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At least 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Optimization and Evaluation of Energy Savings for Connected and Autonomous Off-Road Vehicles

Off-road vehicles, such as wheel loaders, excavators, and harvesters, are extensively utilized across a wide range of industries, including construction, agriculture, and mining. These machines have become indispensable in supporting the day-to-day operational needs of a nation, playing a critical role in various sectors' infrastructure and productivity. However, despite their utility, off-road vehicles are significant consumers of fossil fuels, resulting in substantial emissions that contribute to environmental degradation. This highlights the pressing need for research and technological advancements aimed at improving their energy efficiency and reducing their carbon footprint. There are, however, two primary challenges that must be addressed to achieve these goals. First, off-road vehicles typically perform both driving and working tasks simultaneously, which introduces a high level of complexity into their overall dynamic systems. Analysis the interactions between these functions is challenging. Second, research into off-road vehicles is inherently interdisciplinary, demanding expertise across several domains such as fluid power systems, vehicle dynamics, control theory, optimization techniques, and real-world implementation. Recognizing these challenges, we proposed the project titled "Optimization and Evaluation of Energy Savings for Connected and Autonomous Off-Road Vehicles" as a comprehensive solution to enhance fuel efficiency while simultaneously improving productivity. This project specifically focuses on autonomous off-road vehicles, with particular attention to wheel loaders, and seeks to develop novel methods to optimize energy consumption without sacrificing operational performance. The project integrates real-time control algorithms, vehicle dynamics modeling, and co-optimization of powertrain system and vehicle system to achieve these goals. Our optimization strategy dynamically co-optimizes critical parameters at both the powertrain and vehicle levels, including vehicle speed, working tool movements, powertrain dynamics, and engine operations in real-time. To streamline this optimization process, we developed a vehicle model that captures the key dynamics while significantly enhancing computational efficiency. This allows the system to intelligently minimize fuel consumption, all while maintaining or even improving productivity through real-time calculations during various off-road operations. To validate the effectiveness of this energy optimization method, we introduced a state-of-the-art Hardware-in-the-Loop (HIL) testbed. This reconfigurable testbed seamlessly integrates the actual engine with virtual models of the wheel loader's subsystems, allowing for accurate emulation of real-world operational loads and environments. By simulating these conditions, the HIL testbed enables us to evaluate the wheel loader’s performance under diverse working scenarios, ensuring the developed solution is applicable in real-world operations. This testbed proved to be instrumental in validating the optimization algorithms and demonstrating the system's practical effectiveness. During the evaluation and testing phase, we employed the HIL testbed to rigorously assess the energy savings and productivity improvements generated by the optimized system. The results were highly encouraging, revealing that the automated wheel loader achieved over 30% fuel savings compared to traditional, human-operated cycles, with comparable or even enhanced levels of productivity. The insights gained from this HIL-based testing provided critical validation of our approach and highlighted the potential for deploying these optimized autonomous technologies in real-world off-road vehicles.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Bridging Equipment Reliability Data and Robust Decisions in a Plant Operation Context

In order to reduce operation and maintenance (O&M) costs, nuclear power plants (NPPs) are moving from corrective and periodic maintenance to predictive maintenance strategies. Such transition requires changes on the data that needs to be retrieved and on the type of decision processes to be employed. Advanced monitoring and data analysis technologies are essential to support predictive strategies. They can in fact provide precise information about health of a component, track its degradation trends, and provide information of its expected failure time. With such information, maintenance operations for a component can be performed right before its expected failure time. This dynamic context of O&M operations requires new methods to analyze data, propagate component health information from the component to the system level, and optimize plant resources. In this respect, the risk informed asset management (RIAM) project has been tasked to develop and test this new class of methods into a risk analytics toolset. This toolset consists of data analytics tools coupled with reliability methods designed to manage plant assets and performances in a predictive maintenance context. This report shows the latest improvements on such development and the initial testing of our methods on the three main research areas that the RIAM project is focusing on. These areas are the following: equipment reliability data analytics, system reliability modeling, and plant resources optimization methods. We show how the methods developed in these areas can support predictive maintenance strategies by: 1) analyzing equipment reliability data (either in numeric and textual form), 2) assessing component and system health through an innovative margin-based reliability approach, and 3) identifying the most critical components and set optimal maintenance schedule based on plant economic and operational constraints.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Baseline Fuel Fabrication Facility

