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DOE OSTI2022

Pathways to the Next-Generation Power System With Inverter-Based Resources: Challenges and recommendations

Managing the stability of today's electric power systems is based on decades of experience with the physical properties and control responses of large synchronous generators. Today's electric power systems are rapidly transitioning toward having an increasing proportion of generation from nontraditional sources, such as wind and solar (among others), as well as energy storage devices, such as batteries. In addition to the variable nature of many renewable generation sources (because of the weather-driven nature of their fuel supply), these newer sources vary in size - from residential-scale rooftop systems to utility-scale power plants - and they are interconnected throughout the electric grid, both from within the distribution system and directly to the high-voltage transmission system. Most important for our purposes, many of these new resources are connected to the power system through power electronic inverters. Collectively, we refer to these sources as inverter-based resources.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Fitness-for-Service Analysis of Reactor Components under Flexible Load-Following Operating Conditions

Conventional power-generation plants, including nuclear plants, have been traditionally designed to provide a steady baseload energy capacity, optimizing output efficiency while minimizing variable costs. However, the growing adoption of large-scale renewable energy-generation systems, which rely on intermittent sources such as solar and wind, has introduced more variability into the energy supply in interconnected electricity grids. As a result, the next generation of power plants needs to operate in what is known as the load-following mode, requiring flexible adjustments in electricity production to align with the energy demand on the grid. This transition from the steady baseload operation to load-following operating conditions can significantly increase the number of times various plant components are exposed to transient stresses. This increased thermo-mechanical cycling can lead to accelerated material degradation, thereby elevating the risk of premature failure of a component. It becomes imperative to conduct a comprehensive analysis of fatigue, creep-fatigue, and stress corrosion cracking life, to assess the resilience of the various engineering components under these flexible load-following operating conditions. This study aims to develop a comprehensive numerical model of a light-water reactor pressure vessel (RPV) to investigate its degradation under various operating scenarios. This coupled thermo-mechanical finite element analysis evaluated the stress response of the RPV caused by considering fluctuations in thermal and mechanical loads caused by the varying pressure and temperature occurring during the load-following operation. Critical locations on the RPV are subsequently identified based on the stress response. The stress intensity factors for the postulated flaws at those locations are then calculated, followed by an evaluation of the reactor's life in accordance with the ASME Boiler and Pressure Vessel Code Section XI. This comprehensive life assessment covers a number of transients expected during the flexible load-following operation, providing invaluable insights into the RPV's structural integrity. Moreover, the development methodology can be adapted to other reactor components, as well as components of conventional power stations that are affected by varying operating conditions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Battery Energy Storage Scenario Analyses Using the Lithium-Ion Battery Resource Assessment (LIBRA) Model

Meeting aggressive carbon emission goals will entail widespread deployment of renewable sources of electricity. Because these sources are variable, there is a need to develop scalable energy storage technologies. The U.S. Department of Energy is supporting efforts to increase U.S. manufacturing and recycling capabilities for LIBs and to decrease costs of stationary storage batteries. Many factors influence the domestic manufacturing and cost of stationary storage batteries, including availability of critical raw materials (lithium, cobalt, and nickel), competition from various demand sectors (consumer electronics, vehicles, and battery energy storage), resource recovery (recycling), government policies, and learning in the industry, among other factors. Understanding how these factors interact and identifying synergies and bottlenecks is important for developing effective strategies for the LIB stationary energy storage system. We developed the Lithium-Ion Battery Resource Analysis (LIBRA) model as a tool to help stakeholders better understand the following types of questions: What are the roles of R&D, industrial learning, and scaling of demand in lowering the cost of battery energy storage system production? How do the intersections between the EV and stationary storage sectors affect the battery supply chain? For various stationary storage and EV penetration scenarios, what volumes of critical materials might be required and what role can resource recovery play? What does expected demand for both EVs and stationary storage portend for mineral resources and overall mineral scarcity? The LIBRA model is developed using a System dynamics (SD) modeling approach to represent interactions across the segments of the battery materials supply chain. System dynamics models can capture the complex interactions and feedback between the various system components that influence supply and demand. The LIBRA model is comprised of several interacting modules that represent specific portions of the LIB supply chain. The model tracks the buildout of the domestic LIB industry over time (2020 - 2050) and in the context of competing demands for raw materials, recycling, and markets for LIBs. The LIBRA model represents major systemic feedback loops and delays across the supply chain. This report provides a complete documentation for the LIBRA model, including model assumptions, data, scenario analysis results, and sensitivity analysis of the model's input space.

