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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Accelerating Simulation for High-Fidelity PV Inverter System Reliability Assessment with High-Performance Computing

The overall cost of photovoltaic (PV) systems has shown a downward trend during the last decade; however, PV inverter failures account for the highest cost of operation and maintenance. To address this, reliability tools with powerful computation and better accuracy are required for the lifetime prediction and degradation evaluation of PV inverters. This paper proposes an event-driven parallel computing-based simulator. The proposed simulator applies high-performance computing techniques and other accessory optimization techniques-including cluster merging, adaptive model updates, and steady-state identification-to make reliability assessments for PV inverters under given input mission profiles and operating conditions with high efficiency and high fidelity. The main idea of the simulator and its workflow are introduced. Then, a demo PV inverter system simulator is implemented, and the speedup of the total simulations of the switching model reaches 123.03 times.

high-performance computing↗
DOE OSTI2022

Metal Oxide Varistor (MOV) Lifetime Estimation with Impulse-Based Testing in PV Inverter Systems

Surges caused by lightning strikes could damage electrical components in photovoltaic (PV) systems. Metal oxide varistors (MOVs) are commonly used to protect PV systems from lightning strikes. This paper proposes a holistic impulse-based MOV lifetime estimation framework. The impacts of peak current and fault duration induced by lightning events are considered in the MOV lifetime estimation framework. Moreover, the impact of different parameter combinations on MOV lifetime estimation is analyzed. The effectiveness of the proposed work is validated in a PV inverter test system developed in MATLAB/Simulink.

lifetime estimation↗
DOE OSTI2022

Metal Oxide Varistor (MOV) Lifetime Estimation with Impulse-Based Testing in PV Inverter Systems: Preprint

Surges caused by lightning strikes could damage electrical components in photovoltaic (PV) systems. Metal oxide varistors (MOVs) are commonly used to protect PV systems from lightning strikes. In this paper, a holistic impulse-based MOV lifetime estimation framework is proposed. The impacts of peak current and fault duration induced by lightning events are considered in the MOV lifetime estimation framework. Moreover, the impact of different parameter combinations on MOV lifetime estimation is analyzed. The effectiveness of the proposed work is validated in a PV inverter test system developed in MATLAB/Simulink.

lifetime estimation↗
DOE OSTI2023

PV Inverter Systems Enabled by Monolithically Integrated SiC based Four Quadrant Power Switch (4-QPS) [BiDFET]

The purpose of this project was to develop a new breed of Power Conversion Systems (PCS) for PV integration that is enabled by the newly developed 4-Quadrant Single Die SiC Power Semiconductor Switches (4-QPS) or also referred to as “Bidirectional FET (BIDFET)”. This work includes semiconductor die development, advanced packaging, converter design, development, and testing of 4-QPS enabled hardware prototypes at 1 kW (for single phase residential application) and 10 kW (for three phase commercial application). The BiDirectional Field-Effect Transistor (BiDFET) can enable circuit topologies requiring four-quadrant switches, that were earlier designed using discrete combinations of MOSFETs, IGBTs, GaN HEMTs, and PiN diodes. The monolithic nature of the BiDFET allows lower device count, smaller switch volume, lower inductance, and simpler packaging, and hence more reliable and commercially viable implementation in power electronics converters. The matrix converter topologies, now feasible using BiDFETs, can eliminate the bulky and unreliable dc link capacitors or inductors required for conventional voltage-source or current-source converters in ac–ac and ac–dc applications. The 1.2 kV BiDFET has the potential to disrupt all the applications utilizing 1.2 kV switches, including electric vehicle (EV) drivetrain, bidirectional EV chargers, industrial motor drives, solid-state transformers, datacenter power supplies, elevator drives, dc microgrids, energy storage grid integration, solid-state breakers, etc.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Systems and methods for advanced grid integration of distributed generators and energy resources

A circuit for a smart photovoltaic (PV) inverter system and the smart PV inverter system are described. The circuit includes one or more strings coupled to an electrical load. Each of the one or more strings further includes one or more string members coupled in series, where each of the one or more string members comprises a voltage source and an inverter. The circuit also includes a controller to receive an output from an operator controller and control the strings, where the controller is configured to control the strings by providing a function command to a first string member of each of the one or more strings based on the output from the operator controller. The voltage source may also receive an output from an energy output device. Further, the inverter may be configured to convert the output of energy output device into an energy source of electrical load.

