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DOE OSTI2021

Product Characteristics and Synergy Study on Supercritical Methanol Liquefaction of Lignocellulosic Biomass and Plastic

Bio-oil originating from lignocellulosic biomass (LCB) is a potential next-generation fuel because of its abundant, renewable, and sustainable resources compared to other types. However, these bio-oils are typically of low quality compared to petroleum-derived oils due to their low calorific value, high acidity, and oxygen content. This work intends to provide a feasible method for producing hydrocarbon-rich oils by supercritical methanol (scMeOH) coliquefaction of LCB and plastic waste. Both rice straw (RS) and linear low-density polyethylene (LLDPE) are coliquefied under 300 °C for 60 min in scMeOH at various RS/LLDPE mass ratios of 2:1, 1:1, and 1:2. Positive effects were found in terms of oil yield and fuel quality, such as higher hydrocarbons content and calorific value. The oil yield increased from 26.72 to 30.07 wt % with LLDPE addition of 67%. Around 79.15–92.24% of the oil was hydrocarbons, phenols, ketones, and diverse functional group compounds. The complex compounds led to various degrees of the synergetic effect on oil chemical compositions. Among various RS/LLDPE ratios in this work, RS/LLDPE of 1:2 was supposed to be an optimal ratio for hydrocarbon-rich fuel production because it presented the highest oil yield of 30.07 wt % and quality-high oil with 71.42% hydrocarbons. In addition, scMeOH coliquefaction of LCB and plastic waste shows a synergetic effect on the improvement of carbon and hydrogen contents in solid products. These results indicate that scMeOH coliquefaction of LCB with plastic is a feasible and promising means to improve fuel quality and also to realize the thermal recycling of plastic wastes.

09 BIOMASS FUELS↗

DOE OSTI2021

n-Butanol production by Rhodopseudomonas palustris TIE-1

Anthropogenic carbon dioxide (CO 2 ) release in the atmosphere from fossil fuel combustion has inspired scientists to study CO 2 to biofuel conversion. Oxygenic phototrophs such as cyanobacteria have been used to produce biofuels using CO 2 . However, oxygen generation during oxygenic photosynthesis adversely affects biofuel production efficiency. To produce n-butanol (biofuel) from CO 2 , here we introduce an n-butanol biosynthesis pathway into an anoxygenic (non-oxygen evolving) photoautotroph, Rhodopseudomonas palustris TIE-1 (TIE-1). Using different carbon, nitrogen, and electron sources, we achieve n-butanol production in wild-type TIE-1 and mutants lacking electron-consuming (nitrogen-fixing) or acetyl-CoA-consuming (polyhydroxybutyrate and glycogen synthesis) pathways. The mutant lacking the nitrogen-fixing pathway produce the highest n-butanol. Coupled with novel hybrid bioelectrochemical platforms, this mutant produces n-butanol using CO 2 , solar panel-generated electricity, and light with high electrical energy conversion efficiency. Overall, this approach showcases TIE-1 as an attractive microbial chassis for carbon-neutral n-butanol bioproduction using sustainable, renewable, and abundant resources.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

A Data-Driven Exploration of the Impact of Renewable Energy on Inter-Area Oscillations in the U.S. Eastern Interconnection

As increasing amounts of renewable energy (RE) resources are incorporated into the bulk-power grid, power system oscillations are expected to change. This work investigates how RE generation impacts the frequency and damping ratio (DR) of two dominant inter-area modes in the U.S. Eastern Interconnection (EI) using regularly updated estimates collected over a 12-month period. Quantile regression is used to derive the correlation between operating conditions and mode properties, and a bootstrap method is used to quantify the uncertainty associated with the correlation estimates. Results show that with an increase in system load, the frequency of a mode decreases and DR increases. Evidence that increasing RE generation results in an increase in frequency and decline in DR was found for one of the two modes studied. This work shows that increasing RE levels will impact the properties of inter-area oscillations in the EI, but it does not indicate the presence of immediate threats to grid stability. The outlined approach can be used to periodically assess changing mode properties as RE levels continue to grow and flag stability concerns before they become serious reliability threats.

