkyl substances and improve the performance and durability of NARFBs. In conclusion, our findings suggest that annealed Nexar membranes with tailored TFSI functionality offer a scalable, cost-effective solution for enhancing the efficiency of high-capacity energy storage systems, pivotal for grid integration of renewable sources.

25 ENERGY STORAGE↗

DOE OSTI2023

Platinum group metal-free (PGM-free) integrated tandem junction photoelectrochemical (PEC) water splitting devices (Final Technical Report)

This project involves using solar light, a photoabsorber, and a catalyst to split water and produce hydrogen. The Department of Energy (DOE) targets for integrated photoelectrochemical (PEC) cells emphasize cost (electrode cost < $200/m 2 ), performance (> 15% solar to hydrogen (STH) efficiency), and stability (> 6 months electrode lifetime), but most approaches skew toward one specific metric. This project exploited interfacial integration of platinum group metal-free (PGM-free) catalysts on the high performance and high value tandem solar cells to attain or exceed the DOE benchmark STH energy conversion efficiency and durability. This was investigated in two thrusts by developing two PEC devices for direct comparison: the first is a high-performance monolithic device based on state-of-the-art GaInP 2 /GaAs tandem solar cells developed at National Renewable Energy Laboratory (NREL), and the second is a high-value device based on earth-abundant wide band gap photoabsorber materials including oxynitride and hybrid organic-inorganic perovskite (HOIP) coupled with commercial narrow band gap silicon (Si). Both these devices were paired with electrocatalysts developed for this purpose at Rutgers University by adapting them to thin films on the photoabsorbers. These catalysts are based on the hydrogen evolution reaction (HER) catalysts (Ni 5 P 4 ), oxygen evolution reaction (OER) catalysts (LiCo 2 O 4 ) previously developed at Rutgers for high-efficiency electrolyzers. For using the high-performance tandem solar cell and Ni 5 P 4 catalysts, we achieved a durability of > 200 h at a STH efficiency of > 10%. For using the high-value wide band gap single junction solar cells on n + Si, we achieved 0.73 mA/cm 2 at 1.23V vs reversible hydrogen electrode (RHE) and -15.9 mA/cm 2 at 0V vs RHE using the oxynitride- and HOIP-based photoelectrodes, respectively. After comparing their photocurrent densities, we down selected the HOIP photoabsorber to couple Si for fabrication of a tandem photocathode. However, due to the COVID-19 pandemic, both the laboratories at Rutgers and NREL were locked down for three months and reopened only partially in 2020. The HOIP/Si tandem photocathode using robust nickel phosphide thin film catalysts cannot be developed within the project period, which is expected to achieve a STH efficiency of > 20%. Also, the low-cost LiCo 2 O 4 OER catalysts need to replace the benchmark IrO 2 for evaluation. Finally, techonomic analysis of full high-performance and high-value integrated PEC devices needs to be carried out for comparison in terms of cost.

08 HYDROGEN↗

DOE OSTI2025

Characterizing the Potential for Sustainable Azelaic Acid Production from High-Oleic Vegetable Oil Using Two-Step Oxidative Cleavage

Azelaic acid is a renewable monomer conventionally produced via the energy-intensive ozonolysis of oleic acid. Recent advancements have enabled the use of high-oleic vegetable oils (rather than tallow-derived oleic acid) and replaced ozonolysis with two-step oxidative cleavage using hydrogen and oxygen. Although this shift would improve process safety, the financial viability and environmental implications remain uncertain. In this study, we characterized the sustainability of azelaic acid production from high-oleic vegetable oil using two-step oxidative cleavage. Process design, simulation, technoeconomic analysis (TEA), and life cycle assessment (LCA) were executed under uncertainty using BioSTEAM. The modeled system produces azelaic acid at a market-competitive minimum selling price (MSP) of 8.32 [4.93−13.34] $\$kg$ −1 (median 5th−95th percentiles), below the minimum estimated market price of 9.93 $\$kg$ −1 . Further, it has the potential to approach carbon neutrality (0.0 [−5.5 to 5.6] kg of CO 2 -eq kg −1 ) under displacement allocation. Improvements to dihydroxylation (86 to 99%) and oxidative cleavage conversions (93 to 99%) would reduce MSP to $\$5.24$ kg −1 and carbon intensity to −1.90 kg of CO 2 -eq kg −1 (displacement). Additionally, increasing the feedstock triolein content (75 to 85%) lowers MSP by $\$0.82$ kg −1 . Overall, this research demonstrates the potential for financially viable production of azelaic acid from vegetable oils and the utility of agile TEA/LCA.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Low Temperature Oxidation of Methylpropyl Ether

