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At least 613 records · Page 34

Key Takeaways: Second Cohort of Action Plans for Rapid Power Sector Decarbonization

A collaborative report from the Clean Energy Ministerial (CEM), Lessons Learned for Rapid Decarbonization of Power Sectors, was delivered to energy ministers and presented at the 13th CEM (CEM13) in the United States in September 2022. As a result, Action Plans for power sector decarbonization were developed by the first cohort of countries. The fist cohort included India, Australia, Chile, the European Union, and the United Kingdom. The first cohort's Action Plans were presented at CEM14 in India in July 2023. These Action Plans, supported by the 21st Century Power Partnership and other CEM workstreams via direct technical assistance and capacity building, are intended to focus on select implementation actions given each country's existing power sector goals and activities, and are an opportunity for countries to display leadership in power sector decarbonization. The second set of Action Plans has been developed by Brazil, Canada, the United States, and Uruguay, released at CEM15 in Brazil in October 2024.

21st Century Power Partnership↗

Runway Operations Planning: A Two-Stage Solution Methodology

The airport runway is a scarce resource that must be shared by different runway operations (arrivals, departures and runway crossings). Given the possible sequences of runway events, careful Runway Operations Planning (ROP) is required if runway utilization is to be maximized. Thus, Runway Operations Planning (ROP) is a critical component of airport operations planning in general and surface operations planning in particular. From the perspective of departures, ROP solutions are aircraft departure schedules developed by optimally allocating runway time for departures given the time required for arrivals and crossings. In addition to the obvious objective of maximizing throughput, other objectives, such as guaranteeing fairness and minimizing environmental impact, may be incorporated into the ROP solution subject to constraints introduced by Air Traffic Control (ATC) procedures. Generating optimal runway operations plans was approached in with a 'one-stage' optimization routine that considered all the desired objectives and constraints, and the characteristics of each aircraft (weight class, destination, Air Traffic Control (ATC) constraints) at the same time. Since, however, at any given point in time, there is less uncertainty in the predicted demand for departure resources in terms of weight class than in terms of specific aircraft, the ROP problem can be parsed into two stages. In the context of the Departure Planner (OP) research project, this paper introduces Runway Operations Planning (ROP) as part of the wider Surface Operations Optimization (SOO) and describes a proposed 'two stage' heuristic algorithm for solving the Runway Operations Planning (ROP) problem. Focus is specifically given on including runway crossings in the planning process of runway operations. In the first stage, sequences of departure class slots and runwy crossings slots are generated and ranked based on departure runway throughput under stochastic conditions. In the second stage, the departure class slots are populated with specific flights from the pool of available aircraft, by solving an integer program. Preliminary results from the algorithm implementation on real-world traffic data are included.

Anagnostakis, Ioannis↗

Aggregate modeling of fast-acting demand response and control under real-time pricing

This paper develops and assesses the performance of a short-term demand response (DR) model for utility load control with applications to resource planning and control design. Long term response models tend to underestimate short-term demand response when induced by prices. This has two important consequences. First, planning studies tend to undervalue DR and often overlook its benefits in utility demand management program development. Second, when DR is not overlooked, the open-loop DR control gain estimate may be too low. This can result in overuse of load resources, control instability and excessive price volatility. Our objective is therefore to develop a more accurate and better performing short-term demand response model. We construct the model from first principles about the nature of thermostatic load control and show that the resulting formulation corresponds exactly to the Random Utility Model employed in economics to study consumer choice. The model is tested against empirical data collected from field demonstration projects and is shown to perform better than alternative models commonly used to forecast demand in normal operating conditions. The results suggest that (1) existing utility tariffs appear to be inadequate to incentivize demand response, particularly in the presence of high renewables, and (2) existing load control systems run the risk of becoming unstable if utilities close the loop on real-time prices.