Inter-area oscillation, mode meters, quantile regr↗

DOE OSTI2023

Model Predictive Voltage Control of Large-Scale PV or Hybrid PV-BESS Plants

Increased penetration level of inverter-based resources (IBRs) and renewable energy in the power grid has called for more requirements from the control of IBRs. In this paper, the voltage-reactive power control of a photovoltaic (PV) power plant or hybrid PV-battery energy storage system (BESS) plant connected to a bulk power grid, whilst meeting the grid requirements, is studied. In this paper, a continuous-set model predictive control (MPC) formulation is proposed for voltage-reactive power control. For the same, an aggregated dynamic PV plant model is developed based on the recursive system equivalencing method. The formulation is then implemented in PSCAD simulation on a 125 MW PV plant or hybrid PV-BESS plant. The MPC implementation achieves 10.13% voltage improvement based on PSCAD simulation results in a balanced fault case study. Simulation results further demonstrate that MPC provides improved voltage support over the conventional proportional-integral (PI) controller post-fault occurrence.

Abu rub, Omar↗

DOE OSTI2022

Nuclear Energy in Long-Term System Models: A Multi-Model Perspective

Long-term energy system models–including electric sector capacity expansion models–are widely used tools for informing planning, technology assessment, and policy analysis. Recent decarbonization goals and rapid technological change have increased the need to appropriately represent economic characteristics and technical details of energy system resources, including variable renewable energy, energy storage technologies, carbon-capture-equipped capacity, and nuclear energy. Nuclear power represents about 20% of electricity generation and 50% of carbon-free electricity in the United States as of 2021. However, there are many perspectives on the role of existing and new nuclear in the future U.S. energy system, which is reflected in the broad range of potential contributions reported in the literature. This project aims to understand how issues central to nuclear energy are represented in long-term energy models. Building on earlier collaborations that focused on variable renewable energy and energy storage, this project convenes four modeling teams that use national-scale long-term energy system models from the Electric Power Research Institute, the National Renewable Energy Laboratory, the U.S. Energy Information Administration, and the U.S. Environmental Protection Agency to share methods and data, update models, run coordinated scenarios, and identify research needs. Improving tools can provide more insightful analyses and ensure that methods are more transparent.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

Simultaneous flow of zero-carbon and conventional fuel liquids through Trans-Alaska Pipeline System (Abstract)

The purpose of this CRADA is to address key technical challenges specific to the transport of ammonia, a promising carbon-free fuel and hydrogen-carrier, through crude oil pipelines. Specifically, the project seeks to develop novel technologies for preparing liquid ammonia/ hydrocarbon mixtures for the dual purpose of (i) pipeline transport, and (ii) developing advanced marine fuel blends. By demonstrating compatibility with the Trans-Alaskan Pipeline System (TAPS) ammonia/oil blends may improve access to stranded natural gas and help overcome low-flow issues associated with declining oil productivity. In Alaska, this technology enhances the capabilities of TAPS allowing it to function as a statewide “Hydrogen Highway” for exporting green or blue ammonia. This is strategically important for Alaska which lacks statewide electrical transmission infrastructure but contains vast renewable and fossil resources located in remote regions with few local markets. Nationally, Alaska-sourced green (hydropower) or blue ammonia has the potential to improve reliability of a Pacific Northwest hydrogen storage hub as a hydrogen-carrier by helping to overcome seasonality of green hydrogen produced from solar or wind energy. Globally, this technology project has significant potential to improve the safety and efficacy of ammonia-rich fuel compositions for use in maritime propulsion and other mid-sized engines.

