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At least 325 records · Page 18

Repowering: The Other Side of the Reliability Coin

Extreme weather, cracked backsheets, severe PID, poorly built modules, and installation flaws - all can compromise a solar plant's health and force repowering long before end of life. With more than 70% of U.S. PV capacity less than seven years old, the fleet is young, but its rapid expansion has introduced new materials and system designs that are still being tested under real-world conditions. As a result, reliability - not economics - is what most often drives repowering decisions. Repowering is frequently assumed to be an economically motivated choice, but our work shows that reliability concerns are the real trigger. Drawing from industry interviews, case studies, and modeling, we highlight the physical, electrical, and policy barriers owners face when deciding whether to repair, repower, or decommission. At the same time, repowering can create opportunities: renewed interconnection periods, improved energy yields, and strategic upgrades to extend system value. We present a quantitative framework using NLR's System Advisor Model (SAM) and PV in Circular Economy (PV ICE) tool to evaluate trade-offs across financial, material, and energy impacts. These findings provide practical guidance for navigating the realities of repowering today and underscore the critical role of reliability in shaping the future performance and sustainability of the PV fleet.

14 SOLAR ENERGY↗

Extending Component Lifetime And Improving Inverter Reliability (ECLAIIR)

Inverter reliability remains one of the most persistent challenges limiting the performance, availability, and economic viability of utility‑scale photovoltaic (PV) plants. Industry data consistently show that inverters account for the highest share of corrective maintenance events and unplanned outages across PV fleets. These failures result in energy losses, increased O&M costs, and reduced confidence in long‑term solar asset performance. Motivated by these challenges, this project—Extending Component Lifetime and Improving Inverter Reliability (ECLAIIR)—was undertaken to systematically investigate inverter degradation and failure mechanisms, develop predictive maintenance capabilities, and establish data‑driven pathways to improve service life and reduce the Levelized Cost of Energy (LCOE) for large‑scale PV systems. The primary goal of the project was to identify pre‑failure signatures in string inverters using both lab‑based accelerated lifetime testing and field‑based data and to develop predictive maintenance algorithms that can anticipate inverter faults before they occur. Through collaboration with inverter testing laboratory, solar PV plant owner, and failure‑analysis experts, the project advanced the technical understanding of inverter reliability. By instrumenting inverters with thermistors, humidity sensors, power‑quality meters, and acoustic sensors, the research established how multiple sensing modalities can reliably detect deviations from normal behavior hours to days before failure. These findings substantially enhance scientific understanding of inverter failure kinetics and provide the PV industry with the most comprehensive cross‑OEM characterization of early‑stage failure indicators reported to date. Technically, the project demonstrated the effectiveness of predictive maintenance by developing and validating the PreDICT (Predictive Diagnostics of PV Inverters Using Condition Monitoring and Trend Analysis) framework—a multi‑layer diagnostic architecture combining peer‑to‑peer analytics, historical trend modeling, and advanced machine‑learning techniques such as the Sequential Conditional Variational Autoencoder (SCVAE). This predictive model achieved more than 90% accuracy in detecting pre‑failure conditions and provided up to four days of lead time before inverter failure in field scenarios. Economically, the project’s LCOE analysis showed that predictive maintenance can reduce lifetime energy losses and minimize corrective maintenance interventions. Modeling indicated that, depending on inverter failure rates and replacement timelines, predictive maintenance can significantly reduce LCOE impacts associated with inverter downtime: from as high as 19.4% under conventional maintenance strategies to 0.1%–10.17% when predictive analytics are adopted. These results confirm that predictive maintenance is both technically feasible and economically advantageous for utilities and plant operators. The project’s findings also have broad public benefit. By improving inverter reliability and reducing downtime, predictive maintenance directly increases electricity generation from existing PV assets. Enhanced reliability lowers operational costs for utilities, which can translate over time into lower energy costs for consumers. Furthermore, the project’s technical publications, conference presentations, and industry workshops ensure that knowledge gained is shared broadly across the solar industry, supporting workforce development and enabling utilities of all sizes to adopt modern asset‑health monitoring practices. The retrofitting case study and service‑life prediction framework further support informed decision‑making for aging PV fleets, helping operators extend system life and reduce electronic waste. In summary, the ECLAIIR project significantly advanced the state of knowledge on inverter degradation, demonstrated the technical and economic value of predictive maintenance, and delivered actionable tools and insights that support more reliable, cost‑effective, and sustainable PV plant operation. The outcomes of this project will continue to inform utility practices, guide inverter design improvements, and strengthen the long‑term performance of solar assets nationwide.

