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At least 1,081 records · Page 60

Forming Gas Annealing Improves the Performance of Ex Situ Sb-Doped CdSeTe Thin-Film Solar Cells

Group V doping in cadmium-selenide-telluride (CdSeTe) polycrystalline thin-film solar cells has demonstrated improved power conversion efficiencies (PCEs) and long-term stabilities as compared to the traditional Cu doping in the last decade. The dopants can be successfully incorporated by either in situ or ex situ doping. Here, we report that forming gas (FG) annealing enhances the efficiencies of CdSeTe polycrystalline thin-film solar cells utilizing ex situ antimony (Sb) doping via close-space sublimation of SbCl3 at ambient pressure. The FG annealing increases the hole density and carrier lifetime, reduces the back barrier height, and, therefore, leads to improved open-circuit voltages (VOCs) and fill factors (FFs). The champion device achieves a PCE of 19.2% with a VOC of 877 mV, a current density (JSC) of 30.2 mA/cm2, and an FF of 72.4%. Importantly, the Sb-doped devices showed improved stability under stress tests as compared to Cu-doped devices.

14 SOLAR ENERGY↗

Control Mechanisms for Self‐Sealing in Activated Clay‐Rich Faults Through Controlled Hydraulic Injection Experiment

Abstract In a high‐pressure injection fault activation experiment conducted at the Mont Terri underground research laboratory in Switzerland, the transmissivity of the Opalinus Clay fault significantly increased due to opening and shearing. The fluid injection, spanning a few hours, generated a 10 m radius fault activation patch. Subsequent pressure pulse tests conducted bi‐weekly for a year revealed the gradual return of fault transmissivity to its initial state. The study utilized fluid pressure decay analysis, optical fiber monitoring, continuous active source seismic measurements and borehole displacement sensors for measuring fault displacements. The fault zone exhibited a dilation of approximately 1.4 mm, associated with both normal and tangential movements during activation, resulting in a sudden transmissivity increase from 1 × 10 −12 to 3.2 × 10 −7 m 2 /s. Early post‐activation, transient compaction and the subsequent slow compaction were observed, transitioning to an extension regime. The pressure pulse tests demonstrated a rapid transmissivity drop by more than two orders of magnitude within the first 10 days, followed by a gradual and less pronounced decrease. Plastic shear and compaction dominated the transmissivity evolution until 70 days after injection ended, followed by a period where additional factors, such as clay mineral swelling, influenced the behavior. Extrapolation suggested a sealing process taking at least 50 years after the initial activation. Plain Language Summary A field‐scale fault activation experiment offers valuable insights into the elasto‐plastic processes governing the sealing of shale faults. The experiment reveals a rapid increase in the fault's transmissivity by approximately five orders of magnitude during activation. Subsequent observations show a gradual transmissivity decrease by about three orders of magnitude post‐activation, with slow long‐term plastic shear and compaction of the fault competing against secondary processes, notably clay mineral swelling. All conceptual models employed to interpret these field data converge on the estimation that the fault's return to its initial low transmissivity state would require a minimum of 50 years. Key Points High‐pressure injection fault activation experiment at the Mont Terri underground research laboratory Continuous transmissivity measurements record self‐sealing inside a clay‐rich fault zone Transmissivity undergoes a phase of domination by slow plastic compaction and shearing during the initial post‐activation period, with mineral swelling exerting its influence over the long term

Guglielmi, Yves↗

Implementation of Distributed Memory Computing in MOSAIC to Enable Large 3D Simulations of Irradiated Concrete