25 ENERGY STORAGE↗

DOE OSTI2023

Alternative Energy Carriers: Unique Interfaces for Electrochemical Hydrogenic Transformations

Abstract The shift toward renewable energy generation sources, characterized by their non‐carbon emitting but variable nature, has spurred significant innovation in energy storage technologies. Advancements in foundational understanding from investments in basic science and clever engineering solutions, coupled with increasing industrial adoption, have resulted in a notable reduction in the cost of storing electricity from variable energy generation sources. These developments have paved the way for the exploration of new and innovative forms of energy storage that deviate from traditional technologies. In this perspective, it is posited that the progress made in energy storage research over recent years has opened the door to the development of energy carriers for technologies that are yet to be realized. To illustrate this concept, examples of alternative energy carriers are provided within the context of unique electrochemical interfaces for electrochemical hydrogenic transformations. The unique properties of these interfaces and electrochemical systems can be leveraged in ways not yet imagined, creating new possibilities for energy storage. A perspective on the progress and challenges for each interface as well as a general outlook for the advancement of energy carrier systems are provided.

25 ENERGY STORAGE↗

DOE OSTI2021

Modeling a Lead-Cooled Fast Reactor with Thermal Energy Storage using Optimal Dispatch and SAM

Increased contributions from wind and solar energy have helped set the United States on an attainable pathway towards carbon-free energy production. Though renewable energy is pivotal for this goal, saturating the grid with these variable energy sources has its challenges. Resources for wind and solar vary from factors beyond human control, hence the power output from these energy generators doesn’t necessarily match power demand for a specific region at a given moment in time. Solar photovoltaic production has a drastic mismatch since the peaks for power demand and power production are often out of phase: production peaks with available irradiance while demand peaks during the morning and evening hours. This “duck curve” in energy demand, the difference between high and low demand, grows as the grid becomes more saturated with renewable energy providers.

Soto, Gabriel J.↗

DOE OSTI2023

Techno-Economic Analysis and Optimization of a Compressed-Air Energy Storage System Integrated with a Natural Gas Combined-Cycle Plant

To address the rising electricity demand and greenhouse gas concentration in the environment, considerable effort is being carried out across the globe on installing and operating renewable energy sources. However, the renewable energy production is affected by diurnal and seasonal variability. To ensure that the electric grid remains reliable and resilient even for the high penetration of renewables into the grid, various types of energy storage systems are being investigated. In this paper, a compressed-air energy storage (CAES) system integrated with a natural gas combined-cycle (NGCC) power plant is investigated where air is extracted from the gas turbine compressor or injected back into the gas turbine combustor when it is optimal to do so. First-principles dynamic models of the NGCC plant and CAES are developed along with the development of an economic model. The dynamic optimization of the integrated system is undertaken in the Python/Pyomo platform for maximizing the net present value (NPV). NPV optimization is undertaken for 14 regions/cases considering year-long locational marginal price (LMP) data with a 1 h interval. Design variables such as the storage capacity and storage pressure, as well as the operating variables such as the power plant load, air injection rate, and air extraction rate, are optimized. Results show that the integrated CAES system has a higher NPV than the NGCC-only system for all 14 regions, thus indicating the potential deployment of the integrated system under the assumption of the availability of caverns in close proximity to the NGCC plant. The levelized cost of storage is found to be in the range of 136–145 $/MWh. Roundtrip efficiency is found to be between 74.6–82.5%. A sensitivity study with respect to LMP shows that the LMP profile has a significant impact on the extent of air injection/extraction while capital expenditure reduction has a negligible effect.

25 ENERGY STORAGE↗

DOE OSTI2024

Modeling the Moisture Content and Dry Matter Loss in Dynamic Woody Biomass Storage Piles with Variable Extraction

The urgent need to mitigate climate change has spurred significant interest in renewable energy sources. This paper explores the storage and processing of woody biomass for biofuel production, considering the dynamic nature of biomass piles in real-world scenarios. A model has been developed to analyze moisture content changes and dry matter loss in woody biomass stored in piles prior to processing, taking into account varying extraction methods and environmental conditions. Case studies that examine the effects of different unpiling methods (FIFO, LIFO, and homogeneous) on moisture content and dry matter loss under various feedstock arrival rates and weather conditions are presented. Results indicate that unpiling methods significantly impact moisture content, with LIFO typically resulting in higher moisture content due to the utilization of fresher feedstock. Dry matter loss increases with pile size and time, emphasizing the importance of accurate modeling for assessing carbon emissions and feedstock quality. Furthermore, the model highlights the importance of process loading order and extraction methods in biomass storage, suggesting potential cost benefits associated with decreased moisture content. The difference between different extraction methods could vary the moisture content in the feedstock reaching the biofuel process by as much as 37.6%, however dry matter loss varies minimally for realistic pile changes. Overall, this research contributes to a better understanding of biomass storage dynamics and informs sustainable biofuel production practices.

