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At least 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Battery Degradation Modeling in Hybrid Power Plants: An Island System Unit Commitment Study: Preprint

As hybrid power plants (HPPs), such as photovoltaic (PV) and battery combinations, become increasingly important in power systems with high renewable energy penetration to address PV variability and ensure grid stability. This paper focuses on the urgent need to model the coordination between PV and battery systems in HPPs while accounting for battery degradation. We present a generation scheduling model that explicitly incorporates PV-battery hybridization in the unit commitment problem. Moreover, the cost function of the HPP scheduling problem endogenously considers battery degradation with adjustable weights to strike a balance between minimizing production costs and prolonging battery life, particularly when providing energy arbitrage and ancillary services. Using a realistic island system simulation, we demonstrate that accounting for battery degradation in the scheduling problem can significantly extend battery life with only minor additional production costs.

battery degradation↗
DOE OSTI2021

SMC 2021 : Analyzing Resource Utilization and User Behavior on Titan Supercomputer

Resource utilization statistics of submitted jobs on a supercomputer can help us understand how users from various scientific domains use HPC platforms and better design a job scheduler. We explore to generate insight regarding workload distribution and usage pattern domains from job scheduler trace, GPU failure information, and project-specific information collected from Titan supercomputer. Furthermore, we want to know how the scheduler performance varies over time and how the users' scheduling behavior changes following a system failure. These observations have the potential to provide valuable insight, which is helpful to prepare for system failures. These practices will help us develop and apply novel machine learning algorithms in understanding system behavior, requirement, and better scheduling of HPC systems. There are two datasets, RUR and GPU. RUR: This dataset is the job scheduler traces collected from the Titan supercomputerfrom 01/01/2015 to 07/31/2019 (2015.csv - 2019.csv). These were collected usingResource Utilization Report (RUR), a Cray-developed resource-usage data collectionand reporting system. It contains the usage information of its critical resources (CPU,Memory, GPU, and I/O) of each running job on Titan during that period [2]. ProjectAreas: Every job is associated with a project ID. TheProjectAreas.csvdatasetprovides a mapping of the project ID to its domain science. GPU: There have been some hardware-related issues in the GPUs in Titan that caused some GPUs to fail, sometimes irrecoverably during some job runs. This dataset provides information regarding these failures during the execution of the submitted jobs. GPUs on Titan are uniquely identified by a serial number (SN), and they are installed in a location. A GPU can be installed in a location, then removed from that location following a failure, and then re-installed in a different location after fixing the problem. If the failure can't be recovered, the GPU might be removed entirely from Titan. There are two prominent types of failures that resulted in the removal of GPUs from Titan: Double Bit Error (DBE) and Out of the Bus (OTB). The dataset (gc_full.csv) has the following fields: 1. SN : Serial number of a GPU 2. location : The location where it is installed 3. insert : The time when it was inserted into that location 4. remove : The time when it was removed from that location 5. duration : Amount of time the GPU spent in this location 6. out : If the device was taken out entirely w/o a re-installment into a new location. 7. event : If the GPU was taken out entirely, the reason for its removal. To learn more about this dataset, please refer to the git repositoryhttps://github.com/olcf/TitanGPULifeand the related publication [1]. References [1] George Ostrouchov, Don Maxwell, Rizwan A Ashraf, Christian Engelmann, MallikarjunShankar, and James H Rogers. Gpu lifetimes on titan supercomputer: Survival analysisand reliability. InSC20: International Conference for High Performance Computing,Networking, Storage and Analysis, pages 1-14. IEEE, 2020. [2] Feiyi Wang, Sarp Oral, Satyabrata Sen, and Neena Imam. Learning from five-yearresource-utilization data of titan system. In2019 IEEE International Conference onCluster Computing (CLUSTER), pages 1-6. IEEE, 2019.