Aggregate Modeling↗

Community Solar Program and Subscription Design

This slide deck provides an overview of community solar program design and subscription models. It introduces and explains the different elements of community solar program and subscription design, and proves proven practices and considerations when designing a community solar program. This slide deck was developed for a continuing education course hosted by the American Public Power Association (APPA).

community solar↗

Climate Adaptation Approaches for Water and Electric Utilities: A compendium of existing strategies in a changing climate

Report analyzes plans developed by water and electric utilities to address the impacts of changes in the climate within their service territories. The analysis identifies the main types of changes that utilities address, such as sea level rise, extreme heat, and compound events such as freezing rain/show and extreme wind events. It then identifies adaptation approaches utilities have proposed or adopted to address the changes that are anticipated in their service territories. The report also identifies the mechanisms utilities (and in some cases the governments which the utilities are part of) use to ensure that energy or environmental equity is increased as a result of the resilience program. In summary, the report provides a compendium of adaptation strategies that can be used by others as they review their own need to increase climate resilience.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

SU-F-T-252: An Investigation of Gamma Knife Frame Definition Error When Using a Pre-Planning Workflow

Purpose: To determine causal factors related to high frame definition error when treating GK patients using a pre-planning workflow. Methods: 160 cases were retrospectively reviewed. All patients received treatment using a pre-planning workflow whereby stereotactic coordinates are determined from a CT scan acquired after framing using a fiducial box. The planning software automatically detects the fiducials and compares their location to expected values based on the rigid design of the fiducial system. Any difference is reported as mean and maximum frame definition error. The manufacturer recommends these values be less than 1.0 mm and 1.5 mm. In this study, frame definition error was analyzed in comparison with a variety of factors including which neurosurgeon/oncologist/physicist was involved with the procedure, number of post used during framing (3 or 4), type of lesion, and which CT scanner was utilized for acquisition. An analysis of variance (ANOVA) approach was used to statistically evaluate the data and determine causal factors related to instances of high frame definition error. Results: Two factors were identified as significant: number of post (p=0.0003) and CT scanner (p=0.0001). Further analysis showed that one of the four scanners was significantly different than the others. This diagnostic scanner was identified as an older model with localization lasers not tightly calibrated. The average value for maximum frame definition error using this scanner was 1.48 mm (4 posts) and 1.75 mm (3 posts). For the other scanners this value was 1.13 mm (4 posts) and 1.40 mm (3 posts). Conclusion: In utilizing a pre-planning workflow the choice of CT scanner matters. Any scanner utilized for GK should undergo routine QA at a level appropriate for radiation oncology. In terms of 3 vs 4 post, it is hypothesized that three posts provide less stability during CT acquisition. This will be tested in future work.

