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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Electrostatically Enhanced Buried Interface Binding of Self‐Assembled Monolayers for Efficient And Stable Inverted Perovskite Solar Cells

Inverted p‐i‐n structure perovskite solar cells (PSCs) have outperformed traditional n‐i‐p PSCs in recent years. A key advancement is the use of self‐assembled monolayers (SAMs) as hole transport layers. One class of widely used SAMs is carbazole‐based phosphonic acids. However, it is found that these SAMs lack strong binding with transparent conducting oxides (TCO) and perovskite. The weak binding strength results in suboptimal interfacial adhesion of the buried interface, which limits the device's stability. Here, interfacial binding is enhanced by increasing the dipole moment that creates a strong interfacial electric field that enhances electrostatic interactions at the TCO/perovskite interface, while incorporating tailored functional groups in SAMs to improve chemical anchoring to TCO and binding to perovskite. Specifically, the donor‐acceptor SAM molecule 4‐(7‐(4‐(bis(4‐methoxyphenyl)amino)‐2,5‐difluorophenyl)benzo[c][1,2,5]thiadiazol‐4‐yl)benzoic acid (PAFTB) is employed, which features an enhanced dipole moment along with electron‐donating and electron‐withdrawing functional groups to optimize interfacial interactions. Compared to extensively used [2‐(9H‐carbazol‐9‐yl)ethyl]phosphonic acid (2PACz), PAFTB enhances total interfacial adhesion by 2.8 times, thereby improving the thermal stability of the layer. Using this approach, PSCs are demonstrated with a certified quasi‐steady‐state power conversion efficiency of 24.9% and maintain 80% of the initial efficiency after 900 h of maximum power point tracking at 85 °C.

Interfacial adhesion↗
DOE OSTI2020

Scalable, Physical Effects Measurable Microgrid for Cyber Resilience Analysis (SPEMMCRA)

The ability to advance state of the art automated protections for industrial control systems (ICS) has as a precursor in the ability to understand the tradeoff space. That is, to enable a cyber feedback loop in a control system environment you must first consider both the security mitigation available, the benefits and the impacts to the control system functionality when the mitigation is used. More damaging impacts could be precipitated that the mitigation was intended to rectify. This paper details networked ICS that controls a simulation of the frequency response represented with the swing equation. The microgrid loads and base generation can be balanced through the control of an emulated battery and power inverter. The simulated plant, which is implemented in Raspberry Pi computers, provides an inexpensive platform to realize the physical effects of cyber attacks to show the tradeoffs of available mitigatoins. This network design can include a commercial ICS controller to introduce real world implementation of feedback controls, and provides a scalable, physical effects measurable Microgrid for cyber resilience analysis (SPEMMCRA).

42 ENGINEERING↗
DOE OSTI2025

Virtual Cable Impedance based Load Sharing in a Microgrid for Parallel Connected Grid Forming Converters

This paper presents a novel approach to power sharing between direct connected grid-forming converters, utilizing virtual cable impedance and droop-based outer loop control. To enhance stability, resistive droop is implemented, while virtual cable impedance with non-zero resistive and inductive components ensures improved power sharing. The inner loop controller employs a Lyapunov energy function to achieve superior dynamic performance. The proposed control architecture is validated through comprehensive modeling and real-time processor-in-the-loop simulations, demonstrating its robustness and efficiency under various operating conditions. The results highlight the potential of this control strategy to improve the reliability and efficiency of renewable energy systems. Additionally, a comparative analysis with traditional methods underscores the advantages of the proposed approach in terms of stability and performance. The proposed control architecture offers a scalable and flexible solution for grid-forming converters, enabling seamless integration of renewable energy sources. Its robustness and adaptability make it an attractive solution for real-world applications. Furthermore, the approach can be extended to other power electronic systems, enhancing overall system performance and efficiency. By providing a reliable and efficient control strategy, this paper contributes to the advancement of renewable energy systems and their adoption in the energy sector. The proposed control strategy has far-reaching implications for the widespread adoption of renewable energy sources, enabling a more sustainable and efficient energy future. The overall system is modeled in MATLAB/Simulink and PLECS software domain.

