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DOE OSTI2016

ENVIRONMENTAL REVIEWS AND CASE STUDIES: The National Park Service Visual Resource Inventory: Capturing the Historic and Cultural Values of Scenic Views

Several United States (US) federal agencies have developed visual resource inventory (VRI) and management systems that reflect specific agency missions and visual resource management objectives. These programs have varied in the degree to which they incorporate historic and cultural elements and values into the scenic inventory process. The recent nationwide expansion of renewable energy and associated transmission development is causing an increase in visual impacts on both scenic and historic/cultural resources. This increase has highlighted the need for better integration of visual and historic/cultural resource assessment and management activities for land use planning purposes. The US Department of the Interior National Park Service (NPS), in response to concerns arising from potential scenic impacts from renewable energy, electric transmission, and other types of development on lands and waters near NPS units, has developed a VRI process for high-value views both within and outside NPS unit boundaries. The NPS VRI incorporates historic and cultural elements and values into the scenic resource inventory process and provides practical guidance and metrics for successfully integrating historic and cultural concerns into the NPS’s scenic resource conservation efforts. This article describes the NPS VRI process and compares it with the VRI processes of the US Department of the Interior Bureau of Land Management and the US Department of Agriculture Forest Service, with respect to the incorporation of historic and cultural values. The article discusses why a scenic inventory approach that more robustly integrates the historic and cultural values of the landscape is essential for NPS landscapes, and for fulfillment of NPS’s mission. Inventories are underway at many NPS units, and the results indicate that the VRI process can be used successfully to capture important historic and cultural resource information and incorporate that information into the assessment of the scenic values of views within and outside NPS units. Environmental Practice 18: 166–179 (2016)

cultural↗

DOE OSTI2017

An improved global wind resource estimate for integrated assessment models

This study summarizes initial steps to improving the robustness and accuracy of global renewable resource and techno-economic assessments for use in integrated assessment models. We outline a method to construct country-level wind resource supply curves, delineated by resource quality and other parameters. Using mesoscale reanalysis data, we generate estimates for wind quality, both terrestrial and offshore, across the globe. Because not all land or water area is suitable for development, appropriate database layers provide exclusions to reduce the total resource to its technical potential. We expand upon estimates from related studies by: using a globally consistent data source of uniquely detailed wind speed characterizations; assuming a non-constant coefficient of performance for adjusting power curves for altitude; categorizing the distance from resource sites to the electric power grid; and characterizing offshore exclusions on the basis of sea ice concentrations. The product, then, is technical potential by country, classified by resource quality as determined by net capacity factor. Additional classifications dimensions are available, including distance to transmission networks for terrestrial wind and distance to shore and water depth for offshore. We estimate the total global wind generation potential of 560 PWh for terrestrial wind with 90% of resource classified as low-to-mid quality, and 315 PWh for offshore wind with 67% classified as mid-to-high quality. These estimates are based on 3.5 MW composite wind turbines with 90 m hub heights, 0.95 availability, 90% array efficiency, and 5 MW/km 2 deployment density in non-excluded areas. We compare the underlying technical assumption and results with other global assessments.

17 WIND ENERGY↗

DOE OSTI2021

Tidal Stream Energy Resource Characterization in the Salish Sea

Tidal stream energy holds great potential as a renewable energy source in regions of the world where tidal currents are strong and predictable. The tidal stream energy resource of a region is strongly controlled by its tidal wave characteristics, the local bathymetry, and coastal geometric features. The Salish Sea, a large estuary on the Pacific Northwest coast, represents a great tidal stream resource because of its strong tidal currents in many tidal channels. However, the tidal resource in the Salish Sea has not been systematically characterized, primarily because of its large area and complex bathymetry and coastlines. This paper presents a modeling study conducted to characterize the tidal energy resource of the Salish Sea based on a high-resolution three-dimensional tidal hydrodynamic model of the Salish Sea, which was extensively validated using data derived from 10 tidal gauge stations and 132 Acoustic Doppler Current Profiler stations. Model validation results indicated the Salish Sea hydrodynamic model is skillful in simulating tidal wave propagation and velocity distributions in the Salish Sea. Based on model results, a total of 16 tidal channels with strong tidal currents, 9 in the San Juan Islands and Rosario Strait regions and 7 in the Puget Sound, were identified as hotspots for potential tidal energy development. Velocity probability distributions and exceedance curves of cross-channel average velocity magnitudes were calculated at all 16 channels based on the recommendations of the International Electrotechnical Commission Technical Specifications for tidal energy resource characterization. The tidal energy resource at the 16 hotspots was also characterized using power density distributions and kinetic energy fluxes. The ranking of the kinetic energy fluxes suggested that Admiralty Inlet, Rosario Strait, and Middle Channel are the top three hotspot sites in the Salish Sea for tidal stream energy development. The study demonstrated the need for a high-resolution 3-D modeling framework for accurate simulation of tidal currents in large complex estuarine systems, in the context of tidal energy resource characterization.