10 SYNTHETIC FUELS↗

DOE OSTI2024

Simultaneous flow of zero-carbon and conventional fuel liquids through Trans-Alaska Pipeline System [Abstract]

08 HYDROGEN↗

DOE OSTI2024

Self-Assembling Microgrids for Resilient Distribution Systems of the Future: Implementation in a Commercial DERMS Platform

Microgrids have long provided resilience to critical facilities such as hospitals and military installations, and they are now increasingly being looked at as a building block for future grids to support the energy resilience needs of the grid of the future. State-of-the-art technologies, such as blackstart algorithms using renewable distributed energy resources (DERs) to effectively and seamlessly form microgrids, have been produced by national labs over the years. Their adoption by the utility industry would be critical to reap the most benefits toward energy and climate resilience, and the pathway is via commercialization of these self-assembling microgrid algorithms by integrating them in a commercial product platform. This project brings a national labs team (LLNL, LANL) together with a vendor (Smarter Grid Solutions) to perform proof-of-concept integration of the algorithms into the vendor’s commercial Distributed Energy Resources Management System (DERMS). The project provides a strong pathway to commercialization of the algorithms thereby promoting adoption of resilient microgrid technology by utilities to offer resilience benefits to all customers and especially to disadvantaged and underserved communities.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Loss of Glen Canyon Dam Hydropower Plant Capabilities

The power grid in the western United States is undergoing a major transformation, driven by technological advancements, power markets, policy shifts, and evolving energy demands. The integration of variable renewable energy (VRE) resources, such as wind and solar, into the power grid has become a major driver of change. Between 2018 and 2023, about 19 gigawatts (GW) of new solar capacity and 14 GW of new wind capacity was built in the Western Interconnection (WI) region. These two VRE resources accounted for the majority of WI capacity additions. The Western Interconnection is expected to host 30 GW of wind, 40 GW of solar, and 14 GW of energy storage by 2030 (Western Electricity Coordinating Council n.d.).

13 HYDRO ENERGY↗

DOE OSTI2020

Synthetic Biology and Metabolic Engineering Employing Escherichia coli for C2–C6 Bioalcohol Production

Biofuel production from renewable and sustainable resources is playing an increasingly important role within the fuel industry. Among biofuels, bioethanol has been most widely used as an additive for gasoline. Higher alcohols can be blended at a higher volume compared to ethanol and generate lower greenhouse gas (GHG) emissions without a need to change current fuel infrastructures. Thus, these fuels have the potential to replace fossil fuels in support of more environmentally friendly processes. This review summarizes the efforts to enhance bioalcohol production in engineered Escherichia coli over the last 5 years and analyzes the current challenges for increasing productivities for industrial applications.

09 BIOMASS FUELS↗

DOE OSTI2021

Systemwide Considerations for Electrification of Transportation in Islands and Remote Locations

Electric vehicles (EVs) represent an important socio-economic development opportunity for islands and remote locations because they can lead to reduced fuel imports, electricity storage, grid services, and environmental and health benefits. This paper presents an overview of opportunities, challenges, and examples of EVs in islands and remote power systems, and is meant to provide background to researchers, utilities, energy offices, and other stakeholders interested in the impacts of electrification of transportation. The impact of uncontrolled EV charging on the electric grid operation is discussed, as well as several mitigation strategies. Of particular importance in many islands and remote systems is taking advantage of local resources by combining renewable energy and EV charging. Policy and economic issues are presented, with emphasis on the need for an overarching energy policy to guide the strategies for EVs growth. The key conclusion of this paper is that an orderly transition to EVs, one that maximizes benefits while addressing the challenges, requires careful analysis and comprehensive planning.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2023

Pretreatment of Algae for the Production of Fuels and Chemical Coproducts

Algal biomass is a promising resource for producing renewable fuels and chemicals, but despite decades of research, algal biorefining remains in a pre-commercial state. Recent economic analyses have indicated that high-value co-products are necessary to offset the cost of fuel production, implying the need for algae fractionation technology. One promising fractionation approach is Combined Algal Processing (CAP), which pretreats and extracts algal biomass to produce a fermentable aqueous hydrolysate, an organic lipid fraction, and a residual solids fraction. The CAP approach has historically employed a dilute acid pretreatment to lyse cells and solubilize algal carbohydrates for fermentation of the hydrolysate phase, but we recently identified alternative pretreatments with the potential to decrease costs and environmental impacts, including different implementations of dilute acid pretreatment, dilute alkali pretreatment, enzymatic pretreatment, and flash hydrolysis. We conducted a screening of six different pretreatment approaches across nine algae strains of varying composition, and measured pretreatment effectiveness as a combination of carbon and nitrogen solubilization, lipid extraction yield, and lipid speciation. In this screening, we found traditional dilute acid pretreatment to provide the most robust pretreatment performance, though other pretreatments were competitive, and some performed better for certain strains of algae. These results highlight the interplay between algae composition and pretreatment effectiveness.

