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DOE OSTI2020

Nationwide Energy Saving Potential Evaluation for Office Buildings with Occupant-Based Building Controls

The heating ventilation and air-conditioning (HVAC) system is a major contributor to building energy consumption. This paper aims to quantify the nationwide energy savings potential of implementing the occupancy-based control (OBC) for the HVAC system in typical medium-sized office buildings using a whole building simulation program (i.e., EnergyPlus). First, the medium-sized office from the DOE Commercial Prototype Building Models was modified to have detailed layout and space functions. Then, a statistic-algorithm-based tool was used to generate the dynamic occupancy schedules for various rooms. Next, both a baseline case and two OBC cases were created for the comparison based on the updated ASHRAE Standard 90.1 and ASHRAE Guideline 36. The HVAC operation in the baseline case follows a static occupancy schedule and fixed setpoint schedules for both room air temperatures and minimal system outside air flowrates, while the proposed OBC cases use the room temperature reset, system minimum outdoor airflow reset, and zone minimal supply airflow rate reset. These cases were extended to five climate zones in the United States to further quantify the energy savings potential associated with the OBC on a nationwide scale. The preliminary result of this case study shows that there could be significant energy savings potential from the proposed OBC strategies in medium-sized office buildings in the United States.

Pang, Zhihong↗

DOE OSTI2026

Multi-Agent Control Planes for Quantum Networks: A Scalable Architecture for Autonomous Quantum Internet Management

Quantum networks are expected to enable distributed quantum computing, secure communication, and global entanglement distribution. However, operating such networks presents significant challenges, including stochastic quantum processes, fragile entanglement resources, dynamic topology, and cross-layer control requirements. Current quantum network control architectures largely rely on centralized or hierarchical controllers inspired by classical software-defined networking (SDN). While effective for small testbeds, these approaches face scalability, latency, and reliability limitations as quantum networks grow. This paper proposes a multi-agent control plane architecture for quantum networks. In this design, intelligent software agents operate at quantum nodes, repeaters, and orchestration layers, collectively managing entanglement generation, routing, purification, and scheduling. The distributed intelligence of the agent system allows the network to adapt dynamically to quantum hardware variability and environmental noise. We argue that multi-agent systems provide significant advantages over centralized control approaches, including scalability, resilience, local autonomy, and real-time adaptation. The paper discusses architectural design principles, agent coordination mechanisms, and research challenges in deploying multi-agent control planes for the emerging quantum Internet.

Alnajjar, Anees [ORNL] (ORCID:0000000237101601)↗

NASA NTRS2011

Modeling Off-Nominal Recovery in NextGen Terminal-Area Operations

Robust schedule-based arrival management requires efficient recovery from off-nominal situations. This paper presents research on modeling off-nominal situations and plans for recovering from them using TRAC, a route/airspace design, fast-time simulation, and analysis tool for studying NextGen trajectory-based operations. The paper provides an overview of a schedule-based arrival-management concept and supporting controller tools, then describes TRAC implementations of methods for constructing off-nominal scenarios, generating trajectory options to meet scheduling constraints, and automatically producing recovery plans.

Callantine, Todd J.↗

NASA NTRS1993

Nonlinear dynamic simulation of single- and multi-spool core engines

In this paper a new computational method for accurate simulation of the nonlinear dynamic behavior of single- and multi-spool core engines, turbofan engines, and power generation gas turbine engines is presented. In order to perform the simulation, a modularly structured computer code has been developed which includes individual mathematical modules representing various engine components. The generic structure of the code enables the dynamic simulation of arbitrary engine configurations ranging from single-spool thrust generation to multi-spool thrust/power generation engines under adverse dynamic operating conditions. For precise simulation of turbine and compressor components, row-by-row calculation procedures were implemented that account for the specific turbine and compressor cascade and blade geometry and characteristics. The dynamic behavior of the subject engine is calculated by solving a number of systems of partial differential equations, which describe the unsteady behavior of the individual components. In order to ensure the capability, accuracy, robustness, and reliability of the code, comprehensive critical performance assessment and validation tests were performed. As representatives, three different transient cases with single- and multi-spool thrust and power generation engines were simulated. The transient cases range from operating with a prescribed fuel schedule, to extreme load changes, to generator and turbine shut down.

