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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

Simulation of Photovoltaic Power Output for Solar Integration Studies in the Southeast US

We describe the method used to simulate one year of AC power at one-minute intervals for a large collection of hypothetical utility-scale photovoltaic plants of varying size, employing either fixed-tilt PV modules or single-axis tracking, and for distribution-connected photovoltaic (DPV) power systems assumed for a number of metropolitan areas. We also describe the simulation of an accompanying day-ahead forecast of hourly AC power for utility-scale plants and DPV systems such that forecast errors are consistent with errors reported for current forecasting methods. The results of these simulations are intended for use in a study that examines the possible effects of increased levels of photovoltaic (PV) generation bulk on power variability within the Tennessee Valley Authority (TVA) and Southern Company service territories.

14 SOLAR ENERGY↗
DOE OSTI2023

Statistical analysis and degradation pathway modeling of photovoltaic minimodules with varied packaging strategies

Degradation pathway models constructed using network structural equation modeling (netSEM) are used to study degradation modes and pathways active in photovoltaic (PV) system variants in exposure conditions of high humidity and temperature. This data-driven modeling technique enables the exploration of simultaneous pairwise and multiple regression relationships between variables in which several degradation modes are active in specific variants and exposure conditions. Durable and degrading variants are identified from the netSEM degradation mechanisms and pathways, along with potential ways to mitigate these pathways. A combination of domain knowledge and netSEM modeling shows that corrosion is the primary cause of the power loss in these glass/backsheet PV minimodules. We show successful implementation of netSEM to elucidate the relationships between variables in PV systems and predict a specific service lifetime. The results from pairwise relationships and multiple regression show consistency. This work presents a greater opportunity to be expanded to other materials systems.

electrical measurements↗
DOE OSTI2023

Quantifying Uncertainty in PV Energy Estimates Final Report

Uncertainty in PV energy estimates is "one of the most critical areas of lack of understanding" according to independent engineers, financiers, PV model developers, and other industry stakeholders. The primary problem is a lack of rigorous, transparent, widely accepted methods for quantifying uncertainty in energy production estimates. Uncertainty in energy production estimates arises from variability of the solar resource, inexact PV performance models and their parameters, and system reliability considerations. Uncertainty in annual energy production is frequently calculated for larger projects in order to quantify financial risk. Key statistics for energy, such as the P-values "P50" and "P90" (the annual energy values that are exceeded in future years with 50\% and 90\% probability, respectively) are used by financing institutions to calculate the repayment risk for the project. The current methods to estimate these statistics are typically proprietary, specialized, and involve significant post-processing of commercial performance model results. This black-box approach leads to inconsistent P-value estimates from different parties, which reduces investors' confidence in the results. Since the financial community bases its risk assessment on these estimates, reduced confidence increases perceived project risk, and consequently financing costs. The goal of this project was to establish a set of best practices for quantifying uncertainty in energy production estimates, including identifying what sources of uncertainty must be considered with clear definitions and metrics, determining which sources are the biggest drivers of uncertainty, and providing a computationally efficient framework for combining different sources of uncertainty that is flexible enough to accommodate substitutions of data or methods when better information is available. We engaged a wide set of stakeholders to ensure industry endorsement and adoption, and leveraged complementary projects investigating individual sources of uncertainty in great detail, as well as others' work that started down this path.

ENERGY PLANNING, POLICY, AND ECONOMY,SOLAR ENERGY↗
DOE OSTI2020

Managing Solar Photovoltaic Integration in the Western United States: Power System Flexibility Requirements and Supply

