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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 937 records · Page 52

Low Intensity Low Temperature (LILT) measurements and coefficients on new photovoltaic structures

Past NASA missions to Mars, Jupiter, and the outer planets were powered by radioisotope thermal generators (RTG's). Although these devices proved to be reliable, their high cost and highly toxic radioactive heat source has made them far less desirable for future planetary missions. This has resulted in a renewed search for alternate energy sources, some of them being photovoltaic (PV) and thermophotovoltaic (TPV). Both of these alternate energy sources convert light/thermal energy directly into electricity. In order to create a viable PV and TPV data base for planetary mission planners and cell designers, we have compiled low temperature low intensity (LILT) I-V data on single junction and multi-junction high efficiency solar cells. The cells tested here represent the latest photovoltaic technology. Using this LILT data to calculate dI(sub SC)/dT, dV(sub OC)/dT, dFF/dT, and also as a function of intensity, an accurate prediction of cell performance under the AMO spectrum can be determined. When combined with QUantum efficiency at Low Temperature (QULT) data, one can further enhance the data by adding spectral variations to the measurements. This paper presents an overview of LILT measurements and is only intended to be used as a guideline for material selection and performance predictions. As single junction and multi-junction cell technologies emerge, new test data must be collected. Cell materials included are Si, GaAs/Ge, GainP/GaAs/Ge, InP, InGaAs/InP, InP/InGaAs/InP, and GainP. Temperatures range as low as -175 C and intensities range from 1 sun to .02 suns.

Schelman, David A.↗

From Data to Discovery: AI's Transformative Role in Thin Film Research

The advancement of thin film technologies is pivotal for progress in numerous fields, including energy, electronics, and quantum computing. However, the traditional trial-and-error approach to materials discovery is inherently slow and inefficient. This presentation will showcase how artificial intelligence (AI) is transforming thin film research by enabling a data-driven paradigm shift. We will highlight our past successes in applying AI to understand radiation damage in thin film oxides, demonstrating how graph analytics can unravel complex material behavior. Additionally, we will provide insights into our current work at the National Renewable Energy Laboratory, where we are leading the charge in autonomous materials science. Backed by a $14M investment in our characterization facility, we are developing AI-guided workflows that seamlessly integrate experimentation and AI-guided decision-making. By harnessing the power of AI, we aim to accelerate the discovery and design of high-performance thin films, propelling innovation across a multitude of industries.

36 MATERIALS SCIENCE↗

TEAMER - AquaHarmonics High Fidelity WEC Sim PTO and Control Model Validation, Sim Model

Collaborative effort between AquaHarmonics, Sandia National Laboratories (SNL), and the National Renewable Energy Laboratory (NREL) to revise and validate Aquaharmonics' full wave to wire model, allowing for reduced uncertainty and increased understanding of design requirements of a utility scale wave energy converter (WEC). SNL and NREL in collaboration with AquaHarmonics, will set up and run WEC Simulator (WEC-Sim) models of the AquaHarmonics WEC, building off past model developments for inclusion of custom PTO (power take-off) dynamics. The intent is to review, update, and verify or validate a new WEC-Sim model against wave tank experimental data. Furthermore, the WEC-Sim model will be coupled to an energy storage system model to better understand the wave-to-wire functionality. Project is part of the TEAMER (Testing & Expertise for Marine Energy) RFTS (request for technical support) system of WEC research projects. Testing data can be found in the associated MHKDR link below.

16 TIDAL AND WAVE POWER↗

A parcel-level evaluation of distributed wind opportunity in the contiguous United States

This study examines the potential for distributed wind (DW) energy across the contiguous United States, leveraging advancements in the National Renewable Energy Laboratory's distributed wind model, dWind. The novel modeling approach described here utilizes a high-resolution dataset and analyzes over 150 million parcels, a significant improvement from prior methods that extrapolated results from a smaller random sample. This achievement is enabled through key model performance improvements, such as transitioning to multiprocessing, which reduces runtime by 97 %. This optimized, high-resolution approach allows the inspection of technology deployment potential and impact on a variety of scales tailored to individual properties and regions. The results here align with prior work showing substantial opportunity for energy generation using DW technologies. Key findings reveal a substantial increase from prior results in estimated technical and economic potential for DW. Metrics tuned to highlight economic potential also show increased incentives supporting rural adoption. Results are spatially aggregated for usability and published via the U.S. Department of Energy Wind Data Portal and a custom scenario visualization platform, aiding policymakers, industry, and property owners in assessing DW viability across various scenarios and spatial scales.

