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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 OSTI2014

Improved Modeling Tools Development for High Penetration Solar

One of the significant objectives of the High Penetration solar research is to help the DOE understand, anticipate, and minimize grid operation impacts as more solar resources are added to the electric power system. For Task 2.2, an effective, reliable approach to predicting solar energy availability for energy generation forecasts using the University of California, San Diego (UCSD) Sky Imager technology has been demonstrated. Granular cloud and ramp forecasts for the next 5 to 20 minutes over an area of 10 square miles were developed. Sky images taken every 30 seconds are processed to determine cloud locations and cloud motion vectors yielding future cloud shadow locations respective to distributed generation or utility solar power plants in the area. The performance of the method depends on cloud characteristics. On days with more advective cloud conditions, the developed method outperforms persistence forecasts by up to 30% (based on mean absolute error). On days with dynamic conditions, the method performs worse than persistence. Sky Imagers hold promise for ramp forecasting and ramp mitigation in conjunction with inverter controls and energy storage. The pre-commercial Sky Imager solar forecasting algorithm was documented with licensing information and was a Sunshot website highlight.

14 SOLAR ENERGY↗
DOE OSTI2015

High Penetration Solar PV Deployment Sunshine State Solar Grid Initiative (SUNGRIN)

The report provides results from the Sunshine State Solar Grid Initiative (SUNGRIN) high penetration solar PV deployment project led by Florida State University’s (FSU) Center for Advanced Power Systems (CAPS). FSU CAPS and industry and university partners have completed a five-year effort aimed at enabling effective integration of high penetration levels of grid-connected solar PV generation. SUNGRIN has made significant contributions in the development of simulation-assisted techniques, tools, insight and understanding associated with solar PV effects on electric power system (EPS) operation and the evaluation of mitigation options for maintaining reliable operation. An important element of the project was the partnership and participation of six major Florida utilities and the Florida Reliability Coordinating Council (FRCC). Utilities provided details and data associated with actual distribution circuits having high-penetration PV to use as case studies. The project also conducted foundational work supporting future investigations of effects at the transmission / bulk power system level. In the final phase of the project, four open-use models with built-in case studies were developed and released, along with synthetic solar PV data sets, and tools and techniques for model reduction and in-depth parametric studies of solar PV impact on distribution circuits. Along with models and data, at least 70 supporting MATLAB functions have been developed and made available, with complete documentation.

14 SOLAR ENERGY↗
DOE OSTI2012

Sub-Hourly Impacts of High Solar Penetrations in the Western United States: Preprint

This paper presents results of analysis on the sub-hourly impacts of high solar penetrations from the Western Wind and Solar Integration Study Phase 2. Extreme event analysis showed that most large ramps were due to sunrise and sunset events, which have a significant predictability component. Variability in general was much higher in the high-solar versus high-wind scenario. Reserve methodologiesthat had already been developed for wind were therefore modified to take into account the predictability component of solar variability.

14 SOLAR ENERGY↗
DOE OSTI2017

Voltage-Load Sensitivity Matrix Based Demand Response for Voltage Control in High Solar Penetration Distribution Feeders

This paper presents a voltage-load sensitivity matrix (VLSM) based voltage control method to deploy demand response resources for controlling voltage in high solar penetration distribution feeders. The IEEE 123-bus system in OpenDSS is used for testing the performance of the preliminary VLSM-based voltage control approach. A load disaggregation process is applied to disaggregate the total load profile at the feeder head to each load nodes along the feeder so that loads are modeled at residential house level. Measured solar generation profiles are used in the simulation to model the impact of solar power on distribution feeder voltage profiles. Different case studies involving various PV penetration levels and installation locations have been performed. Simulation results show that the VLSM algorithm performance meets the voltage control requirements and is an effective voltage control strategy.

distribution system modeling↗
DOE OSTI2026

VRN3P: Variational Recurrent Neural Network Based Net-Load Prediction under High Solar Penetration