The concrete biological shield (CBS) of light-water reactors protects workers and the surrounding environment by absorbing neutron and gamma irradiation emitted from the reactor core. The radiation dose increases with the CBS’s operational time and, in the long term, becomes significant enough to raise the question of irradiation effects on concrete—and particularly on the structural integrity of the CBS. Irradiation-induced damage has been identified as one of the main degradation mechanisms in the CBS. Neutron radiation causes the swelling of aggregate-forming minerals at different rates and amplitudes depending on the mineral’s nature. Silicate-bearing minerals such as quartz are particularly sensitive to neutron radiation and experience up to 17.8% volumetric expansion. Aggregates comprise several minerals with different orientations and are, therefore, subject to cracking as a result of mismatch strains. Additionally, the swelling of aggregates creates significant stresses in the surrounding cement paste matrix, which also results in crack formation. In parallel with the collection of characterization and irradiation test data, development of modeling and simulation tools for irradiated concrete is ongoing with the support of the US Department of Energy Office of Nuclear Energy’s Light Water Reactor Sustainability (LWRS) program. This effort resulted in the development and application of the fast-Fourier transform (FFT)–based code Microstructure-Oriented Scientific Analysis of Irradiated Concrete (MOSAIC) at Oak Ridge National Laboratory.

61 RADIATION PROTECTION AND DOSIMETRY↗

Time-series learning of latent-space dynamics for reduced-order model closure

In this work, we study the performance of long short-term memory networks (LSTMs) and neural ordinary differential equations (NODEs) in learning latent-space representations of dynamical equations for an advection-dominated problem given by the viscous Burgers equation. Our formulation is devised in a nonintrusive manner with an equation-free evolution of dynamics in a reduced space with the latter being obtained through a proper orthogonal decomposition. In addition, we leverage the sequential nature of learning for both LSTMs and NODEs to demonstrate their capability for closure in systems that are not completely resolved in the reduced space. We assess our hypothesis for two advection-dominated problems given by the viscous Burgers equation. We observe that both LSTMs and NODEs are able to reproduce the effects of the absent scales for our test cases more effectively than does intrusive dynamics evolution through a Galerkin projection. This result empirically suggests that time-series learning techniques implicitly leverage a memory kernel for coarse-grained system closure as is suggested through the Mori–Zwanzig formalism.

97 MATHEMATICS AND COMPUTING↗

Automatic Crack Segmentation and Feature Extraction in Electroluminescence Images of Solar Modules

The effect of cracks in solar cells on the long-term degradation of photovoltaic (PV) modules remains to be determined. To investigate this effect in future studies, it is necessary to quantitatively describe the crack features (e.g., length) and correlate them with module power loss. Electroluminescence (EL) imaging is a common technique for identifying cracks. However, it is currently challenging and time-consuming to identify cracks in a large number of EL images and quantify complex crack features by human inspection. This article introduces a fast semantic segmentation method (~0.18 s/cell) to automatically segment cracks from EL images and algorithms to extract crack features. Here we fine-tuned a UNet neural network model using pretrained VGG16 as the encoder and obtained an average F1 score of 0.875 and an intersection over union score of 0.782 on the testing set. With cracks and busbars segmented, we developed algorithms for extracting crack features, including the crack-isolated area, the brightness inside the isolated area, and the crack length. We also developed an automatic preprocessing tool for cropping individual cell images from EL images of PV modules (~0.72 s/module). Our codes are published as open-source an software, and our annotated dataset composed of various types of cells is published as a benchmark for crack segmentation in EL images.

14 SOLAR ENERGY↗

Ocean liming effect on a North Atlantic microbial community: changes in composition and rates

The ongoing rise in atmospheric CO 2 levels and the consequent global warming make it increasingly difficult to maintain the global temperature within the 1.5 - 2°C target set by the Paris Agreement. Therefore, strategies to remove carbon dioxide from the atmosphere are being developed, with ocean alkalinity enhancement (OAE) gaining most attention. Within OAE, ocean liming- the addition of quicklime (CaO) or hydrated lime (Ca(OH) 2 )- can not only remove CO 2 from the atmosphere but potentially counteract the effects of ocean acidification. Although quite attractive, these technologies have yet to be tested regarding ecological safety and efficacy. Here we report the impacts of ocean liming on the abundance, composition and extracellular enzymatic activity (EEA) rates of a North Atlantic planktonic community. The results demonstrate that OAE led to a decreased phytoplankton development, mainly diatoms. The bacterial response to OAE was community-specific, with a consistent increase in the relative abundance of the order Oceanospirillales. OAE also led to increased EEA rates, especially within the bacterial community. These findings suggest that while initial effects on phytoplankton may be limited, the specific impacts on bacterial groups suggest that OAE could influence the remineralization of organic matter. If our results apply to other communities, OAE might initially affect marine microbial dynamics, but further studies are needed to determine if these effects are long-term.