grid forming converters (GFM)↗
DOE OSTI2020

CRADA Final Report: Open Microgrid Platform

Current microgrid control technology is mostly proprietary, expensive, and inflexible. An open-source, vendor-neutral, publish-subscribe controller will significantly lower the barrier to entry for new technologies and market entrants: inverter, battery, and load control manufacturers; cloud and services providers; and energy aggregators. An OpenFMB controller can significantly reduce the acquisition, integration, and ongoing operating and maintenance costs and increase revenue opportunities for energy producers and consumers. It allows distributed energy resource (DER) owners to replace individual DER components as richer-function, lower-cost devices become available or to incorporate new forecast and optimization algorithms as they are developed. A standard, secure, full-function DER field controller will also provide a low-cost means for grid operators to effectively manage the variability and uncertainty of solar photovoltaics (PV). Under the terms of this CRADA, ORNL has worked with Open Energy Solutions (OES) to advance the transition of ORNL’s existing open-source microgrid controller into a platform geared toward mainstream implementation. Using a more prevalent and memory-safe programming language, Rust, OES has converted ORNL’s current generation on-grid optimization into an application more suitable for industry use. The results of the ported optimization were analyzed by inputting the same arguments in both the current-generation and next-generation optimizers and verifying that the results were equivalent.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Improving Efficiency and Stability of Perovskite Solar Cells Enabled by A Near-Infrared-Absorbing Moisture Barrier

Simultaneously improving device efficiency and stability is the most important issue in perovskite solar cell (PSC) research. Here, we strategically introduce a multi-functional interface layer (MFIL) with integrated roles of: (1) electron transport, (2) moisture barrier, (3) near-infrared photocurrent enhancement, (4) trap passivation, and (5) ion migration suppression to enhance the device performance. The narrow-band-gap non-fullerene acceptor, Y6, was screened out to replace the most commonly used PCBM in the inverted PSCs. A significantly improved power conversion efficiency of 21.0% was achieved, along with a remarkable stability (up to 1,700 h) without encapsulation under various external stimuli (light, heat, and moisture). Furthermore, systematic studies of the molecular orientation or passivation and the charge carrier dynamics at the interface between perovskite and MFIL were presented. These results offer deep insights for designing advanced interlayers and establish the correlations between molecular orientation, interface molecular bonding, trap state density, non-radiation recombination, and the device performance.

14 SOLAR ENERGY↗
DOE OSTI2024

Photovoltaic Analysis and Response Support (PARS) Platform for Solar Situational Awareness and Resiliency Services

The project's primary objective is to develop a digital-twin based Photovoltaic (PV) Analysis and Response Support (PARS) platform, which aims to provide real-time situational awareness and optimal response plans. This platform is designed to enhance the performance of hybrid PV systems, making them competitive with or even superior to conventional generation resources. The PARS platform enabled the project team to develop and evaluate an extensive suite of grid support functionalities for the hybrid PV systems to enhance grid performance, across key areas including visibility, dispatchability, security, resilience, and reliability. Given the global push toward achieving 100% clean energy by 2035, there is a significant increase in the integration of inverter-based resources (IBRs) throughout the energy grid. Effectively managing the inherent variability and uncertainty associated with IBRs is crucial for ensuring cost-effectiveness, reliability, and security in both the main grid and islanded microgrids. Constrained to a limited array of IEEE test systems or standard feeder models, traditional IBR modeling struggles to assimilate new field data, accurately reflect system dynamics, and adapt to the evolving energy landscape. In our project, we embraced a Digital Twin (DT) strategy for crafting the PARS platform. A digital twin acts as a precise virtual counterpart of a physical system, built on historical data and continuously honed with real-time insights. This enables the high-fidelity DT to accurately mirror current system operations and forecast future scenarios. Consequently, the PARS platform becomes an ideal environment for testing and refining monitoring, control, power, and energy management algorithms designed to boost hybrid PV system performance. The defining feature of the PARS platform, distinguishing it from other advanced simulation tools, is its exceptional adaptability. This is achieved by employing actual network topologies and utilizing real-time field data for fine-tuning and calibration, ensuring a close emulation of real-world conditions. The project deliverables include: 1) High-fidelity IBR models and tools for real-time parameterization, utilizing real-time field measurements to refine IBR models for enhanced accuracy and performance; 2) Grid-forming and Grid-following capabilities to deliver resilience services, including blackstart, voltage and frequency support, cold-load pick-up, power reserves, and three-phase load balancing across grid-connected and microgrid settings; 3) Machine learning-based forecasting tools and methods for generating synthetic data and topologies, creating diverse and realistic simulation environments for evaluating varied operational scenarios; 4) Advanced microgrid power and energy management algorithms for optimizing the integration and operation of PV, storage, and demand response resources within both feeder and community scales. The power grid data sets are provided by four utility companies in North Carolina and the New York Power Administration. Acting as industry advisors, our industry partners communicated stakeholder needs and regulatory standards to the research teams, aiding technology transfer by incorporating the developed methodologies into their daily operations. This collaboration ensures that the PARS platform, functioning as a power system digital twin, enhances our understanding of IBR dynamic behaviors and enables the development and evaluation of IBR control functions that match or exceed the capabilities of conventional synchronous generators.