Bhowmik, Shibashis↗
DOE OSTI2022

Data-Driven Distribution System Coordinated PV Inverter Control Using Deep Reinforcement Learning

The deployment of distributed solar photovoltaic (PV) systems has increased consistently over the past decades. High penetrations of PVs could cause a series of adverse grid impacts, such as voltage violations. The recent development of smart inverter technologies rises the incentives of developing PV control solutions that regulate the inverter output power and seeking the optimization on system operational objectives. This paper proposes a data-driven control solution based on deep reinforcement learning (DRL) to optimize PV inverters for voltage regulation. The proposed solution can minimize PV real power curtailment while maintaining network voltage at an acceptable range. Comparison results between the proposed DRL control algorithms with deep deterministic policy gradient (DDPG) and volt-var control on a real feeder in west Colorado highlight the advantage of the proposed framework in controlling the system voltage while minimizing the PV real power curtailment.

deep reinforcement learning↗
DOE OSTI2022

Failure Mode and Effects Analysis for a Photovoltaic Inverter

While PV panel reliability continues to increase, PV inverters become the limiting factor for PV system reliability. Consequently, it is critical to have a generic tool from a third party for PV inverter reliability assessment to help 1) utilities/PV farm operators schedule maintenance in advance, and 2) inverter developers improve the next-generation design. However, these two things cannot be accomplished without first understanding the reasons behind inverter failure. Following this idea, as the first step, it is essential to identify and investigate the most failure-prone components within a PV inverter system. After all, any system is only as reliable as the components that are contained within it. This motivates the failure mode and effects analysis (FMEA) work presented for this workshop. The FMEA is conducted as follows: first, the overview of the methodology on the development of the FMEA is presented; then, based on a top-down approach starting from the PV inverter system, critical inverter components with high failure rates are identified and summarized; afterward, a thorough FMEA study at a component-level is performed and its results, including failure modes, failure mechanisms, and critical stressors, are tabulated; finally, according to three rankings (chance of occurrence, severity of occurrence, and ease of detection prior to failure) for each failure mechanism provided by the FMEA, risk priority numbers are calculated and the failure mechanisms along with the critical stressors are ranked in terms of their potentially detrimental effect on the PV inverter.

Brown, Buck↗
DOE OSTI2021

Attention Enabled Multi-Agent DRL for Decentralized Volt-VAR Control of Active Distribution System Using PV Inverters and SVCs

This paper proposes attention enabled multi-agent deep reinforcement learning (MADRL) framework for active distribution network decentralized Volt-VAR control. Using the unsupervised clustering, the whole distribution system can be decomposed into several sub-networks according to the voltage and reactive power sensitivity relationships. Then, the distributed control problem of each sub-network is modeled as Markov games and solved by the improved MADRL algorithm, where each sub-network is modeled as an adaptive agent. An attention mechanism is developed to help each agent focus on specific information that is mostly related to the reward. All agents are centrally trained offline to learn the optimal coordinated Volt-VAR control strategy and executed in a decentralized manner to make online decisions with only local information. Compared with other distributed control approaches, the proposed method can effectively deal with uncertainties, achieve fast decision makings, and significantly reduce the communication requirements. Comparison results with model-based and other data-driven methods on IEEE 33-bus and 123-bus systems demonstrate the benefits of the proposed approach.

distribution network↗
DOE OSTI2025

Electromagnetic Transient Simulation of Photovoltaic Inverter Using Implicit-Explicit Solver

This paper introduces the implementation of electromagnetic transient (EMT) simulations of a photovoltaic (PV) inverter module using the Implicit-Explicit (ImEx) solver in the Suite of Nonlinear and Differential/Algebraic Equation Solvers (SUNDIALS). This study demonstrates the effectiveness of the ImEx solver in overcoming the challenges inherent in simulating the complex dynamics of PV inverter modules. Furthermore, using SUNDIALS’ ImEx solver module ARKODE for EMT simulation automates key aspects of the process, such as numerical integration, providing substantial benefits including enhanced consistency, faster implementation, reduced human error, and the capability to handle the complexities of advanced numerical integration. By conducting comparative simulations with an implicit method used in commercial software, the research showcases the ImEx solver’s capability in achieving high accuracy and reliability. Results indicate that leveraging the ImEx approach significantly enhances modeling fidelity and reduces simulation setup times, offering a promising tool for the EMT analysis of PV inverter systems in power electronics-dominated power grids.