16S↗

Fundamental Studies of the Vibrational, Electronic, and Photophysical Properties of Tetrapyrrolic Architectures

The ability to capture and utilize light in the near-ultraviolet (NUV), visible and near-infrared (NIR-I and NIR-II) spectral regions (i.e., 320–400, 400–700, 700–1000, 1000–1700 nm) is essential for any solar-energy conversion scheme. Nature employs chlorophylls and bacteriochlorophylls in light-harvesting architectures to absorb light in the blue and red/NIR regions. Accessory pigments (carotenoids, bilins) augment absorption of the (bacterio)chlorophylls in the green region. The harvested energy is funneled to a reaction center protein, where charge separation occurs. Subsequent migration of the electron and the hole stabilizes and stores the energy from light via redox chemistry. The long-term objective of the Bocian/Holten&Kirmaier/Lindsey research program under this DOE grant has been to develop tetrapyrrole-based molecular architectures that absorb sunlight, funnel energy and separate charge with high efficiency. Integral to the program has been iterative cycles of design, synthesis and characterization that provided deep insights into the relationships between chemical composition, electronic structure, and key static and dynamic properties (vibrational, redox, photophysical, energy/charge transfer) of tetrapyrrolic systems. Such architectures included monomers, dyads, larger arrays, and complexes with accessory components. The objective was to develop molecular designs and guiding principles to enhance current and future energy-conversion schemes. Molecular arrays targeted to address one or more fundamental questions concerning light harvesting and energy/charge transfer were constructed from analogues of the naturally occurring hemes, chlorophylls and bacteriochlorophylls. Diverse, tunable synthetic building blocks were prepared that spanned the three respective tetrapyrrole families, which are the porphyrins, chlorins and bacteriochlorins. Thus, the research focused on porphyrins as well as synthetic surrogates for chlorophylls (chlorins, 13 1 -oxophorbines and chlorin-imides) and bacteriochlorophylls (bacteriochlorins, bacterio-13 1 -oxophorbines and bacteriochlorin-imides), generically termed hydroporphyrins. Although the three tetrapyrrole classes (porphyrins, chlorins and bacteriochlorins) absorb light strongly in the violet-blue spectral region, the long-wavelength absorption band typically lies in the green-orange, red, and NIR regions, respectively, with increasing intensity. Understanding the spectra, electronic structure, and energy/charge-transfer properties of such tetrapyrrolic macrocycles is of central importance for the rational design of molecular architectures for solar-energy conversion. Our integrated program of molecular design and synthesis coupled with a variety of spectroscopic, electrochemical, and computational studies have probed from first principles how structural and electronic properties of tetrapyrrolic macrocycles dictate spectral properties as well as the rates of ground-state hole/electron transfer and excited-state energy flow in multicomponent architectures. Individual molecules and multicomponent architectures were designed to test ideas of fundamental importance, often requiring the development of new synthetic methodology. The members of the collaborative team had almost daily discussions by phone and/or e-mail concerning design of molecules, flow of compounds between the labs, planning of physical characterization studies, discussing results and analysis and integrating into design of next generation architectures, and the preparation of manuscripts. Furthermore, students and postdocs in the different labs routinely communicated with one another to facilitate the advancement of the research activities. In short, a highly integrated and collaborative research program was well established among the groups. The research effort involved molecular design and synthesis of synthetic molecular architectures by the Lindsey group integrated with physicochemical and photophysical characterization by the Bocian group and the Holten&Kirmaier group (Figure 2). The Bocian group carried out electrochemical, electron paramagnetic resonance (EPR), resonance Raman (RR), and Fourier-transform infrared (FT-IR) studies, as well as density functional theory (DFT) calculations and the time-dependent extension (TDDFT) to gain insight into excited-state properties. The Holten&Kirmaier group carried out static and time-resolved absorption and fluorescence spectroscopy studies and simulated absorption spectra using molecular orbital (MO) energies from DFT as input to the four-orbital model to complement the TDDFT calculations. The combined measurements provided understanding of the vibrational/electronic properties of the individual molecules and the changes that occur upon incorporation into multicomponent architectures. This information underpinned elucidating the mechanisms and timescales of ground-state hole/electron transfer and excited-state energy and charge transfer.