Niska, Janel↗

DOE OSTI2023

Beneficial Integration of Energy Storage and Load Management with Photovoltaic (PV)

In recent years, a number of industry activities have aimed at addressing the integration challenges posed by the variability and uncertainty of higher penetration of renewable generation sources, like solar photovoltaic (PV) – one of the key objectives of the Sustainable and Holistic Integration of Energy Storage and Solar PV (SHINES) program launched by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy (EERE). This EPRI led Beneficial Integration of Energy Storge, and Load Management with PV project aimed to design, develop, and demonstrate end-to-end distributed energy resource (DER) integration solution to build on these activities. EPRI led project team designed and implemented a local controller that uses model predictive control (MPC) algorithm to optimally manage DERs on site by planning for a receding horizon while executing the control settings for the first step of its plan. The team has also developed a system controller to interface with the local controller to demonstrate the hierarchical control and how it can leverage DER capabilities to address challenges like over voltage and thermal limit violations which typically limits the DER hosting capacity of distribution feeders. Team has demonstrated how the local controller with optimization algorithm can effectively manage controllable loads like HVAC, water heater, and pool pumps to allow for greater integration of PV with relatively smaller energy storage system requirements. Optimal utilization of the load control can also reduce the depth of discharge of batteries to meet grid export/import limit from behind-the-meter (BTM) DERs. Proper utilization of DER capabilities via local control intelligence, like the one developed and demonstrated in this project can help the industry to address integration challenges of higher penetration of solar PV in economically efficient manner. This can help to accelerate deployment of clean renewable energy systems at lower societal cost.

14 SOLAR ENERGY↗

DOE OSTI2023

Open-Source Steady-State Models for Integration of Wave Energy Converter into Microgrids

This paper proposes a software framework, WEC-Grid, for integrating wave energy converters (WECs) into power flow software, such as Siemens PSS®E, to aid the integration of alternative energy sources into Microgrids. While integrating alternative sources such as WECs presents specific challenges such as cost, power quality, and power variability, wave energy is a promising renewable energy resource. Evaluating the integration of WECs into the power grid is a complex and nuanced problem that requires seamless communication between a WEC model and power flow software. The presented WEC-Grid software framework bridges and extends the functionality of WEC-Sim, an open-source WEC modeling package for MATLAB, through a wave-to-wire (W2W) electro-mechanical power conversion and processing model. WEC-Grid acts as a software wrapper, handler, and communication layer between the W2W modeler and power flow software. The software is designed to represent each grid system as a class object, allowing power system operators to perform power system duties such as contingency planning and dispatch operations. The integration of WECs with PSS®E’s power flow calculations workflow is demonstrated with an IEEE RTS case study.

16 TIDAL AND WAVE POWER↗

DOE OSTI2022

Building energy efficiency and load flexibility optimization using phase change materials under futuristic grid scenario

This work investigates the energy savings and load flexibility capacity of phase change material (PCM) integrated into building envelope under a future energy generation scenario, where 80% of the energy load comes from renewable sources. Using community-scale modeling, we first determine the net thermal storage required to fully manage the demand variability at a utility grid, and then using whole-building simulations we optimize operating parameters - such as PCM thickness, latent heat, interior setpoint profile, PCM distribution, and heat transfer coefficient - to determine the optimal conditions required for maximum energy reduction and load flexibility without compromising occupants' thermal comfort. The optimal PCM-integrated envelope proposed in this study can provide annual load flexibility up to 33.6% and annual energy savings up to 10.8% in a lightweight residential building located in Baltimore, MD. This study is relevant given the increasing contributions of renewable energy in the total energy generation mix, leading to a significant time-imbalance between peak energy demand and peak energy production. While thermal energy storage using PCM is a recognized technique, there is no known prior study dedicated to examining the thermal performance of PCM-integrated envelope under future energy generation scenarios. This study bridges the research gap by investigating a practical way to implement PCMs in the buildings and maximize the energy efficiency as well as load flexibility related benefits.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Hybrid-energy approach enabled by heat storage and oxy-combustion to generate electricity with near-zero or negative CO 2 emissions