algae↗

DOE OSTI2022

GeoThermalCloud: Machine Learning for Geothermal Resource Exploration

Geothermal is a renewable energy source that can provide reliable and flexible electricity generation for the world. In the past decade, the U.S. Geological Survey's resource assessments, Play Fairway Analyses (PFA), and GeoVision report by the U.S. Department of Energy's Geothermal Technologies Office provided insights on enormous untapped potential for geothermal energy to contribute to the U.S. domestic energy needs. The past studies identified that geothermal resources without surface expression (e.g., blind/hidden hydrothermal systems) comprise a huge potential. These blind systems can significantly increase power generation. But a primary challenge is locating and quantifying these hidden resources, which do not have any thermal manifestations on the surface. PFA has successfully identified some blind systems in the western USA (e.g., specific locations in the Great Basin region within Nevada). However, a comprehensive search for these blind systems can be time-consuming, expensive, and resource-intensive with a low probability of success. Accelerated discovery of these blind resources is needed with growing energy needs and higher chances of exploration success. Recent advances in machine learning (ML) have shown promise in shortening the timeline for this discovery. This paper presents a novel ML-based methodology for geothermal exploration towards PFA applications. Our methodology is provided through our open-source ML framework called GeoThermalCloud \url{https://github.com/SmartTensors/GeoThermalCloud.jl}. GeoThermalCloud uses a series of unsupervised, supervised, and physics-informed ML methods available in SmartTensors AI platform \url{https://github.com/SmartTensors}. Here, the presented analyses are performed using our unsupervised ML algorithm called NMF$k$, which is available in the SmartTensors AI platform. Our ML algorithm facilitates the discovery of new phenomena, hidden patterns, and mechanisms that helps us to make informed decisions. Moreover, the GeoThermalCloud enhances the collected PFA data and discovers signatures representative of geothermal resources. Through GeoThermalCloud, we were able to identify hidden patterns in the geothermal field data needed for the efficient discovery of blind systems. Crucial geothermal signatures often overlooked in traditional PFA are extracted using GeoThermalCloud and analyzed by the subject matter experts to provide ML-enhanced PFA, which is informative for efficient exploration. We applied our ML methodology on various open-source geothermal datasets within the U.S. (some of these are collected by past PFA work), and the results provide valuable insights on resource types within those explored regions. This ML-enhanced workflow makes GeoThermalCloud attractive for the geothermal community to improve existing datasets and extract valuable information often unnoticed during geothermal exploration.

machine learning (ML), geothermal energy↗

DOE OSTI2023

Introduction to the Special Section on Control and Management of Electric Power Systems With High Shares of Inverter-Based Resources

The growing interest in the integration of variable renewable energy (VRE) and distributed energy resources (DER) on both policy and economic grounds is driving the transformation of electric power systems. The significant deployment of VRE and DER can effectively displace the conventional synchronous generator-based power plants that for decades have been the foundation for power system generation and stability in electric power systems. Inverter-based resources (IBRs) introduce a high-level of uncertainty, variability, and complexity into the operation of electric power networks, and the transformation to IBRs raises a wide range of technical questions and operational challenges. The optimal coordination and control of these resources requires greater interoperability and necessitates significant upgrades of grid automation, including real-time monitoring.

distributed power generation↗

DOE OSTI2024

Toward sustainable electrochemically mediated separations driven by renewable energy