14 SOLAR ENERGY↗

Characterization of the Aerosol Source Term in Dry Storage Canisters

As long-term dry storage of used nuclear fuel at independent spent fuel storage installations (ISFSI) trends toward the de facto back end of the US fuel cycle, it becomes appropriate to investigate potential degradation and dispersion scenarios for suitable risk mitigation purposes. Pitting and subsequent stress corrosion cracking of the canister wall is currently viewed as a potential scenario leading to a through-wall pathway for contamination to be transferred from within the storage container to the surrounding environment. While stress corrosion cracking measurements are currently underway to further characterize this scenario, a parallel effort endeavors to perform a consequence analysis of conditions in which through wall cracks are indeed formed. This effort consists of engineering scale modeling using the GOTHIC and MELCOR software packages along with experimental depletion and penetration tests.

spent fuel storage, aerosol deposition, Stress Cor↗

Analysis of Radiological Release From Fueled Irradiation Experiments During Manual Handling (Slides)

Irradiation experiments are manually handled at the Advanced Test Reactor (ATR) by qualified operators using long handled tools. Standard handling evolutions include insertion and removal from the reactor vessel, transfer to/from a storage location or cask in the ATR canal, and handling/reconfigurations at a canal working tray. Such routine handling has the potential to result in mechanical damage to the experiment boundary which is credited to retain fission products. Since damage can occur due to operator error, this is an anticipated occurrence. This work determines the radiological consequences to receptors inside the ATR facility, as well as public receptors. Given the wide variety of fuel types tested at the ATR, a generic approach to the analysis is taken. The radiological inventory is determined to bound a variety of fuel types (e.g., ceramic and molten fuel matrices) and fission powers on the U-235 enrichment spectrum. The source term analysis considers different release fractions to bound different fuel types and burnups. The postulated handling events occur underwater; thus, retention of the released isotopic content is considered within the canal water column. Retention of radionuclides in the water column is determined using a modified approach of United States (US) Nuclear Regulatory Commission (NRC) Regulatory Guide (RG) 1.183. Radiological dose to the facility receptor is determined using a compartment release model. Dose to the public receptor is determined using atmospheric dispersion models using site specific atmospheric conditions with the use of the Radiological Safety Analysis Computer (RSAC) program version 7.2.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

Hydraulic performance and wave transmission through nature-inspired perforated hollow-base piles breakwater

Nature-based Solutions (NbS) are critical to achieving long-term sustainable coastlines in deltaic coastlines, particularly susceptible to severe impacts under climate change. In recent years, coastal erosion has accelerated in the Vietnam Mekong Delta (VMD), particularly in the West Sea (from Ca Mau to Kien Giang). Due to the characteristics of muddy coastlines and eroded mangrove forests in this region, only a few engineering solutions have effectively reduced waves and promoted sediment accumulation to facilitate beach accretion. However, these solutions require significant investment and cannot be relocated or reused. Therefore, this study introduces a coastal mangrove-inspired perforated hollow-base piles breakwater (PHBPB), which uses the principle of biomimicry by studying the ability of mangrove groups to protect the coastline, stimulate sediment deposition, and over time, restore mangrove forests in the VMD. The hydraulic parameters of PHBPB were tested in 260 scenarios using a physical model, which included varying parameters such as crest width (B), pile row numbers (n c ), crest freeboard (R c ), and wave parameters (H s , T p ) in determining the capabilities of wave transmission, reflection, and wave dissipation. The results showed that the process of wave energy dissipation through perforated hollow-base breakwaters without piles (PHBBWP) is governed by three main parameters, including the relative water depth of the crest (R c /H m0,i ), the relative width of the crest (B/H m0,i ), and the wave slope at the structure location (s m = H m0,i /L m ). In contrast, for PHBPB, the primary influencing factors are the relative submergence depth or the length of the submerged pile portion (R c /H m0,i ) and the relative width of the pile system (X b /L m ). Finally, the hollow structure is suitable for the soft, weak mud geology in this region with poor load-bearing capacity, allows for rapid installation, is reasonably cost-effective, and can be relocated and reused once regeneration has been completed in each stretch of coastline.