17 WIND ENERGY↗

Economic Analysis of an Electric Thermal Energy Storage System Using Solid Particles for Grid Electricity Storage

As renewable power generation becomes the mainstream new-built energy source, energy storage will become an indispensable need to complement the uncertainty of renewable resources to firm the power supply. When phasing out fossil-fuel power plants to meet the carbon neutral utility target in the midcentury around the world, large capacity of energy storage will be needed to provide reliable grid power. The renewable power integration with storage can support future carbon-free utility and has several significant impacts including increasing the value of renewable generation to the grid, improving the peak-load response, and balancing the electricity supply and demand. Long-duration energy storage (10–100 hours duration) can potentially complement the reduction of fossil-fuel baseload generation that otherwise would risk grid security when a large portion of grid power comes from variable renewable sources. Current energy storage methods based on pumped storage hydropower or batteries have many limitations. Thermal energy storage (TES) has unique advantages in scale and siting flexibility to provide grid-scale storage capacity. A particle-based TES system has promising cost and performance for the future growing energy storage needs. This paper introduces the system and components required for the particle TES to be technically and economically competitive. A technoeconomic analysis based on preliminary component designs and performance shows that the particle TES integrated with an efficient air-Brayton combined cycle power system can provide power for several days by low-cost, high-performance storage cycles. It addresses grid storage needs by enabling large-scale grid integration of intermittent renewables like wind and solar, thereby increasing their grid value. The design specifications and cost estimations of major components in a commercial scale system are presented in this paper. The cost model provides insights for further development and cost comparison with competing technologies.

27 ARPA - Advanced Research Projects Agency-Energy↗

Economic Analysis of a Novel Thermal Energy Storage System Using Solid Particles for Grid Electricity Storage: Preprint

As renewable power generation becomes the mainstream new-built energy source, energy storage will become an indispensable need to complement the uncertainty of renewable resources to firm the power supply. When phasing out fossil-fuel power plants to meet the carbon neutral utility target in the midcentury around the world, large capacity of energy storage will be needed to provide reliable grid power. The integration of renewable power and storage to support future carbon-free utility has several significant and positive impacts including expanding the renewable generation into the grid, improving the peak-load response, and balancing the electricity supply and demand. Long-duration energy storage (10–100 hours duration) can potentially complement the reduction of fossil-fuel baseload generation that otherwise would risk grid security when a large portion of grid power comes from variable renewable sources. Current energy storage methods based on pumped storage hydropower or batteries have many limitations. Thermal energy storage (TES) has unique advantages in scale and siting flexibility to provide grid-scale storage capacity. A particle-based TES system has promising cost and performance for the future growing energy storage needs. This paper introduces the system and components required for the particle TES to be technically and economically competitive. A technoeconomic analysis based on preliminary component designs and performance shows that the particle TES integrated with an efficient air-Brayton combined cycle power system can provide power for several days by low-cost, high-performance storage cycles. It addresses grid storage needs by enabling large-scale grid integration of intermittent renewables like wind and solar, thereby increasing their grid value. The design specifications and cost estimations of major components in a commercial scale system are presented in this paper. The cost model provides insights for further development and cost comparison with competing technologies.

27 ARPA - Advanced Research Projects Agency-Energy↗

High-energy and low-cost membrane-free chlorine flow battery

Abstract Grid-scale energy storage is essential for reliable electricity transmission and renewable energy integration. Redox flow batteries (RFB) provide affordable and scalable solutions for stationary energy storage. However, most of the current RFB chemistries are based on expensive transition metal ions or synthetic organics. Here, we report a reversible chlorine redox flow battery starting from the electrolysis of aqueous NaCl electrolyte and the as-produced Cl 2 is extracted and stored in the carbon tetrachloride (CCl 4 ) or mineral spirit flow. The immiscibility between the CCl 4 or mineral spirit and NaCl electrolyte enables a membrane-free design with an energy efficiency of >91% at 10 mA/cm 2 and an energy density of 125.7 Wh/L. The chlorine flow battery can meet the stringent price and reliability target for stationary energy storage with the inherently low-cost active materials (~$5/kWh) and the highly reversible Cl 2 /Cl − redox reaction.