PRO-RR is the research reactor focused program element of the broader Proliferation Resistance Optimization program (PRO-X) under the National Nuclear Safety Administration (NNSA) in the U.S. Department of Energy (DOE). PRO-X provides a framework for integrating proliferation resistance in nuclear system designs to minimize weapons usable nuclear materials (WUNM) production and diversion pathways while optimizing systems performance for peaceful use missions. PRO-RR applies the PRO-X mission objectives to research reactor system design. This document serves as one of the foundational documents for the PRO-RR-Fuel System Design technical team by documenting a baseline fuel fabrication facility to be used for further optimization studies. The PRO-RR-Fuel System Design technical team consists of subject matter experts from Argonne National Laboratory (Argonne) and Savannah River National Laboratory (SRNL). In order to develop specific strategies for fuel fabrication facilities to optimize proliferation resistance, performance, and safety, a baseline fuel fabrication facility design basis was developed. Having a baseline design basis allows for the qualitative and quantitative comparison of design choices in the optimization process. This report describes the baseline fuel fabrication facility and general optimization strategy. Chapter 2 describes the fuel system selected for examination, the fabrication process used as the baseline, a description of the model developed to track uranium utilization, and a generic floorplan of the fabrication facility. Chapter 3 describes the overarching optimization strategy that could be implemented for a fabrication facility.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

High- and Mid-Fidelity Modeling Comparison for a Floating Marine Turbine System: Preprint

There is a lack of suitable numerical tools, particularly open-source tools, that can be used for designing and optimizing marine turbine systems. The National Renewable Energy Laboratory (NREL) has added features to their widely used mid-fidelity wind turbine modeling code, OpenFAST, to enable modeling of axial flow marine turbines. This necessitated the addition of several physical effects relevant to marine turbines that can be neglected for wind turbines. These include buoyant loads, added mass and inertia loads, wave-current superposition, and changes to the coordinate systems. This updated version of OpenFAST allows for the modeling of both fixed and floating marine turbine systems at a speed comparable to real time. While efficient for long simulations, large sets of load cases, and design studies, mid-fidelity codes cannot capture all of the potentially important physical phenomenon impacting marine turbine systems. High-fidelity computational fluid dynamics (CFD) simulations can capture more flow effects with fewer assumptions and provide detailed body pressure mapping and flow-field information. It is important to compare predictions between mid-fidelity and high-fidelity codes, both to verify the models and to understand the limitations. A floating marine turbine system designed by NREL was modeled both with OpenFAST and with the commercial CFD code, STARCCM+. The CFD model used a 3-D unsteady Reynolds-averaged Navier-Stokes solver for a volume-of-fluid numerical wave and current tank. The blade-resolved simulations used the sliding-interface technique for the spinning rotor and an overset grid to accommodate the rigid-body motion of the floating system. The mooring system was modelled with a custom coupling of the CFD solver with the open-source code, MoorDyn. This improves upon the existing quasi-static catenary solver in STARCCM+, which lacks seabed contact or line-to-line connections. Spatial and temporal convergence studies were conducted. The simulation results for a combined current and wave condition are compared between OpenFAST and CFD, highlighting the capabilities of the mid-fidelity code and identifying the areas where a high-fidelity approach is needed.

CFD↗
DOE OSTI2025

Engineering a new tripartite split-ccGFP system from Corynactis californica for detecting protein–protein interactions

Protein-protein interactions (PPIs) are critical to a range of biological processes and, consequently, aberrant interactions are implicated in many disorders. The study of the complex networks of PPIs promises to elucidate undiscovered roles in cellular processes and the mechanisms of disease. To accomplish this, tools to effectively sense PPIs are necessary. Effective PPI sensors must rapidly detect interactions in real-time with high sensitivity without perturbing the proteins of interest (POIs) under study. Split fluorescent proteins have previously been used to successfully monitor PPIs, in part due to the small size of the tags. Here, we developed an optimized tripartite split GFP system based on Corynactis californica GFP (ccGFP) to detect PPIs in vitro. In this sensor system, ccGFP fragments ccGFP10 and ccGFP11 are tagged to two POIs. PPIs can then be detected via fluorescence by complementation to the third fragment, ccGFP1-9, which reconstitutes functional ccGFP. The optimized ccGFP system shows improved detection kinetics and pH and temperature stability compared to a previous system. We then validated the sensor by monitoring PPIs in two model systems: attractive/repulsive coiled-coils and rapamycin-inducible FRB/FKBP heterodimerization. Finally, we developed an anti-tripartite ccGFP single-chain variable fragment (scFv), which could enable versatile detection of identified protein-protein complexes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Design and Implementation of Surface Eroding Thermocouples for Stage-One Modular Divertor Integration at the DIII-D Tokamak