tidal stream energy, resource characterization, Sa↗

DOE OSTI2016

Resource Sharing Controls Gene Expression Bursting

Episodic gene expression, with periods of high expression separated by periods of no expression, is a pervasive biological phenomenon. This bursty pattern of expression draws from a finite reservoir of expression machinery in a highly time variant way, i.e., requiring no resources most of the time but drawing heavily on them during short intense bursts, that intimately links expression bursting and resource sharing. Yet, most recent investigations have focused on specific molecular mechanisms intrinsic to the bursty behavior of individual genes, while little is known about the interplay between resource sharing and global expression bursting behavior. In this paper, we confine Escherichia coli cell extract in both cell-sized microfluidic chambers and lipid-based vesicles to explore how resource sharing influences expression bursting. Interestingly, expression burst size, but not burst frequency, is highly sensitive to the size of the shared transcription and translation resource pools. The intriguing implication of these results is that expression bursts are more readily amplified than initiated, suggesting that burst formation occurs through positive feedback or cooperativity. When extrapolated to prokaryotic cells, these results suggest that large translational bursts may be correlated with large transcriptional bursts. This correlation is supported by recently reported transcription and translation bursting studies in E. coli. Finally, the results reported here demonstrate a strong intimate link between global expression burst patterns and resource sharing, and they suggest that bursting plays an important role in optimizing the use of limited, shared expression resources.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

An Improved Global Wind Resource Estimate for Integrated Assessment Models: Preprint

This paper summarizes initial steps to improving the robustness and accuracy of global renewable resource and techno-economic assessments for use in integrated assessment models. We outline a method to construct country-level wind resource supply curves, delineated by resource quality and other parameters. Using mesoscale reanalysis data, we generate estimates for wind quality, both terrestrial and offshore, across the globe. Because not all land or water area is suitable for development, appropriate database layers provide exclusions to reduce the total resource to its technical potential. We expand upon estimates from related studies by: using a globally consistent data source of uniquely detailed wind speed characterizations; assuming a non-constant coefficient of performance for adjusting power curves for altitude; categorizing the distance from resource sites to the electric power grid; and characterizing offshore exclusions on the basis of sea ice concentrations. The product, then, is technical potential by country, classified by resource quality as determined by net capacity factor. Additional classifications dimensions are available, including distance to transmission networks for terrestrial wind and distance to shore and water depth for offshore. We estimate the total global wind generation potential of 560 PWh for terrestrial wind with 90% of resource classified as low-to-mid quality, and 315 PWh for offshore wind with 67% classified as mid-to-high quality. These estimates are based on 3.5 MW composite wind turbines with 90 m hub heights, 0.95 availability, 90% array efficiency, and 5 MW/km2 deployment density in non-excluded areas. We compare the underlying technical assumption and results with other global assessments.