Schobeiri, T.↗

NASA NTRS2013

flexplan: Mission Planning System for the Lunar Reconnaissance Orbiter

flexplan is a mission planning and scheduling (MPS) tool that uses soft algorithms to define mission scheduling rules and constraints. This allows the operator to configure the tool for any mission without the need to modify or recompile code. In addition, flexplan uses an ID system to track every output on the schedule to the input from which it was generated. This allows flexplan to receive feedback as the schedules are executed, and update the status of all activities in a Web-based client. flexplan outputs include various planning reports, stored command loads for the Lunar Reconnaissance Orbiter (LRO), ephemeris loads, and pass scripts for automation.

Barnoy, Assaf↗

DOE OSTI2023

Smart thermostat data-driven U.S. residential occupancy schedules and development of a U.S. residential occupancy schedule simulator

Occupancy schedule is one of the key inputs in Building Energy Modeling (BEM) to reflect the interaction between buildings and occupants. Over the past decades, standardized occupancy schedules, developed mainly by engineering rule-of-thumb, have been widely used in BEM due to its simplicity and lack of real measured occupancy data. However, the BEM community has recognized their association with uncertainty and reliability in simulation results from BEM. This study introduces representative occupancy schedules in the U.S. residential buildings, derived from a large smart thermostat dataset and time-series K-means clustering, and an open-source tool to generate a stochastic residential occupancy schedule. Over 90,000 residential occupancy schedules were estimated from the ecobee Donate Your Data dataset. Then, the representative occupancy schedules were identified through clustering. This study further investigated the impacts of three parameters (day, house type, and state) on residential occupancy schedules. Then, a tool, the Residential Occupancy Schedule Simulator (ROSS), is developed using the representative occupancy schedules derived in this study. Details of this tool are presented in this paper. In conclusion, the derived representative occupancy schedules and the ROSS tool can help improve the energy modeling of residential buildings.

42 ENGINEERING↗

NASA NTRS1980

Scheduler software for tracking and data relay satellite system loading analysis: User manual and programmer guide

A user guide and programmer documentation is provided for a system of PRIME 400 minicomputer programs. The system was designed to support loading analyses on the Tracking Data Relay Satellite System (TDRSS). The system is a scheduler for various types of data relays (including tape recorder dumps and real time relays) from orbiting payloads to the TDRSS. Several model options are available to statistically generate data relay requirements. TDRSS time lines (representing resources available for scheduling) and payload/TDRSS acquisition and loss of sight time lines are input to the scheduler from disk. Tabulated output from the interactive system includes a summary of the scheduler activities over time intervals specified by the user and overall summary of scheduler input and output information. A history file, which records every event generated by the scheduler, is written to disk to allow further scheduling on remaining resources and to provide data for graphic displays or additional statistical analysis.

Craft, R.↗

DOE OSTI2026

Intelligent industrial demand response to increase grid flexibility and reliability: A review

The rapid transition toward renewable energy has introduced challenges in grid stability due to the intermittency of non-dispatchable sources like solar and wind. Industrial Demand Response (IDR) offers a promising, cost-effective solution that adjusts energy consumption patterns to align with supply, increases renewable utilization, and reduces costs. This review provides an updated analysis of IDR, sorting technologies into five categories: energy storage, scheduled energy usage, operational flexibility, on-site generation, and intelligent operations. Energy storage solutions, while requiring little flexibility, often have the longest payback periods. While slightly better, on-site generation also has longer payback periods, ranging from 5 to 20 years or more. Scheduled energy usage, operational flexibility, and intelligent operations allow significant peak reduction at lower capital costs but require greater flexibility. While 15–20 % peak reduction is within the range of all five categories, scheduled energy use and on-site energy generation are shown to have reductions of up to 70–80 % in select scenarios. Combining multiple IDR strategies from these five categories maximizes both financial and operational benefits. Synergistic approaches are shown to enhance grid stability while reducing costs. As the grid evolves, IDR will enable a more flexible, renewable-powered future that will benefit industrial facilities and the broader energy system.

Demand flexibility↗

DOE OSTI2020

Technical note: Deep learning for creating surrogate models of precipitation in Earth system models

Abstract. We investigate techniques for using deep neural networks to produce surrogatemodels for short-term climate forecasts. A convolutional neural network istrained on 97 years of monthly precipitation output from the 1pctCO2 run (theCO 2 concentration increases by 1 % per year) simulated by the second-generation Canadian Earth System Model (CanESM2). The neural network clearly outperforms a persistence forecast anddoes not show substantially degraded performance even when the forecast lengthis extended to 120 months. The model is prone to underpredicting precipitationin areas characterized by intense precipitation events. Scheduled sampling(forcing the model to gradually use its own past predictions rather than groundtruth) is essential for avoiding amplification of early forecasting errors.However, the use of scheduled sampling also necessitates preforecasting(generating forecasts prior to the first forecast date) to obtain adequateperformance for the first few prediction time steps. We document the trainingprocedures and hyperparameter optimization process for researchers who wish toextend the use of neural networks in developing surrogate models.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1995