Choi, Jongchan [ORNL] (ORCID:000000025952455X)↗
DOE OSTI2025

An Optimized H5 Hysteresis Current Control with Clamped Diodes in Transformer-Less Grid-PV Inverter

With the rise of renewable energy penetration in the grid, photovoltaic (PV) panels are connected to the grid via inverters to supply solar energy. Transformer-less grid-tied PV inverters are gaining popularity because of their improved efficiency, reduced size, and lower costs. However, they can induce a path for leakage currents between the PV and the grid due to the absence of galvanic isolation. This leads to serious electromagnetic interference, loss in efficiency, and safety concerns. The leakage current is primarily influenced by the nature of the common mode voltage (CMV), which is determined by the switching techniques of the inverter. In this paper, a novel inverter topology of Hysteresis Controlled H5 with Two Clamping Diodes (HCH5-D2) is derived. The HCH5-D2 topology helps decouple the AC part (Grid) and DC part (PV) during the freewheeling period to make the CMV constant, thereby reducing the leakage current. Additionally, the extra diodes help reduce voltage spikes generated during the freewheeling period and maintain the CMV at a constant value. Finally, a 2.2 kW grid-connected single-phase HCH5-D2 PV inverter system’s MATLAB simulation is presented, showing better results compared to a traditional H4 inverter.

42 ENGINEERING↗
DOE OSTI2024

Enhancing PV Inverter Reliability Through Predictive Maintenance: Insights from Retrofitting of PV Inverters

Photovoltaic (PV) systems represent a cornerstone in the global shift toward sustainable energy generation, with inverters serving as the crucial link between solar panels and the grid. Despite their pivotal role, inverters are susceptible to failures, contributing significantly to maintenance events and operational disruptions in large-scale PV plants. This white paper investigates the importance and methodologies of predictive maintenance strategies that monitor the component-level pre-failure signatures on PV inverters. Through a comprehensive survey of literature and industry professionals, insights on preventive maintenance and retrofitting practices have been gathered. The expert elicitation helps shed light on common challenges and opportunities for improving PV system reliability, particularly inverter reliability. By addressing these challenges, the white paper aims to enhance the long-term viability and effectiveness of solar PV plants in the renewable energy landscape, contributing to the global transition toward environmentally friendly energy generation.

14 SOLAR ENERGY↗
DOE OSTI2020

Highly Reliable Multi-Port Smart Inverter Modules for PV-Based Energy Systems

Generally, large electrolytic capacitors (E-caps) are required to decouple the double-line frequency power fluctuation inherent in all single-phase dc-ac or ac-dc converters. These E-caps pose the weak link in the photovoltaic (PV) inverter because they have poor reliability as a result of short life expectancy and higher equivalent series resistance (ESR) which leads to lower system efficiency. In this paper, multiport smart dual-inverter modules are proposed for residential PV inverter systems with balanced outputs to eliminate the requirement of large decoupling capacitors, thus leading to more reliable and highly efficient inverter modules. The balanced dual outputs are controlled in phase quadrature such that the double frequency current is completely eliminated. One phase supports the standalone residential loads, and the other phase interfaces with the grid, which is synchronized to the utility grid. Also, the proposed modular configuration is scalable to accommodate higher power rating by stacking and paralleling multiple modules. Simulation results for the dual-inverter modules rated for 1 kW each are presented to validate the proposed concept. Experimental results from a controller hardware-in-the-loop (CHIL) platform also verify its feasibility.

14 SOLAR ENERGY↗
DOE OSTI2021

Control and Simulation of a Grid-Forming Inverter for Hybrid PV-Battery Plants in Power System Black Start

Power system restoration is an important part of system planning. Power utilities are required to maintain black start capable generators that can energize the transmission system and provide cranking power to non-blackstart capable generators. Traditionally, hydro and diesel units are used as black start capable generators. With the increased penetration of bulk size solar farms, inverter based generation can play an important role in faster and parallel black start thus ensuring system can be brought back into service without the conventional delays that can be expected with limited black start generators. Inverter-based photovoltaic (PV) power plants have advantages that are suitable for black start. This paper proposes the modeling, control, and simulation of a grid-forming inverter-based PV-battery power plant that can be used as a black start unit. The inverter control includes both primary and secondary control loops to imitate the control of a conventional synchronous machine. The proposed approach is verified using a test system modified from the IEEE 9-bus system in the time-domain electromagnetic transient simulation tool PSCAD. The simulation results shows voltage and frequency stability during a multi-step black-start and network energization process.