17 WIND ENERGY↗

DOE OSTI2020

Impacts of Price Formation Efforts Considering High Renewable Penetration Levels and System Resource Adequacy Targets

Future markets with very high penetrations of renewable energy could have many low- to zero-cost periods, which would reduce energy revenues for the generation fleet. This can impact the ability of resources that are needed for long-term reliability to recover operating and capital costs. This paper explores the impact of an alternative pricing mechanism, relaxed minimum pricing, on revenue sufficiency on existing and future resource mixes, including those with high penetrations of wind and solar. This study evaluates eight scenarios encompassing three different sensitivity categories: (1) one alternative pricing mechanism versus traditional LMP pricing, (2) high versus low renewable penetration levels, and (3) using a resource mix that has been adjusted to a preset resource adequacy target versus one that contains a full set of resources. Results show renewable penetration has a greater impact on pricing and resulting profits than does the adjusted resource mix, the two pricing methods have modest variations in profits, and prices under the higher renewable penetration case were higher than under low renewable penetration. These conclusions are not intended to be direct predictions for future outcomes but rather to lead to additional research on the impacts of pricing on investment incentives and future resource adequacy targets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Dynamic and Responsive Distributed Energy Resource Education Solutions for Building, Fire, and Safety Department Officials (Final Technical Report)

From April 2021 through March 2024, the Interstate Renewable Energy Council (IREC) led a collaborative project to develop a free online clearinghouse of educational resources about solar photovoltaics (PV), energy storage systems (ESS), electric vehicle supply equipment (EVSE), and grid-interactive efficient building (GEB) technologies. Two websites—the Clean Energy Clearinghouse and CleanEnergyTraining.org—housed over 70 educational resources. Over the course of the three-year project, 154,272 unique visitors accessed the learning materials. Learner feedback was overwhelmingly positive. Even through the end of the project, there was sustained demand for education and communication. A primary innovation of the project was to drive multiple complementary audiences to the same place. Building owners, designers, installation contractors and developers, authorities having jurisdiction (AHJs), and fire service personnel all benefit from a shared understanding of clean energy technologies, including safety and code-related requirements. When considering the impact on the target audience, the project team worked with partners and advisors to inform resource creation and delivery in such a way as to address key motivational factors of the target audience and compel each user to seek additional information on the topic and return to the Clean Energy Clearinghouse website as their central location for more information. Resources were intentionally developed to be concise—five to 15 minutes—and accessible, meaning not overly technical. Providing basic information demystified the technologies and invited the professional to explore additional learning opportunities. Awardee and partner collaboration was key to project success. IREC facilitated collaboration among the other Topic 2 awardees, Southface and New Buildings Institute (NBI). The three awardees shared relevant information gained through discovery and validation questionnaires that informed product development and reduced duplication of effort by coordinating the development of complementary, and not competing, educational resources. Inspired by this collaboration, IREC brought on additional partners even in the final year of the project. Five regional energy efficiency organizations were part of the project, which expanded the connection between efficiency and distributed energy resources. We also included resources on the Clearinghouse that were developed through other federally funded projects, such as the Buildings Energy Efficiency Frontiers & Innovation Technologies (BENEFIT) program. The website was developed with the learner in mind, and not solely the funding source. Feedback from stakeholders throughout the project, and especially in its final year, indicated the need for continued education and facilitated communication among stakeholders to further the safe and widespread adoption of clean energy.

14 SOLAR ENERGY↗

NASA NTRS2014

Concepts of Operations for Asteroid Rendezvous Missions Focused on Resources Utilization

Several asteroids are the targets of international robotic space missions currently manifested or in the planning stage. This global interest reflects a need to study these celestial bodies for the scientific information they provide about our solar system, and to better understand how to mitigate the collision threats some of them pose to Earth. Another important objective of these missions is providing assessments of the potential resources that asteroids could provide to future space architectures. In this paper, we examine a series of possible mission operations focused on advancing both our knowledge of the types of asteroids suited for different forms of resource extraction, and the capabilities required to extract those resources for mission enhancing and enabling uses such as radiation protection, propulsion, life support, shelter and manufacturing. An evolutionary development and demonstration approach is recommended within the framework of a larger campaign that prepares for the first landings of humans on Mars. As is the case for terrestrial mining, the development and demonstration approach progresses from resource prospecting (understanding the resource, and mapping the 'ore body'), mining/extraction feasibility and product assessment, pilot operations, to full in-situ resource utilization (ISRU). Opportunities to gather specific knowledge for ISRU via resource prospecting during science missions to asteroids are also examined to maximize the pace of development of needed ISRU capabilities and technologies for deep space missions.

radiation protection↗

NASA NTRS2015

Swamp Works: A New Approach to Develop Space Mining and Resource Extraction Technologies at the National Aeronautics Space Administration (NASA) Kennedy Space Center (KSC)

