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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

CRITICAL MINERAL RESOURCE ASSESSMENT OF COALS FROM THE POWDER RIVER BASIN, WYOMING, USA

Coal and associated sediments are potential sources of Rare Earth Elements (REE) and other critical minerals necessary for many consumer and defense-related products and development of energy technologies. For this study, 15 samples were sourced from Dry Fork Mine within the Powder River Basin near Gillette, Wyoming, to determine REE content along with select transition metals (t-metals) of interest in non-combusted coals and associated sediments. An excavator collected samples along a mine highwall, within benched intervals representing a foot to a few feet of coal strata. Homogenized sample subsets were crushed in an aluminum-ceramic vial, then passed through a 106-micron sieve. Sieved samples were pyrolyzed by a LECO TGA-108, which concurrently measured sample moisture, volatile, and ash content. Residual ash was then fused into a glass bead with lithium metaborate at a 6:1 Li-metaborate to sample ratio and then dissolved in 20% nitric acid. The nitric acid solutions containing digested beads were then diluted and passed through a 0.45 micron syringe filter. Filtered samples were analyzed by ICP-MS for REE and select t-metals. Reagent blanks were analyzed to assess for any potential contamination. Total REE plus Y (REE+Y) concentrations across the 15 samples range from 52 ppm to 1015 ppm with an average of 477 ppm on a dry ash basis. When normalized to upper continental crust (UCC; Taylor and McLennan, 1985) values, 13 of the 15 samples show average enrichment factors (EF) for REE+Y greater than 1. EF values indicate M-type enrichment (Sm through Er), as opposed to distinct preferential enrichment of light or heavy REE. T-metals with the highest average concentrations are V, Cu, Ni, and Zr at 215, 243, 123, and 118 ppm, respectively. Multiple t-metals had EF>1; however, Cu, Ge, and Sb have the highest average EF relative to UCC for t-metals, at 9.7, 8.0, and 17.0, respectively.

Copeland, Grant↗
DOE OSTI2024

Initial Feasibility Assessment of Agrivoltaics in Jackson County, IL

Consistent with concerns raised in other rural communities, the agricultural community in Jackson County, IL is reluctant to install ground based photovoltaic (PV) systems on prime agricultural land. Agrivoltaic solutions have the potential to mitigate community concerns of conversion of farmland to solar energy by allowing for both energy production and farming practices to occur on the same land area. To assess the potential for agrivoltaics in Jackson County, IL, the Jackson County Coalition requested technical assistance to perform an initial technoeconomic assessment, resource assessment, and feasibility assessment based on the unique agricultural context present in the area. In this paper, the National Renewable Energy Laboratory (NREL) interviewed five Jackson County experts for five key crops (vineyards, strawberries, pumpkins, apple and pear orchards, and hemp) to examine potential for agrivoltaics integration and identify key barriers that could hamper development. NREL performed technoeconomic analysis for different agrivoltaic system designs to determine the economic constraints and opportunities of agrivoltaics development. Overall, there is no one path for agrivoltaics success in Jackson County. Pilot projects can assist in demonstrating agrivoltaic feasibility to stakeholders reluctant to be first adopters. Based on preliminary analyses, agrivoltaic integration with vineyards may prove most feasible as the per acre returns of grapes are comparable with the returns needed to offset higher solar development costs for agrivoltaic systems. In terms of technical specifications of solar, pumpkins and strawberries could be integrated into more traditional solar designs, but there are concerns with shading and pest control. There is no one size fits all solution, and many options may need exploring before a workable solution is found.

14 SOLAR ENERGY↗
NASA NTRS1992

Remote Assessment of Lunar Resource Potential

Assessing the resource potential of the lunar surface requires a well-planned program to determine the chemical and mineralogical composition of the Moon's surface at a range of scales. The exploration program must include remote sensing measurements (from both Earth's surface and lunar orbit), robotic in situ analysis of specific places, and eventually, human field work by trained geologists. Remote sensing data is discussed. Resource assessment requires some idea of what resources will be needed. Studies thus far have concentrated on oxygen and hydrogen production for propellant and life support, He-3 for export as fuel for nuclear fusion reactors, and use of bulk regolith for shielding and construction materials. The measurement requirements for assessing these resources are given and discussed briefly.