42 ENGINEERING↗
DOE OSTI2021

SMC 2021 Data Challenge: Analyzing Resource Utilization and User Behavior on Titan Supercomputer

Resource utilization statistics of submitted jobs on a supercomputer can help us understand how users from various scientific domains use HPC platforms and better design a job scheduler. We explore to generate insight regarding workload distribution and usage pattern domains from job scheduler trace, GPU failure information, and project-specific information collected from Titan supercomputer. Furthermore, we want to know how the scheduler performance varies over time and how the users' scheduling behavior changes following a system failure. These observations have the potential to provide valuable insight, which is helpful to prepare for system failures. These practices will help us develop and apply novel machine learning algorithms in understanding system behavior, requirement, and better scheduling of HPC systems. There are two datasets, RUR and GPU: RUR dataset is the job scheduler traces collected from the Titan supercomputer from 01/01/2015 to 07/31/2019 (2015.csv - 2019.csv). These were collected using resource Utilization Report (RUR), a Cray-developed resource-usage data collection and reporting system. It contains the usage information of its critical resources (CPU, Memory, GPU, and I/O) of each running job on Titan during that period (https://ieeexplore.ieee.org/abstract/document/8891001). It includes ProjectAreas as additional information, every job is associated with a project ID. TheProjectAreas.csv dataset provides a mapping of the project ID to its domain science. GPU dataset has information regarding GPU failure on Titan. There have been some hardware-related issues in the GPUs in Titan that caused some GPUs to fail, sometimes irrecoverably during some job runs. This dataset provides information regarding these failures during the execution of the submitted jobs. GPUs on Titan are uniquely identified by a serial number (SN), and they are installed in a location. A GPU can be installed in a location, then removed from that location following a failure, and then re-installed in a different location after fixing the problem. If the failure can't be recovered, the GPU might be removed entirely from Titan. There are two prominent types of failures that resulted in the removal of GPUs from Titan: Double Bit Error (DBE) and Out of the Bus (OTB). The dataset (gc_full.csv) has seven attributes, we provided a short description of these attributes in the ReadMe file. To learn more about this dataset, please refer to the git repository https://github.com/olcf/TitanGPULife and the related publication (https://ieeexplore.ieee.org/abstract/document/9355319).

42 ENGINEERING↗
DOE OSTI2020

Models and Strategies for Optimal Demand Side Management in the Chemical Industries

Deregulation and the increase of renewable electricity generation from wind and solar photovoltaics have transformed the U.S. electricity market. Economic and environmental benefits notwithstanding, the presence of renewables has increased variability and uncertainty on the supply side of the grid. Managing demand, rather than generation – a strategy referred to as “demand response (DR)” – is an attractive approach for mitigating this imbalance. DR efforts aim to reduce electricity usage during peak demand times, lessening stress on the grid. Industrial users are particularly attractive entities for DR participation since they present large, localized loads that can provide significant relief on grid demand and –unlike other large loads, such as buildings – are minimally dependent on human needs and preferences. In this project, we accomplished three main objectives. (1) We developed data-driven low-order DR scheduling-relevant dynamic models of chemical processes. Concurrently, we studied the formulation and solution of the associated optimal DR production scheduling problems. (a) A prototype air separation unit (ASU) model was used to generate simulated operating data for initial modeling efforts, which enabled the later use of industrial data for data-driven modeling. (b) We utilized Hammerstein-Wiener (HW) and Finite Step Response (FSR) models to represent nonlinear plant dynamics. (c) The HW models were linearized using exact linearization so they could potentially be embedded in power system models, which are formulated as mixed integer linear programs (MILPs). (d) We solved DR optimization problems under uncertainty and found that even naïve predictions of electricity price and product demand led to significant cost savings benefits. (2) Our DR scheduling optimization problem formulations are amenable to real-time solution. (a) We utilized Lagrangian Relaxation (LR) to efficiently solve the optimization problem by decoupling subproblems linked by complicating constraints. (b) We have achieved computation times for the 3-day DR scheduling problem of an ASU as low as 1.88 minutes. (3) Our representations of the DR behavior of chemical process as grid-level batteries were embedded in power system models. (a) For a small-scale grid, we found that incorporating the dynamics of the chemical plant in the optimal power flow calculations resulted in better resource management leading to up to 15% and 46% cost reduction for the grid and chemical plant operations, respectively, during periods of power line congestion. We have published several works dedicated to modeling and solving DR optimization problems from the user side. These were published in top peer-reviewed journals and are summarized in this report. The most recent work (and papers in preparation) considers DR scheduling from the grid side. Future efforts will consider networked plants (e.g., air separation units operating on a common pipeline) for DR participation, which is expected to amplify the capabilities of industrial DR participants to perform load-shifting. Our consideration of uncertainty in DR has inspired future directions in this area as well: we plan to develop multistage methods to fully account for the effects of uncertainty in DR scheduling.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1981