14 SOLAR ENERGY↗

Accelerated Irradiation and Qualification of Ceramic Nuclear Fuels

Accelerated neutron irradiation testing is an component of accelerated qualification of new nuclear fuels for light water reactor (LWRs), microreactors, and other special purpose reactors. The qualification and licensing of nuclear fuel is a lengthy process that can take 20-25 years to bring a new fuel into service. Accelerated fuel qualification combines both experimental and modeling work to expedite the total qualification time to 5-10 years timeframe. The experimental aspect of this is accelerated irradiation aims to reduce the total time needed for neutron irradiation to achieve targeted burnup, which can take years using conventional irradiation profiles. The data that results from this irradiation testing can then be entered into BISON models to develop robust and reliable performance simulations to ensure safe operation under normal and off normal conditions. This milestone focused on the fabrication of test articles for accelerated irradiation testing at the Advance Test Reactor (ATR).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Evaluation of the DC bus link capacitors and power transistor modules in the qualification testing of PV inverters

To achieve useful, fair, and cost-effective design qualification and type approval testing for PV inverters, two procedures were developed and demonstrated to evaluate the bus link capacitors and power transistor—and where applicable, its module—for long-term reliability. We evaluate the inverter under simulated use conditions with heat run tests to find the highest operating temperatures reached by these components. The procedures are demonstrated in this study with a 4-kVA class string inverter. The maximum temperature of the DC bus link capacitors was determined to be 76.4°C when the ambient temperature was at the inverter's maximum rated temperature of 60°C with derating occurring. On the other hand, the power transistor module's maximum temperature using the heat sink temperature as the index, 92.6°C, occurred in an ambient of 40.8°C when derating was not occurring. The conditions found for upper temperatures exhibited by these components are, respectively, proposed for implementation in the dry heat and thermal cycling tests in the IEC 62093 “Power conversion equipment for photovoltaic systems – Design qualification testing” international standard draft so that the levels applied in the tests are in proportion to those experienced in the field. Finally as a result, fairer evaluation of inverter reliability is realized.

14 SOLAR ENERGY↗

Optimizing Insulation Design for Transformers in Medium Voltage Power Conversion Systems

Medium-frequency transformers (MFTs) play a crucial role in medium-voltage (MV) solidstate transformer (SST) systems, particularly in extreme fast charging applications. Achieving partial discharge (PD)-free operation while maintaining high power density is a significant challenge due to the high electric field (E-field) stresses inherent in MV applications. This dissertation focuses on the insulation design and optimization of MFTs used in both the main power electronics circuits and auxiliary power supplies. The study begins with an overview of insulation testing methodologies, including high potential tests, basic insulation level tests, and PD tests, which are critical for evaluating MFT insulation reliability. Given the importance of PD-free operation for long-term reliability, particular emphasis is placed on understanding PD mechanisms, including void, corona, and surface discharge, and their mitigation strategies. A high voltage isolated auxiliary power supply is then introduced, utilizing a gapped transformer encapsulated in silicone gel. This design achieves PD-free insulation up to 18 kV RMS while maintaining low coupling capacitance to minimize common-mode current. The proposed solution ensures reliable operation in MV environments and offers a scalable approach for auxiliary power in cascaded SST architectures. To improve MFT insulation in main power conversion circuits, a novel structure is developed using polypropylene sheets and potting compounds to create a void-free air gap, effectively mitigating E-field intensity. A prototype transformer with this insulation structure is built and achieves PD-free operation up to 30 kV RMS. This design is experimentally validated in a resonant converter operating at 46 kW, demonstrating its feasibility for MV SST applications. Further optimization is implemented to enhance MFT performance for dual-active-bridge(DAB) converters by integrating a semiconductive shielding layer within the insulation structure. This shielding layer improves the magnetic coupling coefficient while effectively confining the E-field within high insulation materials, thereby reducing eddy current losses. The optimized MFT achieves PD-free operation at 12.6 kV RMS and is successfully tested in a DAB converter operating at 43 kW, which meets the insulation requirements for a 13.2 kV SST system. This dissertation advances MFT insulation design by introducing and experimentally validating novel approaches that improve high voltage insulation while optimizing magnetic coupling and manufacturability. The proposed insulation structures enable PD-free operation while minimizing insulation material usage and simplifying assembly, making them ideal for high power, high voltage applications.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Software-Defined Virtual Synchronous Condenser