25 ENERGY STORAGE↗

A Renewed Search for Elusive Lunar Granophyres

Recent remote sensing studies [e.g., 1-3] indicate that several un-sampled regions of the Moon have significantly higher concentrations of silicic material (also high in [K], [U], and [Th]) than sampled regions. Within these areas are morphological features that are best explained by the existence of chemically evolved volcanic rocks. Observations of silicic domes [e.g., 1-5] suggest that sizable networks of silicic melt were present during crust-formation. Because of these recent findings there is a renewed interest in the petrogenesis of lunar, felsic igneous rocks. Specific questions are: (1) when were these magmas generated?, and (2) what was the source material? The two main hypotheses for generating silicic melts on Earth are fractional crystallization or partial melting of preexisting crust. On the Moon silicic melts are thought to have been generated during extreme fractional crystallization involving end-stage silicate liquid immiscibility (SLI) [e.g. 6, 7]. However, SLI cannot account for the production of significant volumes of silicic melt and its wide distribution, as reported by the remote global surveys [1, 2, 3]. In addition, experimental and natural products of SLI show that U and Th, which are abundant in the lunar granites and seen in the remote sensing data of the domes, are preferentially partitioned into the depolymerized ferrobasaltic magma and not the silicic portion [8, 9]. If SLI is not the mechanism that generated silicic magmas on the Moon then alternative processes such as fractional crystallization (only crystal-liquid separation) or partial melting should be considered as viable possibilities to be tested.

Mills, R. D.↗

Critical Materials Supply Chain White Paper (April 2020)

The DOE Office of Energy Efficiency and Renewable Energy (EERE) Advanced Manufacturing Office (AMO) partners with industry, small business, universities, and other stakeholders to identify and invest in emerging technologies with the potential to create high-quality domestic manufacturing jobs and enhance the global competitiveness of the United States

Advanced Manufacturing Office↗

Pulsed Light Synthesis of High Entropy Nanocatalysts with Enhanced Catalytic Activity and Prolonged Stability for Oxygen Evolution Reaction

The ability to synthesize compositionally complex nanostructures rapidly is a key to high-throughput functional materials discovery. In addition to being time-consuming, a majority of conventional materials synthesis processes closely follow thermodynamics equilibria, which limit the discovery of new classes of metastable phases such as high entropy oxides (HEO). Herein, a photonic flash synthesis of HEO nanoparticles at timescales of milliseconds is demonstrated. By leveraging the abrupt heating and cooling cycles induced by a high-power-density xenon pulsed light, mixed transition metal salt precursors undergo rapid chemical transformations. Hence, nanoparticles form within milliseconds with a strong affinity to bind to the carbon substrate. Oxygen evolution reaction (OER) activity measurements of the synthesized nanoparticles demonstrate two orders of magnitude prolonged stability at high current densities, without noticeable decay in performance, compared to commercial IrO 2 catalyst. This superior catalytic activity originates from the synergistic effect of different alloying elements mixed at a high entropic state. It is found that Cr addition influences surface activity the most by promoting higher oxidation states, favoring optimal interaction with OER intermediates. The proposed high-throughput method opens new pathways toward developing next-generation functional materials for various electronics, sensing, and environmental applications, in addition to renewable energy conversion.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Economic dispatch of offshore renewable energy resources for islanded communities with optimal storage sizing

Coastal or isolated microgrids depend on diesel generators and could benefit from renewable energy resources, especially offshore wind and wave energy. Integrating these resources into microgrids is complicated by their high intermittency, which requires optimal economic dispatch to effectively evaluate. This study considers three coastal or islanded sites, and uses mid-fidelity models of wind and wave energy technologies, and local demand data to solve the optimal economic dispatch problem. An optimal storage sizing method is developed that finds the smallest capacity of energy storage required to meet the microgrid load during each season. The storage capacity decreases by a factor of two at most when adding wave energy converters to a system. Adding wave energy converters to a farm decreases cost by about 30%. Furthermore, the required storage size varies by two to three times from summer to winter. Compared with the state-of-the-art approaches that often overlook realistic offshore renewable energy technology in microgrid economic dispatch and optimal storage sizing, the proposed solution introduced in this study allows for better site selection, microgrid design, converter selection, and storage sizing considerations for isolated microgrids.