The first steps for In Situ Resource Utilization (ISRU) on target bodies such as the Moon, Mars and Near Earth Asteroids (NEA), and even comets, involve the same sequence of steps as in the terrestrial mining of resources. First exploration including prospecting must occur, and then the resource must be acquired through excavation methods if it is of value. Subsequently a load, haul and dump sequence of events occurs, followed by processing of the resource in an ISRU plant, to produce useful commodities. While these technologies and related supporting operations are mature in terrestrial applications, they will be different in space since the environment and indigenous materials are different than on Earth. In addition, the equipment must be highly automated, since for the majority of the production cycle time, there will be no humans present to assist or intervene. This space mining equipment must withstand a harsh environment which includes vacuum, radical temperature swing cycles, highly abrasive lofted dust, electrostatic effects, van der Waals forces effects, galactic cosmic radiation, solar particle events, high thermal gradients when spanning sunlight terminators, steep slopes into craters / lava tubes and cryogenic temperatures as low as 40 K in permanently shadowed regions. In addition the equipment must be tele-operated from Earth or a local base where the crew is sheltered. If the tele-operation occurs from Earth then significant communications latency effects mandate the use of autonomous control systems in the mining equipment. While this is an extremely challenging engineering design scenario, it is also an opportunity, since the technologies developed in this endeavor could be used in the next generations of terrestrial mining equipment, in order to mine deeper, safer, more economical and with a higher degree of flexibility. New space technologies could precipitate new mining solutions here on Earth. The NASA KSC Swamp Works is an innovation environment and methodology, with associated laboratories that uses lean development methods and creativity-enhancing processes to invent and develop new solutions for space exploration. This paper will discuss the Swamp Works approach to developing space mining and resource extraction systems and the vision of space development it serves. The ultimate goal of the Swamp Works is to expand human civilization into the solar system via the use of local resources utilization. By mining and using the local resources in situ, it is conceivable that one day the logistics supply train from Earth can be eliminated and Earth independence of a space-based community will be enabled.

Resource Extraction↗

DOE OSTI2017

Ecological Resource Value, Remediation Options, and Impacts: Functional Remediation at Hanford Site - 17226

Governmental agencies, Tribes, regulators, resource trustees and other stakeholders are interested in understanding the risk to the environment from remediation and restoration, particularly at large DOE sites with complex remediation tasks lasting decades. While each remediation project has the usual environmental impact assessment that include risk to eco-receptors, a piece-meal approach to examining the effect of remediation does not provide an overview of remaining tasks that would aid in sequencing these tasks. The Consortium for Risk Evaluation with Stakeholder Participation (CRESP) developed a risk methodology for Hanford Site that included ecological resources between 2014 and 2015. The ecological methodology included a comparison of the value of on-site resources with the eco-region, with state and federal threatened and endangered species, and with rare and unique habitats. Potential remediation options for particular evaluation units were used in conjunction with the resource level values to determine the risk of remediation of ecological resources. The methodology developed for Hanford Site also considered functional remediation (e.g. number of trucks, personnel, heavy equipment), initiating events (e.g. earthquakes, volcanos) and future land use. These factors were combined to rate the risk to ecological resources on a scale of not-discernible to very high. In this paper seven evaluation units (waste sites requiring remediation) were evaluated to explore the efficacy of the methodology to provide useful information on the comparative risk for decommissioning and waste management sites. The evaluation of resource levels was based on prior site information, state and federal data bases, and field investigations. The final determination of a risk rating for each evaluation unit depended upon both quantitative data, field experience, and professional judgement. It provides a method that can be applied to many remediation sites within a large DOE facility such as Hanford, as well as across the DOE complex. This will provide information for sound decision-making with stakeholder participation, and will allow DOE to reassure stakeholders that they are protecting human and ecological health on the Hanford Site. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2026

Quantifying System Strength From Grid-Forming Resources Using Frequency Scan Approach: Preprint