We assess a hybrid-energy approach that modifies a steam-turbine power plant to use renewable energy sources (electricity, plus options for geothermal and solar heat), plus fossil fuel (natural gas and coal) and/or waste biomass (e.g., Douglas fir woodchips). Heat storage allows heat to be created during periods of excess energy supply and for that heat to be converted to electricity when demanded. Excess electricity, such as from variable renewable energy (VRE), is used to generate oxygen for oxy-combustion furnaces that create very-hot, high-purity CO 2 that heats granular rock beds in insulated vessels. Cool CO 2 leaving the beds is dried, sent to compressors powered by excess VRE electricity, before being sent by pipeline to geologic CO 2 storage. Very-hot CO 2 transfers high-grade heat from storage to the power plant in a closed loop that returns medium-grade heat back to storage, allowing low- and medium-grade renewable-heat sources to be stacked beneath combustion heat, with all heat sources being converted to electricity at the same (high) thermal efficiency. Reliable, on-demand power may be generated with near-zero CO 2 emissions with fossil fuel and with negative CO 2 emissions with waste biomass. Our analyses show that with fossil fuel, up to 35% of gross power can be derived from renewable sources, while for waste biomass, it can be entirely derived from renewable sources. Because our approach has the potential to ensure that grids have a continuous supply of clean energy and because electricity is only generated once, when demanded, it could serve as an efficient alternative to bulk energy storage.

30 DIRECT ENERGY CONVERSION↗

DOE OSTI2025

Optimal Complementarity Analysis of Potential Floating Solar Co-Located With Existing Hydropower Assets Across the Contiguous United States

The U.S. is expected to double its rate of renewable capacity from 2024 to 2030. However, the stochastic nature of renewable energy poses challenges to the operation and reliability of our power grid. The combined generation from renewable energy sources, with dispatchable sources (such as hydropower) operating as a hybrid energy plant, could mitigate this variability. In this paper, the complementarity analysis of selected U.S. reservoirs with existing hydropower assets (EHAs) and potential floating photovoltaics (FPVs) is conducted for the continuous U.S. (CONUS). The optimal FPV capacity for each site is determined by minimizing the variability of the combined output, while adhering to the FPV potential. Our results indicate that over 50% of the analyzed reservoirs achieve a stability coefficient exceeding 0.5, leading to a less-variable output after optimization. Finally, we analyze the complementary hydro-FPV hybrid reservoirs by considering both the Pearson correlation coefficient and the stability coefficient on daily, monthly, and yearly scales. Summaries are included of locations of theoretical FPVs co-located with hydropower plants that exhibit high complementarity based on the selected metrics.

13 - HYDRO ENERGY↗

DOE OSTI2023

Grinding and Pelleting Characteristics of Municipal Solid Waste Fractions

The efficient utilization of low-cost carbon feedstocks, such as municipal solid waste (MSW), in biorefineries has become increasingly important for reducing GHG emissions and meeting the growing demand for renewable energy sources. However, MSW as a feedstock presents several challenges, including high moisture content, compositional variability, particle size and shape, density, and ash content. To address these challenges, the potential of mechanical dewatering and high-moisture pelleting processes for densifying MSW fractions, such as paper, cardboard, thin plastic, and thick plastic, into low-cost carbon feedstocks with improved handling and conversion properties were investigated. The effect of these preprocessing technologies on the critical quality attributes (CQAs) of the resulting pellets, including bulk density, durability, and size uniformity, were evaluated. The results showed that with these preprocessing technologies, the paper and cardboard fractions could be pelleted at moisture contents over 40% (w.b.) while achieving >99% durability and >300 kg/m3, while the high moisture plastic fractions were not suitable for pelleting. The thick plastic fraction processed in a screw press was shown to remove up to 30% of the moisture content in a single pass. These findings suggest that these mechanical preprocessing technologies can improve the physical properties of low-cost municipal solid waste fractions for biofuels production.

09 BIOMASS FUELS↗

DOE OSTI2025

Energy innovation in the US buildings sector: Setting the stage and mapping the future

Jared Langevin is a staff scientist at Lawrence Berkeley National Laboratory, where he leads modeling of US buildings sector innovation and its implications for energy demand, consumer costs, and the power grid. Eric Wilson is a senior research engineer in the Building Technologies and Sciences Center at the National Renewable Energy Laboratory (NREL). Much of his 15-year career at NREL has revolved around modeling and analysis of the US building stock. Jared and Eric co-led the development of a National Blueprint for buildings sector innovation while serving as advisors to the US Department of Energy’s Deputy Assistant Secretary for Buildings and Industry.

