Understanding Uncertainty in Geothermal Energy Development Using a Formalized Performance Assessment Approach.
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The use of automated classification systems in the field of resource management and resource inventory is discussed. Applications of LANDSAT classification are outlined and include: energy load forecasting based upon land use inventories and change analysis, impact analysis of activities related to energy extraction, capability/suitability mapping in support of generation and substation location and transmission line routing, and assessment of solar energy potential in a highly urbanized setting where land values are high. It is found that the use of LANDSAT data is adequate for general inventories where few data categories are required, where resolution of data to around 150 acres minimum is required, and where no other complete imagery set can be obtained.
A mathematical transform, called the Rosette Transform, together with a new method, called the Dense Sampling Method, have been developed. The Rosette Transform is invented to apply to both the mean part and the fluctuating part of a targeted radar signature using the Dense Sampling Method to construct the data in a high-resolution grid at 1-km posting for wind measurements over water surfaces such as oceans or lakes.
A method, apparatus, system, article of manufacture, and computer readable storage medium provide the ability to measure wind. Data at a first resolution (i.e., low resolution data) is collected by a satellite scatterometer. Thin slices of the data are determined. A collocation of the data slices are determined at each grid cell center to obtain ensembles of collocated data slices. Each ensemble of collocated data slices is decomposed into a mean part and a fluctuating part. The data is reconstructed at a second resolution from the mean part and a residue of the fluctuating part. A wind measurement is determined from the data at the second resolution using a wind model function. A description of the wind measurement is output.
Abstract not provided.
Abstract. Oceanic tides are seldom represented in Earth system models (ESMs) owing to the need for high horizontal resolution to accurately represent the associated barotropic waves close to coasts. This paper presents results of tides implemented in the Model for Prediction Across Scales–Ocean or MPAS-Ocean, which is the ocean component within the U.S. Department of Energy developed Energy Exascale Earth System Model (E3SM). MPAS-Ocean circumvents the limitation of low resolution using unstructured global meshing. We are at this stage simulating the largest semidiurnal (M2, S2, N2) and diurnal (K1, O1) tidal constituents in a single-layer version of MPAS-O. First, we show that the tidal constituents calculated using MPAS-Ocean closely agree with the results of the global tidal prediction model TPXO8 when suitably tuned topographic wave drag and bottom drag coefficients are employed. Thereafter, we present the sensitivity of global tidal evolution due to the presence of Antarctic ice shelf cavities. The effect of ice shelves on the amplitude and phase of tidal constituents are presented. Lower values of complex errors (with respect to TPXO8 results) for the M2 tidal constituents are observed when the ice shelf is added in the simulations, with particularly strong improvement in the Southern Ocean. Our work points towards future research with varying Antarctic ice shelf geometries and sea ice coupling that might lead to better comparison and prediction of tides and thus better prediction of sea-level rise and also the future climate variability.
Technical Interchange Meeting was held at Saft America s Research and Development facility in Cockeysville, Maryland on Sept 28th-29th, 2010. The meeting was attended by Saft, contractors who are developing battery component materials under contracts awarded through a NASA Research Announcement (NRA), and NASA. This briefing presents an overview of the components being developed by the contractor attendees for the NASA s High Energy (HE) and Ultra High Energy (UHE) cells. The transition of the advanced lithium-ion cell development project at NASA from the Exploration Technology Development Program Energy Storage Project to the Enabling Technology Development and Demonstration High Efficiency Space Power Systems Project, changes to deliverable hardware and schedule due to a reduced budget, and our roadmap to develop cells and provide periodic off-ramps for cell technology for demonstrations are discussed. This meeting gave the materials and cell developers the opportunity to discuss the intricacies of their materials and determine strategies to address any particulars of the technology.