16 TIDAL AND WAVE POWER↗

Sub-pilot-scale Production of High-Value Products from U.S. Coals

Investigators from the University of Utah, University of Wyoming and Marshall University pursued a program to study the conversion of raw coal to high-value products of carbon fiber and silicon carbide. Team members also developed an initial framework for a data portal that can incorporate laboratory data on coal processing and product quality, and also work with tools for machine learning for data analysis, data visualization and economic assessment. Experimental R&D efforts focused on the conversion of raw coal to coal tar and other byproducts, and the resulting tar intermediates were upgraded to form anisotropic and isotropic pitch materials. These pitch materials were produced from coal using both thermal (pyrolysis) and chemical (mild solvolysis liquefaction) decomposition of raw coal. Four different coals were studied: Utah bituminous coal (Sufco), Wyoming PRB coal (Black Thunder), Illinois bituminous coal (Illinois #6), and West Virginia bituminous coal (Flying Eagle). Both metallurgical-grade coking coals and lower-grade steam coals were investigated, and controlled secondary gas-phase reactions were used during a two-stage pyrolysis process to induce cracking and condensation reactions among the pyrolytic tar species. This approach successfully improved the performance of the lower grade coals for yielding pitch materials, with properties more consistent with a commercial-grade pitch that had previously demonstrated success for quality carbon fiber production. The use of waste plastic materials was also studied, to help improve physical and chemical characteristics of the intermediate tars and final pitch product; in particular, for lowering the pitch softening point to an acceptable level for melt spinning carbon fiber. Mild solvolysis liquefaction was also used as a method for producing pitch for carbon fiber production. As expected, significantly higher pitch yields were obtained using this approach, and waste plastic materials were also successfully used to reduce pitch softening point to an acceptable level. The plastic materials were also utilized to create a solvent for the mild solvolysis process, and this plastic-derived solvent was shown to provide results consistent with more expensive commercial chemical solvents, and could thus avoid the need for costly recovery and recycle of a liquefaction solvent. Additional experimental R&D focused on the production of silicon carbide (β-SiC) from the residual char byproduct from pitch production, and also on the production of carbon fiber from the anisotropic pitch. SiC was successfully synthesized using a mixture of residual char and sandstone at a ratio of 1:1. Reaction temperature and residence time were optimized and yielded a product purity of 81%. For carbon fiber production, the most successful pitch samples were obtained from the mild solvolysis liquefaction approach, combined with the use of a plastic (HDPE)-derived solvent. Fiber properties improved over time as laboratory fiber production methodologies improved, and final yields of carbon fiber were obtained with a diameter of 12.14 ± 1.10 um, Modulus of 173.73 ± 15.25 GPa, and Tensile Strength of 1.04 ± 0.10 GPa. A proof-of-concept Modern Community Research Data Portal (MCRDP) was developed and deployed for coal and coal-derived pitch characterization, with the full support of (i) remote web-based access, (ii) distributed analysis, (iii) interactive visualization and exploration, (iv) shared and long-term data access, (v) advanced query capabilities and (vi) real-time collaboration. The Coal to Products Data Portal “coaltoproducts.org” provides researchers with space to store and share data within a project, tools for analyzing and understanding data for scientific investigation, and the ability to publish data to the broader community for reproducibility. The portal leverages the Material Commons 2.0 (MC) platform developed by the Center for PRedictive Integrated Structural Materials Science (PRISMS) of the University of Michigan, to achieve long-term longevity of data collections and, more importantly, collaborative science. A number of data visualization tools were also assessed and implemented for interrogating the experimental and modeling data. The machine learning portion of this project analyzed datasets from two different coal conversion processes performed on a diverse set of coal samples from both the coal pyrolysis experiments and the solvent liquefaction experiments. The work was initiated by exploring standard regression models on the pyrolysis data, aiming to understand the impact of sample characteristics and processing conditions on key product metrics. Over the course of the project, the focus expanded to include a variety of machine learning tools, delving into both supervised and unsupervised learning methods. Models tested on the pyrolysis data included linear, ridge, lasso, elastic-net, Gaussian process, random forest regression, and AutoSklearn, and the approach was continually refined to enhance predictive accuracy and model interpretability. Similar techniques were applied to the liquefaction data with an additional focus on feature engineering. Along with mesophase content, additional outputs of interest were the pitch yield, softening point, and QI content. Insights derived from these analyses are crucial in determining the factors influencing the quality and yield of coal-derived products. As the work progressed, the research evolved from foundational model comparisons to analyses of random forests, decision paths, and feature importance scores. A thorough market analysis was performed to examine the prospects of coal-based carbon fibers. The best opportunities for coal come from its lower and more stable price relative to petroleum, particularly for subbituminous coals, which is the primary advantage that a coal refinery may have over a petroleum refinery. Before a commercial CTP production facility can be modeled, however, several things need to be understood regarding the nature of the would-be coal refinery. These include the technology to be deployed, the size of facility, the volume(s) of co-product(s), and the waste and emissions profile of the plant. The volume of co-products and waste may be substantial and will require separate market analysis to ensure viability. In the near-term, the importance of coal tar pitch, in the form of carbon pitch, to the aluminum and steel industries is likely to overshadow the alternative use of this material as an input for carbon fiber. The importance of steel and aluminum in building materials, and the need for carbon materials in their manufacturing, will ensure that demand for these products remains for the long run. In addition, carbon fiber may also be the best substitute for steel and aluminum well into the future. While society will eventually be able to shift production of much of its electricity needs to renewables, it will not be able to shift away from fossil fuels for production of high-strength construction and vehicular materials. Demand for carbon fiber is expected to increase quickly, but the volume of carbon fiber and the amount of coal that would be needed to produce even a sizeable share of this market may still be relatively small compared to current coal production. Thus, other coal-based products like graphene, graphite, carbon foams, resins, and carbon-based building products will play important roles in sustaining coal production as coal-fired power generation continues to decline.

