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At least 37 records · Page 2

Techno-economic analysis of offshore wind PEM water electrolysis for H 2 production

A model for producing hydrogen via offshore wind electrolysis was developed and the levelized costs of both energy and hydrogen were calculated. Here, this model calculated the cost of hydrogen produced by offshore wind and showed that the levelized cost of energy for hydrogen production and transportation to shore could be lower than for electricity transmission from offshore wind farms, using real wind data from a particular location. Therefore, direct coupling of the electrolysis system with offshore wind turbine is more advantageous than transmitting electricity to shore and then producing hydrogen via traditional electrolysis; the cost of hydrogen from offshore wind electrolysis is estimated to be $\$2.09$/kg, vs $\$3.86$/kg from traditional electrolysis using wind power.

08 HYDROGEN↗

Prospects of hydrogen cogeneration and carbon dioxide utilization in electrochemical refineries for ethylene production via oxidative coupling of methane: A techno-economic assessment

Ethylene is recognized as one of the most significant chemicals globally. The projected ethylene production for 2023 stands at 227.6 million tonnes, with expectations of continued demand growth. The primary use of ethylene, accounting for over 76%, lies in the production of plastics such as polyethylene, polyvinyl chloride, and polystyrene. Despite the enduring carbon retention potential of plastics themselves, traditional ethylene feedstock production from fossil resources contributes substantially to greenhouse gas emissions, ranging from 0.29 to 2.29 kg CO2 /kg Ethylene depending on various factors like feedstock and process design. Various decarbonization strategies, including the utilization of hydrogen as a primary heat source, have been proposed to reduce the carbon footprint of ethylene production, but their efficacy remains limited, offering at best a 0–30% reduction in on-site CO 2 emissions.

09 BIOMASS FUELS↗

Economic Analysis of the NIF Optics Recycle Loop Systems Investment Options: SAE 560 - Economic Considerations for Systems Engineering at University of Southern California

The National Ignition Facility (NIF) relies on large-scale precision optics to deliver high-energy laser pulses for fusion and high-energy-density physics research; however, the NIF routinely operates above the damage threshold for those optics, decreasing their effectiveness with every experiment. A production line composed of several dozen highly specialized processing systems, collectively referred to as the ‘optics recycle loop’, was established to support refurbishment and re-use of these critical components to reduce reliance on high-cost and high-risk optic replacement strategies. This analysis aims to identify the most cost-effective investment options for improving recycle loop throughput by maximizing availability and production flexibility while minimizing the engineering and infrastructure efforts and cost.

42 ENGINEERING↗

A Technical and Economic Assessment of LWR Flexible Operation for Generation and Demand Balancing to Optimize Plant Revenue

With increased penetration of subsidized variable renewable energy (VRE) resources and competition from low natural gas prices, existing light water reactor (LWR) nuclear power plants (NPPs) are struggling to remain economically competitive. This work examines the potential economic competitiveness of various thermal energy storage (TES) technologies when coupled directly or indirectly with a NPP. To highlight their relative economic competitiveness, we contrast several energy storage solutions in stochastic dispatch optimization. We leverage data from recent work analyzing a range of TES technologies with varying capital costs, performance, and technology readiness level (TRL) to establish our case. We explore inserting these technologies into an electricity market with existing nuclear generation and large projected variable renewable energy (VRE) penetration. Although these technologies' projected capital costs may make them unlikely candidates in their current state, this analysis demonstrates a high-fidelity techno-economic analysis of energy storage. Furthermore, as the projected cost of energy storage technologies evolves, this analysis sets a precedent for similar future investigations. One region with projected trends that may be unfavorable for existing nuclear capacity is the New York Independent System Operator (NYISO) market. New York state’s baseload generation has been historically provided by fossil-fired and nuclear assets. However, amid economic pressures from subsidized VREs and low natural gas prices, the state has recently deactivated Indian Point nuclear power plant units 2 and 3. Furthermore, the state plans to meet its zero-emission generation target by 2040 by replacing fossil-fired capacity with significant investments in VRE resources like wind and solar photovoltaic (PV) and battery storage. Increased intermittent resource penetration lowers the baseload power requirement, adding further economic pressure to the state’s three remaining NPPs still in operation. With three NPPs still in operation in New York, this work analyzes potential economic benefits to NPPs on the New York grid when directly or indirectly coupled with various TES technologies. This work requires two modeling steps to analyze the potential economic benefits of various system configurations of the TES directly or indirectly coupled with nuclear. First, this analysis leverages capacity expansion modeling by experts at the Electric Power Research Institute (EPRI). Using their deterministic capacity expansion model, U.S. Regional Economy, Greenhouse Gas, and Energy (US-REGEN), EPRI analysts evaluated the capacity and generation evolution of the New York state energy market under four projection scenarios. These four projection scenarios were developed to represent the potential evolution of the capacity and generation in NYISO from 2015 to 2050 under various economic, technology, and policy constraints. The results from these capacity expansion models are then used as boundary conditions in the second modeling step. The second modeling step uses the Holistic Energy Resource Optimization Network (HERON) for a set of stochastic techno-economic analyses (STEAs) to investigate the potential increase in the economic viability of various configurations of the TES. With no current capacity expansion capabilities, HERON takes the data generated from US-REGEN for 2050 to generate synthetic load, solar, and wind data. Then HERON economically optimizes the capacity and dispatch of the various TES configurations. The potential economic benefit is the differential net present value (NPV) of the TES configurations from the no-TES baseline. As a stochastic techno-economic analysis package, HERON introduces uncertainty into the economic metrics, while US-REGEN trades resolution for reduced computational complexity. Using HERON also allows the modeling of direct thermal coupling, a feature not common in capacity and dispatch models. As expected, with high capital costs, the costs of introducing energy storage for all the technologies considered outweighed the potential economic benefit of this strategy for flexible plant operation. The benefit of this analysis is primarily in demonstrating a workflow that examines innovative solutions to increase NPP revenue via TES coupling. HERON’s stochastic capacity and dispatch optimization process used in this work has proven an effective tool in observing and evaluating the impact of introducing storage technologies in a grid energy system.