Current industry practices for quantifying the system strength contribution from grid-forming (GFM) resources to ensure stability of power systems dominated by inverter-based resources (IBRs) are primarily based on iterative electromagnetic transient (EMT) time-domain simulation studies. While feasible, these approaches are resource-intensive, lack scalability and intuition, and might not evaluate the system strength contribution over the entire frequency range of interest. This paper introduces a novel, frequency-domain approach to quantify system strength support provided by a GFM resource using frequency scans. The proposed method uses transfer functions from the grid voltage magnitude (V) and phase (?), respectively, to the reactive (Q) and active power (P) output of a GFM resource for quantifying its contribution to system strength. These transfer functions provide a direct measure of the ability of a GFM resource to behave as a stiff voltage source behind a reactance over a specified frequency range, enabling robust quantification of its system strength contribution. The key innovation of this work is the development of a frequency domain system strength metric called the dynamic short-circuit ratio (dSCR) that is suitable for IBR-dominated power systems and is directly related with the familiar short circuit ratio (SCR) metric. The new metric, dSCR, enables the assessment of system strength contributions from both synchronous machines and converter-based GFM resources using a unified benchmark, which is not possible with the traditional SCR metric. The paper also demonstrates how impedance scans could identify if an unstable condition observed during weak grid conditions is a result of the lack active or reactive power support or both. By leveraging the proposed frequency-domain dSCR metric for quantifying system strength contribution from GFM IBRs, the paper demonstrates targeted mitigation strategies for weak grid instabilities without resorting to repeated, time-consuming time-domain simulations. The result is a scalable and efficient approach to remediate stability challenges in power systems with high shares of IBRs and accelerating the integration of GFM technologies for system strength support in power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Valuing wind as a distributed energy resource: A literature review

As more distributed energy resources are deployed on electric grid systems across the world, it is important to identify, characterize, and quantify the value elements of different types of distributed energy resources so that policymakers, developers, and utilities can make informed energy deployment decisions. This paper focuses on the value of wind energy as a distributed energy resource (i.e., “distributed wind”). Because of a lack of distributed wind-specific valuation studies, in this review we document the current state of distributed energy resource valuation, analyze a wide array of distributed energy resource valuation metastudies, and identify several value elements for which we recommend developing more robust and standardized calculation methodologies for their potential inclusion in distributed wind valuation. These value elements are ancillary services and locational, resilience, reliability, and resource diversity benefits. Furthermore, this work lays the foundation for a future comprehensive framework for distributed wind valuation studies.

17 WIND ENERGY↗

DOE OSTI2018

Stochastic Programming Approach for Resource Selection under Demand Uncertainty

Cost-efficient selection and scheduling of a subset of geographically distributed resources to meet the demands of a scientific workflow is a challenging problem. The problem is exacerbated by uncertainties in demand and availability of resources. In this paper, we present a stochastic optimization based framework for robust decision making in the selection of distributed resources over a planning horizon under demand uncertainty. We present a novel two-stage stochastic programming model for resource selection, and implement an L-shaped decomposition algorithm to solve this model. A Sample Average Approximation algorithm is integrated to enable stochastic optimization to solve problems with a large number of scenarios. Using the metric of stochastic solution, we demonstrate up to 30% cost reduction relative to solutions without explicit consideration of demand uncertainty for a 24-month problem. We also demonstrate up to 54% cost reduction relative to a previously developed solution for a 36-month problem. We further argue that the composition of resources selected is superior to solutions computed without explicit consideration of uncertainties. Given the importance of resource selection and scheduling of complex scientific workflows, especially in the context of commercial cloud computing, we believe that our novel stochastic programming framework will benefit many researchers as well as users of distributed computing resources.

scientific workflows, task scheduling, optimizatio↗

DOE OSTI2021

Timing Value of Marine Renewable Energy Resources for Potential Grid Applications

