Solar PV Inverter Reactive Power Disaggregation and Control Setting Estimation
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14 SOLAR ENERGY↗
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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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Side-by-Side Comparison of Subhourly Clipping Models: Preprint
Over the past several years there have been numerous attempts at quantifying the inherent power clipping of inverters due to inter-hourly irradiance variability that is not captured in hourly PV performance models. Different models have been proposed to correct for these clipping losses in PV performance estimates, including matrix lookup models, distribution modeling of the PV power performance within a given hour, and machine learning methods. To date, there have been few comprehensive quantitative comparisons of these inverter clipping correction modeling approaches to evaluate the effectiveness of said approaches in predicting the actual behavior of PV system inverter clipping. In this study, we perform such a comparison, evaluating two different clipping correction loss modeling approaches recently implemented in the System Advisor Model (SAM) against clipping losses modeled with 1-minute climate data. These comparisons will be performed across a variety of climate locations and inverter loading ratios to thoroughly analyze the effectiveness of these modeling approaches relative to each other. Results from this analysis reveal that both clipping correction approaches improve annual energy accuracy to within 2% of 1-minute modeled energy yield. The models can improve accuracy up to 3% in systems with ILR of 2.0, showing the importance of this modeling factor in energy yield estimates.
clipping↗
Three-Dimensional Vibration Isolator for Suppressing High-Frequency Responses for Sage III Contamination Monitoring Package (CMP)
The Stratospheric Aerosol and Gas Experiment (SAGE) III - International Space Station (ISS) instrument will be used to study ozone, providing global, long-term measurements of key components of the Earth's atmosphere for the continued health of Earth and its inhabitants. SAGE III is launched into orbit in an inverted configuration on SpaceX;s Falcon 9 launch vehicle. As one of its four supporting elements, a Contamination Monitoring Package (CMP) mounted to the top panel of the Interface Adapter Module (IAM) box experiences high-frequency response due to structural coupling between the two structures during the SpaceX launch. These vibrations, which were initially observed in the IAM Engineering Development Unit (EDU) test and later verified through finite element analysis (FEA) for the SpaceX launch loads, may damage the internal electronic cards and the Thermoelectric Quartz Crystal Microbalance (TQCM) sensors mounted on the CMP. Three-dimensional (3D) vibration isolators were required to be inserted between the CMP and IAM interface in order to attenuate the high frequency vibrations without resulting in any major changes to the existing system. Wire rope isolators were proposed as the isolation system between the CMP and IAM due to the low impact to design. Most 3D isolation systems are designed for compression and roll, therefore little dynamic data was available for using wire rope isolators in an inverted or tension configuration. From the isolator FEA and test results, it is shown that by using the 3D wire rope isolators, the CMP high-frequency responses have been suppressed by several orders of magnitude over a wide excitation frequency range. Consequently, the TQCM sensor responses are well below their qualification environments. It is indicated that these high-frequency responses due to the typical instrument structural coupling can be significantly suppressed by a vibration passive control using the 3D vibration isolator. Thermal and contamination issues were also examined during the isolator selection period for meeting the SAGE III-ISS instrument requirements.
Li, Y.↗
Experimental investigation of a double-diffused MOS structure
Self-aligned polysilicon gate technology was applied to double-diffused MOS (DMOS) construction in a manner that retains processing simplicity and effectively eliminates parasitic overlap capacitance because of the self-aligning feature. Depletion mode load devices with the same dimensions as the DMOS transistors were integrated. The ratioless feature results in smaller dimension load devices, allowing for higher density integration with no increase in the processing complexity of standard MOS technology. A number of inverters connected as ring oscillators were used as a vehicle to test the performance and to verify the anticipated benefits. The propagation time-power dissipation product and process related parameters were measured and evaluated. This report includes (1) details of the process; (2) test data and design details for the DMOS transistor, the load device, the inverter, the ring oscillator, and a shift register with a novel tapered geometry for the output stages; and (3) an analytical treatment of the effect of the distributed silicon gate resistance and capacitance on the speed of DMOS transistors.