The DIII-D has upgraded its upper divertor to a modular system using copper alloy pedestals to alter the divertor geometry without changing the vessel structure. Six new graphite tiles were designed for the shape and volume rise (SVR) divertor. Here, these new SVR tiles facilitated the formation of a poloidal array of 27 surface eroding thermocouples (SETCs) in the upper divertor region. At one location, a specialized recessed SETC, paired with a standard flush SETC, was installed in one of the ceiling tiles to provide comprehensive heat flux measurements, distinguishing between charged and noncharged particle contributions. Upgrades were made to the SETC system in the small-angle slot (SAS) divertor to improve overall performance. These upgrades included optimizing the feedthrough system to double the thermocouple cable capacity and reallocating cables from the SAS area to the SVR divertor. A compact isolation amplifier system with a fixed gain of 41 was employed to improve the signal level and minimize interference. Additionally, two analog-to-analog fiber systems were implemented for transmitting thermocouple signals over a single fiber, significantly reducing both noise levels and costs. The newly installed SETCs in the SVR divertor successfully completed initial commissioning testing. The SETCs captured the in-out asymmetry in the power distribution between the inner and outer strike points and demonstrated the dependency of the heat flux profile on the outer strike point location. During divertor detachment, heat flux mitigation was noted at the outer strike point location, while significant heat flux contributions from neutral particles were measured in the SVR divertor.

Divertor↗
DOE OSTI2023

Energy-Efficient and Resilient Infrastructure: Simulation, Validation, and Installation

Advanced, high-performance computing at the National Renewable Energy Laboratory (NREL) has enabled access to vast data resources with cutting-edge software techniques to understand, design, plan for, and maintain energy-efficient and resilient infrastructure. We have focused on cities and airports, but the technology we have developed will easily translate to seaports, inland ports, military installations, or other complex and large-scale energy-intensive systems. We can digitally simulate and explore current and future scenarios to make datadriven decisions for optimizing advanced energy systems, transportation and building operations, infrastructure planning and expansion, and battery storage to guide short- and long-term investments, electrification strategies, and integration of new technologies.

Athena↗
DOE OSTI2024

Swarm path planner system for vehicles

A system for determining optimal paths without collision through a travel volume for a swarm of vehicles is disclosed. The system determines a travel path for the swarm leader vehicle using a minimal cost path derived from various measures of environmental cost for avoiding objects in traveling from leader location to target location. The system also determines, for each empty neighbor location of each follower vehicle, relational costs for follower vehicle travel relative to leader vehicle travel. The various measures of relational cost seek to maintain a prescribed positional relationship between each follower vehicle and the leader vehicle given the leader vehicle travel path. Based on various measures of environmental and relational cost, the system determines the best travel path for the each follower vehicle relative to the leader vehicle.

Paglieroni, David W.↗
DOE OSTI2020

Photoinduced charge transfer in transition metal dichalcogenide heterojunctions – towards next generation energy technologies

Increasing interest in using two-dimensional transition metal dichalcogenides (2D TMDCs) in optical energy conversion technologies creates a demand for improving the yields and lifetimes of photogenerated charge carriers. Despite inherently fast photocarrier decay in neat 2D TMDCs, the unique photophysics in these quantum-confined systems motivates continued effort to control the evolution of photoexcited states and create functional devices. Here, an intriguing strategy to accomplish this goal is to employ TMDCs in heterojunctions with appropriate semiconductors, where energy level offsets drive photoinduced charge transfer (PCT) across material interfaces. PCT in TMDC-based systems can be optimized for many different applications, such as driving free carriers to photocatalytic sites for redox reactions like water splitting, extracting charge to perform work in photovoltaics or photodetectors, and manipulating the spin and momentum valley electronic degrees of freedom for quantum computing systems. Here, we review recent strides in optimizing PCT for such applications through greater fundamental understanding of the photophysics that occurs at TMDC/semiconductor interfaces. After giving an overview of isolated TMDC properties, synthetic methods, and the basics of PCT, we discuss TMDCs in heterojunctions with several classes of materials, including other TMDCs, small molecule semiconductors, polymers, single-walled carbon nanotubes, quantum dots, perovskites, and electrolytes. In addition to highlighting the unique benefits of each materials category, we also identify parallels across common themes, such as the roles of charge-transfer states, spin, electronic coupling, delocalization, interfacial atomic morphology, and the precise design of energy landscapes to direct charge and energy motion. We hope to capture a broad range of the valuable work in this fast-paced field to inspire new research directions for employing PCT in targeted TMDC-based systems.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2022

