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This is a presentation delivered at the 2024 FECM/NETL Spring Project Review Meeting as part of the Reversible Solid Oxide Fuel Cell track. The presentation highlights recent progress made in the system analysis efforts as part of the NETL SOFC Field Work Proposal in 2023-2024.
The Power and Energy Storage Systems Toolbox (PSTess) is a MATLAB-based computing package for dynamic simulation and analysis of utility-scale battery storage systems. This codebase is a fork of the Power Systems Toolbox Version 3.0, developed at Rensselaer Polytechnic Institute (RPI) and Cherry Tree Scientific Software. While PSTess shares a common lineage with PST, it is a substantially different application. As the name implies, the main distinguishing characteristic of PSTess is its ability to model inverter-based energy storage systems (ESS). The model that enables this is called ess.m, and it serves the dual role of representing ESS operational constraints and the generator/converter interface. With PSTess, the generator/converter interface is modeled as a controllable current source with the ability to modulate both active and reactive current. The model ess.m permits four-quadrant modulation, which allows it to represent a wide variety of inverter-based resources beyond energy storage when paired with an appropriate supplemental control model. Examples include utility-scale photovoltaic (PV) power plants, type 4 wind plants, and static synchronous compensators (STATCOM). This capability is especially useful for modeling hybrid plants that combine energy storage with renewable resources. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND2021-8322 O
The National Energy Technology Laboratory (NETL) regularly updates legacy analysis with new studies and cases as the Department of Energy objectives change, technology performance improves, costs are reduced, regulations change, market drivers are established, fuel prices fluctuate, and any number of other relevant factors vary in the market. As legacy studies are updated by NETL, the underlying performance and cost of the cases presented changes, and as such, the methods for interpreting and scaling the cost estimates change. Therefore, it is important that NETL maintain public guidance documents associated with different sets of cost estimates that delineate how a specific set, based on report vintage and/or year published, should be scaled. This Quality Guidelines for Energy System Studies report, providing guidance on capital cost scaling, should generally be applied to NETL case costs included in the report “Cost and Performance Baseline for Fossil Energy Plants Volume 1: Bituminous Coal and Natural Gas to Electricity Revision 4b,” (NETL, 2025) or any cases derived from the cases presented in the referenced report.
The Public Service Company of Colorado (PSCo), a subsidiary of Xcel Energy (Xcel), plans to meet its target of an 80% reduction in CO 2 emissions over 2005 levels by 2030 through its Preferred Plan1,2 that includes increasing the wind and solar energy on its system, reducing coal, and adjusting the operation and dispatch of new and existing thermal generation. The objective of our analysis reported here is to identify how the PSCo generation and transmission of its Preferred Plan might operate in the face of specific weather events. We investigate weather events that currently cause stress to PSCo’s system, such as winter storms and extreme heat. In addition, we explore how the future system responds to scenarios that may be considered normal weather conditions today, but that have a large impact on wind and solar generation potential.
Novel uncertainty quantification approach for machine learning based physics informed graph neural networks capable of quickly computing bulk energy system contingencies from a large search space with tolerance to changing grid topologies.
An accommodations analysis performed by the MSFC Preliminary Design Office for a spaceborne Doppler lidar wind measuring system is summarized. A dedicated, free-flying spacecraft design concept is described. Mass and beginning-of-life power requirements are estimated at 2260 kg and 6.0 - 8.5 kW respectively, to support a pulsed, CO2, Doppler lidar having a pulse energy of 10 J, pulse rate of 8 Hz, and efficiency of approximately 5%. Under the assumptions of the analysis, such a system would provide wind measurements on a global scale, with accuracies of a few meters per second.
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Energy storage is essential for the decarbonization of the U.S. energy grid, especially with the increasing deployment of variable renewable energy sources like solar and wind. Geological thermal energy storage (GeoTES) has emerged as a promising long duration, grid scale solution, providing stability and security through flexible operations and valuable grid services. GeoTES utilizes subsurface reservoirs to store thermal energy for power generation and direct-use heating and cooling. This approach significantly enhances the use of low-temperature reservoirs, which would otherwise be unsuitable for geothermal power plants. It also aligns well with depleted oil and gas reservoirs, concentrating solar power, non-flexible renewables (photovoltaic and wind), and geothermal-related power cycles. Given the favorable marginal costs of GeoTES as storage duration increases, it becomes particularly competitive for seasonal, grid-scale dispatch, where few technologies are viable. This paper provides a comprehensive review of GeoTES systems and the research underpinning itsr development. This analysis begins by defining and categorizing the unique characteristics of thermal energy storage techniques, setting GeoTES apart from other technologies. The various components, configurations, subsurface characteristics, and modeling efforts that guide GeoTES development are then explored. Finally, challenges in GeoTES research, development, and deployment are discussed, along with mitigation strategies and lessons from related technologies. Beyond their economic benefits, GeoTES systems support grid resilience and decarbonize industrial processes. Their scalability, broad distribution, seasonal storage potential, and flexible dispatch capacity make GeoTES a valuable tool for expanding renewable energy deployment and addressing climate change.