In this paper, the applicability of marine renewable energy for potential grid applications is presented. We show that many of the unique value streams from marine-based electricity generation stem from their inherent temporal characteristics, especially when compared to wind and solar. Specifically, in this work, we evaluate the timing value for three types of marine energy resources - (a) tidal (b) wave and (c) ocean currents. Firstly, through a suite of novel metrics such as resource availability, persistence and versatility, we evaluate the temporal value characteristics of these resources. Secondly, through a more grid-oriented numerical study, we comment on the potential ramifications of those temporal characteristics in context of energy balancing and effective load carrying capability, for one marine-based resource i.e. wave. Subsequently, we further our understanding of the relative advantages which may be leveraged by operating wave-based generation resources in tandem with more established renewable choices, such as solar and wind. Our results indicate that compared to wind and solar, marine energy resources are consistently more available and persistent on an hourly level, throughout an entire year of operation. In addition to this, wave resources are also seen to reduce both the magnitudes and the degree of volatility in balancing requirements within the power system. Our work not only focuses on sites specific to the Unites States (US), but also includes a parallel study for a location in Great Britain (GB). Results are found to be consistent for sites in both the US and GB, implying that the grid benefits discussed in this work could apply to a number of locations globally.

Bhattacharya, Saptarshi↗

DOE OSTI2016

Assessment of high enthalpy geothermal resources and promising areas of Chile

This work aims to assess geothermal power potential in identified high enthalpy geothermal areas in the Chilean Andes, based on reservoir temperature and volume. In addition, we present a set of highly favorable geothermal areas, but without enough data in order to quantify the resource. Information regarding geothermal systems was gathered and ranked to assess Indicated or Inferred resources, depending on the degree of confidence that a resource may exist as indicated by the geoscientific information available to review. Resources were estimated through the USGS Heat in Place method. A Monte Carlo approach is used to quantify variability in boundary conditions. Estimates of total Indicated resource are confined to 3 geothermal systems; Apacheta, El Tatio and Tolhuaca, yielding a total value of 228 ± 154. MWe. The estimates of the total Inferred resources for Chile include 6 geothermal systems and yield a total value of 431 ± 321. MWe. Standard deviation reflects the high variability of reservoir specific parameters for each system. A set of 65 favorable geothermal areas are proposed as the most likely future development targets. Finally, eight of them have initial exploration results that suggest they are highly favorable targets as potential geothermal resources.

58 GEOSCIENCES↗

DOE OSTI2016

A quantitative model of application slow-down in multi-resource shared systems

Scheduling multiple jobs onto a platform enhances system utilization by sharing resources. The benefits from higher resource utilization include reduced cost to construct, operate, and maintain a system, which often include energy consumption. Maximizing these benefits comes at a price-resource contention among jobs increases job completion time. In this study, we analyze slow-downs of jobs due to contention for multiple resources in a system; referred to as dilation factor. We observe that multiple-resource contention creates non-linear dilation factors of jobs. From this observation, we establish a general quantitative model for dilation factors of jobs in multi-resource systems. A job is characterized by a vector-valued loading statistics and dilation factors of a job set are given by a quadratic function of their loading vectors. We demonstrate how to systematically characterize a job, maintain the data structure to calculate the dilation factor (loading matrix), and calculate the dilation factor of each job. We validate the accuracy of the model with multiple processes running on a native Linux server, virtualized servers, and with multiple MapReduce workloads co-scheduled in a cluster. Evaluation with measured data shows that the D-factor model has an error margin of less than 16%. We extended the D-factor model to capture the slow-down of applications when multiple identical resources exist such as multi-core environments and multi-disks environments. Finally, validation results of the extended D-factor model with HPC checkpoint applications on the parallel file systems show that D-factor accurately captures the slow down of concurrent applications in such environments.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

Connecting Restricted, High-Availability, or Low-Latency Resources to a Seamless Global Pool for CMS

The connection of diverse and sometimes non-Grid enabled resource types to the CMS Global Pool, which is based on HTCondor and glideinWMS, has been a major goal of CMS. These resources range in type from a high-availability, low latency facility at CERN for urgent calibration studies, called the CAF, to a local user facility at the Fermilab LPC, allocation-based computing resources at NERSC and SDSC, opportunistic resources provided through the Open Science Grid, commercial clouds, and others, as well as access to opportunistic cycles on the CMS High Level Trigger farm. In addition, we have provided the capability to give priority to local users of beyond WLCG pledged resources at CMS sites. Many of the solutions employed to bring these diverse resource types into the Global Pool have common elements, while some are very specific to a particular project. This paper details some of the strategies and solutions used to access these resources through the Global Pool in a seamless manner.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

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↗