High-Temperature Latent Heat Storage System using Transportable Heat Pipes for Versatile Integration with Emerging Microreactors

With the growing interest in the development of micro nuclear reactors and their application to microgrid, high-temperature thermal energy storage (TES) has also been receiving great attention as a technology to reinforce the energy utilization and profitability of this class of reactors. Given the importance and research needs of the TES technology, a research project is underway at Idaho National Laboratory (INL) to develop high-temperature TES that can be easily interfaced with emerging micro nuclear reactors. Currently under development is the Heat pipe-Integrated Thermal Battery (HITB), a novel latent heat storage design that enables flexible and robust integration with any design of currently considered micro nuclear reactors. The development of detailed design based on the proposed TES concept, HITB, requires not only development and validation of modeling and simulation capabilities, but also research that spans thermal performance analysis, component- and system-scale design optimization, and experimental demonstrations including high-temperature feasibility testing. The current research efforts (and plans) are divided into the following four areas: (i) Thermal and structural modeling and analysis at both system- and component-scales for evaluating performance and conducting design optimization, (ii) Small-scale experimental demonstrations for the key components of the proposed HITB design, (iii) Modelica-based dynamic model development for developing a control strategy under dynamic operation within integrated energy systems configuration, (iv) Integrated experimental testing and demonstration. This paper introduces the overall research efforts that have been and are being conducted to develop and demonstrate the novel design of the high-temperature latent heat storage device, HITB. The key design features, ongoing research efforts including the development of modeling and simulation capabilities, small-scale demonstrations of the HITB’s key functionalities prior to scaled-up experimental demonstration, are discussed. Then, this paper concludes with a remark on the future research plans for this project.

25 ENERGY STORAGE↗
DOE OSTI2025

Assessing the Performance and Impact of PV Technologies on Storage in Hybrid Renewable Systems

Traditional monofacial photovoltaic (mPV) systems are commonly adopted and well-documented because of their lower upfront costs in comparison to bifacial photovoltaic (bPV) systems. This study investigates how PV technologies impact energy storage in grid-scale hybrid renewable systems, focusing on optimizing and assessing the performance of mPV and bPV technologies integrated with pumped storage hydropower. Using Ludington City, Michigan as a case study and analyzing real-world data such as solar irradiance, ambient temperature, and utility-scale load profiles, the research highlights the operational and economic benefits of bPV systems. The results reveal that bPV systems can pump approximately 10.38% more water annually to the upper reservoir while achieving a lower levelized cost of energy ($0.0578/kWh for bPV vs. $0.0672/kWh for mPV). This study underscores the outstanding potential of bPV systems in enhancing energy storage and management strategies, contributing to a more sustainable and resilient renewable energy future.

13 HYDRO ENERGY↗
DOE OSTI2021

A Novel Framework for Optimizing Ramping Capability of Hybrid Energy Storage Systems

Hybrid Energy Storage System has been widely applied in aerospace, electric vehicle, and microgrid applications. The advantages are that they include complimentary technologies with both high power and energy capabilities. HESS have the potential to be useful to the bulk power systems, for example to increase the value of energy produced by variable generation resource through enabling participation in ancillary service markets. Actualizing the benefits of HESSs requires optimizing the combined ramping capability of aggregated HESS resources. To provide quality ancillary service, source of HESSs locating at multiple sites of variable generation resource must be optimally sized and cohesively controlled. Optimizing aggregated resources can be formulated as an optimization problem. Successfully solving this problem not only requires using effective solution methods but also depends on accurately and rapidly setting the necessary parameters in the problem formula. This article proposes a novel framework with double-layer structure to solve the optimization problem of aggregating ramping capability. Program developed on the upper layer focuses on solving the optimization of aggregating ramping capability among multiple HESSs and is compatible with most existing optimization algorithms. Program on lower layer of the framework targets at optimizing the local control of a single HESS based on a thorough analytics of HESS operation strategy presented in this article. Result of local optimization is also provided to upper layer program for updating the parameters in formula of optimization problem. Real time hardware-in-the-loop test is conducted to verify the performance of the optimization framework developed. The work presented is expected to provide guidance for implementing this framework in practical operation.