This study characterizes navigation conflicts in a region with a large traffic volume along the US Atlantic Coast, utilizing Automated Identification System (AIS) data for 2010. The region includes areas proposed for wind energy development. The characterization could be useful in evaluating the effect of offshore wind areas on navigation conflicts. The study processes the AIS data to provide pairwise comparisons of vessel interactions (encounters and near-misses) as they occurred. Using the vessel encounter data, analyses are made using a ‘blind’ vessel assumption to evaluate the potential for both near-misses and collisions. Then statistical analyses are made to estimate the point values and uncertainty for each type of encounter (crossing, head-on, overtaking). Examination of the frequency/number of collisions from actual observations is made. The examination of actual near-misses, potential near-misses, and potential collisions provides comparable results in the number of near-misses and collisions. The potential near-miss analyses include an examination of the timing of responses made by vessels to prevent near-misses. This informed the statistical analysis but may also have utility in the simulation of navigation conflicts.
The potential use of solar electricity generated from photovoltaic cells is examined for nineteen developing nations. Energy and economic profiles are summarized for each country. A comparison is made between the use of autogeneration and photovoltaics in a rural area of Haiti.
Developing an Energy Service Interface (ESI) specification requires engaging a community of stakeholders including grid operators, Information and Communication Technology implementors, integrators, and finally standards bodies who will define an interface that respects and boundaries of ownership and roles of responsibility in order to activate millions of Distributed Energy Resource for the provision of grid services. By applying Interoperability Maturity Model Criteria and ESI principles to common grid-DER service use cases, the Grid Modernization Lab Consortium team will engage subject matter experts to develop a specification, with an eventual goal of informing development of ESI compliant profiles or standards. The ESI Specification is intended to specify the characteristics, attributes, or qualities that need to be addressed in ESI compliant standards or profiles. This includes addressing interoperability criteria and the service-performance style of the interface.
Once marine energy device developers have a theoretical design in mind, it's time to transform that idea into a commercially ready device. And for that, they can turn to experts at the National Renewable Energy Laboratory (NREL). NREL's marine energy researchers have extensive experience moving technology ideas from prototype manufacturing through laboratory and field validation. The lab's facilities cover five phases of the validation life cycle to ensure marine energy technologies can survive harsh open-water environments. From prototype fabrication to grid integration at all scales, NREL offers end-to-end marine energy device design and validation capabilities.
The National Renewable Energy Laboratory (NREL) is providing scientific and technical services to the Bureau of Ocean Energy Management (BOEM) under an interagency agreement. The purpose of this report is to provide technical assistance in delineating potential lease areas from the California wind energy areas (WEAs) that can be competitively auctioned to wind energy developers. Each wind energy area is presumed to be technically and economically feasible for wind energy development based on the economic cost study performed by NREL in 2020. The subsequent analysis summarized in this report is intended to help BOEM maximize efficient offshore wind energy resource use and ensure fair return to the Government for use of the lease areas, by making recommendations for viable ways to divide the WEAs into auctionable commercial lease areas of approximately equal value. We considered several factors that affect the value of lease areas for wind energy development, including mean wind speeds, water depth, seafloor gradient, seismicity, hard substrate, and access to infrastructure. The largest impact to generating capacity came from the choice of mooring technology and the resulting setback from the lease area boundaries. Based on our setback assumptions, the generating capacity for a wind plant using catenary moorings could be nearly 30% less than with vertical moorings in Humboldt, or approximately 20% less in Morro Bay. The likely range of generating capacity is 1.5 to 3 GW in Humboldt and 3 to 5 GW in Morro Bay.