14 SOLAR ENERGY↗
DOE OSTI2020

Learning in Modal Space: Solving Time-Dependent Stochastic PDEs Using Physics-Informed Neural Networks

One of the open problems in scientific computing is the long-time integration of nonlinear stochastic partial differential equations (SPDEs), especially with arbitrary initial data. We address this problem by taking advantage of recent advances in scientific machine learning and the spectral dynamically orthogonal (DO) and borthogonal (BO) methods for representing stochastic processes. The recently introduced DO/BO methods reduce the SPDE to solving a system of deterministic PDEs and a system of stochastic ordinary differential equations. Specifically, we propose two new physics-informed neural networks (PINNs) for solving time-dependent SPDEs, namely the neural network (NN)-DO/BO methods. The proposed methods incorporate the DO/BO constraints into the loss function (along with the modal decomposition of the SPDE) with an implicit form instead of generating explicit expressions for the temporal derivatives of the DO/BO modes. Hence, the NN-DO/BO methods can overcome some of the drawbacks of the original DO/BO methods. For example, we do not need the assumption that the covariance matrix of the random coefficients is invertible as in the original DO method, and we can remove the assumption of no eigenvalue crossing as in the original BO method. Moreover, the NN-DO/BO methods can be used to solve time-dependent stochastic inverse problems with the same formulation and same computational complexity as for forward problems. Furthermore, we demonstrate the capability of the proposed methods via several numerical examples, namely: (1) A linear stochastic advection equation with deterministic initial condition: we obtain good results with the proposed methods, while the original DO/BO methods cannot be applied directly in this case. (2) Long-time integration of the stochastic Burgers' equation: we show the good performance of NN-DO/BO methods, especially the effectiveness of the NN-BO approach for such problems with many eigenvalue crossings during the whole time evolution, while the original BO method fails. (3) Nonlinear reaction diffusion equation: we consider both the forward problem and the inverse problems, including very noisy initial point values, to investigate the flexibility of the NN-DO/BO methods in handling inverse and mixed type problems. Taken together, these simulation results demonstrate that the NN-DO/BO methods can be employed to effectively quantify uncertainty propagation in a wide range of physical problems, but future work should address the efficiency issue of PINNs for forward problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Development and Refinement of DER Steady State Model for QSTS Analysis

EPRI formed a working group of utilities and software vendors called the Distribution Advanced PV Model Working Group (DAWG). The working group has been focused on building consensus regarding the models that represent the reactive power capabilities outlined in Section 5 of IEEE Std 1547™-2018. This report provides an overview of the reactive and active power capabilities specified in IEEE Std 1547™-2018 and outlines a specification of key functions for usage during steady state snapshot and time series power flow analysis. Additionally, it presents a framework for performing tests to verify the correct operation of functions during power flow analysis.

14 SOLAR ENERGY↗
DOE OSTI2021

Distributed Wind Controls: A Research Roadmap for Microgrids, Infrastructure Resilience, and Controls Launchpad (MIRACL)

The Microgrids, Infrastructure Resilience, and Advanced Controls Launchpad (MIRACL) project’s controls research area aims to expand the benefits from distributed wind (DW) generation assets beyond solely providing low cost power directly to consumers. To make distributed wind turbines operate more effectively there is a need for more advanced ways to control them, allowing power companies, businesses, and energy consumers to take advantage of the unique characteristics of wind energy. DW can contribute to the safe and secure operation of grid by providing services such as voltage regulation, frequency regulation, spinning reserves, and even black start capabilities. In the larger DER context where much of the research has focused around solar technologies, the inertia available in wind technologies has generally not been considered. For wind turbines to provide these services in an optimal and expanded way, development and demonstration of control methods and communication interfaces within a grid and microgrid framework are required. In this document, NREL led the literature review in collaboration with SNL, of DER controls-focused integration research to establish a baseline for the controls research under the MIRACL project to identify specific control functions to be focused on throughout this project. This literature review focused primarily on the control functions of variable distributed generation, largely pulling from past solar PV and battery controls works, with a specific focus on applicability for distributed wind energy systems. The goal of this document is to identify a research roadmap based on the open literature and past national laboratory works to inform advanced wind turbine and power electronics control functions for four use cases: 1) distributed wind in isolated systems, 2) grid-connected microgrids (wind-hybrid systems and islanded operation), 3) behind-the-meter distributed wind applications in the power distribution systems, and 4) front-of-the-meter distributed wind applications in the power distribution systems.