Taylor, G. Jeffrey↗
DOE OSTI2023

The importance of capturing power system operational details in resource adequacy assessments

Traditional methods for assessing the resource adequacy (RA) of a power system are becoming obsolete due to emerging trends such as the increasing deployment of variable renewable energy and storage. Consequently, analysts are recommending that RA be assessed using a Monte Carlo simulation approach that models chronological power system operations over many instances of possible operating conditions. However, this approach is necessarily more complex and computationally demanding, which is an obstacle to real-world implementation. Here, in this study, we investigate which operational details of power systems are important to capture in order to accurately evaluate a system's RA, versus details that add complexity but do not meaningfully affect RA results. To do so, we develop a probabilistic RA assessment framework by adapting an existing production cost model and apply it to a case study based on the IEEE Reliability Test System. Our results indicate that multi-year data, storage dispatch, and transmission limits are key details to incorporate. Accurate RA results can be obtained using non-economic dispatch strategies as long as they are coordinated with detailed operational strategies. We also demonstrate how popular expectation-based RA metrics can mask important differences in the characteristics of loss of load events.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2006

Towards Designing an Integrated Earth Observation System for the Provision of Solar Energy Resource and Assessment

The GEOSS strategic plan specifically targets the area of improved energy resource management due to the importance of these to the economic and social viability of every nation of the world. With the world s increasing demand for energy resources, the need for new alternative energy resources grows. This paper overviews a new initiative within the International Energy Agency that addresses needs to better manage and develop solar energy resources worldwide. The goal is to provide the solar energy industry, the electricity sector, governments, and renewable energy organizations and institutions with the most suitable and accurate information of the solar radiation resources at the Earth's surface in easily-accessible formats and understandable quality metrics. The scope of solar resource assessment information includes historic data sets and currently derived data products using satellite imagery and other means. Thus, this new task will address the needs of the solar energy sector while at the same time will serve as a model that satisfies GEOSS objectives and goals.

Stackouse, Paul W., Jr.↗
DOE OSTI2022

Insights into Methodologies and Operational Details of Resource Adequacy Assessment: A Case Study with Application to a Broader Flexibility Framework

Assessing and maintaining resource adequacy (RA) is a core pillar of power systems. However, recent changes in the physical makeup of these systems and the conditions under which these systems must operate have yielded a renewed interest in the methods, metrics, and assumptions that underpin RA assessments. In this paper, we systematically explore a wide range of RA modeling dimensions, including: the objective function and level of operational detail in the underlying model formulation; the quantity (look-ahead) and quality (accuracy) of data that is available for making operational decisions within those models; and the physical configuration of solar photovoltaics (PV) with battery storage hybrid resources. We apply a set of probabilistic RA tools and production cost modeling tools to a realistic test system based loosely on a future Electric Reliability Council of Texas power system dominated by solar PV resources. Under the assumptions of our system and models, we find that multi-stage probabilistic assessments may provide a more robust evaluation of RA by capturing a wider range of operational and system interactions, but this comes at a computational cost of 1-2 orders of magnitude longer run time depending on the specific configuration. In addition, the information on thermal generator availability impacts RA performance by an order of magnitude more than solar resource forecasts, which is driven by the comparatively larger magnitude of thermal outages than solar forecast errors within our test system. Lastly, the flexibility provided by hybrid and other resources can help reduce system load-shedding event frequencies and enable the system to be more robust to inaccurate forecast information, and alternative hybrid inverter sizes can impact RA levels by 1-2 orders of magnitude. Our results point to the importance of a broader flexibility framework to describe the interaction between (1) flexibility "supply" from both physical resource capabilities and operational constraints considered in the modeling, and (2) flexibility "demand" from forecast errors, thermal generator outages, and other sources of uncertainty, as well as their RA impacts. Results are likely sensitive to the system buildout explored; future work could consider additional system configurations and conditions.