60 APPLIED LIFE SCIENCES↗

Automated ISS Flight Utilities

During my internship at NASA Johnson Space Center, I worked in the Space Radiation Analysis Group (SRAG), where I was tasked with a number of projects focused on the automation of tasks and activities related to the operation of the International Space Station (ISS). As I worked on a number of projects, I have written short sections below to give a description for each, followed by more general remarks on the internship experience. My first project is titled "General Exposure Representation EVADOSE", also known as "GEnEVADOSE". This project involved the design and development of a C++/ ROOT framework focused on radiation exposure for extravehicular activity (EVA) planning for the ISS. The utility helps mission managers plan EVAs by displaying information on the cumulative radiation doses that crew will receive during an EVA as a function of the egress time and duration of the activity. SRAG uses a utility called EVADOSE, employing a model of the space radiation environment in low Earth orbit to predict these doses, as while outside the ISS the astronauts will have less shielding from charged particles such as electrons and protons. However, EVADOSE output is cumbersome to work with, and prior to GEnEVADOSE, querying data and producing graphs of ISS trajectories and cumulative doses versus egress time required manual work in Microsoft Excel. GEnEVADOSE automates all this work, reading in EVADOSE output file(s) along with a plaintext file input by the user providing input parameters. GEnEVADOSE will output a text file containing all the necessary dosimetry for each proposed EVA egress time, for each specified EVADOSE file. It also plots cumulative dose versus egress time and the ISS trajectory, and displays all of this information in an auto-generated presentation made in LaTeX. New features have also been added, such as best-case scenarios (egress times corresponding to the least dose), interpolated curves for trajectories, and the ability to query any time in the EVADES output. As mentioned above, GEnEVADOSE makes extensive use of ROOT version 6, the data analysis framework developed at the European Organization for Nuclear Research (CERN), and the code is written to the C++11 standard (as are the other projects). My second project is the Automated Mission Reference Exposure Utility (AMREU).Unlike GEnEVADOSE, AMREU is a combination of three frameworks written in both Python and C++, also making use of ROOT (and PyROOT). Run as a combination of daily and weekly cron jobs, these macros query the SRAG database system to determine the active ISS missions, and query minute-by-minute radiation dose information from ISS-TEPC (Tissue Equivalent Proportional Counter), one of the radiation detectors onboard the ISS. Using this information, AMREU creates a corrected data set of daily radiation doses, addressing situations where TEPC may be offline or locked up by correcting doses for days with less than 95% live time (the total amount time the instrument acquires data) by averaging the past 7 days. As not all errors may be automatically detectable, AMREU also allows for manual corrections, checking an updated plaintext file each time it runs. With the corrected data, AMREU generates cumulative dose plots for each mission, and uses a Python script to generate a flight note file (.docx format) containing these plots, as well as information sections to be filled in and modified by the space weather environment officers with information specific to the week. AMREU is set up to run without requiring any user input, and it automatically archives old flight notes and information files for missions that are no longer active. My other projects involve cleaning up a large data set from the Charged Particle Directional Spectrometer (CPDS), joining together many different data sets in order to clean up information in SRAG SQL databases, and developing other automated utilities for displaying information on active solar regions, that may be used by the space weather environment officers to monitor solar activity. I consulted my mentor Dr. Ryan Rios and Dr. Kerry Lee for project requirements and added features, and ROOT developer Edmond Offermann for advice on using the ROOT library. I also received advice and feedback from Dr. Janet Barzilla of SRAG, who tested my code. Besides these inputs, I worked independently, writing all of the code by myself. The code for all these projects is documented throughout, and I have attempted to write it in a modular format. Assuming that ROOT is updated accordingly, these codes are also Y2038-compliant (and Y10K-compliant). This allows the code to be easily referenced, modified and possibly repurposed for non-ISS missions in the future, should the necessary inputs exist. These projects have taught me a lot about coding and software design - I have become a much more skilled C++ programmer and ROOT user, and I also learned to code in Python and PyROOT (and its advantages and disadvantages compared to C++/ ROOT). Furthermore, I have learned about space radiation and radiation modeling, topics that greatly interest me as I pursue a degree in physics. Working alongside experimental physicists like Dr. Rios, I have developed a greater understanding and appreciation for experimental science, something I have always leaned towards but to which I lacked significant exposure. My work in SRAG has also given me the invaluable opportunity to witness the work environment for physicists at NASA, and what a career in academia may look like at a government laboratory such as NASA Johnson Space Center. As I continue my studies and look forward to graduate school and a future career, this experience at NASA has given me a meaningful and enjoyable opportunity to put my skills to use and see what my future career path might hold.

Offermann, Jan Tuzlic↗

A Scalable Solution Framework for Stochastic Transmission and Generation Planning Problems. Draft

Current commercial software tools for transmission and generation investment planning have limited stochastic modeling capabilities. Because of this limitation, electric power utilities generally rely on scenario planning heuristics to identify potentially robust and cost effective investment plans for a broad range of system, economic, and policy conditions. Several research studies have shown that stochastic models perform significantly better than deterministic or heuristic approaches, in terms of overall costs. However, there is a lack of practical solution approaches to solve such models. In this paper we propose a scalable decomposition algorithm to solve stochastic transmission and generation planning problems, respectively considering discrete and continuous decision variables for transmission and generation investments. Given stochasticity restricted to loads and wind, solar, and hydro power output, we develop a simple scenario reduction framework based on a clustering algorithm, to yield a more tractable model. The resulting stochastic optimization model is decomposed on a scenario basis and solved using a variant of the Progressive Hedging (PH) algorithm. We perform numerical experiments using a 240-bus network representation of the Western Electricity Coordinating Council in the US. Although convergence of PH to an optimal solution is not guaranteed for mixed-integer linear optimization models, we find that it is possible to obtain solutions with acceptable optimality gaps for practical applications. Our numerical simulations are performed both on a commodity workstation and on a high-performance cluster. The results indicate that large-scale problems can be solved to a high degree of accuracy in at most two hours of wall clock time.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Using LANDSAT to update the Schoharlie County, New York, land cover inventory

A demonstration project to examine the utility of LANDSAT at the county and local government level is discussed. The project deals with the updating of the New York State land use and natural resources maps, valuable planning and development tools utilized by county governments. Both the feasibility of producing these maps and the transferability of them to the county government level are evaluated.