25 ENERGY STORAGE↗

Contrasting coordination of non‐structural carbohydrates with leaf and root economic strategies of alpine coniferous forests

Non-structural carbohydrates (NSCs), as the labile fraction and dominant carbon currency, are essential mediators of plant adaptation to environments. However, whether and how NSC coordinates with plant economic strategy frameworks, particularly the well-recognized leaf economics spectrums (LES) and root economics space (RES), remains unclear. We examined the relationships between NSC and key plant economics traits in leaves and fine roots across 90 alpine coniferous populations on the Tibetan Plateau, China. We observed contrasting coordination of NSC with economics traits in leaves and roots. Leaf total NSC and soluble sugar aligned with the leaf economic spectrum, conveying a trade-off between growth and storage in leaves. However, NSC in roots was independent of the root economic spectrum, but highly coordinated with root foraging, with more starch and less sugar in forage-efficient, thinner roots. Further, NSC-trait coordination in leaves and roots was, respectively, driven by local temperature and precipitation. These findings highlight distinct roles of NSC in shaping the above- and belowground multidimensional economics trait space, and NSC-based carbon economics provides a mechanistic understanding of how plants adapt to heterogeneous habitats and respond to environmental changes.

54 ENVIRONMENTAL SCIENCES↗

Spaced out: An economic framework to explore the impacts of PV panel spacing on large-scale farming in Colorado

CONTEXT Agrivoltaic systems co-locate solar technologies with agricultural operations on an integrated plot of land and potentially provide benefits to both energy and agricultural systems. To date, large-scale (>5-MW) agrivoltaic projects in the United States have been limited to grazing and ecovoltaic applications, raising questions about the impact and scalability of agrivoltaic crop systems. Many agrivoltaic designs raise the height of the solar panels to accommodate agricultural practices while keeping energy density high. However, raising the panels results in increased photovoltaic (PV) development costs, which often are higher than the economic returns of crop production underneath the panels. This leads to unfavorable project economics and the need for other agrivoltaic solutions than raising panels. OBJECTIVE To explore other solutions, we perform an initial feasibility analysis for an agrivoltaic solution that can integrate with large-scale farming practices by increasing the row spacing in between panels. Increased PV row spacing is a low-cost approach for scaling agrivoltaics to accommodate crop production and this spacing can be tailored to required crop equipment for different regions. Increasing row spacing will reduce the power density (PV installed per acre), but in areas that are not land limited, these agrivoltaic designs could be economically feasible. Our analysis establishes a framework for a feasibility analysis for where and with what crops spaced out panel agrivoltaic solutions might be economical. METHODS Using a case study for large-scale agriculture crops in Colorado, we establish a framework for wide-row agrivoltaic economic feasibility analysis. We utilized the System Advisor Model to calculate technoeconomic metrics to compare different row spacing solutions and capture tradeoffs of these system designs. RESULTS AND CONCLUSIONS We find that, in some circumstances, wider row agrivoltaic solutions that allow for continued mechanized crop production can provide economic benefits over a traditional utility-scale PV system. For most crops examined in this analysis, roughly $\$$200/acre in agricultural profit justified spacing out the panels to at least 31.7 ft. to accommodate agrivoltaic configurations versus PV only configurations. Additionally, opportunities for increased agricultural revenue with agrivoltaic systems allow PV project economics to tolerate a larger range of CAPEX variability while remaining economically viable relative to the PV only configurations. SIGNIFICANCE This framework can be adapted for a wide variety of crops and regions and allows for examination of economically favorable sites for future agrivoltaic systems that utilize different configuration and expand opportunities for agrivoltaics.