Ethers are potential high-performance fuels that can be produced from renewable carbon sources such as biomass, but their combustion properties are not clearly understood. The cetane numbers (CN) for ethers, a measure of autoignition tendency, can range from less than 10 to greater than 100, and predictive tools based upon the molecular structures are desirable in order to focus fuel development research. In this study, we used molecular modeling, chemical kinetic modeling, and experimental measurements to understand the important reactions that lead to the autoignition of methylpropyl ether (MPE), a model for ethers containing alkyl chains long enough for intramolecular hydrogen transfer. These reactions are known to be important in the autoignition of alkanes and ethers and we propose to investigate the relationship between alkyl and ether reaction pathways. A reaction mechanism for MPE was created using MIT's Reaction Mechanism Generator (RMG) and G4 quantum calculation results and models were tested using the ChemKin Pro suite of software. Results from atmospheric pressure, flow tube reactor experiments and rapid compression machine (RCM) experiments were used to test the kinetic model and suggest refinements.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2020

Effects of Deep Reductions in Energy Storage Costs on Highly Reliable Wind and Solar Electricity Systems.

We use 36 years (1980-2015) of hourly weather data over the contiguous United States (CONUS) to assess the impact of low-cost energy storage on highly reliable electricity systems that use only variable renewable energy (VRE; wind and solar photovoltaics). Even assuming perfect transmission of wind and solar generation aggregated over CONUS, energy storage costs would need to decrease several hundred-fold from current costs (to ~$1/kWh) in fully VRE electricity systems to yield highly reliable electricity without extensive curtailment of VRE generation. The role of energy storage changes from high-cost storage competing with curtailment to fill short-term gaps between VRE generation and hourly demand to near-free storage serving as seasonal storage for VRE resources. Energy storage faces "double penalties" in VRE/storage systems: with increasing capacity, (1) the additional storage is used less frequently and (2) hourly electricity costs would become less volatile, thus reducing price arbitrage opportunities for the additional storage.

14 SOLAR ENERGY↗

DOE OSTI2024

Ultra-stable trimetallic phosphide heterostructure with regulated electronic structure for overall water splitting at high current densities

Developing ultra-stable electrocatalysts for highly efficient overall water splitting at high current density (HCD) is critical for renewable hydrogen/oxygen production in the industry. However, the most active electrocatalysts for large current-driven water splitting are seriously handicapped by insufficient electrical contact kinetics due to the intensive bubble overflow. Herein, we demonstrate the ultra-stable trimetallic phosphides of NiFeP/NiCoP catalysts on a hydrophilic Ni foam skeleton via a corrosion-hydrothermal-phosphating strategy. The optimized NiFeP/NiCoP catalyst stabilizes for 600 h at -1 A cm -2 for hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) in alkaline solution, and it only needs low overpotentials of 237 and 314 mV to drive HER and OER at 1 A cm -2 , respectively. As expected, the optimized NiFeP/NiCoP electrode maintains 1000 h at 0.5 A cm -2 for water splitting, ranking among the top performers among reported catalysts. Such excellent performance could be attributed to the fast electron transfer for electrochemical reactions, the electron-deficient Fe/Ni sites contribute to forming robust metal oxyhydroxide during OER, and electron-rich Co sites facilitate H adsorption during HER. In conclusion, the findings present a highly promising candidate for ultra-stable non-noble metal electrocatalysts, offering a viable option for hydrogen/oxygen supply for fuel cells and metal-air batteries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Transforming Energy Through Computational Excellence: A View From NREL

At the National Renewable Energy Laboratory (NREL)—a U.S. Department of Energy laboratory—computational science, high-performance computing, applied mathematics, advanced computer science, visualization, and data play a pivotal role in advancing energy abundance, affordability, security, and reliability. From fundamental scientifc discovery to systems engineering and analysis, NREL researchers tackle market-relevant challenges to develop solutions for an independent energy system that is reliable, resilient and secure. Collaborative partnerships with industry, government, and academia ensure that our research remains cutting edge, impactful, applicable, and aligned with real-world energy needs. This special issue of Computing in Science & Engineering highlights exemplary NREL projects where computational tools and methodologies drive discovery and accelerate innovation in scalable and integrated energy systems. The featured articles explore the role of computational modeling, high-performance computing, generative AI, and adaptive computing in advancing independent energy solutions, optimizing sustainability research, and enhancing decision-making for energy solutions using a broad mix of energy technologies. Here, these contributions demonstrate how NREL’s computational research bridges the gap between theoretical advancements and practical implementation, emphasizing interdisciplinary collaboration and a commitment to innovation, with a focus on translating computational excellence into real-world impact, thus accelerate progress toward national energy goals. By showcasing cutting-edge research at the intersection of computational science and energy systems, this issue aims to inspire and inform researchers, practitioners, and policymakers dedicated to shaping a more reliable energy future.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