Buildings contribute 40% of global greenhouse gas emissions; therefore, strategies that can substantially reduce emissions from the building stock are key components of broader efforts to mitigate climate change and achieve sustainable development goals. Models that represent the energy use of the building stock at scale under various scenarios of technology deployment have become essential tools for the development and assessment of such strategies. Within the past decade, the capabilities of building stock energy models have improved considerably, while model transferability and sharing has increased. Given these advancements, a new scheme for classifying building stock energy models is needed to facilitate communication of modeling approaches and the handling of important model dimensions. In this article, we present a new building stock energy model classification framework that leverages international modeling expertise from the participants of the International Energy Agency's Annex 70 on Building Energy Epidemiology. Drawing from existing classification studies, here we propose a multi-layer quadrant scheme that classifies modeling techniques by their design (top-down or bottom-up) and degree of transparency (black-box or white-box); hybrid techniques are also addressed. The quadrant scheme is unique from previous classification approaches in its non-hierarchical organization, coverage of and ability to incorporate emerging modeling techniques, and treatment of additional modeling dimensions. The new classification framework will be complemented by a reporting protocol and online registry of existing models as part of ongoing work in Annex 70 to increase the interpretability and utility of building stock energy models for energy policy making.
Marine Energy is a nascent, but growing industry and will need a strong workforce to be successful. This paper examines the resources and programs needed to achieve the industry's goals.
Developing secure, resilient, and adaptive energy infrastructure that fosters economic growth while reducing environmental impact is among the most pressing challenges—and greatest opportunities—of our time. It will require the next generation of thought leaders to capably and creatively guide this vital energy sector transition. Through a new interdisciplinary graduate program, Colorado School of Mines (Mines) and the National Renewable Energy Laboratory (NREL) are cultivating the rich opportunity landscape needed to develop these future innovators. The Mines/NREL Advanced Energy Systems (AES) degree program prepares researchers at the doctoral level and energy professionals at the master’s level to address the full complexity of tomorrow's infrastructure, economic, and environmental challenges. The combination of a thriving cleantech market in Colorado, world-class resources and researchers at NREL, and rigorous educational and technical programs at Mines create a truly one-of-a-kind opportunity for advancing fields related to energy systems. These links can uniquely equip top-caliber students to become the scientists and engineers at the forefront of our global energy economy transformation.
Development criteria and recommendations for coal feed system selections that include supporting data are presented. Considered are the areas of coal feed coasts, coal feed system reliability, and the interaction of the feed system with the conversion process.
The Renewable Energy (RE) Data Explorer is a user-friendly, geospatial analysis tool for analyzing renewable energy potential and informing decisions. Developed by the National Renewable Energy Laboratory (NREL) and supported by the U.S. Agency for International Development (USAID), RE Data Explorer performs visualization and analysis of renewable energy potential that can be customized for different scenarios. RE Data Explorer can support prospecting, integrated planning, policymaking, and other decision-making activities to accelerate renewable energy deployment. This document provides information on how the RE Data Explorer can support private sector utility-scale renewable energy project development.
This publication details newly created energy storage models developed within the HYBRID Modelica repository as part of the Department of Energy Office of Nuclear Energy (DOE-NE) Integrated Energy Systems (IES) program, led by Idaho National Laboratory (INL). Model development to-date includes creation of dynamic systems-level models of concrete, latent heat, and packed-bed thermocline energy storage technologies for deployment in the IES-based HYBRID repository. Models are developed using the latest publicly available data and incorporate the possibility of control strategy inclusion for use with the existing IES modeling, analysis, and optimization toolset. Simulations showcase the abilities of each technology to cyclically charge and discharge when exposed to time-varying boundary conditions. In addition, low-level surrogate models for some of the thermal energy storage technologies were created using Python. These lower order Python files are much cheaper to run (i.e., computationally faster) and thus operate well when incorporated within the stochastic optimization problems run for the IES program. Moreover, economic data was collected for use within the INL-developed Framework for Optimization of ResourCes and Economics (FORCE). This information is incorporated within the FORCE platform. This work has resulted in creation of systems-level models for concrete, latent heat, and thermocline thermal energy storage systems with associated control systems. Now that these models are available, they can be utilized within different integrated energy park concepts to understand optimal system operation, control, and dispatching. Moreover, given the generic nature of the models, industrial partner technologies (e.g., Storworks Power, EnergyNest) can be quickly added to the repository using the existing models as a basis. Additional dynamic models for thermal energy storage concepts can be developed and added to the HYBRID repository as needed.