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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Inverters: A Pivotal Role in PV Generated Electricity

This presentation discusses the pivotal role inverters play in PV generated electricity. Topics include: the inverter as the center of the system--increasingly becoming the brain, with more features and capabilities (hybrid systems, safety, islanding, monitoring, etc.); increasing inverter-based generated electricity associated with many renewable energy sources; increased dependence for grid support and forming capability; communication within the grid and security increasingly required; increasing complexity leads to more chances to fail; as in most PV segments, there is cost reduction pressure, which makes it more challenging to keep the reliability high.

ENGINEERING,SOLAR ENERGY↗
DOE OSTI2023

PV Inverter Failures Cause AC Breaker Damage - Power Quality

This poster discusses how PV inverter failures cause AC breaker damage and is intended to help system owners identify power quality issues and origins, help inverter and/or circuit breaker manufacturers develop safer failure modes, and develop addendums to standards for failure testing of breakers and inverters.

arc↗
DOE OSTI2020

Hierarchical, Grid-Aware, and Economically Optimal Coordination of Distributed Energy Resources in Realistic Distribution Systems

Renewable portfolio standards are targeting high levels of variable solar photovoltaics (PV) in electric distribution systems, which makes reliability more challenging to maintain for distribution system operators (DSOs). Distributed energy resources (DERs), including smart, connected appliances and PV inverters, represent responsive grid resources that can provide flexibility to support the DSO in actively managing their networks to facilitate reliability under extreme levels of solar PV. This flexibility can also be used to optimize system operations with respect to economic signals from wholesale energy and ancillary service markets. Here, we present a novel hierarchical scheme that actively controls behind-the-meter DERs to reliably manage each unbalanced distribution feeder and exploits the available flexibility to ensure reliable operation and economically optimizes the entire distribution network. Each layer of the scheme employs advanced optimization methods at different timescales to ensure that the system operates within both grid and device limits. The hierarchy is validated in a large-scale realistic simulation based on data from the industry. Simulation results show that coordination of flexibility improves both system reliability and economics, and enables greater penetration of solar PV. Discussion is also provided on the practical viability of the required communications and controls to implement the presented scheme within a large DSO.

distribution network↗
DOE OSTI2021

Security Vulnerability and Mitigation in Photovoltaic Systems

Software and firmware vulnerabilities pose security threats to photovoltaic (PV) systems. When patches are not available or cannot be timely applied to fix vulnerabilities, it is important to mitigate vulnerabilities such that they cannot be exploited by attackers or their impacts will be limited when exploited. However, the vulnerability mitigation problem for PV systems has received little attention. This paper analyzes known security vulnerabilities in PV systems, proposes a multi-level mitigation framework and various mitigation strategies including neural network-based attack detection inside inverters, and develops a prototype system as a proof-of-concept for building vulnerability mitigation into PV system design.

14 SOLAR ENERGY↗
DOE OSTI2021

Photovoltaic (PV) System Levelized Cost of Energy (LCOE) Evaluation with Grid Support Function Valuation and Service Lifetime Estimation

Photovoltaic (PV) systems play a critical role in renewable energy resource grid integration, and levelized cost of energy (LCOE) is commonly used to evaluate PV system feasibility in modern power grids. In this work, a revised PV system LCOE calculation model is derived to quantify the potential of LCOE reduction. Particularly, the grid support functions are valuated to offset the investment and operation costs of PV systems, which thereby reduces the LCOE. Meanwhile, PV system service lifetime is also estimated with the derived PV inverter reliability model, considering the critical components (i.e., semiconductor devices and capacitors). The case studies with field datasets are conducted to validate the effectiveness of the developed LCOE calculation model.