Project resource reallocation algorithm

A methodology for adjusting baseline cost estimates according to project schedule changes is described. An algorithm which performs a linear expansion or contraction of the baseline project resource distribution in proportion to the project schedule expansion or contraction is presented. Input to the algorithm consists of the deck of cards (PACE input data) prepared for the baseline project schedule as well as a specification of the nature of the baseline schedule change. Output of the algorithm is a new deck of cards with all work breakdown structure block and element of cost estimates redistributed for the new project schedule. This new deck can be processed through PACE to produce a detailed cost estimate for the new schedule.

Myers, J. E.↗
NASA NTRS1990

Dynamic load-sharing using predicted process resource requirements

Heuristics which use predicted process resource requirements to make scheduling decisions are proposed. Four heuristics are presented. The first two, MINQ and SMPL, employ centralized scheduling and the remaining two, DMINQ and FDMINQ, use distributed scheduling. These heuristics are first compared against random scheduling and then against two conventional heuristics, CENTEX and DISTED, which schedule processes solely based on system state information. Results based on trace-driven simulations show that the proposed centralized heuristics offer significantly improved mean response time and they require fewer status update messages. In experiments using the same status update rates, SMPL response times were, on the average, 22 percent lower than those for CENTEX; MINQ response times were, on the average, 18 percent lower. The simulations also showed that MINQ and SMPL can perform as well as, or better than, CENTEX while using up to 70 percent fewer status update messages. The use of fewer status update messages imposes less overhead on the system. The use of prediction for distributed scheduling produced similar results. When prediction was used to filter small processes and execute them locally a 50 percent improvement in response times was obtained.

Goswami, Kumar K.↗
NASA NTRS1991

Resource representation in COMPASS

A set of viewgraphs on resource representation in COMPASS is given. COMPASS is an incremental, interactive, non-chronological scheduler written in Ada with an X-windows user interface. Beginning with an empty schedule, activities are added to the schedule one at a time, taking into consideration the placement of the activities already on the timeline and the resources that have been reserved for them. The order that the activities are added to the timeline and their location on the timeline are controlled by selection and placement commands invoked by the user. The order that activities are added to the timeline and their location are independent. The COMPASS code library is a cost effective platform for the development of new scheduling applications. It can be effectively used off the shelf for compatible scheduling applications or it can be used as a parts library for the development of custom scheduling systems.

Fox, Barry R.↗
NASA NTRS1991

Operations mission planner beyond the baseline

The scheduling of Space Station Freedom must satisfy four major requirements. It must ensure efficient housekeeping operations, maximize the collection of science, respond to changes in tasking and available resources, and accommodate the above changes in a manner that minimizes disruption of the ongoing operations of the station. While meeting these requirements the scheduler must cope with the complexity, scope, and flexibility of SSF operations. This requires the scheduler to deal with an astronomical number of possible schedules. The Operations Mission Planner (OMP) is centered around minimally disruptive replanning and the use of heuristics limit search in scheduling. OMP has already shown several artificial intelligence based scheduling techniques such as Interleaved Iterative Refinement and Bottleneck Identification using Process Chronologies.