Baumann, P. R.↗

Estimating Reduced Consumption for Dynamic Demand Response

Growing demand is straining our existing electricity generation facilities and requires active participation of the utility and the consumers to achieve energy sustainability. One of the most effective and widely used ways to achieve this goal in the smart grid is demand response (DR), whereby consumers reduce their electricity consumption in response to a request sent from the utility whenever it anticipates a peak in demand. To successfully plan and implement demand response, the utility requires reliable estimate of reduced consumption during DR. This also helps in optimal selection of consumers and curtailment strategies during DR. While much work has been done on predicting normal consumption, reduced consumption prediction is an open problem that is under-studied. In this paper, we introduce and formalize the problem of reduced consumption prediction, and discuss the challenges associated with it. We also describe computational methods that use historical DR data as well as pre-DR conditions to make such predictions. Our experiments are conducted in the real-world setting of a university campus microgrid, and our preliminary results set the foundation for more detailed modeling.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A CIM Based Data Integration Framework for Distribution Utilities

With the proliferation of distributed energy resources and advanced metering, modern electric power distribution systems are data rich and include advanced capabilities for distribution automation. Distribution utilities need applications for planning and operations that can integrate all the available data from the enterprise applications and may incorporate distributed approaches to operate and control. This paper describes a framework for standardizing and integrating the data available at different vendor specific applications in a utility utilizing the Common Information Model (CIM). Theframework incorporates the conversion of these the standardized CIM models into models compatible with GridLAB-D, an open source distribution system simulator, for developing advanced planning and operation strategies.

data integration platform, object-oriented data mo↗

Dosimetric comparison of sector-blocked and non–sector-blocked Gamma Knife Perfexion treatment plans for trigeminal neuralgia

The purpose of this study is to compare the quality of trigeminal neuralgia (TN) treatment plans with and without utilizing sector blocking. Twelve patients with 13 cases of TN were evaluated in this retrospective study. Identical magnetic resonance imaging (MRI) contour sets and prescription doses used in treatments were reused for all plans. Treatment plans were compared on the basis of the amount of dose received by critical structures (i.e., brainstem, ipsilateral temporal lobe, optic chiasm, optic nerves, cochlea) and the estimated total treatment time. The use of sector blocking resulted in a statistically significant decrease in the radiation dose to the brainstem but increased doses to the cerebellum and temporal lobe regions. The magnitude of these differences was small and individual patient anatomy specific. The use of sector blocking also resulted in a statistically significant increase in the treatment time. The magnitude of the change in treatment time was dependent on the number of sectors blocked. Our study suggests some potential benefits, as well as disadvantages, to the use of sector blocking in the treatment of TN. Treatment decision needs to be individualized based on the patient's anatomy and overall condition.

61 RADIATION PROTECTION AND DOSIMETRY↗

The Future of Electricity Resource Planning

Electricity resource planning is the process of identifying longer-term investments to meet electricity reliability requirements and public policy goals at a reasonable cost. Resource planning processes provide a forum for regulators, electric utilities, and electricity industry stakeholders to evaluate the economic, environmental, and social benefits and costs of different investment options. By facilitating a discussion on future goals, challenges and strategies, resource planning processes often play an important role in shaping utility business decisions. Resource planning emerged more than three decades ago in an era of transition, where declining electricity demand and rising costs spurred fundamental changes in electricity industry regulation and structure. Despite significant changes in the industry, resource planning continues to play an important role in supporting investment decision making. Over the next two decades, the electricity industry will again undergo a period of transition, driven by technological change, shifting customer preferences and public policy goals. This transition will bring about a gradual paradigm shift in resource planning, requiring changes in scope, approaches and methods. Even as it changes, resource planning will continue to be a central feature of the electricity industry. Its functions — ensuring the reliability of high voltage (“bulk”) power systems, enabling oversight of regulated utilities and facilitating low-cost compliance with public policy goals — are likely to grow in importance as the electricity industry enters a new period of technological, economic and regulatory change. This report examines the future of electricity resource planning in the context of a changing electricity industry. The report examines emerging issues and evolving practices in five key areas that will shape the future of resource planning: (1) central-scale generation, (2) distributed generation, (3) demand-side resources, (4) transmission and (5) uncertainty and risk management. The analysis draws on a review of recent resource plans for 10 utilities that reflect some of the U.S. electricity industry’s extensive diversity.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