Scheduling time-critical graphics on multiple processors

This paper describes an algorithm for the scheduling of time-critical rendering and computation tasks on single- and multiple-processor architectures, with minimal pipelining. It was developed to manage scientific visualization scenes consisting of hundreds of objects, each of which can be computed and displayed at thousands of possible resolution levels. The algorithm generates the time-critical schedule using progressive-refinement techniques; it always returns a feasible schedule and, when allowed to run to completion, produces a near-optimal schedule which takes advantage of almost the entire multiple-processor system.

Meyer, Tom W.↗

DOE OSTI2020

Bayesian Structural Time Series for Behind-the-Meter Photovoltaic Disaggregation

Distributed photovoltaic (PV) generation often occurs ``behind the meter": a grid operator can only observe the net load, which is the sum of the gross load and distributed PV generation. This lack of observability poses a challenge to system operation at both bulk level and distribution level. The lack of real-time or near-future disaggregated estimates of gross load and PV generation will lead to over scheduling of energy production and regulation reserves, reliability constraints violations, wear and tear of controller devices, and potentially cascading failures of a system. In this paper we propose the use of a Bayesian Structural Time Series (BSTS) model with local solar irradiance measurements to disaggregate the summed PV generation and gross load signals at a downstream measurement site. BSTSs are a highly expressive model class that blends classic time series models with the powerful Bayesian state space estimation framework. Disaggregation is done probabilistically, which automatically quantifies the uncertainties of the estimated PV generation and gross load consumption. Depending on the data availability in real-time, it can be used to disaggragate PV and gross load at customer site, or can be used at the feeder level. In this paper, we focus on solving the problem at feeder level. We compare the performance of a BSTS model as well as a handful of state-of-the-art methods on a Pecan Street AMI dataset, using the National Solar Radiation Database (NSRDB) to estimate local irradiance.

bayesian structural time series↗

NASA NTRS1991

Optimum-AIV: A planning and scheduling system for spacecraft AIV

A project undertaken for the European Space Agency (ESA) is presented. The project is developing a knowledge based software system for planning and scheduling of activities for spacecraft assembly, integration, and verification (AIV). The system extends into the monitoring of plan execution and the plan repair phase. The objectives are to develop an operational kernel of a planning, scheduling, and plan repair tool, called OPTIMUM-AIV, and to provide facilities which will allow individual projects to customize the kernel to suit its specific needs. The kernel shall consist of a set of software functionalities for assistance in initial specification of the AIV plan, in verification and generation of valid plans and schedules for the AIV activities, and in interactive monitoring and execution problem recovery for the detailed AIV plans. Embedded in OPTIMUM-AIV are external interfaces which allow integration with alternative scheduling systems and project databases. The current status of the OPTIMUM-AIV project, as of Jan. 1991, is that a further analysis of the AIV domain has taken place through interviews with satellite AIV experts, a software requirement document (SRD) for the full operational tool was approved, and an architectural design document (ADD) for the kernel excluding external interfaces is ready for review.

Arentoft, M. M.↗

NASA NTRS2016

Departure Queue Prediction for Strategic and Tactical Surface Scheduler Integration

A departure metering concept to be demonstrated at Charlotte Douglas International Airport (CLT) will integrate strategic and tactical surface scheduling components to enable the respective collaborative decision making and improved efficiency benefits these two methods of scheduling provide. This study analyzes the effect of tactical scheduling on strategic scheduler predictability. Strategic queue predictions and target gate pushback times to achieve a desired queue length are compared between fast time simulations of CLT surface operations with and without tactical scheduling. The use of variable departure rates as a strategic scheduler input was shown to substantially improve queue predictions over static departure rates. With target queue length calibration, the strategic scheduler can be tuned to produce average delays within one minute of the tactical scheduler. However, root mean square differences between strategic and tactical delays were between 12 and 15 minutes due to the different methods the strategic and tactical schedulers use to predict takeoff times and generate gate pushback clearances. This demonstrates how difficult it is for the strategic scheduler to predict tactical scheduler assigned gate delays on an individual flight basis as the tactical scheduler adjusts departure sequence to accommodate arrival interactions. Strategic/tactical scheduler compatibility may be improved by providing more arrival information to the strategic scheduler and stabilizing tactical scheduler changes to runway sequence in response to arrivals.

departure scheduling↗

NASA NTRS1975

Manned orbital systems concept study. Book 4: Programmatics for extended-duration missions

The cost estimates, schedule data, and funding distributions generated in the Manned Orbital Systems Concepts (MOSC) study are presented. The overall objectives were to examine the requirements for, and to describe, a cost-effective concept for an orbital facility capable of supporting manned operations in earth orbit beyond the 7-to-30-day mission duration provided by the Shuttle/Spacelab system. The cost, schedule, and other programmatic data were developed to provide information useful for their long-range planning activities. The major portion of the data documented and discussed consists of project- and system-level schedule and funding information and also project-, system-, and subsystem-level cost summaries.