Langevin, Jared↗

DOE OSTI2026

Pumped Thermal Energy Storage Using Low-Cost Particles and a Fluid Bed Heat Exchanger for Maximum Power Efficiency

Robust, efficient, cost-effective long-duration electricity storage (LDES) solutions can enhance grid resiliency, support existing transmission and distribution infrastructure, and enable a greater share of low-cost, variable alternative energy sources to penetrate the market. To meet this need, the project team at the National Renewable Energy Laboratory developed a transformative LDES system based on pumped thermal energy storage (TES) using low-cost particles and a fluid bed heat exchanger for maximum power efficiency (PUMP). The PUMP system is composed of high-temperature, low-cost particle TES coupled with an advanced pressurized fluid bed heat exchanger (PFB HX) that supports a high-efficiency pumped thermal energy storage (PTES) system integrated with concentrating solar thermal power (CSP). The PUMP project developed and de-risked a PFB HX and particle CSP system intended to be integrated with reversible turbomachinery and a modeling tool to assess PTES cost and performance.

14 SOLAR ENERGY↗

DOE OSTI2023

Design of a Geothermal Power Plant With Solar Thermal Topping Cycle: Preprint

Geothermal power plants are a reliable source of low-carbon power generation. However, modern electricity markets comprise relatively large proportions of variable renewable energy generation that may require power plants to dispatch energy flexibly. The power output, efficiency, and dispatch flexibility of a geothermal plant can be enhanced by integrating solar thermal energy into the system, as well as possibly compensating against ambient temperature variations. Concentrating Solar Thermal (CST) can generate temperatures much higher than conventional geothermal systems. Using a solar topping cycle is one way to efficiently convert high-temperature solar heat to electricity while also adding lower-temperature heat to the geothermal power cycle, thereby increasing its power output and possibly its efficiency. A hybrid power cycle design is proposed and is simulated using SimTech IPSEpro process modelling software. The design configuration depends upon the expected temperature of the geothermal resource and the quantity of solar heat added at the design point. These design considerations are described and expected performance is calculated. The solar heat addition varies throughout the day and year, therefore off-design models are necessary to assess the impact of solar availability (and ambient temperature) on the power plant performance. Off-design models are developed and combined with hourly weather data to facilitate an evaluation of annual system performance.

concentrating solar power↗

DOE OSTI2023

Design of a Geothermal Power Plant With Solar Thermal Topping Cycle

Geothermal power plants are a reliable source of low-carbon power generation. However, modern electricity markets comprise relatively large proportions of variable renewable energy generation that may require power plants to flexibly dispatch energy. The power output, efficiency, and dispatch flexibility of a geothermal plant can be enhanced by integrating solar thermal energy into the system, as well as possibly compensating against ambient temperature variations. Concentrating solar thermal (CST) can generate temperatures much higher than conventional geothermal systems. Using a solar topping cycle is one way to efficiently convert high-temperature solar heat to electricity while also cascading lower-temperature heat to the geothermal power cycle, thereby increasing its power output and possibly its efficiency. A hybrid power cycle design is proposed and simulated using SimTech IPSEpro process modeling software. The design configuration depends on the expected temperature of the geothermal resource and the quantity of solar heat added at the design point. These design considerations are described and expected performance is calculated. The solar heat addition varies throughout the day and year; therefore, off-design models are necessary to assess the impact of solar availability (and ambient temperature) on the power plant performance. Off-design models are developed and combined with hourly weather data to facilitate an evaluation of annual system performance.

concentrating solar power↗

DOE OSTI2025

Selection of Global Climate Model Data for Downscaling With Generative Machine Learning and Use in the Power Planning for Alignment of Climate and Energy Systems Project

The range of results from climate models and scenarios is important to the understanding of uncertainty in power planning analysis. A U.S. Department of Energy-funded analytic project called Power Planning for Alignment of Climate and Energy Systems is developing data and analytic methods to reflect the effects of climate change on key variables for power system planning, as part of the Grid Modernization Lab Consortium. This project will select and prepare global climate model results for use in power system planning models. A related report (Evaluation of Global Climate Models for Use in Energy Analysis) assesses the performance of various global climate models from the Coupled Model Intercomparison Project Phase 6 data archive for their historical skill with respect to energy system performance and for their future projections under multiple climate change scenarios. Building from that report, we describe the selection of a climate scenario (Shared Socioeconomic Pathway [SSP] 2-4.5) and five climate models: TaiESM1, EC-Earth3-CC, GFDL-CM4, EC-Earth3-Veg, and MPI-ESM1-2-HR. We describe the model selection criteria, which were based on the quality of the match between model results under historical conditions and on the representation of the range of future values for several variables. These results will be downscaled via an open-source generative machine learning method called Super-Resolution for Renewable Energy Resource Data with Climate Change Impacts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