54 ENVIRONMENTAL SCIENCES↗

2.2.5.401 - Ocean Observing Prize

The Powering the Blue Economy: Ocean Observing Prize is a $2.4M contest that challenges innovators to develop solutions that integrate marine renewable energy with ocean observation platforms to revolutionize our ability to monitor, manage, and understand the ocean. Competitors are challenged to design, build, and test novel, wave-powered, self-charging autonomous underwater vehicle (AUV) systems that could be suitable for a 6-month deployment in the Atlantic Ocean to monitor hurricane formation. Through engagement with the end user ocean observing community, the team identified challenges in a lack of data on storm intensity, endangering coastal communities. This challenge could be addressed by collecting data before, during, and after a hurricane develops and strengthens at sea. Amassing this data, however, requires an ocean observing system that can be deployed at sea for long periods, waiting for approaching storms. To help solve this problem, competitors are working to integrate wave energy capture with AUV systems to collect this data, helping to better protect coastal communities from oncoming storms. Solutions developed through this prize aim to enable long-term collection of data before, during, and after a hurricane that will help better forecast storm intensity. The prize mechanism provides an environment to accelerate technology development for innovators and helps to improve awareness of marine energy and its ability to provide power to blue economy applications.

coastal communities↗

Effects of input gradient regularization on neural networks time-series forecasting of thermal power systems

This study proposes using neural networks, specifically gated recurrent unit (GRU), long-short-term memory (LSTM), and transformer networks, to improve control strategies in a 450 MW coal-fired power plant. However, neural networks face issues of becoming overly dependent on just a few variables to make predictions, which negatively impacts control decisions that rely on the model to determine the value of all manipulated variables. The paper introduces regularization techniques, including noise injection and input gradient regularization, during the training phase. Here, the work presents novel contributions in adapting neural networks to control industrial systems and applying regularization techniques from computer vision to industrial process control. Results demonstrate the effectiveness of input gradient regularization in reducing model dependence on subsets of variables, emphasizing the balance between fidelity and controllability. Further exploration is recommended, including the development of recurrent transformers, closed-loop control testing, and a sensitivity analysis on computer models to provide further insight.

20 FOSSIL-FUELED POWER PLANTS↗

Robust Unencapsulated Perovskite Solar Cells Protected by a Fluorinated Fullerene Electron Transporting Layer

The emergent perovskite photovoltaics technology faces challenges like the long-term durability combining moisture, thermal, and photo stresses that prevents them from competing with established technologies. In this work, we introduce a series of new fluorinated fullerenes as an electron-transporting layer (ETL) for robust perovskite photovoltaics that deliver a high power conversion efficiency of 21.27% with substantially improved durability against environmental stressing. The hydrophobic nature of the new fullerene protects the unencapsulated perovskite cell with stability over 1400 h in 85% relative humidity. Notably, the unencapsulated device maintained 80% of their original performance (T-80) after being immersed in water for over 10 min. Detailed characterizations suggest that the fluorinated fullerene can immobilize the cations in perovskites and passivate the surface traps. Therefore, the T-80 lifetime of the devices under constant illumination reached 1920 h. On the basis of the accelerated test, we estimate a lifetime approaching 10 years with encapsulation. The successful demonstration of the new ETL can stimulate further research and momentum for future photovoltaic technology development.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Prototype Design of Global Common Module for ATLAS Experiment’s Phase-II Upgrade