This is the final technical report for the SETO-funded VRN3P project (PNNL# 76914). The goal of this project, led by Pacific Northwest National Laboratory (PNNL), in collaboration with Lawrence Livermore National Laboratory (LLNL) and Portland General Electric (PGE), was to develop and validate a deep variational recurrent neural network-based net-load prediction (VRN3P) framework for probabilistic time-series forecasting of day-ahead net-load under high solar penetration scenarios. The project team reports successful design of a novel probabilistic net-load forecasting architecture, comprising of a variational autoencoder and a recurrent neural network, which demonstrates 30% improvement in forecast performance, 60% improvement in training time, and consumes 44% less memory, when compared with conventional baseline models. The team tested the VRN3P model performance on GridLAB-D test-cases representing varying BTM solar penetration levels of 20%, 30%, and 50%, with integrated time-series net-load profiles provided by the utility partner (PGE). The VRN3P model demonstrate <2% hourly MAPE (averaged over the year) for day- ahead net-load forecast on the test scenario with 20% BTM solar. Transfer learning extension of the VRN3P model has demonstrated 8.33× speed-up in training, while still achieving acceptable forecast performance of 2.24% hourly MAPE on the 30% BTM solar penetration test-scenario. A preliminary version of the VRN3P GridAPPS-D™has been developed, along with a web-based interactive user-interface (named ‘Forte’) which has made available on GitHub for public use.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Resilient Operation of Networked Community Microgrids with High Solar Penetration

This project, funded by the US Department of Energy’s Solar Energy Technologies Office (SETO), focused on the operation of microgrids as a coordinated network. The primary objective, which was successfully achieved, was to develop both control strategies and hardware solutions to support the resilient and efficient operation of networked microgrids with high solar penetration. The work was structured around the following four main tasks: • Development of distributed and scalable optimization algorithms for AC-coupled networked microgrids. • Design and implementation of a novel DC interconnection hardware to enable precise power exchange between microgrids. • Laboratory operational validation of the developed technologies using 480 V testbeds and commercially available hardware. • Field operational validation of the complete solution in Adjuntas, Puerto Rico, interconnecting two kW-scale, split-phase microgrids of Casa Pueblo’s microgrids. This project addressed multiple technical challenges across the domains of optimization, control, hardware interconnection, and protection. One of its key contributions was delivering tangible, real-world solutions for networking microgrids. In contrast to purely theoretical or simulation-based work, this project included full-scale hardware operational validation both in the lab and in the field. The work conducted as part of this project—in collaboration with the University of Puerto Rico; the University of Tennessee, Knoxville; the University of Central Florida; and Casa Pueblo—has advanced the state of the art in networked microgrids. Key contributions include the development of distributed control strategies, practical solutions for real-world implementation challenges, and the introduction of a novel DC interlink approach for microgrid interconnection. The project featured both laboratory and field validation using commercial off-the-shelf components. The field deployment successfully validated that a group of microgrids can operate in a coordinated manner, enabling precise power flow between systems and mutual support during extreme events. This project resulted in 15 journal publications and 15 conference papers; 5 graduate students and 15 undergraduate students were supported. The codes of distributed optimization and forecasting were made open-source through OSTI.gov for distributed optimization and forecasting. All the publications are available in the ORNL-hosted project landing page. The DC interlink with state-of-charge balancing control was operationally validated in Adjuntas by interconnecting two real-world, 240 V split-phase microgrids. To the best knowledge of the team, this represents the first operational validation of AC microgrids interconnected via DC-interlinks. As a culmination of this project, a follow-on grant was awarded to support the technology transfer of the distributed optimization framework to a commercial microgrid controller, Stellar Edge, developed by the California-based company New Sun Road.