Lin, H. C.↗
Self-Security for Grid-Interactive Smart Inverters Using Steady-State Reference Model
Smart inverters exchange information with other devices through a shared communication link, making the inverters more prone to receive harmful commands from external parties. This erroneous data can be received due to an anomaly in the system, such as a device fault, unintentional utility operator action, or a cyber-attack. In this paper, a device-level self-security strategy is implemented using reference models for a grid-interactive inverter to examine the incoming power setpoints, detect the anomalies, and protect the system accordingly. The PQ setpoints received from the utility supervisory controller are autonomously examined using the inverter’s normal and stable operating regions before engaging the setpoints to the inverter’s local controller. Grid parameters are estimated in real-time during the examination process. The efficacy of the self-security algorithm is tested using a three-phase 3-kVA SiC-MOSFET inverter and a 12-kW NHR 9410 regenerative grid emulator. The results verify that the proposed method can detect harmful PQ setpoints that can cause abnormal or unstable inverter operation.
Gursoy, Mehmetcan↗
Disruption of Commercial Solar Inverter System by TLS Proxy Man-in-the-Middle Attack
Transport Layer Security (TLS) is a cryptographic protocol that encrypts communication data, providing end-to-end communication encryption and authentication. Currently, TLS is widely adopted for securing communication between servers and end devices, including solar inverter systems. Therefore, users/operators can securely access the solar inverters through a web user interface (WebUI) application programmable interface (API) on a PC or server over TLS-enabled Wi-Fi or Ethernet. However, the security of the TLS-based network becomes compromised if it is breached by a TLS proxy man-in-the-middle (MITM) exploit. This report explores potential vulnerabilities in a commercial solar inverter system that leverages a TLS proxy MITM and discusses the impacts through assume-breached penetration testing. Furthermore, the paper explores recommended mitigation methods against the TLS proxy MITM exploit in solar inverters.
97 MATHEMATICS AND COMPUTING↗
Dynamic Validation of CNN-Based Surrogate Models for Inverter-Based Resources in Open-Source Solvers
Traditionally, distribution system planning has focused on steady-state analyses, with limited consideration of dynamic behavior. However, as large or medium-scale inverter-based resources (IBRs), particularly grid-following (GFL) inverters in commercial or industry buildings, become more prevalent, understanding their dynamic impact is essential for grid planning and operation. This article presents an innovative deep-learning (DL)-approach using convolutional neural networks technique to model the GFL inverters. Developed from real grid-tied commercial IBR transient data, these dynamic DL models overcome proprietary constraints by requiring minimal knowledge of internal converter physics while maintaining high accuracy and flexibility. To demonstrate their applicability, the models were incorporated into GridLAB-D, an open-source, three-phase distribution analysis tool. This integration enables dynamic simulations of large-scale distribution networks with high IBR penetration stability analysis. Rigorous testing and validation, aligned with industry standards, confirmed the reliability and efficiency of this approach, paving the way for enhanced planning and operational assessments of modern power systems.
Deep-learning↗
Near-conjugate observations of inverted-V electron precipitation using DE 1 and DE 2
A major focus of auroral research has been related to the inverted-V electron precipitation event, distinguished by the 'inverted-V' variation of peak energy flux in an energy-time spectrogram. Thieman and Hoffman (1984), in an examination of plasma data from near-conjugate DE 1/2 passes in the southern hemisphere, have found that some inverted-V events remain reasonably stable over a time span of up to 18 min, while other events change over shorter time periods. The present investigation has the objective to study quantitatively the energization of inverted-V electron fluxes and to compare the results with predictions from adiabatic acceleration by an electrostatic field. The obtained results suggest that the turbulent processes might contirbute minimally to the energy flux of secondary electrons for some events, but significantly for others.
Lin, C. S.↗
Towards a data-driven model of hadronization using normalizing flows
We introduce a model of hadronization based on invertible neural networks that faithfully reproduces a simplified version of the Lund string model for meson hadronization. Additionally, we introduce a new training method for normalizing flows, termed MAGIC, that improves the agreement between simulated and experimental distributions of high-level (macroscopic) observables by adjusting single-emission (microscopic) dynamics. Our results constitute an important step toward realizing a machine-learning based model of hadronization that utilizes experimental data during training. Finally, we demonstrate how a Bayesian extension to this normalizing-flow architecture can be used to provide analysis of statistical and modeling uncertainties on the generated observable distributions.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
The Effect of Inverter Loading Ratio on Energy Estimate Bias: Preprint
Subhourly effects, particularly variability in solar irradiance, can lead to underestimation of inverter clipping losses and overestimation of energy in hourly photovoltaic system performance models, particularly for systems with high inverter loading ratios. Direct simulation of this error can be complicated by factors such as the representation of spatial and temporal variability in hourly weather data and transient system conditions. In this work we take an alternative approach using real system power measurements to show that energy predictions from typical industry models suffer from a bias that increases with inverter loading ratio. We also show that this loading ratio-dependent bias is strongly correlated with an empirical subhourly inverter clipping bias derived from real power plant data. Finally, we show that this bias is not necessarily specific to any one model or weather dataset by recreating similar biases with alternatives of each.