Nguyen, Quan H.↗
DOE OSTI2024

Simulation-Based Analysis of Feeder Operation with Different PV Smart Inverter Functions on an Actual Distribution System: Preprint

High penetration of photovoltaics (PV) in distribution feeders can cause problems, such as overvoltage, reverse power flow, and large net load changes. Traditional voltage regulation devices, such as capacitors and voltage regulators, can solve some of these problems but might have some delays. Today, smart inverters are gradually being used to provide voltage regulation and frequency support in distribution systems. Different smart inverter settings have been recommended in various rules and standards; however, the potential benefits and their impacts on distribution system operation are not well compared and studied. This paper presents a comparison of different smart inverter settings as applied to a distribution system. An actual feeder model from San Diego Gas & Electric Company is used to conduct the simulation. Additionally, a load disaggregation method is proposed to disaggregate the load and PV profile for each load location using advanced metering infrastructure net load measurements. Then, different smart inverter settings are applied to the PV systems in the feeder, and the simulation results are compared. The results show that the implementation of specific functions of smart inverters can reduce voltage exceedances, and the utility can determine the specific inverter setting based on its operational requirements.

distribution system↗
DOE OSTI2020

Optimal PV Inverter Control in Distribution Systems via Data-Driven Distributionally Robust Optimization

Distribution systems with high penetration of uncertain solar generation call for advanced control strategies of photovoltaics (PVs) inverters. This paper proposes a data-driven distributionally robust optimization (DDDRO) approach to optimally controlling the PV inverters to improve the system operation performance under solar power uncertainties. In the proposed DDDRO approach, a Wasserstein ball-based method is proposed to construct the distributional ambiguity set to model the uncertainties of PV generation through partial observations of historical data without knowing exact probability distributions. We further reformulate the computationally intractable DDDRO model to a mixed integer second order cone programming (MISOCP) problem. The effectiveness and out-of-sample performance of the proposed approach have been demonstrated on a modified IEEE 33-node system. We conduct a comparative study to compare the proposed method with traditional chance constrained programming (CCP). It shows that the proposed DDDRO approach can provide a less conservative yet robust solution to minimize the worse-case expectation of the total network loss while maintaining nodal voltages in a secure range.

Xue, Yaosuo↗
DOE OSTI2022

Multi-Agent Deep Reinforcement Learning for Realistic Distribution System Voltage Control Using PV Inverters

Over the last few decades, the deployment of distributed solar photovoltaic (PV) systems has increased consistently. High PV penetration could cause adverse effects on the grid, such as voltage violations. This paper proposes a new distributed soft actor-critic based multi-agent deep reinforcement learning (SAC-MADRL) control solution to minimize the PV real power curtailment while keeping the grid voltage in an acceptable range. New reward functions have been designed to coordinate different agents during the learning process, yielding improved convergence. Comparison results with other control methods on a real feeder in western Colorado U.S. with 80% penetration of PVs demonstrate that the proposed method has better capability of effectively regulating voltage while minimizing the PV real power curtailment.

distribution system↗
DOE OSTI2023

A Robust Method to Secure Multi-Inverter Grid Tied PV and Battery Energy Storage Systems Against Cyber Intrusions

This paper details a robust method to secure a multi-inverter grid tied system that interfaces photovoltaic (PV) and battery energy storage against potential cyber-attacks. The method can be applied to any third-party inverter systems without a need to modify their internal controls. A small random private excitation signal termed "watermark" is injected into the DC input voltage terminals (via a series transformer) connected to the PV/battery inverter system. An external robust cyber intrusion detector (CID) hardware consisting of a digital signal processor (DSP) generates the "watermark" and also receives the sensor signals that control the setpoints of the PV/battery grid tied system. The CID algorithm is shown to detect all possible cyber intrusions (such as false data injection(FDI)) on external sensor signals such as P and Q measured by a smart meter that control the overall system operation. The proposed CID computes online system ID and two variance tests in real time on each sensor signal and is able pinpoint intrusion location in a multi-inverter system. Results on a hardware in the loop (HIL) of a two-inverter grid connected system demonstrate effectiveness of the proposed CID system for FDI and unobservable FDI. Test results on a laboratory prototype will be discussed in the conference presentation.

Ibrahim, Hasan↗
DOE OSTI2020

Performance and Techno-Economic Evaluation of a Three-Phase, 50-kW SiC-Based PV Inverter

The technical capabilities and benefits of silicon carbide (SiC) compared to silicon (Si) based power electronics converters as well as the premium associated with using SiC instead of Si are well understood. This work proves that the benefits provided by SiC, such as increased efficiency, would result in a lower levelized cost of energy (LCOE) compared to both commercially available, state-of-the-art inverters and the benchmark commercial system cost calculated for the U.S. Department of Energy Solar Energy Technologies Office's SunShot program. The LCOE is calculated to be same as the commercial benchmark despite the installed system cost being 8% more than the benchmark. The LCOE calculation is based on both experiential values obtained from testing the SiC photovoltaic (PV) inverter and on the bottoms-up modeled volume cost for the same 50-kW SiC-based inverter. The PV system used for the LCOE model is also explained, and the system cost breakout is presented in this paper. Furthermore, multiple scenarios with variations in the PV system are presented to show their effect on the system LCOE.

14 SOLAR ENERGY↗