Topics related to architectural and institutional considerations are discussed along with studies of components and subsystems. Subjects in the area of system design and analysis are also explored. Residential and commercial applications are considered, taking into account hot-water usage in a typical single-family residence, solar heating and cooling of mobile homes, aspects of design and performance in the case of a solar heating system using a reflective pyramid optical condenser, solar heating in a Boston school, a performance analysis of solar service hot water systems, comparative performance analyses of three solar heated and cooled buildings, and the use of solar energy in a soybeam processing operation. Applications related to power generation are also examined, giving attention to solar thermal electric power systems and photovoltaic research. Individual items are announced in this issue.
Here, we synthesize available literature, data, and analysis on the degree to which growth in variable renewable energy (VRE) has impacted or might in the future impact bulk power system assets, pricing, and costs in the United States. Most studies of future scenarios indicate that VRE reduces wholesale energy prices and capacity factors of thermal generators. Traditional baseload generators are more exposed to these changing market conditions than low-capital cost and more flexible intermediate and peak-load generators. From analysis of historical data we find that VRE is already influencing the bulk power market through changes in temporal and geographic patterns areas with higher levels of VRE. The most significant observed impacts have concentrated in areas with significant VRE and/or nuclear generation along with limited transmission, with negative pricing also often occurring during periods with lower system-wide load. So far, however, VRE, has had a relatively modest impact on historical average annual wholesale prices across entire market regions, at least in comparison to other drivers. The reduction of natural gas prices is the primary contributor to the decline in wholesale prices since 2008. Similarly, VRE impacts on thermal plant retirements have been limited and there is little relationship between the location of recent retirements and VRE penetration levels. Finally, although impacts on wholesale prices have been modest so far, impacts of VRE on the electricity market will be more significant under higher VRE penetrations.
NREL's Solar and Storage Techno-Economic Analysis (TEA) team reviews live polling results from the Photovoltaic Reliability Workshop (PVRW) related to module technology trends believed to have the greatest reliability impacts. Then, the team reviews the publicly available tools and inputs necessary for evaluating reliability tradeoffs between initial module and system costs, degradation profiles, and levelized cost of energy (LCOE). These tools include the online Detailed Cost Analysis Models (DCAM) and the DuraMAT LCOE calculator.
The study focuses on achieving energy self-sufficiency in Wastewater Treatment Plants by proposing a comprehensive model for integrating, sizing, and optimizing an Organic Rankine Cycle system. The Organic Rankine Cycle system is designed to utilize waste heat from the gensets at As Samra Wastewater Treatment Plant in Jordan, where it will contribute to the overall electrical energy supply of the plant. Real data from As Samra Wastewater Treatment Plant is used to model and calculate the available waste heat using TRNSYS® software. The Organic Rankine Cycle model is then developed using ASPEN PLUS® software to explore the impact of operational parameters and determine their optimal values for maximizing the plant's energy profile. An economic analysis is conducted to assess the feasibility of the proposed model, considering system components, installation, operation, and maintenance costs. To optimize the Organic Rankine Cycle system, the study employs the Multi-Output Support Vector Regression technique to capture nonlinear relationships between independent variables (fluid type, turbine inlet pressure, turbine inlet temperature, turbine outlet pressure, and mass flow rate) and dependent variables (pump power input, waste heat input, and turbine specific work). The Osprey optimization algorithm is used to address the multi-objective optimization problem, with the proposed Pareto-based Osprey Optimization Algorithm and the Multi-Objective Particle Swarm Optimization technique being employed to evaluate critical performance and economic parameters such as system thermal efficiency, net power output, and the levelized cost of electricity. The results of the optimization strategies indicate that the M-SVR model's prediction accuracy is significantly improved after parameter optimization, with the model returning high R 2 and low Mean Square Error values of 0.991 and 0.00216, respectively. The Pareto-Based Osprey Optimization Algorithm optimizer identifies the best working fluid as Isobutane/Isopentane in a ratio of 66:34, with optimal turbine inlet pressure and temperature of 15 bars and 218 °C, respectively. In conclusion, the Organic Rankine Cycle model at these optimal conditions achieves a cycle efficiency of 19.93% and an Levelized Cost of Electricity value of 0.0353 USD/kWh.