Environmental pollution, water scarcity, resource shortage, and fossil fuel reliance have all represented threats to a sustainable future. Separation processes play a pivotal role in improving sustainability in fields such as industrial processes, resource recycling, wastewater treatment, and water desalination, among others. Electrochemical systems have gained increased attention as effective separation platforms, not only in performance but also as a potentially energy-efficient approach. However, the reliance on non-renewable energy sources, such as fossil fuels, for electricity generation limits the advancement toward a fully sustainable separation process. Integration of separation processes with eco-friendly renewable energy sources can increase overall sustainability and decrease carbon footprint. Here, in this review, we provide an overview of electrochemical separations and recent efforts to integrate them with renewable energy sources such as heat and solar energy. We discuss electrochemical separations, including electrosorption and electrodialysis, and research to transition these processes to thermoelectrochemical (TEC) and photoelectrochemical (PEC) platforms. Finally, we discuss current challenges and future prospects in direct integration of renewable energy sources with separation processes.

electrochemistry↗

DOE OSTI2023

The Global Technical, Economic, and Feasible Potential of Renewable Electricity

Renewable electricity generation will need to be rapidly scaled to address climate change and other environmental challenges. Doing so effectively will require an understanding of resource availability. We review estimates for renewable electricity of the global technical potential, defined as the amount of electricity that could be produced with current technologies when accounting for geographical and technical limitations as well as conversion efficiencies; economic potential, which also includes cost; and feasible potential, which accounts for societal and environmental constraints. We consider utility-scale and rooftop solar photovoltaics, concentrated solar power, onshore and offshore wind, hydropower, geothermal electricity, and ocean (wave, tidal, ocean thermal energy conversion, and salinity gradient energy) technologies. We find that the reported technical potential for each energy resource ranges over several orders of magnitude across and often within technologies. Therefore, we also discuss the main factors explaining why authors find such different results. According to this review and on the basis of the most robust studies, we find that technical potentials for utility-scale solar photovoltaic, concentrated solar power, onshore wind, and offshore wind are above 100 PWh/year. Hydropower, geothermal electricity, and ocean thermal energy conversion have technical potentials above 10 PWh/year. Rooftop solar photovoltaic, wave, and tidal have technical potentials above 1 PWh/year. Salinity gradient has a technical potential above 0.1 PWh/year. The literature assessing the global economic potential of renewables, which considers the cost of each renewable resource, shows that the economic potential is higher than current and near-future electricity demand. Fewer studies have calculated the global feasible potential, which considers societal and environmental constraints. While these ranges are useful for assessing the magnitude of available energy sources, they may omit challenges for large-scale renewable portfolios.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Grid-Forming Inverter-Based Resource Research Landscape: Understanding the Key Assets for Renewable-Rich Power Systems

The shift to net zero energy systems has changed the face of our power grid. Traditional large-scale synchronous generators found inside coal and natural gas plants are being replaced with inverter-based resource (IBR) technologies. This transition to an IBR-dominant power grid introduces new characteristics, altering how our grid operates. Therefore, the role of IBRs has expanded, requiring them to provide a range of essential services to keep our grid reliable, resilient, and secure.

energy management↗

DOE OSTI2021

Storage Requirements for Grid Integration of Marine Renewable Energy - a Parametric Study

Marine resources such as waves and tides house immense potential to serve as energy-rich sources of renewable power generation. They are known to be highly available,persistent and predictable in nature. Therefore, these can serve as one of the critical components for a primarily renewable energy-driven, resilient and robust future power grid. Although some inherent temporal characteristics of these resources lend themselves favorably to potential grid applications, the inclusion of storage allows the benefits and value streams to become realized more fully. In this paper, we present a framework for assessing impact of marine energy resources inclusion on the overall load generation balance and its impact on the relevant storage requirements to obtain the desired level of renewable energy penetration. From this study, we can critically infer two main points - (a) the relative storage requirements for grid operations with and without marine energy, and (b) the avoided cost of storage by including marine energy into the generation mix. We demonstrate our framework for two different locations across the United States.

Hanif, Sarmad↗