01 COAL, LIGNITE, AND PEAT↗

Frequency-Nadir-Constrained Unit Commitment for Low-Inertia, High-IBR Island Power Systems [Slides]

The process of energy decarbonization in island power systems is accelerated due to the swift integration of inverter-based renewable energy resources (IBRs). The unique features of such systems, including rapid frequency changes resulting from potential generation outages or imbalances due to the unpredictability of renewable power, pose a significant challenge in maintaining the frequency nadir without external support. This paper presents a unit commitment (UC) model with data-driven frequency nadir constraints, including either frequency nadir or minimum inertia requirements, helping to limit frequency deviations after significant generator outages. The constraints are formulated using a linear regression model that takes advantage of real-world, year-long generation scheduling and dynamic simulation data. The efficacy of the proposed UC model is verified through a year-long simulation in an actual island power system using historical weather data. The alternative minimum inertia constraint, derived from actual system operation assumptions, is also evaluated. Findings demonstrate that the proposed frequency nadir constraint notably improves the system's frequency nadir under high photovoltaic (PV) penetration levels, albeit with a slight increase in generation costs, when compared to the alternative minimum inertia constraint.

14 SOLAR ENERGY↗

Grid Strength Assessment for High Levels of Inverter-based Resources in the Puerto Rico Power

A system-wide assessment of the Puerto Rico power system grid strength is studied when considering high levels of inverter-based resource penetration. This study is carried out in PSSE and assesses the impact of inverter-based resource (IBR) contributions in response to three-phase ground faults. A hypothetical 100% inverter-based generation scenario is created to assess the extreme impact on short circuit levels and a realistic scenario is considered to assess the impact to short circuit ratios. The overall conclusion is that short circuit capacity and current will drastically decrease in a high IBR scenario, an effect that is quantified in this paper. The short circuit ratio metric is typically used to assess the impact of IBR but generally overestimates grid strength due to not accounting for the impact from multiple IBRs. Other methods such as equivalent circuit based short circuit ratio and weighted short circuit ratio offer a more comprehensive consideration for multiple IBRs and can better account for their mutual interactions. The work presented in this paper is part of the PR100 study.

inverter based resources, PR100, grid strength↗

Hydrogen production from lignocellulosic hydrolysate in an up-scaled microbial electrolysis cell with stacked bio-electrodes

Hydrogen production from renewable resources via microbial electrolysis cells (MECs) is a promising approach for sustainable energy production. Yet high hydrogen yield from real feedstocks has not been demonstrated in up-scaled MECs. In this study, a 10-L single chamber MEC with a high electrode surface area to volume ratio (66 m 2 /m 3 ) was constructed and electroactive cathodic biofilms were enriched for hydrogen evolution reaction. A high hydrogen yield of 91% was achieved using lignocellulosic hydrolysate with a hydrogen production rate of 0.71 L/L/D at an organic loading rate of 0.4 g/D. The anodic and cathodic microbial communities, with Enterococcus spp. as the known electroactive bacteria, were capable of achieving current densities of 13.7 A/m 2 and 16.5 A/m 2 , respectively. Finally, a machine learning algorithm was used to investigate the correlation between community data and electrochemical performance, and the critical genera on determining current density were identified.