clipping↗
Canopy reflectance modeling in a tropical wooded grassland
Geometric/optical canopy reflectance modeling and spatial/spectral pattern recognition is used to study the form and structure of savanna in West Africa. An invertible plant canopy reflectance model is tested for its ability to estimate the amount of woody vegetation from remotely sensed data in areas of sparsely wooded grassland. Dry woodlands and wooded grasslands, commonly referred to as savannas, are important ecologically and economically in Africa, and cover approximately forty percent of the continent by some estimates. The Sahel and Sudan savannas make up the important and sensitive transition zone between the tropical forests and the arid Sahara region. The depletion of woody cover, used for fodder and fuel in these regions, has become a very severe problem for the people living there. LANDSAT Thematic Mapper (TM) data is used to stratify woodland and wooded grassland into areas of relatively homogeneous canopy cover, and then an invertible forest canopy reflectance model is applied to estimate directly the height and spacing of the trees in the stands. Because height and spacing are proportional to biomass in some cases, a successful application of the segmentation/modeling techniques will allow direct estimation of tree biomass, as well as cover density, over significant areas of these valuable and sensitive ecosystems. The model being tested in sites in two different bioclimatic zones in Mali, West Africa, will be used for testing the canopy model. Sudanian zone crop/woodland test sites were located in the Region of Segou, Mali.
Simonett, David↗
Effects of Reactive Power on Photovoltaic Inverter Reliability and Lifetime
For predicting the reliability and lifetime of Photovoltaic (PV) inverters, thermal cycling is considered the most important stressors in the inverter system. To realize this, a detailed electrothermal model of the PV inverter was developed along with the controllers. The model was verified by developing an in-house inverter, which was placed inside a thermal chamber to verify the losses and temperature rise within the system at various temperatures. After the verification of the model, a reduced order model of the inverter was implemented which can translate the mission profile of ambient temperature and solar irradiance into load profile of junction temperatures of the switches. The estimated junction temperature data was used to identify the reliability indices and predict the useful lifetime of the inverter system. After developing the models to predict useful lifetime of the system, the impact of reactive power on the overall reliability of the system was studied. Experiments show that lifetime and reliability of the inverter decreases as the operating power factor decreases from unity. The results are presented and discussed here.
14 SOLAR ENERGY↗
Automating the Solar Interconnection Technical Evaluation Process: PREconfiguring and Controlling Inverter SEt-Points (PRECISE)
Utilities are receiving an increasing number of interconnection requests for distributed solar photovoltaic (PV) systems from their customers, requiring a solution to quickly and intelligently perform technical assessments of these requests and to manage these new renewable energy assets. In this paper, we present a stand-alone interconnection tool, PREconfiguring and Controlling Inverter SEt-points (PRECISETM), and how it overcomes the challenges of accelerating technical evaluations and leverages smart inverter functionality to provide local voltage support on an as-needed basis. The paper details the purpose and architecture of PRECISE, including tools, data source requirements, the model-based interconnection evaluation process, and technical results. PRECISE is an integrated software tool that customizes PV inverter settings for utilities by modeling and assessing impacts on local voltages and the need for advanced inverter functions (AIFs) (e.g., volt-VAR and volt-watt). PRECISE maximizes the use of readily available utility data sets to make fast online assessments of incoming PV interconnection requests and makes accept/reject recommendations along with custom settings for AIFs.
ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗
Regularization of soft-X-ray imaging in the DIII-D tokamak
We developed an image inversion scheme for the soft X-ray imaging system (SXRIS) diagnostic at the DIII-D tokamak in order to obtain the local soft X-ray emission at a poloidal cross-section from the spatially line-integrated image taken by the SXRIS camera. The scheme uses the Tikhonov regularization method since the inversion problem is generally ill-posed. The regularization technique uses the generalized singular value decomposition to determine a solution that depends on a free regularization parameter. The latter has to be chosen carefully, and the so called {\it L-curve} method to find the optimum regularization parameter is outlined. A representative test image is used to study the properties of the inversion scheme with respect to inversion accuracy, amount/strength of regularization, image noise and image resolution. Moreover, the optimum inversion parameters are identified, while the L-curve method successfully computes the optimum regularization parameter. Noise is found to be the most limiting issue, but sufficient regularization is still possible at noise to signal ratios up to 10%-15%. Finally, the inversion scheme is applied to measured SXRIS data and the line-integrated SXRIS image is successfully inverted.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Wind turbine blade design with airfoil shape control using invertible neural networks
Wind turbine blade design is a highly multidisciplinary process that involves aerodynamics, structures, controls, manufacturing, costs, and other considerations. More efficient blade designs can be found by controlling the airfoil cross-sectional shapes simultaneously with the bulk blade twist and chord distributions. Prior work has focused on incorporating panel-based aerodynamic solvers with a blade design framework to allow for airfoil shape control within the design loop in a tractable manner. Including higher fidelity aerodynamic solvers, such as computational fluid dynamics, makes the design problem computationally intractable. In this work, we couple an invertible neural network trained on high-fidelity airfoil aerodynamic data to a turbine design framework to enable the design of airfoil cross sections within a larger blade design problem. We detail the methodology of this coupled framework and showcase its efficacy by aerostructurally redesigning the IEA 15-MW reference wind turbine blade. The coupled approach reduces the cost of energy by 0.9% compared to a more conventional design approach. This work enables the inclusion of high-fidelity aerodynamic data earlier in the design process, reducing cycle time and increasing certainty in the performance of the optimal design.
17 WIND ENERGY↗
UPS XML Format and Data
This is the XML data and format for UPS supercomponent including subcomponents: Grid following inverter (GFL), Grid forming inverter (GFM), and dc-dc converter connected to the energy storage and the AI load.
Marthi, Phani Ratna Vanamali [ORNL] (ORCID:0000000↗
Subsurface electrical conductivity across the BEO site inferred using a capacitively coupled resistivity survey in May 2013, Utqiagvik, Alaska
Multiple transects across and around the Barrow Environmental Observatory (BEO) site were surveyed using a capacitively coupled resistivity tool to infer the subsurface electrical conductivity in the top ~6 m in order to improve the understanding of heterogeneity in ice and salinity content. This work was led by the environmental geophysics team from Lawrence Berkeley National Laboratory as part of the Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic). The acquisition was performed in May 2013 using a capacitively coupled resistivity tool (OhmMapper from Geometrics, Inc) mounted behind a sled hooked to a snowmobile. Twenty-eight ~750 m long transects cover the NGEE intensive site (polygon areas A, B, C, D) in the BEO with a measurement (apparent resistivity for 5 different geometries) taken every 1.5 to 2 m. The survey also includes other transects that have been acquired along Electrical Resistivity Tomography (ERT) transects previously acquired at the site (Site 0, AB, and BD), and several long transects (up to 7 km each) around the BEO site crossing several Drained Thawed Lake Basins (DTLB). The various transects acquired during this survey cover a distance of about 100 km. All the datasets are provided with the acquisition geometry and the associated subsurface apparent electrical conductivity. In addition, the 28 transects at the BEO intensive site were inverted to infer the subsurface electrical conductivity. Unprocessed and processed data products are included in this package. This metadata document contains a description of the survey and processing steps and the inferred products.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska, and 2) multiple areas in the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).
54 ENVIRONMENTAL SCIENCES↗
Voltage Optimization
Voltage optimization refers to a volt-var optimization technique which was originally designed to minimize energy consumption and improve end-use efficiency on the distribution system. This reduces source voltage at a substation, which lowers generation demand, reduces system losses, and improves system stability. This has been the conventional implementation of voltage optimization: focusing on regulation of voltages throughout the distribution system via coordinated adjustments of load tap changers, line-voltage regulators, switched shunt compensation, and the targeted placement of new shunt compensation. These methods have received increased focus following a growth in distributed-energy resources (DERs) interconnecting at the distribution level, given their developing capability to participate in voltage regulation. This is paired with the intermittency challenges they pose, load imbalances, and voltage fluctuations. Voltage optimization has long been an area of extensive research within the distribution system, with various strategies and philosophies demonstrating a range of effects. The conventional focus on the distribution system owes to the typical operation of transmission systems, which assumes firm local resources and flows strictly from generation resources to loads. The strategies employed in distribution have also been optimized for this typically radial configuration and operation of the distribution system.
24 - POWER TRANSMISSION AND DISTRIBUTION↗