ENERGY PLANNING, POLICY, AND ECONOMY,POWER TRANSMI↗
DOE OSTI2024

Dashboard for Marine Energy Site Assessment and Monitoring

The marine energy (ME) industry presently relies upon fragmented site assessment solutions that require high resource expenditure for deployment at each site and do not leverage the wealth of readily available tools and information. A wave energy resource assessment dashboard, currently in development, will substantially improve siting, permitting, operations, and maintenance of ME projects by providing an integrated solution that is a one-stop-shop for a developer’s needs. The Site Energy Assessment and MOnitoring Dashboard (SEAMOD) will be of commercial interest to anyone seeking to deploy an ME project and is easily expandable to include tidal and wind energy site assessments. The integrated dashboard is being developed using state-of-the-art database and cloud computing methods and data-assimilative modeling tools that can be coupled with low-cost, rapidly deployable wave buoys and environmental sensing hardware. The combined software and hardware dashboard will reduce wave energy site characterization and wave climate monitoring costs by more than 60 percent and provide assessments that meet international industry standards. To realize a thriving global ME industry, the physical environment at a potential deployment site must be understood, not only for resource characterization, but also for optimization of device and power conversion performance. SEAMOD directly addresses these needs with a commercially marketable product. SEAMOD is a low-cost solution that provides comprehensive ME resource assessments, baseline environmental monitoring, and offshore characterizations required for successful ME development. The key technical objectives for Phase I were a series of software development goals, which when implemented with monitoring solutions, produced an initial proof-of-concept low-cost wave energy resources dashboard. In Phase II, the development of the prototype SEAMOD continued. The basic framework employed was the development of a revised dashboard and monitoring tool customized for ME applications by focusing on IEC site assessment and method requirements. Development was focused on the integration of full hindcast metocean products to provide hindcast resource characterization and environmental information. The final integrated dashboard provides a low-cost solution that delivers comprehensive, scalable, industry-standard energy resource assessments and offshore characterizations required for successful ME development. The integrated dashboard offers visibility of the most recent site modeling, measurements, and historical data. The application and integration of consensus-based standards for wave energy resource assessment, as determined by the International Electrotechnical Commission (IEC), are crucial for the impact and value of SEAMOD. SEAMOD includes monthly, seasonal, and yearly statistics, as well as the total 30-year record, offering temporal resolution of the IEC parameters to aid potential developers in determining the available wave energy resources in their area of interest.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

GeoRePORT Protocol Volume VI: Resource Size Assessment Tool

GeoRePORT is based on the concept that a geothermal system can be described both in terms of the quality of the geothermal resource as it relates to the potential to extract heat ("Resource Grade") and the progress of research and development over the lifetime of the project ("Project Progress"). Resource grade and project progress are reported for three assessment categories: geologic, technical, and socio-economic. Each category has specific criteria and guidelines for assessing both resource grade and project progress, as outlined in each of the following assessment tools (and associated colors): (1) Geological Assessment Tool (representative colors: reds, oranges, browns); (2) Technical Assessment Tool (representative colors: blues, purples); (3) Socio-Economic Assessment Tool (representative colors: greens, yellows). Additionally, users may need to estimate the project size (often reported in MWe or MWth). The resource size assessment tool (RSAT) is an essential addition to GeoRePORT due to the economic and legal context of geothermal development. In order to utilize a geothermal resource, a competitive Power Purchase Agreement (PPA), or similar, often must be obtained, for which the resource's power capacity must be demonstrated. To determine that a geothermal heat or power project is worthy of development, investors or other funding mechanisms often require information on the anticipated heat and/or power potential of the reservoir. They might also be interested in the certainty of that estimate. However, proving the existence and size of a geothermal resource is comparatively expensive and risky relative to other renewable technologies; it can cost developers 5 to 10 million USD to demonstrate a financially viable geothermal resource (Young et al. 2017). GeoRePORT aims to address this barrier to development by providing a consistent and clear assessment of resource quality and certainty. The RSAT will enable GeoRePORT users to not only qualitatively report on a given a resource, but also to compare standard methodologies for quantitatively estimating a resource size in terms of potential heat and/or power output.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

A Geo-Data Science Method for Assessing Unconventional Rare-Earth Element Resources in Sedimentary Systems