Luo, Yushen↗
DOE OSTI2021

Evaluating Utility-Scale PV-Battery Hybrids in an Operational Model for the Bulk Power System

Systems that combine solar photovoltaic and battery energy storage technologies (PV-BES) are increasingly being proposed and deployed on the bulk power system. The operations and value of PV-BES systems have been extensively studied from the project developer's perspective through analyses that maximize plant-level revenue. However, PV-BES hybrids' operational characteristics are seldom studied from the perspective of bulk power system operators, who seek to optimize the performance of a suite of generation and storage assets that are connected via the transmission network. This work presents modeling approaches for representing and evaluating PV-BES hybrids in a model that optimizes operations across the bulk power system. Its novel contributions include demonstrating a technique to modify a unit commitment and dispatch model to represent the operational synergies of PV-BES hybrids. In particular, we describe the challenges and an approach for representing so-called DC-coupled PV-BES - which utilize a single bi-directional inverter - as a dispatchable resource in a commercial, production cost model (PCM), PLEXOS. We demonstrate this technique in a PCM study of the Los Angeles Department of Water and Power (LADWP) test system, by replacing existing PV and battery generators on the test system with our PV-BES hybrids. We then pursue scenario analysis that is designed to isolate the various drivers of operational strategies for DC-coupled PV-BES hybrids, including the nature of coupling, PV penetration on the system, and varying inverter loading ratios (or degrees of over-sizing of the PV field). Results from the analysis include utilization profiles for the PV DC energy across available pathways, dispatch profiles for the battery component, and the hybrid technologies' impacts on system-wide production costs. The approach presented in this paper can be used in any PCM that is looking to study PV-BES hybrids as a resource in different power system configurations and services.

14 SOLAR ENERGY↗
DOE OSTI2023

A comprehensive review on regeneration strategies for direct air capture

Direct air capture (DAC), which removes CO 2 directly from ambient air, is a critical negative emission technology for mitigating global climate change. Efficiency and the source of energy are crucial considerations for DAC to enable negative emissions. Substantial technological progress has been made in DAC technologies, and promising opportunities exist for commercial-scale deployments. However, DAC technologies require high regeneration energy to release CO 2 from sorbents. Various approaches have been tested and optimized for different DAC systems. This review demonstrates that the work equivalent regeneration energy demand (supported by either the electric grid or fossil fuel combustion) ranges from 0.5–18.75 GJ/t-CO 2 for solid sorbent DAC systems and 0.62–17.28 GJ/t-CO 2 for liquid solvent DAC systems. The regeneration process is the energy-demanding process in DAC that is a key step for efficient operation. Potential methods to lower the regeneration energy demand include microwave, ultrasound, magnetic particle heating, and electric swing. Although the potential methods to date are still at the lab scale, significant work is being done to optimize DAC system processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Pumpchart v1.0.0

Pumpchart is a graphical tool that plots the state of a hydraulic system overlayed on a pump curve and system curve. It assists with determining the optimal performance of the system. One advantage of Pumpchart over other softwares is that it is integrated with the Grafana dashboarding software, so that data can be plotted in real-time for instant operator feedback. It is intended to be used at NERSC to monitor the performance of our cooling water pumps.

Venture, Nicholas [Lawrence Berkeley National Labo↗
DOE OSTI2024

Integrating HPC, AI, and Workflows for Scientific Data Analysis: Report from Dagstuhl Seminar 23352

The Dagstuhl Seminar 23352, titled “Integrating HPC, AI, and Workflows for Scientific Data Analysis,” held from August 27 to September 1, 2023, was a significant event focusing on the synergy between High-Performance Computing (HPC), Artificial Intelligence (AI), and scientific workflow technologies. The seminar recognized that modern Big Data analysis in science rests on three pillars: workflow technologies for reproducibility and steering, AI and Machine Learning (ML) for versatile analysis, and HPC for handling large data sets. These elements, while crucial, have traditionally been researched separately, leading to gaps in their integration. The seminar aimed to bridge these gaps, acknowledging the challenges and opportunities at the intersection of these technologies. The event highlighted the complex interplay between HPC, workflows, and ML, noting how ML has increasingly been integrated into scientific workflows, thereby enhancing resource demands and bringing new requirements to HPC architectures, like support for GPUs and iterative computations. The seminar also addressed the challenges in adapting HPC for large-scale ML tasks, including in areas like deep learning, and the need for workflow systems to evolve to leverage ML in data analysis fully. Moreover, the seminar explored how ML could optimize scientific workflow systems and HPC operations, such as through improved scheduling and fault tolerance. A key focus was on identifying prestigious use cases of ML in HPC and understanding their unique, unmet requirements. The stochastic nature of ML and its impact on the reproducibility of data analysis on HPC systems was also a topic of discussion.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Delivery of a Solar-Powered Forward Osmosis Seawater Desalination Plant: Trevi’s 500 m3/day Zero-Carbon FO Seawater Desalination Plant at NELHA