Synchronous condensers (SCs) play important roles in integrating wind energy into relatively weak power grids. However, the design of SCs usually depends on specific application requirements and may not be adaptive enough to the frequently-changing grid conditions caused by the transition from conventional to renewable power generation. This paper devises a software-defined virtual synchronous condenser (SDViSC) method to address the challenges. Our contributions are fourfold: 1) design of a virtual synchronous condenser (ViSC) to enable full converter wind turbines to provide built-in SC functionalities; 2) engineering SDViSCs to transfer hardware-based ViSC controllers into software services, where a Tustin transformation-based software-defined control algorithm guarantees accurate tracking of fast dynamics under limited communication bandwidth; 3) a software-defined networking-enhanced SDViSC communication scheme to allow enhanced communication reliability and reduced communication bandwidth occupation; and 4) Prototype of SDViSC on our real-time, cyber-in-the-loop digital twin of large-wind-farm in an RTDS environment. Furthermore, extensive test results validate the excellent performance of SDViSC to support reliable and resilient operations of wind farms under various physical and cyber conditions.

17 WIND ENERGY↗

Lessons from the IEC Durability of Adhesion Accelerated Test Sequence

The IEC 62788-1-1 and IEC 63209-2 standards use aging sequences for durability of adhesion in photovoltaic (PV) modules, which may be evaluated using the single cantilever beam (SCB) test. Because the encapsulant forms critical interfaces with the front glass and solar cells, degradation at those interfaces under ultraviolet (UV) exposure, elevated temperature, and humidity can lead to interfacial delamination - compromising the long-term reliability. In this work, adhesion durability of UV-transmitting poly(ethylene-co-vinyl acetate) (EVA) encapsulant to glass and to silicon solar cells is evaluated after sequenced UV and damp heat aging (85C/85%RH). Laminates were prepared using StarPhire solar front glass with thin glass or PERC cells, and two EVA formulations with different concentrations of siloxane coupling agent. Adhesion was quantified by measuring critical debond energy using the SCB method. Both formulations exhibit similar qualitative trends, while different adhesion is observed at the periphery despite the use of low-shrink manufacturing. The results show that while glass/EVA adhesion remains stable or increases after UV exposure and shows only moderate changes after damp heat, the EVA/cell interface exhibits an irreversible loss of adhesion following UV and then damp heat exposure. Although glass/EVA interfaces generally exhibit lower debond energies, the EVA/cell interface is significantly more vulnerable to UV-driven degradation, identifying it as the dominant reliability risk location through early- and intermediate-module life. These results demonstrate that accelerated aging sequences can expose large, interface-specific losses in adhesion durability and underscore the importance of interface engineering for long-term PV module reliability.

14 SOLAR ENERGY↗

Systems and methods for distributed authentication of devices

A lightweight, fast, and reliable authentication mechanism compatible with the 5G D2D ProSe standard mechanisms is provided. A distributed authentication with a delegation-based scheme avoids repeated access to the 5G core network key management functions. Hence, a legitimate user equipment device (e.g., a drone) is authorized by the cellular network (e.g., 5G cellular network) via offering a proxy signature to authenticate itself to other drones. Test results demonstrate that the protocol is lightweight and reliable.

Akkaya, Kemal↗

Fabrication and Testing of Two Passively Actuated Creep-Fatigue Surveillance Test Articles

This report describes the fabrication, testing, and analysis of two families of passively-actuated creep-fatigue test articles. These test articles induce cyclic mechanical load in a test section actuated solely through a mismatch in the thermal expansion coefficient of two materials and driven by a change in the specimen temperature. Test articles of this type could provide material degradation data for a materials surveillance program in future operating molten salt reactors, where variations in the reactor temperature caused by normal or upset cycles would provide the temperature change in the sample. The purpose of the current experimental campaign is to demonstrate the feasibility of fabricating realistically-sized test articles, test the articles under repeated thermal cycling to assess their robustness, particularly the reliability of the bimetallic welds, and collect strain data from instrumented samples to validate the methods used to size the test articles to match key features of the mechanical response of operating reactor components. The thermal cycling tests are ongoing but the test data to date suggests the current test article design is viable, robust, and can be successfully designed to match a target mechanical response. Finally, the report describes preliminary work on welding refractory alloys to 316H stainless steel. Replacing the test article driver material, currently Alloy 617, with a refractory would increase the coefficient of thermal expansion mismatch and support further miniaturization of the test articles.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