17 WIND ENERGY↗
DOE OSTI2020

Highly Integrated WBG Power Module for Next Generation Plug-In Vehicles

Current inverter technologies used in electric vehicles (EVs) are bulky, heavy, and expensive. The performance of the inverter is also limited by the traditional Si-based semiconductor and packaging technology. These constraints are responsible for extra weight and volume in the vehicle that reduces the driving range along with usable space within the vehicle. Moreover, operating temperature restrictions, and boundaries on the inverter location within the vehicle drastically reduces the inverter performance. Thus an improved inverter design is required for next generation electric vehicles. The objective of this project was to research, develop and demonstrate a highly integrated WBG power module targeting the next generation of plugin hybrid electric vehicles (PHEVs). This power module needed to be functionally and mechanically optimized for General Motors (GM) traction inverter architecture. General Motors was the prime contractor, led the project, and oversaw the design, build, and test of the integrated power module. Virginia Polytechnic Institute and State University (VT) performed modeling and simulation tasks as well as power module design support. Monolith Semiconductor, Inc provided SiC dies and consulted on devices for the inverter. Oak Ridge National Laboratory (ORNL) performed power module technology evaluations, design evaluations of interconnect options, and performed material analysis and cross-sectioning of die activities.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Smart Meter Pinging and Reading Through AMI Two-Way Communication Networks to Monitor Grid Edge Devices and DERs

Today’s power distribution system is changing to a power-electronics-enabled distribution system, especially with the increasing penetration of distributed energy resources (DERs). To monitor and manage those electronic devices and DERs at the grid edge, the advanced metering infrastructure (AMI) with two-way communications presents great potential. At present, extensive research explores the upstream communication from smart meters to electric utilities (e.g., meter reading) but few examine the downstream communication from the utilities to smart meters (e.g., meter pinging). This article discusses the AMI two-way communication and its recent industrial practice in the U.S., especially for applying the smart meter pinging functionality to monitor grid-edge devices and DERs. This paper then develops the two-way communication model and the network calculus method to quantify the impact of the two-way communication on the AMI network. In the end, the proposed method is validated with ns-3 simulation using the modified 13-node test feeder and real-world feeder systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Strictly Enforcing Invertibility and Conservation in CNN-Based Super Resolution for Scientific Datasets

Abstract Recently, deep convolutional neural networks (CNNs) have revolutionized image “super resolution” (SR), dramatically outperforming past methods for enhancing image resolution. They could be a boon for the many scientific fields that involve imaging or any regularly gridded datasets: satellite remote sensing, radar meteorology, medical imaging, numerical modeling, and so on. Unfortunately, while SR-CNNs produce visually compelling results, they do not necessarily conserve physical quantities between their low-resolution inputs and high-resolution outputs when applied to scientific datasets. Here, a method for “downsampling enforcement” in SR-CNNs is proposed. A differentiable operator is derived that, when applied as the final transfer function of a CNN, ensures the high-resolution outputs exactly reproduce the low-resolution inputs under 2D-average downsampling while improving performance of the SR schemes. The method is demonstrated across seven modern CNN-based SR schemes on several benchmark image datasets, and applications to weather radar, satellite imager, and climate model data are shown. The approach improves training time and performance while ensuring physical consistency between the super-resolved and low-resolution data. Significance Statement Recent advancements in using deep learning to increase the resolution of images have substantial potential across the many scientific fields that use images and image-like data. Most image super-resolution research has focused on the visual quality of outputs, however, and is not necessarily well suited for use with scientific data where known physics constraints may need to be enforced. Here, we introduce a method to modify existing deep neural network architectures so that they strictly conserve physical quantities in the input field when “super resolving” scientific data and find that the method can improve performance across a wide range of datasets and neural networks. Integration of known physics and adherence to established physical constraints into deep neural networks will be a critical step before their potential can be fully realized in the physical sciences.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Faster-than-real-time Simulation with Demonstration for Resilient DER Integration