A new Global Trigger subsystem will be installed in the Level-0 Trigger as part of HL-LHC Upgrade of ATLAS during the upcoming Long-Shutdown 3. It will feature new and improved trigger hardware and algorithms, and an increased maximum output rate of 1 MHz. The Global Trigger will run offline-like trigger algorithms on full-granularity data, gathered from several sub-detectors and trigger-processing subsystems. A single Global Common Module (GCM) hardware is implemented across the Global Trigger system to be used as Multiplexer Processor, Global Event Processor and CTP Interface (gCTPi). This common hardware platform method will minimize the complexity of the firmware and simplify the system design and long-term maintenance. The GCM prototype is an ATCA front form factor board with two Xilinx Virtex UltraScale+ FPGA VU13P and one ZYNQ UltraScale+ FPGA ZU19EG and seventeen 25.78125 Gb/s FireFly duplex optical modules on it. The total power consumption of this board must be less than 350 W, and the temperature of the optical modules should be less than 70 °C in the worst case. The VU13Ps serve as algorithms processor nodes such as MUX, GEP and gCTPi, and the ZU19EG with Peta Linux OS running on it, is used as Command/Control/Readout Unit to configure and monitor the board and communicate with the ATLAS Detector Control System (DCS). The development of an ATCA blade with three large FPGAs and about 200 optical links running at 25Gb/s is a very challenging task, and the successful test results have demonstrated this GCM prototype as an advancement of state-of-the-art electronics module design in HEP experiments. This paper presents the hardware design considerations, functionalities, and performance test results of this GCM prototype.

47 OTHER INSTRUMENTATION↗

(Invited) Fuel Cell Component Durability for Million Mile Fuel Cell Trucks

While significant advances have been made and early commercial fuel cell light-duty vehicles (LDVs) are starting to be produced, fuel cells in the heavy-duty-vehicle (HDV) transportation sector (including trucks, long-haul semitrailers, maritime, trains, etc.) are nascent, despite the fact that advantages of fuel cells compared to both diesel and electric powertrains are very compelling in terms of emissions, charging time, efficiency, power-to-weight ratio, among others. However, the fuel-cell technology for HDVs requires a paradigm shift in fuel-cell research and development compared to LDVs, where the emphasis becomes efficiency and improvements in durability instead of a focus on increased power densities and lower cell costs. Heavy-duty applications require significantly longer vehicle lifetimes (>25,000 hours/1,000,000 miles for heavy-duty trucks), and therefore require improved fuel cell durability compared to light-duty vehicles. In 2020, HFTO formed the Million Mile Fuel Cell Truck Consortium (M2FCT) that includes a core team of five national laboratories to overcome durability and efficiency challenges in PEMFCs for heavy-duty applications with an initial focus on long-haul trucks. While targets and testing protocols have been developed for light-duty vehicles, the same level of targets and testing protocols have not been established for heavy-duty transportation. With operational times of greater than > 25,000 hours required, the need for well-developed accelerated stress tests (ASTs) is amplified. Results from these ASTs demonstrate the need for more durable electrode layers and well-controlled potential variations. Finally, this presentation will provide an overview of the DOE's Fuel Cell R&D approach, highlighting past and current activities, as well as strategies to enable fuel cell competiveness for heavy-duty applications.

25 ENERGY STORAGE↗

Coordination Chemistry as a Universal Strategy for a Controlled Perovskite Crystallization