Biefeld, Eric↗
NASA NTRS1992

A practical approach to astronomy mission replanning

The schedule editing concept called EDTRON is presented and its features and functions in the overall mission planning scheme and the experience obtained from its first use during the Astro-1 mission are presented. This EDTRON program was designed specifically to edit the astronomy schedules generated by the ASTAR project, but any schedule with the same on/off format can be successfully changed. Though designed for the real-time environment concept, it can also be employed premission for schedule modification in situations where elements of the baseline schedule need to be preserved or when new requirements emerge that cannot be defined in existing scheduling algorithms.

Guffin, O. T.↗
NASA NTRS1992

Constraint monitoring in TOSCA

The Job-Shop Scheduling Problem (JSSP) deals with the allocation of resources over time to factory operations. Allocations are subject to various constraints (e.g., production precedence relationships, factory capacity constraints, and limits on the allowable number of machine setups) which must be satisfied for a schedule to be valid. The identification of constraint violations and the monitoring of constraint threats plays a vital role in schedule generation in terms of the following: (1) directing the scheduling process; and (2) informing scheduling decisions. This paper describes a general mechanism for identifying constraint violations and monitoring threats to the satisfaction of constraints throughout schedule generation.

Beck, Howard↗
NASA NTRS1995

Real-time design with peer tasks

We introduce a real-time design methodology for large scale, distributed, parallel architecture, real-time systems (LDPARTS), as an alternative to those methods using rate or dead-line monotonic analysis. In our method the fundamental units of prioritization, work items, are domain specific objects with timing requirements (deadlines) found in user's specification. A work item consists of a collection of tasks of equal priority. Current scheduling theories are applied with artifact deadlines introduced by the designer whereas our method schedules work items to meet user's specification deadlines (sometimes called end-to-end deadlines). Our method supports these scheduling properties. Work item scheduling is based on domain specific importance instead of task level urgency and still meets as many user specification deadlines as can be met by scheduling tasks with respect to urgency. Second, the minimum (closest) on-line deadline that can be guaranteed for a work item of highest importance, scheduled at run time, is approximately the inverse of the throughput, measured in work items per second. Third, throughput is not degraded during overload and instead of resorting to task shedding during overload, the designer can specify which work items to shed. We prove these properties in a mathematical model.

Goforth, Andre↗
NASA NTRS1996

Explicit and Implicit Resources: A Simplified Approach to User Requirements Modeling

The International Space Station (ISS) program is dependent on the concept of distributed planning, which places a large responsibility in the hands of the science users. The users assume the responsibility in submitting the operations scheduling requirements in the format required by the scheduling software. The concept of explicit and implicit resources, developed to facilitate the operations scheduling of ISS by non-scheduling experts, is presented. The proposed concepts are defined and examples of scheduling requirements, implemented using explicit and implicit resources, are described together with the requirements modeling and scheduler formatting functions. The software developed to support the implicit and explicit resources concept is discussed.