As penetrations of variable renewable energy generation technologies such as wind and solar photovoltaics (PV) continue to increase across the United States, greater uncertainty and variability in the net load often lead to a concern about how power systems may adapt. Managing the system net load (i.e., load minus contribution from variable generation technologies) may become more challenging with increasing variable generation, as the magnitude and frequency of net ramps increase. However, there is inherent flexibility in power systems through the conventional generator fleet (under least-cost unit commitment and economic dispatch), less-conventional generation sources (e.g., storage, demand response, concentrating solar power with thermal energy storage), and imports and exports with neighbors. In this analysis, we create an open-source tool to analyze the flexibility of the results of a specific commercial unit commitment and economic dispatch tool (PLEXOS), but the code can be applied generically as well. The tool assesses the flexibility requirements (or demand) of a system through a net load analysis. The constraints and limitations of each generator are then considered to determine the availability (or supply) of flexibility. Then, the supply and demand of flexibility are compared to gain a more complete picture of potential flexibility concerns. We apply this open-source tool to high-penetration PV scenarios constructed for three focus regions in the western United States defined using the Resource Planning Model (RPM) capacity expansion modeling tool: RPM-OR, RPM-CO, and RPM-AZ. Generally, we find few flexibility concerns, as the western United States represents a large and interconnected power system with significant inherent flexibility. In addition, the PV scenarios we analyzed are overbuilt on capacity, leaving plenty of ramping ability on the system. We do find that for each focus region, the impact of imports on meeting ramping needs is essential. This means the PV integration in each focus region impacts the entire rest of the system. Each system has different dominant sources of flexibility. The conventional generator fleet (especially coal and gas combined-cycle technologies) as well as less-conventional sources such as storage are all shown to be important sources of flexibility. The scenarios evaluated here were designed to study the planning and operations impact of high solar penetration in each of three focus regions. However, none of the three focus regions likely will deploy PV in isolation, meaning the ability of imports and exports to provide flexibility may be considerably different in scenarios with strong PV deployment in every region. Overall, we intend that the framework we present here will be useful in future analysis of other system evolutions to identify whether and how flexibility may constrain the successful deployment of variable generation technologies.

14 SOLAR ENERGY↗
DOE OSTI2021

Secondary Frequency Regulation from Variable Generation through Uncertainty Decomposition: An Economic and Reliability Perspective

The rapid integration of variable generation (VG), such as photovoltaics (PV), necessitates an increase in the secondary frequency regulation (SFR) to handle the system intra-dispatch interval imbalance because of VG's variation. Although PV has the control capability to provide SFR, the main challenge is in guaranteeing the delivery of PV's energy and SFRs capacities in the automatic generation control (AGC) within each dispatch interval considering its uncertainty. This paper proposes a deliverable VG SFR provision model with endogenous VG's power uncertainty decomposition. First, the uncertainty of VG is decomposed using distributionally robust chance constraints through which the deliverable SFR provision is guaranteed. Next, the intra-interval frequency response of PV's SFR is validated with a user defined AGC model including the PV power plant. Finally, the economic benefits and the reliability improvements such as the frequency deviation reduction with PV providing SFRcan be integrated and evaluated. The proposed model is tested in a modified 18-bus system and in the Western Electricity Coordinating Council test system. Results demonstrate that with the deliverable SFR from PV, the system cost and the frequency reliability can be improved simultaneously. PV's SFR performance can be guaranteed with the proposed model.

14 SOLAR ENERGY↗
DOE OSTI2024

Method for Spatiotemporal Solar Power Profile Estimation for a Proposed U.S.–Caribbean–South America Super Grid under Hurricanes

Solar photovoltaic (PV) generation technology stands out as a scalable and cost-effective solution to enable the transition toward decarbonization. However, PV solar output, beyond the daily solar irradiance variability and unavailability during nights, is very sensitive to weather events like hurricanes. Hurricanes nucleate massive amounts of clouds around their centers, shading hundreds of kilometers in their path, reducing PV power output. This research proposes a spatiotemporal method, implemented in MATLAB R2023b coding, to estimate the shading effect of hurricanes over a wide distribution of PV solar plants connected to a high-voltage power infrastructure called the U.S.–Caribbean–South America super grid. The complete interconnection of the U.S., the Caribbean, and South America results in the lowest power valley levels, i.e., an overall percentual reduction in PV power output caused by hurricane shading. The simulations assess the impact of hurricanes in 10 synthetic trajectories spanning from Texas to Florida. The Caribbean would also experience lower power valleys with expanded interconnectivity schemes. The U.S.–Caribbean–South America super grid reduces Caribbean variability from 37.8% to 8.9% in the case study. The proposed spatiotemporal method for PV power profile estimation is a valuable tool for future solar power generation expansion, transmission planning, and system design considering the impact of hurricanes.

14 SOLAR ENERGY↗
DOE OSTI2016

ENVI-PV: An Interactive Web Client for Multi-Criteria Life Cycle Assessment of Photovoltaic Systems Worldwide

