REopt Lite Tutorial: Financial Outputs
This tutorial explains the financial modeling analysis outputs in the REopt Lite™ web tool.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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REopt Lite Tutorial: Financial Outputs
This tutorial explains the financial modeling analysis outputs in the REopt Lite™ web tool.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
System capacity and economic modeling computer tool for satellite mobile communications systems
A unique computer modeling tool that combines an engineering tool with a financial analysis program is described. The resulting combination yields a flexible economic model that can predict the cost effectiveness of various mobile systems. Cost modeling is necessary in order to ascertain if a given system with a finite satellite resource is capable of supporting itself financially and to determine what services can be supported. Personal computer techniques using Lotus 123 are used for the model in order to provide as universal an application as possible such that the model can be used and modified to fit many situations and conditions. The output of the engineering portion of the model consists of a channel capacity analysis and link calculations for several qualities of service using up to 16 types of earth terminal configurations. The outputs of the financial model are a revenue analysis, an income statement, and a cost model validation section.
Wiedeman, Robert A.↗
RODeO (Revenue Operation and Device Optimization Model) [SWR 20-67]
The Revenue, Operation, and Device Optimization (RODeO) model explores optimal system design and operation considering different levels of grid integration, equipment cost, operating limitations, financing, and credits and incentives. RODeO is a price-taker model formulated as a mixed-integer linear programming (MILP) model in the GAMS modeling platform. The objective is to maximizes the net revenue for a collection of equipment at a given site. The equipment includes generators (e.g., gas turbine, steam turbine, solar, wind, hydro, fuel cells, etc.), storage systems (batteries, pumped hydro, gas-fired compressed air energy storage, long-duration systems, hydrogen), and flexible loads (e.g., electric vehicles, electrolyzers, flexible building loads). The input data required by RODeO can be classified into three bins: 1) utility service data, which refers to retail utility rate information (meter cost, energy and demand charges), 2) electricity market data, which include energy and reserve prices, 3) other inputs, which refer to additional electrical demand, product output demand, technological assumptions, financial properties, and operational parameters.
Guerra Fernandez, Omar Jose↗
Nuclear Integrated Hydrogen Production Analysis Tool
This is an Excel-based time-independent discount cash flow calculator for LWR-HTSE systems. The tool incorporates (1) discounted cash flow and levelized cost of hydrogen (LCOH) analysis, (2) sensitivity analysis with respect to select financial performance metrics with output ‘tornado’ charts, (3) profitability analysis represented by heat maps using the two most sensitive parameters, (4) electricity versus hydrogen production preference analysis by comparing change in net present value (?NPV) between NPP-HTSE and business-as-usual electricity production for the grid, and (5) competitiveness analysis by comparing the calculated LCOH for NPP-HTSE with that of steam methane reforming, which is the conventional process to produce hydrogen.
Cheng, WenChi [Idaho National Laboratory (INL), Id↗
The Geothermal Probabilistic Cost Model with an Application to a Geothermal Reservoir at Heber, California
A financial accounting model that incorporates physical and institutional uncertainties was developed for geothermal projects. Among the uncertainties it can handle are well depth, flow rate, fluid temperature, and permit and construction times. The outputs of the model are cumulative probability distributions of financial measures such as capital cost, levelized cost, and profit. These outputs are well suited for use in an investment decision incorporating risk. The model has the powerful feature that conditional probability distribution can be used to account for correlations among any of the input variables. The model has been applied to a geothermal reservoir at Heber, California, for a 45-MW binary electric plant. Under the assumptions made, the reservoir appears to be economically viable.
Orren, L. H.↗
Market expectations of a warming climate
In this paper, we compare prices of financial derivatives whose payouts are based on future weather outcomes to CMIP5 climate model predictions as well as observed weather station data across eight cities in the US from 2001 through 2020. Derivative prices respond both to short-term weather forecasts for the next two weeks and longer-term warming trends. We show that the long-term trends in derivative prices are comparable to station-level data and climate model output. The one exception is February in the northeastern US, where financial markets price in a polar vortex-induced cooling effect, a recent scientific finding that was not present in the older CMIP5 climate output. When looking at the spatial and temporal heterogeneity in trends, futures prices are more aligned with climate model output than observed weather station trends, suggesting that market participants closely align their expectations with scientific projections rather than recent observations.