High-temperature thermal energy storage with thermophotovoltaic energy conversion (Final Report)

This project began with a simple concept: that thermal energy storage paired with thermophotovoltaic power conversion could be a cost-effective solution to the challenge of renewables variability. Renewable energy sources such as solar and wind energy are clean, affordable, and abundant worldwide, but their variability presents a major problem for the incorporation of a large amount of these resources in global power systems. Systems with high penetrations of renewables frequently see periods of overproduction, where renewable energy is thrown away, and periods of underproduction, where expensive and polluting fossil fuel resources must be used to fill in the gaps. While energy storage technologies such as lithium ion batteries can help store energy from times of overproduction to times the energy is needed, current and projected future prices for these technologies are not low enough to support very renewables-heavy power grids. The research also focused on the techno-economics of using thermal energy storage and thermophotovoltaics to store the energy from solar and wind energy sources when they are available and release this energy back to the grid when it is needed. One of the biggest outcomes of this research was the conclusion that battery prices must drop 10x from their current values in order to meet this need, and this is unlikely to happen with current technologies such as lithium ion batteries.

14 SOLAR ENERGY↗

DOE OSTI2021

The Solar Curtailment Paradox

This presentation summarizes work recently published in a Joule article, "The Curtailment Paradox in the Transition to High Solar Power Systems." Rising penetrations of variable renewable energy (VRE) in power systems are expected to increase the curtailment of these resources because of oversupply and operational constraints. We evaluate the effect on curtailment from various flexibility approaches, including storage, thermal generator flexibility, operating reserve eligibility rules, transmission constraints, and temporal resolution, by using a highly resolved realistic system. Results reveal two aspects of a curtailment paradox as the system evolves to higher solar penetration levels. First, thermal generator parameters, especially in restricting minimum operating levels and ramp rates, affect VRE curtailment more in mid-PV penetration levels (~25%–40%) but much less at lower (~20%) or higher (~45%) PV penetration levels. Second, although allowing VRE and storage to provide operating reserve results in significant operating costs and curtailment benefits, the price suppression effect from these resources reduces incentives for PV to provide operating reserves with curtailed energy.

41 EE - Solar Energy Technologies Office (EE-4S)↗

DOE OSTI2022

Peer-to-Peer Energy Trading under Network Constraints Based on Generalized Fast Dual Ascent

We report the wide deployment of renewable energy resources, combined with a more proactive demand-side management, is inducing a new paradigm in both power system operation and electricity market trading, which especially boosts the emergence of the peer-to-peer (P2P) market. A more flexible local market mechanism is highly desirable in response to fast changes in renewable power generation at the distribution network level. Moreover, large-scale implementation of P2P energy trading inevitably affects the secure and economic operation of the distribution network. This paper presents a new P2P electricity trading framework with distribution network security constraints considered using the generalized fast dual ascent method. First, an event-driven local P2P market framework is presented to facilitate short-term or immediate local energy transactions. Then, the sensitivity analysis of nodal voltage and network loss with respect to nodal power injections is used to evaluate the impacts of P2P transactions on the distribution network, which ensures the secure operation of the distribution system. Thereby, the external operational constraints are internalized, and the cost of P2P energy trading can be appropriately allocated in an endogenous way. Moreover, a generalized fast dual ascent method is employed to implement distributed market-clearing efficiently. Finally, numerical results indicate that the proposed model could guarantee secure operation of the distribution system with P2P energy trading, and the solution method enjoys good convergence performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Simulation of Cross-Border Renewable Energy Trading in South Asia [Slides]

India's national renewable energy zones for wind power and solar photovoltaics (PV) could become regional green power resources if South Asian countries liberalize their rules for cross-border energy trading (CBET). Similarly, Nepal's wealth of hydropower could be more valuable to Nepal and its neighbors with greater market integration. These are the findings of a study by the U.S. National Renewable Energy Laboratory (NREL) that tested trading scenarios for wind power, solar power, and hydropower among Bangladesh, India, Nepal, and Sri Lanka. The NREL study found that wheeling power through India's interstate transmission system (ISTS) could be just as efficient operationally as building new high-voltage direct current (HVDC) lines from the renewable energy zones directly to the importing country. This means that CBET integration could substitute for new long-distance HVDC transmission - which could cost billions of dollars - while delivering to all participating countries the same benefits for renewable energy development and decarbonization.

13 HYDRO ENERGY↗

DOE OSTI2020

Cross-Border Electricity Trading and Renewable Energy Zones

14 SOLAR ENERGY↗