14 SOLAR ENERGY↗
DOE OSTI2024

Convolution Neural Network for Fault Identification in Distribution Feeder with High Penetration Solar PV

Identification and zonal classification of the faults is a decisive factor in the relay’s decision to trip or not. Different types of fault like three-phase, line-to-line-to-ground and single-line-to-ground can occur at various locations in the feeder. These faults are seen as the variation in the instantaneous values of three-phase voltages and currents, i.e., waveforms, that are measured at the relay location. The objective of this work is to develop a machine learning model that can identify a fault and classify it to various protection zones based on measured waveforms. In this work, a data-driven relay based on Convolutional Neural Network (CNN) is proposed for fault identification in distribution feeders with high penetration solar PV. The proposed CNN model takes local current and voltage waveforms as input and classify it into fault, no-fault or a capacitor switching. Further, the CNN also attempts to identify fault zones based on the images of waveforms. The overall testing accuracy of the trained model exceeds 95%.

Ramesh, Meghana↗
DOE OSTI2026

High Penetration Solar and Battery Project in Noatak, Alaska

Through funding from the Department of Energy’s Office of Indian Energy, the Northwest Arctic Borough (NAB) and the Native Village of Noatak (NNV) formed a Tribal Energy Development Organization (TEDO) to implement the Noatak Solar and Battery Project to reduce reliance on costly imported diesel, stabilize energy costs, and strengthen local energy sovereignty.

14 SOLAR ENERGY↗
DOE OSTI2016

Final Technical Report: Integrated Distribution-Transmission Analysis for Very High Penetration Solar PV

Transmission and distribution simulations have historically been conducted separately, echoing their division in grid operations and planning while avoiding inherent computational challenges. Today, however, rapid growth in distributed energy resources (DERs)--including distributed generation from solar photovoltaics (DGPV)--requires understanding the unprecedented interactions between distribution and transmission. To capture these interactions, especially for high-penetration DGPV scenarios, this research project developed a first-of-its-kind, high performance computer (HPC) based, integrated transmission-distribution tool, the Integrated Grid Modeling System (IGMS). The tool was then used in initial explorations of system-wide operational interactions of high-penetration DGPV.

14 SOLAR ENERGY↗
DOE OSTI2019

A Tool-Suite to Improve Reliability and Performance of Combined Transmission-Distribution Under High Solar Penetration

The main motivating factor behind the work is to study the interaction between the transmission and the distribution system in more detail than currently possible. This is particularly important at high PV penetration levels. The developed toolkit allows capturing the coupling between the transmission and the distribution system (T&D) for steady-state and dynamic analysis, thereby furthering our understanding of how the T&D systems interact. One of the objectives of the work is to answer the question, “which analysis require T&D simulation”. To this end, the team held discussions with the utility advisory group (UAG) and identified use cases that are of most interest and studied them in detail. Based on the use cases the team was able to suggest whether the T&D analysis is a necessity for a particular study. The developed techniques, which are documented in detail through publications, are important additions to the literature in power system co-simulation. The publications and the open sourced tools (PFLOW and IGMS) that resulted from this project are highly valuable resources to the researchers in this area.

14 SOLAR ENERGY↗
DOE OSTI2019

Distribution System State Estimation in the Presence of High Solar Penetration

In recent years, the low-to-medium voltage distribution networks are experiencing rising levels of distributed energy resources, including renewable generation, along with improved sensing, communication and automation infrastructure. As such, state estimation methods for distribution systems are becoming increasingly relevant as a means to enable better control strategies that can both leverage the benefits and mitigate the risks associated with high penetration of variable and uncertain distributed generation resources. Primary challenges of this problem include modeling complexities (nonlinear non-convex power-flow equations), limited availability of sensor measurements, and high penetration of uncertain renewable generation. This paper formulates the distribution system state estimation as a nonlinear weighted least squares problem, based on sensor measurements as well as forecasts data (both load and generation). We investigate the sensitivity of state estimator accuracy to (load/generation) forecast uncertainties, sensor accuracy, and sensor coverage levels.