Abstract Rare-earth elements (REEs) supply raw materials that constitute many of our modern critical infrastructure, defense, technology, and electrification needs. Despite REE accumulations occurring in conventional bedrock and ion-adsorption deposits sourced from weathering of igneous rocks, unconventional host materials such as coal and related sedimentary strata have been identified as promising sources of REEs to meet growing demand. To maximize the potential of unconventional resources such as REE-coal systems, new approaches are needed overcome challenges from mineral systems with no known deposits and areas with sparse geochemical data. This article presents a systematic knowledge-data resource assessment method for predicting and identifying REE resource potential and occurrence in these unconventional systems. The method utilizes a geologic and geospatial knowledge-data approach informed and guided by REE accumulation mechanisms to systematically assess and identify areas of higher enrichment. An assessment of the Powder River Basin is presented as a test case to demonstrate the method workflow and results. The key output is a potential enrichment score map reported with varying confidence levels based on the amount of supporting evidence. Results from the test case indicate several locations with promising potential for different types of coal-REE deposits, demonstrating the viability of the method for exploration and assessment of unconventional REE resources. The method is flexible by design and, with sufficient applicable knowledge and data, can be adapted for assessing critical mineral systems in other sedimentary systems as well.

58 GEOSCIENCES↗
NASA NTRSDate not supplied

Novel Approach to Simulating Diagnostic Capabilities in Medical Resource Risk Assessment

Diagnostics represent a key subset of medical resources considered for helping mitigate and control spaceflight medical risk. Historically, when modeling the medical risk domain for spaceflight, diagnostic resources have been handled like any other medical resource used for treatment. That is to say, the resource being unavailable will result in the related condition having suboptimal treatment outcomes. However in the real world, should a diagnostic resource be unavailable, a more analogous effect would be that the condition might be misdiagnosed, and thus inappropriate treatment applied. This talk presents an alternative means of representing diagnostic resources within the Medical Extensible Dynamic Probabilistic Risk Assessment Tool (MEDPRAT) that can simulate the effect both in risk, resource consumption, and competition for resources of a missing or depleted diagnostic. The scenario where a differential diagnosis may not be possible for abdominal conditions that use an ultrasound machine as a diagnostic tool is considered. Two approaches for modeling the effect of not having a diagnostic capability on the medical system are demonstrated. In the “simple” approach, it is assumed that any abdominal condition requiring the ultrasound machine for diagnosis is mis-diagnosed and treated as an appendicitis. This is represented by replacing the treatment for the affected conditions with the treatment for appendicitis, thereby changing the optimized medical set available for treatment for the remainder of the mission. In the “complex” approach, MEDPRAT treatment clusters are utilized to capture and represent overlapping treatment between the misdiagnosed condition and appendicitis. This elicits both the effect that inappropriate treatment is applied, resulting in wasted resource consumption, and that treatment which was truly needed for the misdiagnosed condition was not applied, which reduces the treatment effectiveness. In this talk, results comparing the simple and complex diagnostic capability approach to a baseline where the diagnostic is treated as a traditional resource is presented. Either approach provides an option for a more analogous representation of diagnostic resources and provides insight into how the modeled spaceflight medical resources and outcomes change when that diagnostic is unavailable.

C. M. Gasiewski↗
DOE OSTI2023

A Guide for Improved Resource Adequacy Assessments in Evolving Power Systems: Institutional and Technical Dimensions

This paper identifies and evaluates issues in traditional resource adequacy (RA) assessment practices, and how adjusting these practices may affect and depend on existing institutional arrangements for planning and procurement. The paper proposes a technical-institutional roadmap that would allow regulators in vertically-integrated jurisdictions and system planners and operators in restructured jurisdictions to revise RA practices across a range of components. First, we compile a critical review of current RA assessment practices based on (1) interviews with RA practitioners and (2) a review of recent technical literature. We find that (i) RA may need to expand beyond capacity adequacy to ensure energy adequacy – relevant for energy-limited resources such as storage – and potentially some form of ancillary service adequacy (e.g. enough ramping-up and ramping-down capability in the system); (ii) chronological hourly simulations for all hours in the year are the current best practice; (iii) metrics and models used do not reflect economic criteria in system operation and loss of load; and (iv) there is a need to improve representation of weather dependencies and weather data. Second, we review planning and RA reports for several private and public entities that plan generation and/or transmission infrastructure in the continental U.S. to look for existing practices involving resilience assessments. We find no systematic treatment of the costs of extreme weather and other hazards, the benefits of resilience, and resilience metrics in planning analyses and no systematic treatment of resilience metrics, methods, and outcomes for resource adequacy purposes. Third, we create a technical framework for probabilistic RA assessment and use it to study how key choices about how to model power system operations affect the values that are obtained for RA metrics. We find that (i) non-economic dispatch schemes that ignore economic objectives can lead to accurate RA assessments when coordinated with detailed operational strategies; (ii) multi-year data is critical to capture a wide variety of system conditions; (iii) not incorporating transmission limits into RA assessment could lead to substantial underestimation of traditional “expected value” RA metrics; and (iv) new RA metrics that capture event-specific shortfall characteristics should be used as supplements to traditional metrics. Finally, we examine RA assessments and use this information to propose a guide of evolving industry standards for resource adequacy assessments in resource planning and transmission planning. We report minimum, best, and frontier practices for temporal resolution of assessments, metrics and targets, weather data, load forecasting, characterization of variable renewable resources, characterization of transmission and market transactions, RA modeling and integration with planning processes, and capacity accreditation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Assessing the Resource Adequacy and Community Impacts of an Evolving Grid: Considerations for State Regulators