The most efficient and stable perovskite solar cells (PSCs) are made from complex mixture of precursors, which are practically always dissolved in combinations of the volatile (and toxic) N, N-Dimethylformamide (DMF), and the non-volatile (and green) dimethyl sulfoxide (DMSO) solvents. Typically, to then form a thin film, an extreme oversaturation of the perovskite precursor is initiated to trigger nucleation sites, e.g. by vacuum, an airstream or a so-called antisolvent. Unfortunately, most such oversaturation triggers do not expel the lingering (and highly coordinating) DMSO, which is highly coordinating, from the thin films; this detrimentally affects long-term stability. Here, for the first time, we introduce (the green) dimethyl sulfide (DMS) as a novel nucleation trigger for perovskite films combining, uniquely, high coordination and high vapor pressure. More precisely, DMS coordinates more strongly than all currently used solvents, hence replacing them, including DMSO, effectively during film formation. Crucially, DMS also has among the highest vapor pressures reported in literature, thus effectively leaving the thin film shortly after formation. This gives DMS a universal scope: DMS replaces other solvents by coordinating more strongly and removes itself once the film formation is finished. To demonstrate this novel coordination chemistry approach, we process MAPbI 3 PSCs, typically dissolved in hard-to-remove (and green) DMSO achieving 21.6% efficiency, among the highest reported efficiencies for this system. To confirm the universality of our strategy, we tested DMS for FAPbI 3 as another composition, which showed higher efficiency of 23.5% compared to 20.9% for fabricated device with CB. Finally, this work provides a universal strategy to control perovskite crystallization using coordination chemistry heralding the revival of perovskite compositions with pure DMSO, such as MAPbI 3 .

36 MATERIALS SCIENCE↗

Non-Intrusive Appliance Identification with Appliance-Specific Networks

The problem of noninstrusive load monitoring (NILM) is usually formulated as a single-channel blind source separation task, whose successful solution enable fast and convenient load identification and energy disaggregation. When applied at test time, NILM algorithms aim to identify the operating characteristics of individual appliances from an aggregate power measurement of the entire house. Recent advances in deep learning gave rise to many methods that mostly focus on learning a direct mapping from aggregate measurement to individual appliance power. However, these methods are not only computationally expensive, but they often suffer from overfitting and do not generalize very well. In this article, we propose a novel NILM method that leverages advances in statistical learning that have not been properly applied in this domain before. The proposed method consists of three stages: first, a Bayesian nonparametric learning-based approach for appliance state extraction; second, synthetic minority oversampling technique for data augmentation and mitigating the heavy imbalance in switching events; and third, appliance-specific lightweight long short-term memory networks for status classification for each appliance. Here, we adopt a “differential” input (the difference before and after the switching event) to reduce the complexity of network training and make the proposed method robust to multiappliance switching events. Experiments are conducted to demonstrate the effectiveness of the proposed method, achieving superior performance when compared to recent methods. An ablation study is conducted to demonstrate the effectiveness of each module of our method. Finally, we investigate the quality of generated synthetic samples.

42 ENGINEERING↗

Assessment of the impacts of renewable energy variability in long-term decarbonization strategies

To meet the nationally determined contributions proposed by the countries that signed the Paris Agreement, investments must be made in renewable generation technologies such as solar and wind. However, due to their high variability, these technologies pose challenges in terms of meeting demand or generating excess electricity. For this reason, energy system models are designed to capture this variability by considering flexibility technologies. Nevertheless, it is important to note that some energy system models lack integration with other sectors. Therefore, integrated assessment models have been employed to evaluate mitigation strategies, as they endogenously consider the linkages between energy and non-energy sectors. In addition, due to their complexity, these models do not account for the variability of renewable resources. Hence, this research aims to address this issue. Here, this work represents the first attempt to evaluate how the introduction of hourly resolution affects the outcomes of integrated assessment models, specifically focusing on the Global Change Analysis Model (GCAM). We employ a soft-linking approach between the GCAM and the Highway to Renewable Energy Systems model (H2RES, an hourly level energy system model) to accomplish this. The proposed approach is tested using Chile’s Nationally Determined Contributions under different hydrological profiles in the power sector. The results show that it is possible to use the capacity obtained from the Global Change Analysis Model and implement it on an hourly scale. However, the feasibility of implementation depends on high levels of flexibility technologies, such as battery energy storage. When given the choice of investments in renewable sources and flexible technologies, the optimal dispatch of the H2RES model show small differences than those obtained by GCAM-Chile. H2RES differs from GCAM-Chile in approximately 5% for wind and 3% for solar electricity generation in the year 2050. However, feasible integration of significant renewable sources is obtained with relatively high Critical Excess Electricity Production levels, reaching 20% in 2050. This excess electricity is attributed to the necessity for flexible technologies to manage the intermittency of renewables sources when hourly profiles of such sources are considered.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