This paper presents an account of Trevi’s delivery of a 500 m3/day solar powered forward osmosis (FO) seawater desalination plant at the Ocean Science and Technology Park of the Natural Energy Laboratory of Hawaii Authority (NELHA). The project aimed to demonstrate the viability of solar thermal-powered desalination for agricultural applications through the integration of a 2MW micro-dish solar thermal array with a state-of-the-art FO system. Highlighted in the paper are the three distinct project phases; Planning and Design, System Construction, Installation & Testing followed finally by System Operation and Optimization. Results and decisions which led to the final plant design will be shared, highlighting how Trevi Systems succeeded in producing a zero-carbon FO seawater desalination plant with a projected Levelized Cost of Water (LCOW) estimate competitive with existing carbon-intensive RO technologies (based on some assumptions and the cost of heat which is required for FO.

14 SOLAR ENERGY↗
DOE OSTI2021

Case Study: Hybrid Carbon Conversion Using Low-Carbon Energy Sources in Coal-Producing States

The demand for more carbon efficient power sources and a decrease in natural gas prices has decreased the desire for coal power. This decrease in demand has led to massive job losses in coal mining regions over the past decade. The purpose of this project is to develop a hybrid energy system utilizing both a coal power plant and advanced reactor, which is competitive with natural gas by improving on profitability and decreasing carbon emissions. This report details the problem with a summary of the impact on the coal industry and the availability of renewable energy sources in the Appalachian region. Because of the geography of the region, variable renewable energy sources are not available without significant size and siting restrictions. However, biomass in the form of wood waste is abundant and can be used as a carbon neutral energy source. Combining biomass and coal processing, in addition to thermal power plants, can increase system profits and efficiency by providing peaking power and conversion opportunities for secondary markets. The electric load is based on publicly available demand data from Appalachian Power, which services the western Virginia and southern West Virginia in the Appalachian region. The demand information is combined by service, normalized, and scaled to an average demand of 1000 kW, which will be the basis for sizing the hybrid energy system. A traditional screening curve analysis for a coal plant and advanced reactor shows that the least cost design varies significantly based on the assumed discount rate and capital recovery period. An optimization program to size the design in TEAL based on the load curve gives 10 optimal designs, all with a negative resulting net present value (NPV) and a coal plant capacity of less than 15%. Including profits from selling captured carbon at a flat rate results in a positive NPV; however, the coal capacity factor only increases to about 40%. There are limitations with this optimization as well since the price of CO2 is likely to decrease as more is sold to the conversion market. The suggested design will combine coal power, an advanced reactor, and coal and biomass coprocessing to produce a variety of products that can be sold to the conversion market while increasing system efficiency. The analysis of conversion pathways for coal and biomass reveals that multiple options will need to be included in the analysis to produce the optimal system design. Three systems will be optimized and compared to determine the best design based on the figures of merit of total NPV and cost of carbon avoided. The first system will include a coal power plant and an advanced reactor that will sell electricity to the grid to meet demand and sell captured carbon to the conversion market. The second system adds a high-temperature steam electrolysis plant, which will utilize electricity during times of low demand to produce hydrogen and sell it to the conversion market. The third system adds biomass and coal processing with options for hydrocarbon oils, syngas to be produced for the conversion market, and electricity generation to power components within the system or provide peaking power. This analysis will be based on a new approach that combines traditional screening curve methods with a dispatch algorithm that optimizes the system based on the opportunity cost of different production options. The resulting optimization algorithm should provide results with less processing time than HERON’s decision tree method. The results from this analysis will determine an optimal design and reinforce the benefits of coal power when used in a hybrid energy system. The initial results show that the addition of a secondary market for carbon sales could result in a positive NPV and increases the capacity factor of the coal plant as compared to a design with only sales to the electricity market. The addition of more markets and additional coal consumption from biomass coprocessing could increase NPV further, replace carbon in other markets through the sale of biomass-derived hydrocarbons, and demonstrate the value of coal power technology.

01 COAL, LIGNITE, AND PEAT↗