Hagopian, Jeff↗
NASA NTRS2002

Science Planning for Multi-Spacecraft Coordinated Observations

Fulfilling the promise of an era of great observatories, NASA now has more than three space-based astronomical telescopes operating in different wavebands. This situation provides astronomers with a unique opportunity to simultaneously observe with multiple observatories. Yet scheduling multiple observatories simultaneously is highly inefficient when compared to single observatory observations. Thus, programs using multiple observatories are limited not due to scientific restrictions, but due to operational inefficiencies. Each year, a number of proposals are accepted by a space-based observatory for conduction of astronomical observations and gathering of science data for the study of galactic events. Since each space-based observatory uses a set of instruments designed to operate in specific energy regions, most such studies are conducted by submitting observation proposals to multiple observatories, with requests to coordinate among themselves. To assure that the proposed observations can be scheduled, each observatory's staff has to check that the observations are valid and meet all the constraints for their own observatory; in addition, they have to verify that the observations satisfy the constraints of the other observatories. Thus, coordinated observations require painstaking manual collaboration among the observatory staff at each observatory. In order to exploit new paradigms for observatory operation, the Goddard Space Flight Center's Advanced Architectures and Automation Branch has developed a prototype tool called the Visual Observation Layout Tool (VOLT). The main objective of VOLT is to provide a visual tool to automate the science planning of coordinated observations for multiple spacecraft, as well as to increase the scheduling probability of observations. However, VOLT is also useful for single observatory planning to optimize observatory control. Three space-based missions are interested in using VOLT (the Hubble Space Telescope, the Chandra X-Ray Observatory, and the Far Ultraviolet Spectroscopic Explorer). The VOLT team members have collaborated with these missions to gather requirements and obtain feedback on their mission planning processes. VOLT has been developed as a cross-platform Java client application for use by scientists and observatory science planning staff to visualize scheduling options and constraints. It also supports a lightweight graphical user interface for remote viewing via a Web front end. Additionally, it uniquely supports the ability to interact with multiple, diverse scheduling packages in order to determine windows of opportunity for observations and visually portray the constraints of each observation request. VOLT enables science data capture scenarios which are currently either impossible, or which require extensive time and manpower to coordinate amongst multiple observatories. it supports early detection of planning conflicts by generating coordinated solutions based on observatory schedulability and constraints. The project development approach has included frequent prototype demonstrations to our interested missions to obtain feedback after each release of the software. We will present an overview of our lessons learned in infusing the VOLT tool into the operations of the missions we have collaborated with and a brief demonstration of the software.

Maks, Lori↗
NASA NTRS2002

A System for Planning Ahead

A software system that uses artificial intelligence techniques to help with complex Space Shuttle scheduling at Kennedy Space Center is commercially available. Stottler Henke Associates, Inc.(SHAI), is marketing its automatic scheduling system, the Automated Manifest Planner (AMP), to industries that must plan and project changes many different times before the tasks are executed. The system creates optimal schedules while reducing manpower costs. Using information entered into the system by expert planners, the system automatically makes scheduling decisions based upon resource limitations and other constraints. It provides a constraint authoring system for adding other constraints to the scheduling process as needed. AMP is adaptable to assist with a variety of complex scheduling problems in manufacturing, transportation, business, architecture, and construction. AMP can benefit vehicle assembly plants, batch processing plants, semiconductor manufacturing, printing and textiles, surface and underground mining operations, and maintenance shops. For most of SHAI's commercial sales, the company obtains a service contract to customize AMP to a specific domain and then issues the customer a user license.

Source record↗
NASA NTRS2001

Power Management for Space Advanced Life Support

Space power systems include the power source, storage, and management subsystems. In current crewed spacecraft, solar cells are the power source, batteries provide storage, and the crew performs any required load scheduling. For future crewed planetary surface systems using Advanced Life Support, we assume that plants will be grown to produce much of the crew's food and that nuclear power will be employed. Battery storage is much more costly than nuclear power capacity and so is not likely to be used. We investigate the scheduling of power demands by the crew or automatic control, to reduce the peak power load and the required generating capacity. The peak to average power ratio is a good measure of power use efficiency. We can easily schedule power demands to reduce the peak power from its maximum, but simple scheduling approaches may not find the lowest possible peak to average power ratio. An initial power scheduling example was simple enough for a human to solve, but a more complex example with many intermittent load demands required automatic scheduling. Excess power is a free resource and can be used even for minor benefits.