54 ENVIRONMENTAL SCIENCES↗
H2A-Lite (Hydrogen Analysis Lite Production Model) [SWR-24-69]
Within H2A-Lite, users can provide a minimal number of inputs—such as hydrogen production technology of choice —to produce estimates about characteristic scale, capital, and operations. Price projections for energy and feedstock are based on the Energy Information Administration's Annual Energy Outlook 2022, AEO2022 Reference case. The model additionally allows users to override technology default values to adapt to specific technology scales or regional energy prices. As output, H2A-Lite provides cost breakdown from rigorous financial analysis as well as greenhouse gas and criteria pollutant emissions characteristics.
Penev, Michael [National Laboratory of the Rockies↗
Pilgrim Hot Springs: GEOPHIRES Inputs and Outputs for Direct-Use Geothermal District Heating and Cooling
This dataset includes files for a techno-economic analysis conducted using the GEOPHIRES simulator to examine the feasibility of expanding a larger district heating site in a remote location: Pilgrim Hot Springs, Alaska. Files included here are GEOPHIRES inputs and outputs for five different scenarios with varying demand, cycle, and system design characteristics to analyze. Also included is the link to the GEOPHIRES GitHub, as well as a link to the dataset that contains the energy modelling used to determine the heating demand for the district. For a list of the differences between scenarios, see the included "Input Overview.txt" file. Fields included in the input files are: subsurface technical parameters, surface technical parameters, financial parameters, capital and O&M parameters, as well as simulation parameters. The output files are case reports that summarize all equipment, reservoir characteristics, costs, and heating profiles.
15 GEOTHERMAL ENERGY↗
Towards an open model intercomparison platform for integrated assessment models scenarios
The majority of scenarios in the IPCC database are generated by integrated assessment models (IAMs) and come from model intercomparison projects. However, the way in which the current model intercomparison projects are organized is not open to all IAM teams worldwide. Here we propose a transparent and inclusive platform that is open to anyone with an IAM regarding protocols development, scenario submissions and results evaluation. We discuss the challenges of this approach, particularly human resources and financial support. Here, we identify diversity in the level of model capability and quality of model output as possibly critical issues. Despite such challenges, the IAM community and its scientific activities can improve and benefit from the proposed platform, ultimately contributing to better climate policymaking.
IAM↗
Cryogenic Carbon Capture™ Technoeconomic Analysis
The Cryogenic Carbon Capture™ (CCC) process significantly decreases cost and energy demands for CO 2 separation and pressurization to 150 bar compared to alternatives. The process is a post-combustion technology that cools CO 2 -laden flue gas to desublimation temperatures (-100 to -135 °C), separates solid CO 2 —that forms from the flue gas—from the light gases, uses the cold products to cool incoming gases in a recuperative heat exchanger, compresses the solid/liquid CO 2 to final pressures (100–200 bar), and delivers a compressed CO 2 stream separated from an atmospheric pressure light-gas stream. The overall energy and economic costs are about 30-50% lower than most competing processes that involve air separation units (ASUs), solvents, or similar technologies. In addition, the CCC process enjoys several ancillary benefits, including (a) it is a minimally invasive Bolton technology, (b) it provides highly efficient removal of most pollutants (Hg, SOx, NO 2 , HCl, etc.), and (c) possible energy storage capacity. This report outlines the process details and economic and energy comparisons relative to other well-documented alternatives. This paper presents the results of a detailed techno-economic comparison of CCC with amine-based systems. The comparison uses identical financial and economic assumptions similar process assumptions as the detailed analyses published by US DOE in the greenfield analysis. Specifically, the comparison assumes power plants that produce the same net output, one equipped with and a second without carbon capture. Separately, the paper compares similar analyses for retrofitting existing systems using typical plant characteristics in the US (initial capital costs have been paid, high plant utilization), though there are no DOE estimates available for direct comparison. Financial and technical assumptions for all comparisons are maintained as close to the DOE reference studies as possible. The results demonstrate about 30-50% lower costs and energy demands for capture from greenfield coal plants. Natural gas plants produce substantially lower CO 2 concentrations which makes the cost of capturing a ton of CO 2 at the same capture rate as the coal plant higher for all processes while the cost of CO 2 capture per unit of power generation is lower. However, CCC maintains about the same absolute energy and cost advantages for NG as for coal compared to amine systems. Finally, the costs of retrofitting a station are compared to those of building a new station with and without capture. The retrofit costs are comparable to (slightly lower than) new plant costs without capture. In all cases operating and capital cost comparisons show that the CCC process can be retrofitted to a variety of plants to cost effectively reduce CO 2 emissions. Further process integration into the upstream processes and unique process features like water recovery, and integrated energy storage bring the effective cost of carbon capture using the CCC process down further and increase its advantages over alternatives. This technoeconomic analysis shows that the CCC process has the potential to the be lowest cost carbon capture technology under development today.