Distribution system state estimation, nonlinear op↗
DOE OSTI2023

Modeling of a Networked Community Microgrid with High Solar Penetration Considering Control Dynamics of Inverter-Based Resources

Microgrids help facilitate the integration of renewable energy in distribution-level grids and increase the resilience of the electric grid to extreme weather, especially in rural areas. Compared to traditional microgrids, a networked microgrid leverages multiple grid-forming sources to form a potential meshed grid and is more flexible in operation. This paper demonstrates the simulation modeling of an actual networked microgrid located in Adjuntas, Puerto Rico. The model contains representations of power inverters that connect the battery energy storage systems and photovoltaic generation systems to the networked microgrid and is capable of simulating fast grid transients as well as long-term operation of the networked microgrid. The modeling technique for power inverters allows the time-efficient simulation of the microgrid with a minimal penalty on model accuracy.

Li, Dingrui↗
DOE OSTI2018

Operational impacts of high penetration solar power on a real-world distribution feeder

Higher penetration of solar photovoltaic (PV), with their uncontrollable generation variability, imposes various grid stability challenges on distribution system operation. The primary problem is significant voltage rise in the distribution feeder that forces existing voltage control devices such as on-load tap-changers and line voltage regulators to operate more frequently. The consequence is the deterioration of the operating life of the voltage control mechanism. The objective of this paper is to investigate the voltage impact of increased penetration of PV systems on distribution load tap changer operations. Both steady-state and quasi-static power flow analyses have been conducted to assess the impact on load tap changes under different solar PV penetration levels. Two real-world distribution feeder circuits are used as a test system in this study. Simulations are carried out for up to one-year period with 1-minute time step using OpenDSS. A comparison study was performed to investigate potential voltage rise issues in the network by increasing total PV penetration from 0 to 100% in the feeder. Results show significant increase in the total number of tap operations as solar PV penetration increases. Impacts on nodal voltages and feeder net power are also presented.

Dong, Jin↗
DOE OSTI2015

Grid Inertial Response-Based Probabilistic Determination of Energy Storage System Capacity Under High Solar Penetration

It is well-known that responsive battery energy storage systems (BESSs) are an effective means to improve the grid inertial response to various disturbances including the variability of the renewable generation. One of the major issues associated with its implementation is the difficulty in determining the required BESS capacity mainly due to the large amount of inherent uncertainties that cannot be accounted for deterministically. In this study, a probabilistic approach is proposed to properly size the BESS from the perspective of the system inertial response, as an application of probabilistic risk assessment (PRA). The proposed approach enables a risk-informed decision-making process regarding (1) the acceptable level of solar penetration in a given system and (2) the desired BESS capacity (and minimum cost) to achieve an acceptable grid inertial response with a certain confidence level.

25 ENERGY STORAGE↗
DOE OSTI2016

On the Path to SunShot. The Environmental and Public Health Benefits of Achieving High Solar Penetrations in the United States

Compared with fossil fuel generators, photovoltaics (PV) and concentrating solar power (CSP) produce far lower lifecycle levels of greenhouse gas (GHG) emissions and harmful pollutants including fine particular matter (PM2.5), sulfur dioxide (SO 2 ), and nitrogen oxides (NO x ). In this report, we monetize the emission reductions from achieving the U.S. Department of Energy's SunShot deployment goals: 14% of U.S. electricity demand met by solar in 2030 and 27% in 2050. We estimate that achieving these goals could reduce cumulative power-sector GHG emissions by 10% between 2015 and 2050, resulting in savings of $238-$252 billion. This is equivalent to 2.0-2.2 cents per kilowatt-hour of solar installed (cents/kWh-solar). Similarly, realizing these levels of solar deployment could reduce cumulative power-sector emissions of PM2.5 by 8%, SO 2 by 9%, and NOx by 11% between 2015 and 2050. This could produce $167 billion in savings from lower future health and environmental damages, or 1.4 cents/kWh-solar--while also preventing 25,000-59,000 premature deaths. To put this in perspective, this estimated combined benefit of 3.5 cents/kWh-solar due to SunShot-level solar deployment is approximately equal to the additional levelized cost of electricity reduction needed to make unsubsidized utility-scale solar competitive with conventional generators today. In addition, the analysis shows that achieving the SunShot goals could save 4% of total power-sector water withdrawals and 9% of total power-sector water consumption over the 2015-2050 period--a particularly important consideration for arid states where substantial solar will be deployed. These results have potential implications for policy innovation and the economic competitiveness of solar and other generation technologies.