As U.S. power systems continue to decarbonize, state regulators must be able to broadly assess the cost and reliability implications of proposed fossil retirements and the corresponding resources that are coming online to replace them. Specifically, regulators must evaluate whether proposed infrastructure investments are sufficient to ensure the long-term reliability of the system, while also protecting rate payers by ensuring that such investments are necessary and not excessive. Broadly speaking, this objective is typically framed in terms of maintaining long-term resource adequacy at the lowest cost, while also ensuring that other social and/or environmental objectives are satisfied. System planners currently have a host of sophisticated analytical tools at their disposal to evaluate the cost-benefit trade-offs of different approaches to ensuring resource adequacy. However, most of these tools and associated metrics were designed with traditional power systems in mind. Over the past decade, it has become increasingly clear that the metrics and models that have reliably assessed resource adequacy in systems dominated by large thermal and hydropower resources will be insufficient for systems with significant contributions from emerging technologies such as wind, solar and storage. Therefore, in recent years many new metrics and modeling approaches have been developed, and are increasingly being implemented, to meet the needs of the clean energy transition.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

When less is more: How increasing the complexity of machine learning strategies for geothermal energy assessments may not lead toward better estimates

Previous moderate- and high-temperature geothermal resource assessments of the western United States utilized data-driven methods and expert decisions to estimate resource favorability. Although expert decisions can add confidence to the modeling process by ensuring reasonable models are employed, expert decisions also introduce human and, thereby, model bias. This bias can present a source of error that reduces the predictive performance of the models and confidence in the resulting resource estimates. Our study aims to develop robust data-driven methods with the goals of reducing bias and improving predictive ability. We present and compare nine favorability maps for geothermal resources in the western United States using data from the U.S. Geological Survey's 2008 geothermal resource assessment. Two favorability maps are created using the expert decision-dependent methods from the 2008 assessment (i.e., weight-of-evidence and logistic regression). With the same data, we then create six different favorability maps using logistic regression (without underlying expert decisions), XGBoost, and support-vector machines paired with two training strategies. The training strategies are customized to address the inherent challenges of applying machine learning to the geothermal training data, which have no negative examples and severe class imbalance. We also create another favorability map using an artificial neural network. We demonstrate that modern machine learning approaches can improve upon systems built with expert decisions. We also find that XGBoost, a non-linear algorithm, produces greater agreement with the 2008 results than linear logistic regression without expert decisions, because the expert decisions in the 2008 assessment rendered the otherwise linear approaches non-linear despite the fact that the 2008 assessment used only linear methods. The F1 scores for all approaches appear low (F1 score < 0.10), do not improve with increasing model complexity, and, therefore, indicate the fundamental limitations of the input features (i.e., training data). Until improved feature data are incorporated into the assessment process, simple non-linear algorithms (e.g., XGBoost) perform equally well or better than more complex methods (e.g., artificial neural networks) and remain easier to interpret.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Performance of wind assessment datasets in United States coastal areas