14 SOLAR ENERGY↗

Microreactor Optimization Using Simulation And Economics (mouse)

Microreactor Optimization Using Simulation and Economics (MOUSE) is a tool that integrates both nuclear microreactor design and reactor economics to provide comprehensive evaluations and optimizations. This tool enables stakeholders to explore the interplay between technical and economic variables, guiding them towards effective and competitive microreactor solutions. For the reactor core simulations, MOUSE leverages the OpenMC Monte Carlo Particle Transport Code to perform detailed core simulations for various microreactor designs. The included OpenMC models are 2D core designs of a Liquid Metal Thermal Microreactor (LMTR), a Gas-Cooled TRISO-Fueled Microreactor (GCMR), and a Heat Pipe Microreactor. Beyond core design, MOUSE includes simplified calculations for: - Calculating the masses of heat exchangers within the system. - Mechanical power of pumps. - Estimating the area occupied by various buildings within the nuclear plant. For the economic analysis, MOUSE provides detailed bottom-up cost estimates, encompassing a wide range of costs including preconstruction costs, direct costs, indirect costs, training costs, financial costs, operation & maintenance (O&M) costs, and fuel costs. These cost estimations are developed using data from the MARVEL project and additional literature sources, enabling the calculation of total capital costs and levelized cost of energy for both first-of-a-kind and nth-of-a-kind microreactors. MOUSE also enables analysis of the cost drivers and competitiveness in the electricity market. MOUSE allows users to modify a wide array of technical and economic parameters to evaluate different scenarios and their impacts. Examples of these parameters include: Fuels, coolants, or reflector materials Enrichment levels Control drum materials and geometry Fuel pin geometry and materials Moderator pin geometry and materials Reactor core and reflector dimensions Packing factor for the TRISO particles Nuclear reactor power and reactor burnup Number of sensors Shielding thickness Reactor vessel and guard vessel dimensions Operational staff requirements Number of emergency shutdowns Levelization period Interest rate Construction duration Since MOUSE is powered by the WATTS toolkit, it supports optimization studies, parametric analyses, and uncertainty calculations/propagation. The optimization techniques enable users to identify optimal design and economic configurations. The parametric analysis tools allow users to explore the sensitivity of various parameters, while uncertainty propagation helps quantify the impact of uncertainties on overall performance and cost. User Interface and Workflow: Currently, MOUSE is a command-line-based tool. Users can input various reactor design or economic parameters, modify the designs, run simulations, and visualize results through comprehensive data visualization and reporting capabilities. The typical workflow involves setting up the reactor model, defining economic parameters, running simulations, and analyzing the results to make informed decisions. By combining advanced design calculations with detailed economic modeling, MOUSE provides a robust framework for optimizing nuclear microreactor technologies, enhancing their competitiveness, and guiding stakeholders towards innovative and cost-effective solutions.

Hanna, Botros [Idaho National Laboratory (INL), Id↗

Solar energy system economic evaluation for Elcam-Tempe, Tempe, Arizona and Elcam-San Diego, San Diego, California

The long term economic performance of the solar energy system at its installation site is analyzed and four additional locations selected to demonstrate the viability of the design over a broad range of environmental and economic conditions. The economic analysis of the solar energy systems that were installed at Tempe, Arizona and San Diego, California, is developed for these and four other sites typical of a wide range of environmental and economic conditions in the continental United States. This analysis is accomplished based on the technical and economic models in the f Chart design procedure with inputs based on the characteristics of the installed system and local conditions. The results are expressed in terms of the economic parameters of present worth of system cost over a projected twenty year life: life cycle savings; year of positive savings; and year of payback for the optimized solar energy system at each of the analysis sites. The sensitivity of the economic evaluation to uncertainites in constituent system and economic variables is also investigated. The results demonstrate that the solar energy system is economically viable at all of the sites for which the analysis was conducted.