14 SOLAR ENERGY↗
DOE OSTI2021

Scalable/Secure Cooperative Algorithms and Framework for Extremely-high Penetration Solar Integration (SolarExPert) (Final Technical Report)

This SolarExPert project has developed a Sustainable Grid Platform (SGP) with scalable architecture of distributed control and optimization. The SGP consists of the following major functions: 1) an advanced grid architecture with hierarchical and distributed communication and control, combined with the OpenFMB standard and implemented on the Multi-Agent OpenDSS (MA-OpenDSS) platform; 2) an online distributed stochastic optimal power flow; 3) an online distributed system state estimation algorithm; 4) the distributed Volt/VAR optimization and frequency control algorithms; 5) the distributed distribution system restoration strategy. The developed SGP together with advanced functions are tested in 1 million (1M)-node distribution system on the MA-OpenDSS platform. Furthermore, the models and algorithms are tested in 100,000-node system HiL simulation, and also in P-HiL implementation with 100 physical devices. The developed functions haven been validated and tested on the selected actual distribution feeder with the data collected from the field of Maui Meadows in Hawaii. The distributed PV hosting capacities with cooperative Volt/VAR and Volt/VAR/Watt control are estimated and compared to provide recommendations for customers and the utility company.

14 SOLAR ENERGY↗
DOE OSTI2017

A Three-Stage Enhanced Reactive Power and Voltage Optimization Method for High Penetration of Solar

This paper presents a three-stage enhanced volt/var optimization method to stabilize voltage fluctuations in transmission networks by optimizing the usage of reactive power control devices. In contrast with existing volt/var optimization algorithms, the proposed method optimizes the voltage profiles of the system, while keeping the voltage and real power output of the generators as close to the original scheduling values as possible. This allows the method to accommodate realistic power system operation and market scenarios, in which the original generation dispatch schedule will not be affected. The proposed method was tested and validated on a modified IEEE 118-bus system with photovoltaic data.

photovoltaic, Volt/Var Control, indexes, simulatio↗
DOE OSTI2016

The environmental and public health benefits of achieving high penetrations of solar energy in the United States

Here, we estimate the environmental and public health benefits that may be realized if solar energy cost reductions continue until solar power is competitive across the U.S. without subsidies. Specifically, we model, from 2015 to 2050, solar power–induced reductions to greenhouse gas (GHG) emissions, air pollutant emissions, and water usage. To find the incremental benefits of new solar deployment, we compare the difference between two scenarios, one where solar costs have fallen such that solar supplies 14% of the nation's electricity by 2030 and 27% by 2050, and a baseline scenario in which no solar is added after 2014. We monetize benefits, where credible methods exist to do so. We find that under these scenarios, solar power reduces GHG and air pollutants by ~10%, from 2015 to 2050, providing a discounted present value of 56–789 billion USD (central value of ~250 billion USD, equivalent to ~2 ¢/kWh-solar) in climate benefits and 77–298 billion USD (central value of 167 billion USD, or ~1.4 ¢/kWh-solar) in air quality and public health benefits. The ranges reflect uncertainty within the literature about the marginal impact of emissions of GHG and air pollutants. Solar power is also found to reduce water withdrawals and consumption by 4% and 9%, respectively, including in many drought-prone states.

14 SOLAR ENERGY↗