Solar photovoltaics (PV) is the second largest source of new capacity among renewable energies. The worldwide capacity encompassed 135 GW in 2013 and is estimated to increase to 1721 GW in 2030 and 4674 GW in 2050, according to a prospective high-renewable scenario. To achieve this production level while minimizing environmental impacts, decision makers must have access to environmental performance data that reflect their high spatial variability accurately. We propose ENVI-PV (http://viewer.webservice-energy.org/project_iea), a new interactive tool that provides maps and screening level data, based on weighted average supply chains, for the environmental performance of common PV technologies. Environmental impacts of PV systems are evaluated according to a life cycle assessment approach. ENVI-PV was developed using a state-of-the-art interoperable and open standard Web Service framework from the Open Geospatial Consortium (OGC). It combines the latest life cycle inventories, published in 2015 by the International Energy Agency (IEA) under the Photovoltaic Power Systems Program (PVPS) Task 12, and some inventories previously published from Ecoinvent v2.2 database with solar irradiation estimates computed from the worldwide NASA SSE database. ENVI-PV is the first tool to propose a worldwide coverage of environmental performance of PV systems using a multi-criteria assessment. The user can compare the PV environmental performance to the environmental footprint of country electricity mixes. ENVI-PV is designed as an environmental interactive tool to generate PV technological options and evaluate their performance in different spatial and techno-economic contexts. Its potential applications are illustrated in this paper with several examples.

14 SOLAR ENERGY↗
DOE OSTI2023

AI-Based EMT Dynamic Model of PV Systems

Several electromagnetic transient (EMT) dynamic modeling methods are available to model systems like photovoltaic (PV) plants, wind power plants, variable-speed drives, among others. The methods include: (a) physics-based models and (b) data-driven models. The physics-based dynamic models may include high-fidelity switched system model and average-value model that both require the control algorithms included in the models. However, manufacturers typically prefer to provide black-box models to avoid disclosing proprietary. One of the solutions to prevent disclosing control algorithms is the use of data-driven dynamic EMT models of PV systems. In this paper, data-driven dynamic EMT model based on artificial intelligence (AI) algorithms are presented. The AI algorithms evaluated include convolutional neural networks, recurrent neural networks, and nonlinear auto-regressive exogenous model. Automation in generating data and training these models is also discussed in this paper. The results generated by the best AI algorithms have been observed to be greater than 95 % accurate.

Debnath, Suman↗
DOE OSTI2020

Voltage positioning using co-optimization of controllable grid assets in radial networks

With increasing penetration of solar PV, some distribution feeders are experiencing highly variable net-load flows and even reverse flows. To optimize distribution systems under such conditions, the scheduling of mechanical devices, such as OLTCs and capacitor banks, needs to take into account forecasted solar PV and actual grid conditions. However, these legacy switching assets are operated on a daily or hourly timescale, due to the wear and tear associated with mechanical switching, which makes them unsuitable for real-time control. Therefore, there is a natural timescale- separation between these slower mechanical assets and the responsive nature of inverter-based resources. In this paper, we present a network admissible convex formulation for holistically scheduling controllable grid assets to position voltage optimally against solar PV. An optimal hourly schedule is presented that utilizes mechanical resources to position the predicted voltages close to nominal values, while minimizing the use of inverter-based resources (i.e., DERs), making them available for control at a faster time-scale (after the uncertainty reveals itself). A convex, inner approximation of the OPF problem is adapted to a mixed-integer linear program that minimizes voltage deviations from nominal (i.e., maximizes voltage margins). Here, the resulting OPF solution respects all the network constraints and is, hence, robust against modeling simplifications. Simulation based analysis on IEEE distribution feeders validates the approach.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

On the Path to SunShot - Emerging Issues and Challenges with Integrating High Levels of Solar into the Distribution System

Wide use of advanced inverters could double the electricity-distribution system’s hosting capacity for distributed PV at low costs—from about 170 GW to 350 GW (see Palmintier et al. 2016). At the distribution system level, increased variable generation due to high penetrations of distributed PV (typically rooftop and smaller ground-mounted systems) could challenge the management of distribution voltage, potentially increase wear and tear on electromechanical utility equipment, and complicate the configuration of circuit-breakers and other protection systems—all of which could increase costs, limit further PV deployment, or both. However, improved analysis of distribution system hosting capacity—the amount of distributed PV that can be interconnected without changing the existing infrastructure or prematurely wearing out equipment—has overturned previous rule-of-thumb assumptions such as the idea that distributed PV penetrations higher than 15% require detailed impact studies. For example, new analysis suggests that the hosting capacity for distributed PV could rise from approximately 170 GW using traditional inverters to about 350 GW with the use of advanced inverters for voltage management, and it could be even higher using accessible and low-cost strategies such as careful siting of PV systems within a distribution feeder and additional minor changes in distribution operations. Also critical to facilitating distributed PV deployment is the improvement of interconnection processes, associated standards and codes, and compensation mechanisms so they embrace PV’s contributions to system-wide operations. Ultimately SunShot-level PV deployment will require unprecedented coordination of the historically separate distribution and transmission systems along with incorporation of energy storage and “virtual storage,” which exploits improved management of electric vehicle charging, building energy systems, and other large loads. Additional analysis and innovation are neede