The atmospheric dynamics that occur near the intersection of land and water offer exciting and challenging opportunities for wind energy deployment in coastal locations. New models and tools are continually being developed in support of wind resource assessment, and three recent products are explored in this work for their performance in representing characteristics of the wind resource at coastal locations: the Global Wind Atlas 3 (GWA3), the 2023 National Offshore Wind dataset (NOW-23), and the wind climate simulations that are a component of the Wind Integration National Dataset (WIND) Toolkit Long-Term Ensemble Dataset (WTK-LED Climate). These relatively new products are freely available and user-friendly so that anyone – from a utility-scale developer to a resident or business owner – can evaluate the potential for wind energy generation at their location of interest. The validations in this work provide guidance on the accuracy of wind resource assessments for coastal customers interested in installing small or midsize wind turbines (≤ 1 MW in capacity) to support energy needs at the residential, business, or community scale, such as the island and remotely located participants of the U.S. Department of Energy's Energy Transitions Initiative Partnership Project. At 23 coastal locations across the United States, dataset performance varies according to different evaluation metrics. All three recent datasets tend to overestimate the observed coastal wind resource. GWA3 produces the smallest annual average wind speed relative errors, whereas WTK-LED Climate is in best agreement in terms of representing diurnal wind speed cycles. NOW-23 is the highest performing of the datasets for representing seasonal and interannual trends in the coastal wind resource. While GWA3 and WTK-LED Climate are relatively insensitive to the dataset output heights selected for wind resource assessment at small and midsize wind turbine hub heights (20–60 m), significant variation in the NOW-23 representation of wind shear across the wind profile in the lowest 100 m of the atmosphere leads to notable differences in wind speed estimates according to the dataset output heights selected for evaluation. GWA3 exhibits challenges in the representation of observed wind speed diurnal cycles at small and midsize turbine hub heights, likely due to the dataset's consistent treatment of hourly wind speed trends regardless of altitude.

17 WIND ENERGY↗
DOE OSTI2025

A resource adequacy assessment of correlated wide-area outages in the power grid

As the power grid is undergoing rapid transformations, numerous questions are emerging about its vulnerability to wide-area extreme events (WAEE), which could influence its operations. Relatively few analyses have been conducted to date regarding the impact of correlated outages during WAEEs on the grid’s ability to balance resources with demand. This study addresses this gap by conducting a resource adequacy analysis for a hurricane-inspired WAEE on a 2035 synthetic power grid system for the United States. A sensitivity analysis was also conducted to characterize the relative impact of weather on unserved energy. Our results indicate that although the magnitude and duration of the shortfalls vary depending on weather conditions, persistent shortfalls are observed in some regions. Initial explorations indicate a strong correlation between transmission-constrained regions and regions with persistent shortfalls. Future work could generate empirically-grounded representations for generator outages as well as conduct causal analyses of these shortfalls to improve understanding of drivers as well as possible mitigation strategies. Continued exploration of extreme weather impacts on the grid is important to develop more robust understanding of the reliability and resilience of our power systems, especially as they undergo rapid transformations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Electric Grid Reliability in an Era of Unprecedented Uncertainty: A Review of Advances in Electric Sector Resource Adequacy Assessment and Planning

Recent changes to the principal causes of energy shortage events on the electric grid have necessitated are thinking of paradigms for resource adequacy (RA) assessment and the related topic of procurement of a reliable portfolio. Prior studies have laid out elements of a modern paradigm for these planning activities, but there does not exist a comprehensive overview of the topic spanning academic and gray literature, and the relationship of these suggested paradigms to methods used in industry has also not been surveyed. In this paper we review recent literature establishing best practices for RA assessment and reliable portfolio procurement, and survey current practices used in industry in relation to these best practices. We establish seven key best practices for RA assessment, cover a modern methodology for capacity accreditation, and find that industry practices are not far behind the identified best practices, though some key gaps remain. We also present a suggested agenda for both academic research on the topic and opportunities for advancement in the industry.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

The Marine and Hydrokinetic ToolKit for Data Quality Control and Analysis: Preprint

The ability to handle data is critical at all stages of marine energy (ME) development. The marine hydrokinetic toolkit (MHKiT) is an open-source marine energy software, which includes modules for ingesting, applying quality control, processing, visualizing, and managing data. MHKiT-Python and MHKiT-MATLAB provide robust and verified functions that are needed by the ME community to standardize data processing. Calculations and visualizations adhere to International Electrotechnical Commission (IEC) technical specifications and other guidelines. A resource assessment of NDBC buoy 46050 near PACWAVE is performed using MHKiT and discusses comparisons to the resource assessment provided performed by Dunkel et al.

marine energy↗