20 FOSSIL-FUELED POWER PLANTS↗
Finding diverse ways to improve algebraic connectivity through multi-start optimization
The algebraic connectivity, also known as the Fiedler value, is a spectral measure of network connectivity that can be increased through edge addition. We present an algorithm for producing many diverse ways to add a fixed number of edges to a network to achieve a near optimal Fiedler value. Previous Fielder value optimization algorithms (i.e. the greedy algorithm) output only one solution. Obtaining a single solution is rarely good enough for real-world network redesign problems, as practical constraints (political, physical or financial) may prevent implementation. Our algorithm takes a multi-start optimization approach, adding a random initial edge and then applies a greedy heuristic to improve the Fiedler value. The random choice moves us to a new region of the search space, enabling discovery of diverse solutions. Additionally, we present a Determinantal Point Process framework for quantifying diversity. We then apply a Markov chain Monte Carlo technique to sift through the large number of output solutions and locate a smaller, more manageable collection of highly diverse solutions that can be presented to network redesign engineers. We demonstrate the effectiveness of our algorithm on real-world graphs with varied structures.
97 MATHEMATICS AND COMPUTING↗
Economic Risk-Informed Maintenance Planning and Asset Management (Final Report)
The proposed work will provide a holistic framework for cost-minimizing risk-informed maintenance planning, including inspection, in light water reactors (LWRs). Specifically, we develop a two-tier framework that (a) coarsely minimizes the total maintenance cost during the remaining normal operating cycle of the plant prior to the next scheduled outage (long-term), subject to safety requirements, and (b) uses the outputs of the first model to develop a secondary optimization model to finely schedule maintenance activities to maximize the financial impact of these activities in the next week (short-term).
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Hydropower and environmental flow management: System-level trade-offs at Glen Canyon Dam
The research focuses on the Colorado River Basin, specifically examining the Glen Canyon Dam (GCD) and its influence on surrounding aquatic ecosystems. This area is crucial due to its role in hydropower production and its impact on downstream environments, including the Grand Canyon National Park. This study explores the integration of environmental factors into hydro dispatch modeling at GCD to tackle ecological challenges posed by the invasive smallmouth bass (SMB). Utilizing the GTMax SL and SERM models, the research assesses the effects of SMB control experiments on hydropower generation, economic value, and grid stability. The study examines the financial and economic impacts of bypass flows designed to release colder water to prevent SMB spawning, which can significantly reduce hydropower output and increase costs. The research identifies that declining reservoir levels and rising water temperatures in Lake Powell have facilitated SMB spawning, posing a threat to native fish populations like the endangered humpback chub. The findings highlight the importance of adaptive management strategies to balance ecological preservation with hydropower generation amid long-term weather-related challenges. The study underscores the need for comprehensive assessments of flow options to prevent SMB establishment below GCD, considering the broader implications for sediment dynamics and ecological interactions.
Ecological impact assessment↗
The cost of energy from utility-owned solar electric systems. A required revenue methodology for ERDA/EPRI evaluations
This methodology calculates the electric energy busbar cost from a utility-owned solar electric system. This approach is applicable to both publicly- and privately-owned utilities. Busbar cost represents the minimum price per unit of energy consistent with producing system-resultant revenues equal to the sum of system-resultant costs. This equality is expressed in present value terms, where the discount rate used reflects the rate of return required on invested capital. Major input variables describe the output capabilities and capital cost of the energy system, the cash flows required for system operation amd maintenance, and the financial structure and tax environment of the utility.