14 SOLAR ENERGY↗
DOE OSTI2016

Utility-Scale Lithium-Ion Storage Cost Projections for Use in Capacity Expansion Models

This work presents U.S. utility-scale battery storage cost projections for use in capacity expansion models. We create battery cost projections based on a survey of literature cost projections of battery packs and balance of system costs, with a focus on lithium-ion batteries. Low, mid, and high cost trajectories are created for the overnight capital costs and the operating and maintenance costs. We then demonstrate the impact of these cost projections in the Regional Energy Deployment System (ReEDS) capacity expansion model. We find that under reference scenario conditions, lower battery costs can lead to increased penetration of variable renewable energy, with solar photovoltaics (PV) seeing the largest increase. We also find that additional storage can reduce renewable energy curtailment, although that comes at the expense of additional storage losses.

25 ENERGY STORAGE↗
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 OSTI2024

Bias Correction and Statistical Downscaling of Solar Radiation Using NA-CORDEX and the NSRDB

The current state-of-art for estimating long-term PV production uses long-term estimates of solar radiation variables, such as global horizontal irradiance (GHI), from previous years. This data is used in models such as the System Advisor Model (SAM) or PYSyst to predict annual production for a PV plant. This information is then used to estimate the production over the next 20 years (a typical plant lifetime) under the assumption that the variability over the current period is representative of the future. As the PV industry moves to extend plant lifetimes to 50 years the current assumptions of representativeness of weather may not be appropriate. This is especially true as our climate changes rapidly. To assess long-term PV production, future projections for solar radiation based on projected carbon emissions are readily available in regional and global climate models. However, climate model projections contain inherent biases that may need to be corrected for accurate analysis of future projections of climate variables. Several studies have analyzed projections of solar radiation for future years, however the accuracy of the model output compared to current and historic data has not been widely studied. Chen (2021) showed that available climate models do not accurately represent solar radiation in some cases, over-projecting GHI at the surface while under-projecting its obstructions, such as clouds and aerosols. This works aims to (1) increase understanding of the accuracy of solar radiation currently available in global and regional climate models and (2) implement bias correction through linear models based on reanalysis data compared to observed solar radiation. The latter aim will be conducted using available observed solar radiation data and modeled data from several regional climate models (RCMs). The bias correction method will be applied to projections of solar radiation resulting in a more accurate representation of the future of solar production.

climate data↗
DOE OSTI2017

Demonstration of Essential Reliability Services by a 300-MW Solar Photovoltaic Power Plant

The California Independent System Operator (CAISO), First Solar, and the National Renewable Energy Laboratory (NREL) conducted a demonstration project on a large utility-scale photovoltaic (PV) power plant in California to test its ability to provide essential ancillary services to the electric grid. With increasing shares of solar- and wind-generated energy on the electric grid, traditional generation resources equipped with automatic governor control (AGC) and automatic voltage regulation controls -- specifically, fossil thermal -- are being displaced. The deployment of utility-scale, grid-friendly PV power plants that incorporate advanced capabilities to support grid stability and reliability is essential for the large-scale integration of PV generation into the electric power grid, among other technical requirements. A typical PV power plant consists of multiple power electronic inverters and can contribute to grid stability and reliability through sophisticated 'grid-friendly' controls. In this way, PV power plants can be used to mitigate the impact of variability on the grid, a role typically reserved for conventional generators. In August 2016, testing was completed on First Solar's 300-MW PV power plant, and a large amount of test data was produced and analyzed that demonstrates the ability of PV power plants to use grid-friendly controls to provide essential reliability services. These data showed how the development of advanced power controls can enable PV to become a provider of a wide range of grid services, including spinning reserves, load following, voltage support, ramping, frequency response, variability smoothing, and frequency regulation to power quality. Specifically, the tests conducted included various forms of active power control such as AGC and frequency regulation; droop response; and reactive power, voltage, and power factor controls. This project demonstrated that advanced power electronics and solar generation can be controlled to contribute to system-wide reliability. It was shown that the First Solar plant can provide essential reliability services related to different forms of active and reactive power controls, including plant participation in AGC, primary frequency control, ramp rate control, and voltage regulation. For AGC participation in particular, by comparing the PV plant testing results to the typical performance of individual conventional technologies, we showed that regulation accuracy by the PV plant is 24-30 points better than fast gas turbine technologies. The plant's ability to provide volt-ampere reactive control during periods of extremely low power generation was demonstrated as well. The project team developed a pioneering demonstration concept and test plan to show how various types of active and reactive power controls can leverage PV generation's value from being a simple variable energy resource to a resource that provides a wide range of ancillary services. With this project's approach to a holistic demonstration on an actual, large, utility-scale, operational PV power plant and dissemination of the obtained results, the team sought to close some gaps in perspectives that exist among various stakeholders in California and nationwide by providing real test data.