Zhao, Shijia↗
DOE OSTI2023

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↗
DOE OSTI2020

Opportunistic Hybrid Communications Systems for Distributed PV Coordination

A full-scale, operational implementation of the opportunistic hybrid communications systems for distributed photovoltaic (PV) coordination was successfully developed, simulated, and validated in this 3-year project. The system is considered hybrid because it uses different communications pathways from the scale of residential PV inverters to a transmission network; primary technologies harnessed include Low-Power Wireless Personal Area Network (LoWPAN), Power Line Communication (PLC), WiFi mesh, Worldwide Interoperability for Microwave Access (WiMAX), Ethernet cable, and Optical Ethernet systems. It is opportunistic in that it chooses to route messages through each of these systems based on recent data about latency and availability to ensure reliable message passing.

14 SOLAR ENERGY↗
DOE OSTI2020

Estimation of solar photovoltaic energy curtailment due to volt–watt control

The widespread deployment of autonomous inverter‐based solutions for mitigating voltage and frequency excursions caused by high‐penetration photovoltaic (PV) systems has drawn increased attention due to their potential impact on PV production. It is now important to quantify the amount of solar energy curtailed as a result of the activation of inverter‐based grid support functions (GSFs). This study proposes a methodology for estimating the impact of volt–watt on customer PV energy curtailment using smart meter voltage data. This method estimates maximum possible curtailment for a given volt–watt curve based on the customer smart meter voltage during the time period of interest. This study compares the proposed methodology with field measurements using irradiance and customer inverter data from Hawaii as well as with results from a previous simulation‐driven study on the impact of advanced inverter GSF activation on PV energy curtailment. Results show that the proposed method for estimating lost PV production caused by volt–watt control aligns reasonably well with field measurements and computer simulations for hundreds of customers. The proposed method could be used to estimate customer energy curtailment, which could inform future compensation mechanisms for utilities leveraging customer‐sited resources to mitigate high voltage and defer infrastructure upgrades.

Emmanuel, Michael↗
DOE OSTI2024

Experimental Setup and Learning-Based AI Model for Developing Accurate PV Inverter Models

The integration of power electronics-based interfaces presents challenges due to the absence of detailed models and the high computational complexity. Generic models used in system studies lack accuracy in capturing converter dynamics. This paper proposes a data-driven approach developed from experimental setup data. This approach enhances accuracy in photovoltaic inverter modeling. We used two types of PV inverters in the experiment. The recorded experimental data undergo processing through a machine learning model. Results from the model trained through machine learning is also presented.

artificial intelligence↗
DOE OSTI2024

Seasonal Cost-Benefit Analysis of Automated Distribution Feeder Upgrades with Advanced Mitigation Technologies

The increasing deployment of distributed solar photovoltaics (DPV) to meet clean energy goals can trigger adverse grid operation issues, such as voltage excursions and the violation of thermal loading constraints of the power delivery elements (e.g., lines and transformers) on the evolving electricity infrastructure. Such integration issues would require distribution upgrades with associated costs to mitigate them and to maintain reliable and resilient grid operating conditions. Traditional distribution network upgrade approaches use a specific single snapshot analysis that is overly conservative. This study considers a multi-time point analysis to capture both moderate (probable bounds) and extreme grid operating conditions using time points such as minimum load with minimum photovoltaics (PV), maximum load with maximum PV, maximum load with minimum PV, and minimum load with maximum PV. Further, this study investigates seasonal variation impacts and associated distribution upgrade costs for a spring season case (March, representing a low load and high PV scenario) and a summer case (July, representing a high load and high PV scenario). Such seasonal analysis will allow system operators to characterize upgrade requirements and associated costs across various periods. Because the spatial distribution of DPV can impact upgrade and associated costs, this study investigates three common DPV deployment scenarios - randomly deployed, close to the substation, and far from the substation - at different penetration levels. Apart from spatial distribution impacts, this project evaluates the techno-economic impacts of the nodal photovoltaic penetration factor (NPPF) for generating the various DPV deployment scenarios at increasing penetration levels. This project investigates the impact of varying nodal PV-to-load ratios using conservative and extreme NPPF values of 3 and 10, respectively. This study investigates the deployment of traditional infrastructure upgrade strategies, such as installing new voltage regulating equipment, transformers and lines replacements, and the activation of advanced inverter functionality (e.g., autonomous volt/VAR) in expanding PV hosting capacity. Existing DPV systems are assumed to operate with the legacy unity power factor, and we considered the possibility of retrofitting such systems with the activation of volt/VAR control as integration standards and regulations continue to evolve to allow such functions. The cost-benefit analysis metrics used in study include distribution upgrade costs, average cost per watt of the upgrade cost, average marginal cost per watt of the upgrade cost, and power losses.