Source record↗

Techno-Economic Wind Blade Manufacturing Model to Identify Opportunities for Cost Improvements Phase II IACMI Project 4.6/4.8

In IACMI Project 4.6 and IACMI Project 4.8, an Excel-based Techno-Economic Model (TEM) of the manufacturing process for composite wind turbine blades and a DELMIA Factory Flow Simulation of a generic wind blade manufacturing facility was developed. Together, these two tools provide a combined economic modeling capability that accounts for the material, labor, overhead and full-lifecycle operating costs associated with wind blade manufacturing as well as the impact of process flow and factory layout on overall manufacturing efficiency. The tools provide a novel means of detailed comparative analysis of the economic feasibility of proposed technologies and process changes for blade manufacturing. The modeling tools were developed with close support from members of industry and visits to multiple blade manufacturing facilities. With industry oversight, a detailed generalized manufacturing process plan and facility layout were developed with manufacturing parameters, material costs and economic factors based on historical data. Dassault Systèmes and the University of Texas at Dallas (UTD) contributed to the development of the Techno-Economic Model by providing macros to enable the generation of Bill of Material (BOM) data from a 3D blade design in either CATIA or NuMAD format, respectively. The TEM was built with the capability to directly import a Bill of Materials for economic analysis, and with the addition of the macros provided by Dassault and UTD, the TEM can directly import blade designs from both CATIA and NuMAD file formats. The modeling tools developed in Project 4.6 were used to investigate four wind blade manufacturing concepts in detail and select one to explore with laboratory-scale experimentation in Project 4.8. The four manufacturing concepts that were investigated were down-selected by the full project team from a larger list of concepts. The selections were made based on a number of criteria ranking viability and level of interest for each concept. The ‘One-Step Close’ manufacturing concept was ultimately selected for investigation in Project 4.8 and the demonstration was performed at the NREL CoMET facility. The TPI advanced manufacturing facility in Warren, RI contributed the production of several prototype components, the designs for which were developed by Janicki Industries. The demonstration project provided clear indication of the viability of the One-Step Close manufacturing concept for blade manufacturing and good validation of the Techno-Economic Model’s prediction of its economic impact.

17 WIND ENERGY↗

Solar energy system economic evaluation: Fern Tunkhannock, Tunkhannock, Pennsylvania

The economic performance of an Operational Test Site (OTS) is described. The long term economic performance of the system at its installation site and extrapolation to four additional selected locations to demonstrate the viability of the design over a broad range of environmental and economic conditions is reported. Topics discussed are: system description, study approach, economic analysis and system optimization, and technical and economical results of analysis. Data for the economic analysis are generated through evaluation of the OTS. The simulation is based on the technical results of the seasonal report simulation. In addition localized and standard economic parameters are used for economic analysis.

Source record↗

Policy impact on economic and environmental sustainability of anaerobic digestion: Industrial case study Insights

This paper thoroughly examines how policy incentives impact the economic and environmental sustainability of anaerobic digestion (AD) systems. It uses techno-economic and life cycle analyses, along with real industry data, to explore the entire AD process—from feedstock acceptance to digestate disposal. It evaluates the effects of various U.S. policy crediting programs on the economic viability of different AD pathways for treating sewage sludge and food waste. Furthermore, tipping fees are identified as the primary driver of profitability, while policy credits play a crucial role in enhancing economic feasibility, particularly for renewable natural gas production. However, future regulatory changes could reshape this economic landscape. All AD pathways are found to significantly reduce greenhouse gas emissions, though economic outcomes are highly sensitive to digestate disposal costs and feedstock tipping fees. Co-digestion with food waste is proposed as a strategy to reduce dependence on policy credits and improve long-term economic stability.

Anaerobic Digestion↗

Regional Economic Impacts of the Los Angeles 100% Renewable Energy Transition

To help mitigate greenhouse gas (GHGs) generation from burning fossil fuels, many state and local governments are requiring utilities to dramatically increase the share of electricity generated from renewable sources. The City of Los Angeles has set a target of 100% renewable energy by 2045 and has formulated a plan that considers nine potential alternative scenarios that differ by technology, location, and timing. Each scenario has a unique set of local investments, operating and maintenance (O&M) costs, and concomitant rate structures. In this study we develop and apply a computable general equilibrium (CGE) model built specifically for LA to estimate and compare the economic impacts for each of the scenarios over time relative to a reference case. We find differences in economic impacts across scenarios, depending on the level and timing of investment and O&M expenditures, as well as differences in the relative rate changes across scenarios. Results show that employment and economic output are positively correlated with greater capital and O&M spending, while higher electricity rates can dampen economic activity. Several scenarios generate positive economic impacts relative to the reference case, showing that the transition need not have harmful economic impacts, and all scenarios generate a number of other positive co-benefits, such as reduced damage to health from the reduction of ordinary air pollutants. The net employment impacts from 2026 to 2045 across the scenarios range from a low of 3,600 job-year losses annually to 4,700 job-year gains, both around only 0.1% of the baseline average annual employment in the city over that period. The analysis also indicates that lower-income households are relatively more affected than others by the scenarios. Overall, even in the most negatively impactful case, the economic output and employment effects are quite small when taken in the context of the overall size of the regional economy and the large reduction in GHGs.

economic impact modeling↗