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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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The State and Local Planning for Energy (SLOPE) Platform is a tool to enable more data-driven state and local energy planning by integrating dozens of distinct sources of energy efficiency, renewable energy, and (coming in 2020) sustainable transportation data and analyses.
To present a methodology to use pulmonary gas exchange maps to guide functional avoidance treatment planning in radiation therapy (RT) and evaluate its efficacy compared with ventilation-guided treatment planning.
As part of the U.S. Agency for International Development (USAID)-National Renewable Energy Laboratory (NREL) Young Leaders Workforce Training Program in Colombia, the Grupo Energía Bogotá (GEB) participants leveraged their training and professional experience to develop an action plan for modeling and evaluating Bogotá's projected electric vehicle (EV) charging needs to meet future demand. This case study summarizes the collaboration between USAID-NREL, GEB, and the Bogotá Department of Transportation Mobility Secretariat (SDM) to estimate EV charging station needs to meet projected future EV sales in the city of Bogotá and determine high-priority locations within the greater Bogotá metropolitan area for planning and applying EVSE investment and installation.
The increased electrification of buildings across the United States is being driven by technical advancements, cost reductions for some building technologies, consumer preferences, and policy goals for decarbonization. However, the effects of this load growth on the electric distribution system are often only a minor consideration in policymaking and long-term planning studies. The long lead time and useful life of power system equipment means that the decisions taken today are expected to support our society well into the 2060s and beyond. Distribution planning stakeholders can take steps today to establish a grid foundation that captures the new challenges presented by building electrification. This report focuses on building electrification for the residential and commercial sectors, focusing most heavily on space heating, as this end use stands to most strongly impact demand.1 Across all end uses, building electrification could require somewhere between 10% and 70% more electricity generation capacity than exists today depending on technology adoption and energy efficiency.
El Plan de Acción Comunitario de Energía para Pastillo Tibes es una estrategia integral orientada a fortalecer la resiliencia del sistema eléctrico en la comunidad frente a los desafios energéticos. Este documento preliminar enfatiza la importancia de asumir la responsabilidad del plan, además de la inclusión y la adaptabilidad en el proceso de planificación, y está especificamente diseñado para esta comunidad.
Planning, programming, and budgeting system as aid to U.S. government agencies in management planning and decision making
As the severity and frequency of wildfires increase, infrastructure, properties, national parks, animal habitats, and human lives (civilians and firefighters) are put at greater risk. This paper examines the possible application of algorithmic path planning for UAV reconnaissance to reduce damage and safety risks, as aforementioned. When the location of a wildfire is known, UAVs are immediately dispatched from an operating base to fly to the fire and support the firefighters as quickly as possible. Then, the algorithm incrementally analyzes different environmental factors to create a path for the UAV to follow. This work focuses on generating a path for the UAV to follow given a set of polygons representing obstacles. The most important features of this algorithm are its fast response time and obstacle maneuverability. The use of an efficient path planning algorithm could potentially save lives, infrastructure, and acres of forest destruction.
This presentation focuses on several community engagement strategies related to the planning and implementation of clean energy projects, with a focus on collaboration and participatory methods.
Many enterprises invest on drone delivery research and development to drop off packages at consumers’ doorsteps in a matter of minutes. We study delivery drone route planning over a battery swapping network allowing farther reach by penetrating current battery capacity constraints. A mixed-integer nonlinear programming model is created to plan efficient drone routing over the swapping machines by minimizing the delivery lead time. We develop an exact solution method, evaluate its performance, and compare it with a straightforward nonlinear solver application. A case study highlights the applicability of the model. Data and source code to the solver are publicly shared.