The Waypoint Planning Tool: Real Time Flight Planning for Airborne Science

NASA Earth science research utilizes both spaceborne and airborne real time observations in the planning and operations of its field campaigns. The coordination of air and space components is critical to achieve the goals and objectives and ensure the success of an experiment. Spaceborne imagery provides regular and continual coverage of the Earth and it is a significant component in all NASA field experiments. Real time visible and infrared geostationary images from GOES satellites and multi-spectral data from the many elements of the NASA suite of instruments aboard the TRMM, Terra, Aqua, Aura, and other NASA satellites have become norm. Similarly, the NASA Airborne Science Program draws upon a rich pool of instrumented aircraft. The NASA McDonnell Douglas DC-8, Lockheed P3 Orion, DeHavilland Twin Otter, King Air B200, Gulfstream-III are all staples of a NASA's well-stocked, versatile hangar. A key component in many field campaigns is coordinating the aircraft with satellite overpasses, other airplanes and the constantly evolving, dynamic weather conditions. Given the variables involved, developing a good flight plan that meets the objectives of the field experiment can be a challenging and time consuming task. Planning a research aircraft mission within the context of meeting the science objectives is complex task because it is much more than flying from point A to B. Flight plans typically consist of flying a series of transects or involve dynamic path changes when "chasing" a hurricane or forest fire. These aircraft flight plans are typically designed by the mission scientists then verified and implemented by the navigator or pilot. Flight planning can be an arduous task requiring frequent sanity checks by the flight crew. This requires real time situational awareness of the weather conditions that affect the aircraft track. Scientists at the University of Alabama-Huntsville and the NASA Marshall Space Flight Center developed the Waypoint Planning Tool, an interactive software tool, that enables scientists to develop their own flight plans (also known as waypoints) with point-and-click mouse capabilities on a digital map draped with real time satellite imagery. The Waypoint Planning Tool has further advanced to include satellite orbit predictions and seamlessly interfaces with the Real Time Mission Monitor which tracks the aircraft s position when the planes are flying. This presentation will describe the capabilities and features of the Waypoint Planning Tool highlighting the real time aspect, interactive nature and the resultant benefits to the airborne science community.

He, Yubin↗

Utilization of ERTS-1 data in geological evaluation, regional planning, forest management, and water management in North Carolina

The author has identified the following significant results. ERTS-1 imagery has been evaluated for use in resource planning and management in North Carolina, and found to be useful for general reconnaissance purposes in forestry, geology, and water resources work. It has also been used for studying large-scale transient phenomena such as river plumes and movement of sediment in the sounds. ERTS-1 imagery has been an aid to geologic and land-use mapping. Stereoscopes, projectors of various kinds, and microscopes have proved useful instruments for the kinds of data acquisition needed by resource planners and managers.

Welby, C. W.↗

Technology Assessment and Experimentation Plan

An assessment is given of the critical and enhancing technologies necessary to build the basic personal terminal (BPT), the supplier, and the Network Management Center (NMC). The experimentation plan for testing the Personal Access Satellite System (PASS) utilizing ACTS is detailed. The experiment plan gives a list of candidate experiments and describes the proposed experimental set-up. ACTS will be used in the Microwave Switch Matrix (MSM) mode. The Microwave Switch Matrix - Link Evaluation Terminal (MSM-LET) at the NASA Lewis Research Center will serve as the microwave front-end for the PASS supplier and the NMC. Link budgets are given for both the forward and return links between the supplier and the basic personal terminal. The equipment required for the experiments is identified.

Estabrook, Polly↗