The US electric grid is facing operational, stability, and security challenges. Transmission system operators need some measure of visibility into distribution system renewable generation. Distribution system generation needs to support transmission system voltage. The grid is experiencing an expansion in measurement systems. How to take full advantage of this expansion and defend against attacks, both cyber and physical, poses additional challenges. The Faster-than-real-time Simulation with demonstration for Resilient DER Integration project set out to do the following: a. Flatten the voltage profile through the feeders and system for cost saving and voltage stabilization needs. b. Increase the amount of intermittent distributed energy resources (IDERs) that could be deployed on a utility feeder and provide 100% or more energy needed for the demands on that feeder, and c. based on an accurate model (Digital Twin) of the utilities system, be able to detect any abnormalities on the utilities distribution system. To manage the voltage and increase IDER penetration (a,b), Graph Trace Analysis is employed in a time-series, optimal power flow to coordinate the time-varying feedback control setpoints of a distribution feeder’s utility control devices. Under the coordinated control are a Load Tap Changing Transformer, a voltage regulator, and five switched capacitor banks. The feeder serves over 2000 customers, the feeder secondaries are modeled, and the feeder has 2.3 MW of PV generation, corresponding to a 17.4% penetration of PV generation. The feeder model has over 12,000 components, where every customer load bus and PV generator are modeled. The accuracy of the power flow solution is compared against historical meter voltage measurements, the improvement in conservation voltage reduction energy savings as a function of the coordinated control desired voltage profile is investigated, and the increase in PV penetration of the coordinated control over the existing control is presented. To achieve improved control performance while observing system operation constraints, bellwether Advanced Metering Infrastructure (AMI) voltage measurements are used to adjust the desired voltage profile used by the optimal power flow analysis. To detect and alleviate or negate attacks or failures on the distribution and transmission utility grids (c) the grid needs to be resilient and self-healing. In this project software was designed to do just that. At the center of the software is an Integrated System Model (ISM) that spans from transmission to secondary distribution. The ISM is employed in real-time abnormality detection, voltage stability forecasting, and multi-mode control. Testing results are presented for: 1—attacks on utility infrastructure; 2—energy savings from optimal control; 3—distribution system control response during a low voltage transmission system event; 4—cyber-attacks on PV inverters, where physical inverters are used in hard-ware-in-the-simulation-loop studies. Contributions of this work include real-time analysis that spans from three-phase transmission through secondary distribution; an approach for detecting abnormalities that employs measurements from three independent measurement systems; and a multi-mode distribution system control that responds to cyber-attacks, physical attacks, equipment failures, and transmission system needs.

Integrated System Model, Graph Trace Analysis, Adv↗
DOE OSTI2021

Highly Integrated Wide Bandgap Power Module for Next Generation Plug-In Vehicles (Final Report)

Wide bandgap devices are key enablers for high power density traction inverters. A highly integrated wide bandgap (WBG) power module enables higher temperature operation, higher inverter efficiency and overall smaller die area with the same power delivery. However, it requires careful design of the power module to take advantage of all the superior material properties that silicon carbide (SiC) provides over conventional silicon (Si) Insulated Gate Bipolar Transistor (IGBT) based design. This project developed an efficient and densely packed SiC power module for an automotive traction inverter application. Extensive study was performed to select the best performing SiC die considering a wide range of temperature variation, suitability to integrate into target packaging, robust body diode performance and overall high electrical efficiency. Multiple design ideas were explored to achieve lower stray inductance for both power loop and signal loop, uniform current distribution, compact form factor, and very high thermal performance. The final power module package includes all six inverter switches in the same module (six-pack) with die sintered at both bottom and top surfaces utilizing high performance substrate to achieve high electrical and thermal performance. Two power module variants were developed using 900 V and 1200 V devices for operating at two different high voltage levels (> 600 V HV battery). Both power modules were comprehensively characterized, and high efficiency operation of the inverter was confirmed through analysis. Finally, a complete functional inverter was built with the 1200V power modules using other essential components (HV capacitors, gate driver board, controller board, current sensor, connectors etc.) and tested using GM’s standard test procedure. There are several challenges associated with adopting WBG devices for high voltage operation. In order to assess and mitigate those challenges, GM and subrecipients of this project have conducted multiple detailed studies. This includes phase current reconstruction using integrated Rogowski coil, device junction temperature estimation using on-state gate resistance, modeling and testing the effect of high voltage and fast switching on motor insulation and bearings, partial discharge inception voltage measurement under different environmental conditions. Findings of all these studies are summarized in this report.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