CAMERA: A method for cost-aware, adaptive, multifidelity, efficient reliability analysis

Estimating probability of failure in aerospace systems is a critical requirement for flight certification and qualification. Failure probability estimation involves resolving tails of probability distributions, and Monte Carlo sampling methods are intractable when expensive high-fidelity simulations have to be queried. Here, we propose a method to use models of multiple fidelities that trade accuracy for computational efficiency. Specifically, we propose the use of multifidelity Gaussian process models to efficiently fuse models at multiple fidelity, thereby offering a cheap surrogate model that emulates the original model at all fidelities. Furthermore, we propose a novel sequential acquisition function based experiment design framework that can automatically select samples from appropriate fidelity models to make predictions about quantities of interest at the highest fidelity. We use our proposed approach in an importance sampling setting and demonstrate our method on the failure level set and probability estimation on synthetic test functions and two real-world applications, namely, the reliability analysis of a gas turbine engine blade using a finite element method and a transonic aerodynamic wing test case using Reynolds-averaged Navier-Stokes equations. We show that our method predicts the failure boundary and probability more accurately and at a fraction of the computational cost compared with using just a single expensive high-fidelity model. Finally, we show that our sequential approach is guaranteed to asymptotically converge to the true failure boundary with high probability.

97 MATHEMATICS AND COMPUTING↗

Acceleration Factors for Combined‐Accelerated Stress Testing of Photovoltaic Modules

Combined‐accelerated stress testing (C‐AST) is developed to establish the durability of photovoltaic (PV) products, including for degradation modes that are not a priori known or examined in standardized tests. C‐AST aims to comprehensively represent the sample, stress factors, and their combinations using levels at the statistical tails of the natural environment. Acceleration factors for relevant climate sequences within the C‐AST cycle with respect to the Florida USA climate are estimated for selected degradation mechanisms. It is found that for degradation of the outer backsheet polymer layer, the acceleration factor of the tropical climate sequence (the longest of the climate sequences) is f ( T , G ) = 17.3 with ultraviolet photodegradation; for polyethylene terephthalate hydrolysis (backsheets), f ( T , RH ) = 426; for electrochemical corrosion (PV cell), f ( I ) = 14.1; and for PbSn solder fatigue f (Δ T , r ( T )) = 17.3. Here, T is the module temperature, G is the broadband spectrum irradiance on the plane of array of the module, RH is the relative humidity on the module surface, I is the leakage current through the module packaging, and r ( T ), the number of temperature reversals. The methods discussed herein are generally applicable for evaluating acceleration factors in other accelerated test methods.

14 SOLAR ENERGY↗

KBKit: A Python Toolkit for Kirkwood–Buff Theory from Molecular Dynamics

Thermodynamic properties of liquid mixtures govern processes that range from drug delivery to energy storage, yet extracting these properties from molecular simulations remains challenging. Kirkwood–Buff (KB) theory offers a rigorous route by linking microscopic pair distribution functions to macroscopic free energies, but practical use of the theory has been hindered by two obstacles: (i) the long simulations needed to obtain well-converged Kirkwood-Buff integrals (KBIs) and (ii) the specialized corrections required to translate finite-size data to the thermodynamic limit. $\texttt{KBKit}$ is an open-source Python package that removes these barriers. It automatically computes KBIs and derived thermodynamic quantities from GROMACS input files, applies state-of-the-art finite-size corrections, and provides built-in diagnostic tools to quantify statistical uncertainty. Written with modern software-engineering practices—continuous integration, extensive unit testing, and thorough documentation—$\texttt{KBKit}$ is both reliable and easy to extend. By condensing complex KBI analysis into a few intuitive commands, $\texttt{KBKit}$ enables researchers to incorporate KB theory into routine simulation workflows and accelerate the discovery of solution-phase thermodynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

SASHIMI-SIDM: semi-analytical subhalo modelling for self-interacting dark matter at sub-galactic scales