14 SOLAR ENERGY↗
DOE OSTI2021

Security assessment and impact analysis of cyberattacks in integrated T&D power systems

In this paper, we examine the impact of cyberattacks in an integrated transmission and distribution (T&D) power grid model with distributed energy resource (DER) integration. We adopt the OCTAVE Allegro methodology to identify critical system assets, enumerate potential threats, analyze and prioritize risks for threat scenarios. Based on the analysis, attack strategies and exploitation scenarios are identified which could lead to system compromise. Specifically, we investigate the impact of data integrity attacks in inverted-based solar PV controllers, control signal blocking attacks in protective switches and breakers, and coordinated monitoring and switching time-delay attacks. Index Terms—Cyberattacks, security assessment, impact analysis, case studies, integrated power systems.

14 SOLAR ENERGY↗
DOE OSTI2023

Modular HF Isolated MV String Inverters Enable a New Paradigm for Large PV Farms

The “Modular HF Isolated MV String Inverters Enable a New Paradigm for Large PV Farms” project focuses on exploring alternative power converter and system-level plant configurations to achieve the lowest cost and highest energy output for a given solar plus storage (e.g., PV + battery) plant, including the use of medium voltage (MV) collection while taking into account detailed models of all elements. To realize this objective, four approaches were utilized (i) employ a novel Medium Voltage String Inverter (MVSI) topology (soft switching solid state transformer – S4T) to convert 1000 Vdc to 4.16 kVac; (ii) plant collection using standard, low-cost overhead MV distribution network; (iii) enable energy storage integration without additional converter cost to achieve dispatchability of the PV resource; and (iv) provide advanced functionality (autonomous operation, track ISO signals for dynamic balancing and ancillary services, and PV farm operation as a virtual grid resource). Subsequently and in alignment with the previously mentioned approaches, the project was structured in five efforts (i) S4T MVSI simulation and design; (ii) system analysis and storage optimization; (iii) financial analysis; (iv) power converter prototype build and test; and (v) regulatory and commercial impact study. The outcomes provided by each effort can be summarized as follows (i) Project explored the use of MV AC distribution architecture for hybrid PV+storage utility-scale PV farms; (ii) Detailed loss and LCOE analysis for AC and DC side BESS architecture, including multiple converter topologies, as well as for proposed MVSI/MDCT systems; (iii) MVSI was built and holds promise but needs lower-cost high-voltage Si-C devices, which does not seem possible in the near term; (iv) MDCT provides a simpler modular building block – validated through HIL and farm level modeling, simulation and experimental validation; (v) 300 kVA MDCT prototype built and tested, technology is being commercialized; and (vi) Regulatory model of utility building PV plants, where PV panels are treated as DC generation (IPP), seems viable and can allow improved grid integration.