Jones, Harry↗
NASA NTRS1996

Phase-shifting human circadian rhythms: influence of sleep timing, social contact and light exposure

1. Both the timing of behavioural events (activity, sleep and social interactions) and the environmental light-dark cycle have been reported to contribute to entrainment of human circadian rhythms to the 24 h day. Yet, the relative contribution of those putative behavioural synchronizers to that of light exposure remains unclear. 2. To investigate this, we inverted the schedule of rest, sedentary activity and social contact of thirty-two young men either with or without exposure to bright light. 3. On this inverted schedule, the endogenous component of the core temperature rhythm of subjects who were exposed to bright light showed a significant phase shift, demonstrating that they were adapting to the new schedule. In contrast, the core temperature rhythm of subjects who were not exposed to bright light moved on average 0.2 h later per day and after 10 days had not significantly adapted to the new schedule. 4. The direction of phase shift in the groups exposed to bright light was dependent on the time of bright light exposure, while control subjects drifted to a later hour regardless of the timing of their schedule of sleep timing, social contact and meals. 5. These results support the concept that the light-dark cycle is the most important synchronizer of the human circadian system. They suggest that inversion of the sleep-wake, rest-activity and social contact cycles provides relatively minimal drive for resetting the human circadian pacemaker. 6. These data indicate that interventions designed to phase shift human circadian rhythms for adjustment to time zone changes or altered work schedules should focus on properly timed light exposure.

Non-NASA Center↗
NASA NTRS2005

Nexus: Planning Tomorrow, Today

To prepare for future human space flight programs, the Mission Operations Laboratory (MOL) at the Marshall Space Flight Center (MSFC) has been investigating new planning and scheduling paradigms. To support and prove this investigation, MOL technologists have developed a working prototype of a scheduling system to support the new paradigms. The new planning and scheduling system is called Nexus and has a web site at http://nexus.nasa.gov/. Nexus is based on a comprehensive modeling schema to capture all scheduling requirements typical to human space missions, an incremental scheduling engine tailored to the modeling schema, and remote access (including Personal Data Assistant (PDA) access) to the scheduling system. This paper describes the proposed paradigm shift and the enabling software. It also describes a typical Nexus demonstration which emphasizes how it works, how it enables the paradigm shift, and possible applications. Demonstrations include access to the full functionally of Nexus from a personal computer and access to limited functionally via a PDA. An appendix includes a description and screen shots of the demonstrations.

Jaap, John↗
NASA NTRS2010

Interaction Between Strategic and Local Traffic Flow Controls

The loosely coordinated sets of traffic flow management initiatives that are operationally implemented at the national- and local-levels have the potential to under, over, and inconsistently control flights. This study is designed to explore these interactions through fast-time simulations with an emphasis on identifying inequitable situations in which flights receive multiple uncoordinated delays. Two operationally derived scenarios were considered in which flights arriving into the Dallas/Fort Worth International Airport were first controlled at the national-level, either with a Ground Delay Program or a playbook reroute. These flights were subsequently controlled at the local level. The Traffic Management Advisor assigned them arrival scheduling delays. For the Ground Delay Program scenarios, between 51% and 53% of all arrivals experience both pre-departure delays from the Ground Delay Program and arrival scheduling delays from the Traffic Management Advisor. Of the subset of flights that received multiple delays, between 5.7% and 6.4% of the internal departures were first assigned a pre-departure delay by the Ground Delay Program, followed by a second pre-departure delay as a result of the arrival scheduling. For the playbook reroute scenario, Dallas/Fort Worth International Airport arrivals were first assigned pre-departure reroutes based on the MW_2_DALLAS playbook plan, and were subsequently assigned arrival scheduling delays by the Traffic Management Advisor. Since the airport was operating well below capacity when the playbook reroute was in effect, only 7% of the arrivals were observed to receive both rerouting and arrival scheduling delays. Findings from these initial experiments confirm field observations that Ground Delay Programs operated in conjunction with arrival scheduling can result in inequitable situations in which flights receive multiple uncoordinated delays.

Grabbe, Son↗