We combine the semi-analytical structure formation model, SASHIMI, which predicts subhalo populations in collisionless, cold dark matter (CDM), with a parametric model that maps CDM halos to self-interacting dark matter (SIDM) halos. The resulting model, SASHIMI-SIDM, generates SIDM subhalo populations down to sub-galactic mass scales, for an arbitrary input cross section, in minutes. We show that SASHIMI-SIDM agrees with SIDM subhalo populations from high-resolution cosmological zoom-in simulations in resolved regimes. Crucially, we predict that the fraction of core-collapsed subhalos peaks at a mass scale determined by the input SIDM cross section and decreases toward higher halo masses, consistent with the predictions of gravothermal models and cosmological simulations. For the first time, we also show that the core-collapsed fraction decreases toward lower halo masses. While the dependence of the collapse time on mass and concentration implies such behaviour, our semi-analytical approach allows us to quantify and illustrate this trend clearly across the full mass spectrum of subhalos, including for subhalo masses below the resolution limit of any current cosmological SIDM simulation. As a proof of principle, we apply SASHIMI-SIDM to predict the boost to the local dark matter density and annihilation rate from core-collapsed SIDM subhalos, which can be enhanced relative to CDM by an order of magnitude for viable SIDM models. Thus, SASHIMI-SIDM provides an efficient and reliable tool for scanning SIDM parameter space and testing it with astrophysical observations. The code is publicly available at https://github.com/shinichiroando/sashimi-si.

cosmological simulations↗

Cryogenic single-port calibration for superconducting microwave resonator measurements

Superconducting circuit testing and materials loss characterization requires robust and reliable methods for the extraction of internal and coupling quality factors of microwave resonators. Additionally, a common method, imposed by limitations on the device design or experimental configuration, is the single-port reflection geometry, i.e. reflection-mode. However, impedance mismatches in cryogenic systems must be accounted for through calibration of the measurement chain while it is at low temperatures. In this paper, we demonstrate a data-based, single-port calibration using commercial microwave standards and a vector network analyzer with samples at millikelvin temperature in a dilution refrigerator, making this method useful for measurements of quantum phenomena. Finally, we cross reference our data-based, single-port calibration and reflection measurement with over-coupled 2D- and 3D-resonators against well established two-port techniques corroborating the validity of our method.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Millions of Small Pressure Cycles Drive Damage in Cracked Solar Cells

Here, we applied time-varying air pressure to a PV module containing newly cracked cells. The test used a new dynamic mechanical acceleration (DMX) apparatus. We applied pressure cycles similar to natural, wind-driven cycles. Compared to standard dynamic mechanical load (DML) tests, we applied much lower pressure (10 Pa to 300 Pa RMS) and many more cycles (one million at each of four pressure levels). We present a case study on a single cell in a commercial module. We monitored electrical continuity loss across cracks using electroluminescence (EL) imaging. 10 Pa pressure cycles caused negligible change. 30 Pa pressure cycles caused permanent damage that continued worsening even after tens of thousands of cycles. After one million 30 Pa cycles, a series of 100 Pa cycles still caused new, permanent damage to existing cracks. 300 Pa cycles caused further worsening and introduced new cracks.

14 SOLAR ENERGY↗

Restoring Critical Loads In Resilient Distribution Systems using A Curriculum Learned Controller

In this paper, we propose a curriculum learned reinforcement learning (RL) controller to facilitate distribution system critical load restoration (CLR), leveraging RL's fast online response and its outstanding optimal sequential control capability. Like many grid control problems, CLR is complicated due to the large control action space and renewable uncertainty in a heavily constrained non-linear environment with strong intertemporal dependency. The nature of the problem oftentimes causes the RL policy to converge to a poor-performing local optimum if learned directly. To overcome this, we design a two-stage curriculum in which the RL agent will learn generation control and load restoration decision under different scenarios progressively. Via curriculum learning, the trained RL controller is expected to achieve a better control performance, with critical loads restored as rapidly and reliably as possible. Using the IEEE 13-bus test system, we illustrate the performance of the RL controller trained by the proposed curriculum-based method.

curriculum learning↗

A Sequential Model Predictive and Deep Reinforcement Learning-Based Controller for Distribution System Outage Mitigation under Hurricane Events

This paper proposes a proactive outage mitigation framework for power distribution networks to withstand hurricane-induced disruptions. It leverages Model Predictive Control (MPC) to identify safe lines for proactive switching during hurricanes, minimizing the risk of cascading failures and voltage violations. The switching strategies optimized by MPC are sequentially integrated with a Deep Reinforcement Learning agent using the Advantage Actor-Critic algorithm, enabling dynamic line switching to maximize connected buses and minimize voltage violations in real time. Using a probabilistic hurricane model, the framework predicts line failures and adapts to varying conditions to enhance grid resilience. Simulations on the IEEE 123-bus system demonstrate its effectiveness in maintaining high connectivity and minimizing disruptions. Real-time testing with an RTDS confirms the practicality and reliability of the proposed approach.

Selim, Alaa [University of Connecticut]↗