14 SOLAR ENERGY↗
DOE OSTI2025

Assessing Climate Change-Induced Variability in Generation Potential and Droughts of Renewable Energy Systems in India

Solar photovoltaic (PV) and wind energy systems are crucial for decarbonizing the electricity sector and achieving climate goals. However, these systems are weather-dependent, and ignoring the potential changes in their generation levels due to climate change could compromise achieving climate targets and meeting future electricity demand. This study evaluates the impact of climate change on the generation potential of wind and solar PV systems in India for three future periods, 2030 (2021-2040), 2050 (2041-2060), and 2070 (2061-2080) compared to the baseline year 2000 (1991-2010), under three emission scenarios: SSP245, SSP370, and SSP585. Solar PV generation levels consistently decline (up to 10 %) across all regions and scenarios. Wind energy shows more pronounced variability (-20 % to 30 %). The South and Southeastern regions of India show improvements in wind potential across all scenarios and time periods. This study also investigated the projected changes in the generation droughts of both energy systems. For solar PV, drought days increase across most regions (exceeding 500 days under SSP370 across the 20-year period). In contrast, wind energy sees a reduction in drought days, especially in parts of South and Southeast India (declines exceeding 50 days across different scenarios). For both energy systems, the patterns of generation drought and generation potential are similar, and indicate that Western and Northern India may be less favorable for the future expansion of solar PV and wind energy, respectively. These results highlight the need to account for the potential impacts in future capacity planning.

14 SOLAR ENERGY↗
DOE OSTI2016

Sensor network based solar forecasting using a local vector autoregressive ridge framework

The significant improvements and falling costs of photovoltaic (PV) technology make solar energy a promising resource, yet the cloud induced variability of surface solar irradiance inhibits its effective use in grid-tied PV generation. Short-term irradiance forecasting, especially on the minute scale, is critically important for grid system stability and auxiliary power source management. Compared to the trending sky imaging devices, irradiance sensors are inexpensive and easy to deploy but related forecasting methods have not been well researched. The prominent challenge of applying classic time series models on a network of irradiance sensors is to address their varying spatio-temporal correlations due to local changes in cloud conditions. We propose a local vector autoregressive framework with ridge regularization to forecast irradiance without explicitly determining the wind field or cloud movement. By using local training data, our learned forecast model is adaptive to local cloud conditions and by using regularization, we overcome the risk of overfitting from the limited training data. Our systematic experimental results showed an average of 19.7% RMSE and 20.2% MAE improvement over the benchmark Persistent Model for 1-5 minute forecasts on a comprehensive 25-day dataset.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

A reduced-form approach for representing the impacts of wind and solar PV deployment on the structure and operation of the electricity system

In many climate change mitigation scenarios, integrated assessment models of the energy and climate systems rely heavily on renewable energy technologies with variable and uncertain generation, such as wind and solar PV, to achieve substantial decarbonization of the electricity sector. However, these models often include very little temporal resolution and thus have difficulty in representing the integration costs that arise from mismatches between electricity supply and demand. The global integrated assessment model, MESSAGE, has been updated to explicitly model the trade-offs between variable renewable energy (VRE) deployment and its impacts on the electricity system, including the implications for electricity curtailment, backup capacity, and system flexibility. These impacts have been parameterized using a reduced-form approach, which allows VRE integration impacts to be quantified on a regional basis. In addition, thermoelectric technologies were updated to include two modes of operation, baseload and flexible, to better account for the cost, efficiency, and availability penalties associated with flexible operation. In this paper, the modeling approach used in MESSAGE is explained and the implications for VRE deployment in mitigation scenarios are assessed. Three important stylized facts associated with integrating high VRE shares are successfully reproduced by our modeling approach: (1) the significant reduction in the utilization of non-VRE power plants; (2) the diminishing role for traditional baseload generators, such as nuclear and coal, and the transition to more flexible technologies; and (3) the importance of electricity storage and hydrogen electrolysis in facilitating the deployment of VRE.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