As a result of climate change, extreme weather events are occurring more frequently and with increasing impact. This trend poses a significant challenge for distribution utilities and system operators to ensure that there is uninterrupted power supply to critical loads in their networks; thus, the level of proactive preparation of the distribution system to be able to handle severe impacts of extreme weather events represents the system's resilience. One method that distribution system planners can use to prepare for future extreme events is to plan multiple microgrids which can use local generation as much as possible to supply critical loads. But partitioning an existing distribution system such that multiple feasible islands are planned and which are capable of supporting critical loads is still challenging for distribution systems - first, because of the size of the network graph partitioning problem and, second, because of the difficulty in properly formulating the desired attributes of such islands or microgrids. Therefore, this paper presents a genetic algorithm based approach that facilitates incorporating multiple objectives for grid partitioning by formulating two types of problems - node allocation and edge elimination - and it considers multiple topological and resilience-enhancing objectives. The performance of the proposed genetic algorithm-based approach is numerically evaluated on multiple test systems as well as on a real distribution feeder in Colorado, United States.
The dataset consists of results and various input data that are used in the GAMS model for the publication "Repeal of the Clean Power Plan: Social Cost and Distributional Implications". All the data are either excel files or in the .inc format which can be read within GAMS or Notepad. Main data sources include: agriculture, transportation and electricity data. Model details can be found in the paper and the GAMS model package.
Commercialization of carbon capture and storage (CCS) within the SECARB-USA region is scaling up and will continue as governments and private companies expand on current decarbonization efforts. The Inflation Reduction Act (2022) enhanced 45Q tax credits beyond the 2018 Bipartisan Budget Act levels by incentivizing previously uneconomic projects to develop CCS plans and infrastructure. Additionally, the continued interest and support for CCS mitigates the relative risk of commercial-scale projects that are seeking long-term viability to develop capture facilities to accommodate their emissions reduction goals. This multifaceted Commercialization Plan provides an overview of the current status and potential for CCS in the Southeast and the pathways to achieve emissions reduction goals in the region by 2050. Specifically, the study addresses: • The current status of CCS activities in the SECARB region, • Assessment of buildout pathways for CCS projects and carbon transport infrastructure development opportunities, • Estimation of CCS job creation and economic impacts, and • The social justice considerations and public benefits associated with CCS activities in the SECARB-USA region.
Observatory integration and test plan and launch operations plan for Earth Resources Technology Satellite
The Phase C/D definition of the Modular Space Station has been developed. The modular approach selected during the option period was evaluated, requirements were defined, and program definition and preliminary design were accomplished. The Space Station Project is covered in depth, the research applications module is limited to a project-level definition, and the shuttle operations are included for interface requirements identification, scheduling, and costing. Discussed in detail are: (1) baseline program and project descriptions; (2) phase project planning; (3) modular space station program schedule; (4) program management plan; (5) operations; (6) facilities; (7) logistics; and (8) manpower.
The System Trades Study and Design Methodology Plan is used to conduct trade studies to define the combination of Space Shuttle Main Engine features that will optimize candidate engine configurations. This is accomplished by using vehicle sensitivities and engine parametric data to establish engine chamber pressure and area ratio design points for candidate engine configurations. Engineering analyses are to be conducted to refine and optimize the candidate configurations at their design points. The optimized engine data and characteristics are then evaluated and compared against other candidates being considered. The Evaluation Criteria Plan is then used to compare and rank the optimized engine configurations on the basis of cost.
The increasing load density in the LC-39 area of Kennedy Space Center (KSC) can be met by either modifying the existing substation and increasing its capacity or by planning an additional new substation. Evidence that the later approach is more economical, enhances the system reliability, and would produce more satisfactory performance indices is provided. Network theory is the basis for the optimal location determination of the proposed substation. A load reallocation plan which minimizes investment cost and power losses and meets other desirable system features is drafted. The report should be useful to the system designer and can be a useful guideline for future facility planners.
In this paper we describe preliminary work done in the CORTES project, applying the Heuristic Scheduling Testbed System (HSTS) to a transportation planning and scheduling domain. First, we describe in more detail the transportation problems that we are addressing. We then describe the fundamental characteristics of HSTS and we concentrate on the representation of multiple capacity resources. We continue with a more detailed description of the transportation planning problem that we have initially addressed in HSTS and of its solution. Finally we describe future directions for our research.