We present the first systematic dispersive-optical-model analysis of 16,18 O, 40,48 Ca, 58,64 Ni, 112,124 Sn, and 208 Pb. In all systems, roughly half the total nuclear binding energy is associated with the most-bound 10% of the total nucleon density. The extracted neutron skins reveal interplay of asymmetry, Coulomb, and shell effects on the skin thickness. Here, our results indicate that optical-model fits on isotopic pairs are effective for constraining nuclear structural quantities otherwise difficult to observe experimentally.
As part of the Innovative Deep-Water Mooring Systems for Floating Wind Farms (DeepFarm) R&D project, led by Principle Power Inc., the National Renewable Energy Laboratory (NREL) performed an LCOE analysis to compare the changes in LCOE between floating wind farms with individual anchors versus shared anchors. This report presents a comparative analysis of the LCOE of two different wind farms with different mooring systems: one with taut mooring lines each connected to individual suction pile anchors, and one with taut mooring lines connected to shared anchors. A brief description of the methodology employed to conduct the LCOE comparison is given, including the underlying assumptions. Then, results are presented with a compilation of key findings.
High-impact low-probability (HILP) events can wreak havoc on electric power systems without appropriate preparedness. In this paper, the recent development of a tool, named Recovery Simulator and Analysis (RSA), is described and demonstrated. While there are many issues to consider when recovering electric power systems, the focus of RSA is on the coordination of transmission and subtransmission recovery with generation dispatch to minimize unserved energy. RSA focuses on recovery simulation to evaluate resilience as part of a planning process. RSA is demonstrated on an approximately 1400-bus Puerto Rican power system for 100 simulated instances of Hurricane Maria. Analysis of the recovery determines how many lines are critical to the recovery and which loads may experience delayed recovery. The results demonstrate the potential uses of RSA for identifying recovery decisions with low unserved energy and for identifying assets critical to recovery which can then be hardened prior to a HILP event.
The Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100) comprehensively analyzes possible pathways for Puerto Rico to achieve its renewable energy goals while incorporating stakeholder perspectives and advancing energy resilience for all Puerto Ricans. PR100 is a wide-ranging and in-depth examination of Puerto Rico's energy system investment options. The findings are the culmination of two years of stakeholder engagement, scenario modeling, and impact analysis. The PR100 report and Implementation Roadmap contain a range of results and actions that reflect Puerto Rico's priorities around energy justice, resilience, and reliability. Led by the U.S. Department of Energy's Grid Deployment Office with funding from the Federal Emergency Management Agency, the PR100 study leveraged and integrated dozens of best-in-class models and in-depth analyses from researchers across six national laboratories: National Renewable Energy Laboratory (which led the study), along with Argonne National Laboratory, Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory, Pacific Northwest National Laboratory, and Sandia National Laboratories (which conducted the study). For more information, please see the "PR100 Project Website" resource below.
Public outreach fact sheet about the Los Angeles 100% Renewable Energy Study (LA100), which is the most comprehensive, detailed study done to model an entirely renewable-based power system as complex as LA's.
Mixed Ta 2 O 5 – TiO 2 binary system was studied by a combination of differential thermal analysis (DTA), scanning electron microscopy-energy dispersive spectrometry (SEM-EDS), X-ray diffraction (XRD) and in situ high temperature X-ray diffraction (HT-XRD) techniques. Different compositions of the mixed oxide powders were fabricated by ball–milling the powdered compositions, pelletizing the homogenized composite powders, and heating the green pellets in air at different temperatures for fixed time intervals. The sintered pellets were evaluated and characterized with respect to porosity, morphology, and phase distribution. DTA runs of the un-sintered powders indicated the onset temperatures for both exothermic and endothermic changes in the binary system. Significant amount of sintering was observed to take place at temperatures higher than 900 °C. Both room and high temperature X-ray diffraction patterns exhibited consistency in phase formation. A ternary compound (TaTiO 4 ) and a ternary solid solution (Ti 0.33 Ta 0.67 O 2 ) were observed to form in both room and high temperatures in addition to the respective binary phases (Ta 2 O 5 and TiO 2 ). A sintering temperature in the range 900–1000 °C was observed to be adequate to achieve the requisite mechanical strength and optimum internal porosity (40–48%) for subsequent electrochemical polarization experiments.