Autonomous Grid Support Functionality in Variable-Speed Drive-Based End-Use Loads

High penetration of inverter-based resources into power systems causes lower inertia, and it becomes more challenging to maintain grid stability during contingency events. While conventional demand response and shedding at the load side suffer from slow response, impact by unavailability, and issues from communication, variable-speed drives (VSDs) are becoming strong candidates for fast frequency response (FFR) thanks to their fast response and reduced user impact from variable power adjustment capability. In this letter, we propose an autonomous frequency support control method for a residential refrigerator with a VSD, a promising target small end-use load for FFR. We analyze the effect of the proposed controller on grid stability, and we verify the performance through laboratory experiments with a commercially available refrigerator.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Surface reaction for efficient and stable inverted perovskite solar cells

We report perovskite solar cells (PSCs) with an inverted structure (often referred to as the p-i-n architecture) are attractive for future commercialization due to their easily scalable fabrication, reliable operation, and compatibility with a wide range of perovskite-based tandem device architectures. However, the power conversion efficiency (PCE) of p-i-n PSCs falls behind n-i-p (or normal) structure counterparts. This large performance gap could undermine efforts to adopt p-i-n architectures, despite their other advantages. Given the remarkable advances in perovskite bulk materials optimization over the past decade, interface engineering has become the most important strategy to push PSC performance to its limit. Here, we report a reactive surface engineering approach based on a simple post-growth treatment of 3-(Aminomethyl)pyridine (3-APy) on top of a perovskite thin film. First, the 3-APy molecule selectively reacts with surface FA+, reducing perovskite surface roughness and surface potential fluctuations associated with surface steps/terraces. Second, the reaction product on the perovskite surface decreases the formation energy of charged iodine-vacancies, leading to effective n-type doping with a reduced work function in the surface region. With this reactive surface engineering, the resulting p-i-n PSCs obtained a PCE over 25%, along with retaining 87% of the initial PCE after over 2400 h of one-sun operation at about 55 degrees C in air.

14 SOLAR ENERGY↗
DOE OSTI2020

Renewable Integration in Hybrid ac-dc Systems using Multi-port Autonomous Reconfigurable Solar power plant (MARS)

To increase inertia and improve primary frequency response of future grids, grid-forming inverters connecting PV to grid and energy storage systems (ESSs) are likely to play an important role. Moreover, high-voltage direct current (HVdc) links will also be an enabler to transfer remote PV generation and for improved grid stability. That is, with increased penetration of PV, discrete development of PV and ESS connecting to transmission ac grid and HVdc links is one of the solutions for stable operation of grid. Here, an integrated concept for integration of PV and ESS to transmission ac grid and HVdc links is proposed that is named as multi-port autonomous reconfigurable solar power plant (MARS). The proposed integrated development reduces the cost associated with respect to discrete development of PV-ESS systems connecting to transmission ac grid and HVdc links. The integrated development incorporates advanced control methods to provide inertial and primary frequency response, reactive power support, and transient stability to manage PV and ESS resources. In this paper, high-fidelity switched system model of the integrated system and grids are developed and detailed simulation results are provided to showcase the stable operation of the integrated system and provision of grid support functions.

14 SOLAR ENERGY↗
DOE OSTI2020

Impacts of Voltage-Based Grid Support Functions on Energy Production of PV Customers

This paper presents the impact of inverter grid- support functions (GSFs) on photovoltaic (PV) customer energy production on a real distribution feeder in Oahu, HI. These autonomous GSFs based on local voltage measurements are good alternatives to increase PV hosting capacity. However, these functions can result in PV energy curtailment to the customer, and this study addresses the concerns about the impact of inverter GSFs through detailed quasi-static time series (QSTS) simulations. It proposes four metrics: maximum and average GSF curtailment, average increased generation and average net generation change, to assess the impact of a given control on PV systems located on customer sites. It was found that curtailment of PV production is negligible for customers where peak voltage is within ANSI C84.1 range. A reliable relationship between curtailment and peak customer voltage is demonstrated, suggesting that peak voltage could be used as an indicator of customer curtailment.

24 POWER TRANSMISSION AND DISTRIBUTION↗