54 ENVIRONMENTAL SCIENCES↗

Optimizing mixed cool thermal storage systems across a connected community

A high level of electric demand flexibility must be integrated into our building infrastructure to enable greater renewable energy penetration in the grid. In the U.S., 9% of electricity generated is used to cool buildings in a periodic manner, making this end-use an ideal target for active management through cool thermal energy storage (CTES) technologies. Historic uses for CTES are designed around central chilled water plants, but these systems cool less than 25% of U.S. commercial floorspace. Emerging technologies are under development to serve the many smaller distributed cooling systems, such as rooftop units (RTUs), and have the potential to add CTES to an additional 66% of cooled commercial floorspace. However, these unitary thermal storage systems (UTSS) lack the modeling and analysis tools to evaluate them in the future interactive grid context. Here, this study develops the modeling and optimization tools necessary to simultaneously examine central and distributed ice storage systems within the multi-building, connected community context. An integrated simulation-optimization workflow is created to allow for rapid customized analysis. Results demonstrate the energy and flexibility tradeoffs of various implementations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Anion-exchange membranes with internal microchannels for water control in CO 2 electrolysis

Electrochemical reduction of carbon dioxide (CO 2 R) poses substantial promise to convert abundant feedstocks (water and CO 2 ) to value-added chemicals and fuels using solely renewable energy. However, recent membrane-electrode assembly (MEA) devices that have been demonstrated to achieve high rates of CO 2 R are limited by water management within the cell, due to both consumption of water by the CO 2 R reaction and electro-osmotic fluxes that transport water from the cathode to the anode. Additionally, crossover of potassium (K + ) ions poses concern at high current densities where saturation and precipitation of the salt ions can degrade cell performance. Herein, a device architecture incorporating an anion-exchange membrane (AEM) with internal water channels to mitigate MEA dehydration is proposed and demonstrated. A macroscale, two-dimensional continuum model is used to assess water fluxes and local water content within the modified MEA, as well as to determine the optimal channel geometry and composition. The modified AEMs are then fabricated and tested experimentally, demonstrating that the internal channels can both reduce K + cation crossover as well as improve AEM conductivity and therefore overall cell performance. This work demonstrates the promise of these materials, and operando water-management strategies in general, in handling some of the major hurdles in the development of MEA devices for CO 2 R.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Machine Learning-Assisted Stability Boundary Determination of Multiport Autonomous Reconfigurable Solar Power Plants

The multiport autonomous reconfigurable solar (MARS) power plant is a promising solution to integrate renewable resources and energy storage systems into the alternating current (ac) power grid and an high-voltage direct current (HVdc) link. In the MARS system, various input power sources are connected to the individual submodules (SMs) through direct current (dc)–dc converters. However, the presence of external power sources can result in unbalanced capacitor voltages of SMs, thereby violating stability constraints under multiple/diverse operating conditions. This article aims to address the gap by accurately determining the stability boundary of the MARS system. As such, a novel machine learning (ML)-assisted energy balancing control (EBC) criterion is proposed. Further, in conjunction with a refined EBC, this approach ensures balanced capacitor voltages across various types of SMs, significantly enhancing the overall system efficiency. The proposed EBC criterion effectively controls EBC activation and deactivation, achieving remarkable accuracy. Both power systems computer aided design (PSCAD)/electromagnetic transients including direct current (EMTDC) simulations and control hardware-in-the-loop (cHIL) tests are conducted to validate the feasibility and efficiency of the proposed method. By combining the EBC and ML-assisted EBC criterion, efficient energy management is achieved for systems featuring multiple input power sources, such as MARS. This approach enables the system to fully exploit its potential across an expanded operational range while upholding high-efficiency standards.

14 SOLAR ENERGY↗