14 SOLAR ENERGY↗
DOE OSTI2024

Interoperable, Inverter-Based Distributed Energy Resources (DERs) Enable 100% Renewable and Resilient Utility Microgrids

Project overcomes frequency stability and system control issues when operating distribution microgrids in a low inertia, high PV penetration environment without fossil fuel generators. The team implemented a grid-forming inverter and advanced control features at SDG&E's Borrego Springs Microgrid to demonstrate islanding and blackstart using renewable resources. Simulation and emulation in advance of deployment de-risks field operations.

battery energy storage systems↗
DOE OSTI2024

Novel Approach to PV Inverter Modeling and Simulation Leveraging Experiments, Learning Based Modeling and Co-Simulation: Preprint

Photovoltaic inverter (PV) inverter manufacturers use custom, proprietary control approaches and topologies in their inverter design. Due to this proprietary nature, it is not possible to share EMT domain models for system studies. This research work presents a novel approach in experimental design, high fidelity data collection, use of learning-based modeling, and co-simulation to enhance the PV inverter modeling. We used a 20 kW off-the-shelf grid following PV inverter and subjected the inverter to controlled tests including voltage and frequency step changes, as well as solar irradiance variations. The recorded high frequency data was used in learning-based model training. This learning-based model was imported into an Electromagnetic Transient (EMT) simulation tool using co-simulation techniques to complete the modeling effort and integrate the model into an EMT simulation tool. The three key components in this research work are the design of experimental setup, use of learning-based approach for model development and use of co-simulation to complete the approach. The proposed approach will allow users to develop a model in a really short period of time and achieve reasonable inverter models.

artificial intelligence↗
DOE OSTI2025

Advancing Dynamic Modeling of Grid-Connected PV Inverter Using Bi-LSTM-Based AI Model

Power electronic converters (PECs) are widely used in modern power systems to facilitate the interconnection between various AC or DC sources and loads. Because of the extensive integration, the power system has grown into a more dynamic system in which the dynamics of the PECs must be adequately modeled. The paper presents a new bidirectional long short-term memory (Bi-LSTM) method for evaluating grid-connected inverter-based resources (IBR) dynamics. The method is tested using real hardware data from a grid -connected commercial inverter in laboratory experiments. Results show the Bi-LSTM model accurately reproduces the detailed IBR model's dynamics, even when the internal structure is unknown and parameters are unknown, preventing the disclosure of the manufacturer's confidential data.

Subedi, Sunil [ORNL] (ORCID:000000034069090X)↗
DOE OSTI2023

Model Predictive Control-Based Dual-Mode Operation of an Energy-Stored Quasi-Z-Source Photovoltaic Power System

The energy-stored quasi-Z-source inverter (ES-qZSI) has attracted much attention for photovoltaic (PV) power generations, due to its capability to stabilize the PV power fluctuations with simple structure and other advantages of Z-source inverter. The improved dual-mode (DM) ES-qZSI is able to support all-weather operation even at night or cloudy days when PV power is extremely low. However, the traditional proportional–integral (PI) based control suffers from complicated controller design and poor dynamic response during mode transition, due to two sets of PI control required for the daytime and night operation modes. In order to overcome that, here in this article, we propose a model predictive control strategy for the DM-ES-qZSI PV power system. The system predictive models in both day and night operating modes are derived. The control strategy is disclosed to ensure high performance of the system, through calling the predictive models and defined cost functions of the two modes within a single control loop. Simulation and experiment are carried out to verify the effectiveness of the proposed control strategy.

14 SOLAR ENERGY↗
DOE OSTI2022

Model Predictive Control of Dual-Mode Energy-Stored Quasi-Z-Source Photovoltaic System

The energy-stored quasi-Z-source inverter (ES-qZSI) has attracted much attention for photovoltaic (PV) power generations, due to its capability to stabilize the PV power fluctuations and other advantages of Z-source inverter. Traditional ES-qZSI suffers from poor operation at night or cloudy days when PV power is extremely low. In order to overcome that, this paper proposes a model predictive control (MPC) strategy for an improved dual-mode ES-qZSI, which is designed to support all-weather operation of PV power generation system. The system predictive models in both day and night operating modes are derived. And the control strategy based on MPC is disclosed to ensure the high-performance operation of the system. Simulation is carried out on PV power fluctuation in daytime and switching between the two modes, to verify the effectiveness of proposed control strategy.

Xue, Yaosuo↗