Source record↗

NASA NTRS1992

End-to-end planning and scheduling systems technology for space operations

Consideration is given to planning and scheduling operations concepts from an end-to-end perspective, through both mission operations and institutional support functions. An operations concept is proposed which is based on a flexible request language used to state resource requirements and mission constraints to a scheduling system. The language has the potential to evolve into an international standard for exchanging service request information on international space networks. The key benefit of the flexible scheduling request concept is the shift of a significant conflict resolution effort from humans to computers, reducing the time for generating a week's worth of schedules to hours instead of days.

Moe, Karen L.↗

NASA NTRS2005

A Strategy for Autogeneration of Space Shuttle Ground Processing Simulation Models for Project Makespan Estimations

Space Shuttle Processing is a complicated and highly variable project. The planning and scheduling problem, categorized as a Resource Constrained - Stochastic Project Scheduling Problem (RC-SPSP), has a great deal of variability in the Orbiter Processing Facility (OPF) process flow from one flight to the next. Simulation Modeling is a useful tool in estimation of the makespan of the overall process. However, simulation requires a model to be developed, which itself is a labor and time consuming effort. With such a dynamic process, often the model would potentially be out of synchronization with the actual process, limiting the applicability of the simulation answers in solving the actual estimation problem. Integration of TEAMS model enabling software with our existing schedule program software is the basis of our solution. This paper explains the approach used to develop an auto-generated simulation model from planning and schedule efforts and available data.

Madden, Michael G.↗

DOE OSTI2021

Analysis of Residential Time-of-Use Utility Rate Structures and Economic Implications for Thermal Energy Storage

Thermal energy storage (TES) is an increasingly popular tool to level out the daily electrical demand and add stability to the electrical grid as more intermittent renewable energy sources are installed. TES systems can locally decouple high thermal loads from the operation of a heat pump or reduce the electrical energy demand of the heat pump by providing a more favorable temperature gradient. In addition, many policy makers and utility providers have introduced time-of-use (TOU) rate schedules for residential customers to better reflect the price of electricity generation and demand for specific times. TOU rate schedules price grid-provided electricity differently throughout the day depending on the region’s climate, time of year, and electrical production. Large differences between on-peak and off-peak electrical prices may create an economic advantage for a residential customer to install a TES system. In this work, the economic and energy savings are calculated for a modeled 2,400 square foot residential building with water/ice-based TES using a TOU rate structure. The weather data is from Fresno County, CA, ASHRAE climate zone 3B, and a representative residential TOU utility rate structure from Pacific Gas and Electric (PG&E) was used. The results showed that total energy consumption could be reduced by 14.5% with an 87.5% reduction in on-peak energy usage when the TES is installed. The cost of operating this system for space cooling was reduced by nearly 20% using the sample utility rate plan.

Sultan, Sara↗

NASA NTRS1998

Development and Preliminary Results of CTAS on Airline Operational Control Center Operations

Continued growth and expansion of air traffic and increased air carrier economic pressures have mandated greater flexibility and collaboration in air traffic management. The ability of airspace users to select their own routes, so called "free-flight", and to more actively manage their fleet operations for maximum economic advantage are receiving great attention. A first step toward greater airspace user and service provider collaboration is information sharing. In this work, arrival scheduling and airspace management data generated by the NASA/FAA Center/TRACON Automation System (CTAS) and used by the FAA service provider is shared with an airline with extensive operations within the CTAS operational domain. The design and development of a specialized airline CTAS "repeater" system is described, as well as some preliminary results of the impact and benefits of this information on the air carrier's operations. FAA controller per aircraft scheduling information, such as that provided by CTAS, has never before been shared in real-time with an airline. Expected airline benefits include improved fleet planning and arrival gate management, more informed "hold-go" decisions, and avoidance of costly aircraft diversions to alternate airports when faced with uncertain airborne arrival delays.

Zelenka, Richard↗