Source record↗
FECM/NETL Unconventional Shale Well Economic Model (UShWEM)
FECM/NETL Unconventional Shale Well Economic Model (UShWEM) is an Excel-based model that evaluates the economics of an unconventional shale well on a per-well and per-pad basis. The model calculates the net cash flow, internal rate of return (IRR), net present value (NPV), earnings before interest, taxes, depreciation, and amortization (EBITDA), payout month and year, and breakeven price (for either oil- or gas-wells). The model can be used to estimate the economics of a well or pad over its lifetime (development through site reclamation) based on (1) the capital and operating costs associated with well/pad development and operations, (2) the revenue associated with oil, gas, and condensate production streams, and (3) accounting for relevant tax policies and asset depreciation applicable for oil and gas operations. The main input for the model is the completion design and production data. Key financial considerations in the model include oil, gas, and condensate market prices, tax-related settings, royalty rates, the discount rate, minimum economic hurdle (IRR) [if performing break-even analysis], and project contingency. The financial consideration can be adjusted to reflect the level of granularity the user requires as input when calculating the economics for a well or pad development. In addition, the model affords users the option to provide their user inputs for all cost categories considered. As a result, the model can be used to generate a multitude of scenario cases for sensitivity analysis of the various financial considerations, as well as production and cost profiles. To make this seamless, the model has the capability for key economic outputs to be exported in large batches through macros-enabled functions on its “Model Output Summary” and “Multi-Well Cost Analysis. The spreadsheet model includes macros and user-defined functions, so the user must enable Excel’s macro capability for the model to function correctly.
Sheriff, Alana↗
Enhancing the EVI-X National Framework to Address Emerging Questions on Charging Infrastructure Deployment
As large national investments in EV charging continue to be made, this project seeks to improve the state-of-the-art in EV infrastructure analysis. New and improved quantitative analysis capabilities will position VTO to support EERE Leadership, assist the DOT/DOE Joint Office through timely analysis, and provide a strategy for the deployment of the national charging network. This project supports on-going development of NREL's EVI-X Suite of charging infrastructure analysis tools, including tools supporting large-scale network planning, local site design decisions, and comprehensive financial analysis. EVI-X development complements and leverages other VTO-funded efforts to ensure inputs to EVI-X and output produced by EVI-X are consistent with and well-integrated into the VTO portfolio (e.g., EV adoption scenarios from TEMPO, charging infrastructure design provided to EVs@Scale, etc.).
ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
Storage Enabled Flexibility of Conventional Generation Assets (StorFlex)
The power systems have faced progressively more demanding operational requirements over the last two decades. Several factors contribute to these challenging operating conditions, including load growth, aging infrastructure, increasing penetrations of distributed energy resources (DERs), electrification of the economy, and policy initiatives such as decarbonization. The power system and its components must provide high operational flexibility to mitigate these challenges. For example, the proliferation of intermittent DERs such as wind and solar has increased the need for conventional generation assets like hydropower plants to respond to sudden load-generation imbalances. The higher flexibility requirements for hydropower plants cause more wear and tear, potentially shortening the useful lifespan of hydropower turbines. To reduce the need for hydropower plants to follow sudden changes in the dispatch signal, we investigate their combined operation with the energy storage systems (ESSs; “ESS-based hybridization”). Our analyses focuses on improving the lifespan of hydropower plants through ESS-based hybridization. Wear and tear on hydropower turbines (particularly Francis turbines) is modeled using a loss-of-life concept that is based on damage experienced by the turbine due to various cycles of operation. Then, we show that using ESSs to offset some of the high variation increases the remaining life of the hydropower plants. To demonstrate this, a few modeling tools were developed for this work: (1) a dynamic model for various components of the turbine and its governor; (2) a control strategy that assigns a slow-varying dispatch signal to a hydropower unit versus a fastmoving signal to ESS, such that the overall power request remains the same; and (3) models for the financial analysis to quantify the economic merits of such a framework. We used the models we developed to analyze the dispatch pattern of an actual hydropower plant with a power output of 50 MW and a head height of 152 m. This work showed that ESS-based hybridization could extend the life of the hydropower plant by 5% on average. This extension in life was then used to estimate the economic benefit in terms of cost deferrals associated with hydropower plant maintenance and replacement: on average, $3.6 million. Sensitivity analysis with respect to the size of ESS and cost of turbines was performed to show the variation in benefits over the range of turbine costs and ESS sizes. Crucially, stacking damage reduction and lifetime extension with other ESS value streams such as providing ancillary services could substantially increase the financial benefits of ESS-based hybridization. The higher costs associated with ESS of appropriate size would make more financial sense when multiple value streams are stacked and co-optimized to extract the maximum benefit. This dimension will be explored in future work.
13 HYDRO ENERGY↗