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Results for “Power Generation and Scheduling”

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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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Consumer safety-oriented scheduling of rotating power outages during heat waves

Extreme heat events have widespread effects on power systems, reducing available generation capacity, limiting transmission capabilities, and causing unusual demand patterns on the consumer side. As these combined effects expose bulk transmission systems to potential large-scale blackouts, utilities may be required to schedule and apply rotating outages, by temporarily and alternately disconnecting distribution substations to reduce overload. However, utilities lack mechanisms to inform these events, exacerbating the negative effects of heat waves on affected communities. This paper introduces a novel framework for scheduling rotating outages during heat waves while considering impacts on consumers’ safety. Instead of random sequential load shedding, we propose a methodology to rotate power outages considering a metric that quantifies the indoor overheating risk of groups of consumers during a power outage. The overheating risk is derived from a detailed building simulation using CityBES, where the buildings are modeled based on available data—use type, year built, floor area, number of stories, location—while presence of air conditioning and occupancy are calibrated from smart meter data. Based on the metric, an algorithm to schedule the rotating outages is applied to prioritize feeders for disconnection at each hour according to their overheating risk to meet a utility load reduction target. Applied to two substations and seven feeders in the Portland General Electric territory, the results show that this approach effectively leads to the lowest overheating risk during the resulting outage schedules, with an average 10.1% lower overheating compared to uninformed schedules.

Building thermal simulation↗
NASA NTRS1991

Planning and Resource Management in an Intelligent Automated Power Management System

Power system management is a process of guiding a power system towards the objective of continuous supply of electrical power to a set of loads. Spacecraft power system management requires planning and scheduling, since electrical power is a scarce resource in space. The automation of power system management for future spacecraft has been recognized as an important R&D goal. Several automation technologies have emerged including the use of expert systems for automating human problem solving capabilities such as rule based expert system for fault diagnosis and load scheduling. It is questionable whether current generation expert system technology is applicable for power system management in space. The objective of the ADEPTS (ADvanced Electrical Power management Techniques for Space systems) is to study new techniques for power management automation. These techniques involve integrating current expert system technology with that of parallel and distributed computing, as well as a distributed, object-oriented approach to software design. The focus of the current study is the integration of new procedures for automatically planning and scheduling loads with procedures for performing fault diagnosis and control. The objective is the concurrent execution of both sets of tasks on separate transputer processors, thus adding parallelism to the overall management process.

Morris, Robert A.↗
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 NTRS2026

Deep RL for Fast Long-Horizon Operations Scheduling on NASA's Carruthers Geocorona Observatory Mission

Spacecraft operations scheduling is a highly constrained, long-horizon combinatorial optimization problem that traditionally relies on heuristics, constraint programming, or manual planning. We present a scalable deep reinforcement learning framework developed and deployed for NASA’s Carruthers Geocorona Observatory mission. Our framework introduces a macro-action abstraction known as activity blocks coupled with dynamic action-masking to navigate the intractably large search space and strictly enforce complex power, thermal, and instrument constraints. The resulting architecture generates globally feasible schedules with overwhelming probability, establishes operational trust, and executes a full training cycle in under six hours, circumventing the need for policy robustness by enabling rapid, on-demand retraining. Further, resulting schedules outperform baseline heuristics in scheduled science quality. The deep reinforcement learning framework was deployed as the default operational scheduler for the Carruthers Geocorona Observatory mission from the outset of the mission, demonstrating that deep reinforcement learning can be trusted for real spacecraft operations under complex, evolving constraints.

Geocorona↗
NASA NTRS1990

High voltage interactions of a sounding rocket with the ambient and system-generated environments

EPSAT (environment power system analysis tool) is used to examine the design of SPEAR III, which is scheduled to fly in early 1991. It will test high-voltage designs in both ambient and system-generated environments. Two of the key questions that the experiment hopes to address are whether or not the earth's magnetic field can cause the current that a high-voltage object draws from the plasma to be far less than the current that would be drawn in the absence of the magnetic field and under what neutral environmental conditions a discharge from the high-voltage object to the plasma will occur. The EPSAT program makes it possible to perform a variety of analyses on a preliminary or conceptual-level description of a system in a short period of time. The calculations presented on SPEAR III are all done for a conceptual-level description. The calculations indicate that the experiment will produce the conditions necessary to address these questions.

Kuharski, Robert A.↗
NASA NTRS1985

Effect of accuracy of wind power prediction on power system operator

This research project proposed a modified unit commitment that schedules connection and disconnection of generating units in response to load. A modified generation control is also proposed that controls steam units under automatic generation control, fast responding diesels, gas turbines and hydro units under a feedforward control, and wind turbine array output under a closed loop array control. This modified generation control and unit commitment require prediction of trend wind power variation one hour ahead and the prediction of error in this trend wind power prediction one half hour ahead. An improved meter for predicting trend wind speed variation is developed. Methods for accurately simulating the wind array power from a limited number of wind speed prediction records was developed. Finally, two methods for predicting the error in the trend wind power prediction were developed. This research provides a foundation for testing and evaluating the modified unit commitment and generation control that was developed to maintain operating reliability at a greatly reduced overall production cost for utilities with wind generation capacity.

Schlueter, R. A.↗
DOE OSTI2022

Developing a Reduced 240-Bus WECC Dynamic Model for Frequency Response Study of High Renewable Integration

The ongoing changes in the generation resource mix, driven by the rapid adoption of inverter-based resources (IBR) as well as the early retirement of synchronous generators, are bringing new challenges to the planning and operation of bulk electric power systems. Consequently, there is an increasing need to understand, design, and quantify the reliability service provision from IBRs by performing integrated scheduling and dynamic simulations. However, test systems that have consistent scheduling and dynamic models rarely exist largely because of the decoupled nature of the two simulations on a synchronous generator-dominated system. This paper develops the dynamic model of a reduced Western Electricity Coordinating Council (WECC) system. In conjunction with the existing scheduling model, it is suitable for integrating scheduling and dynamic simulations. The reduced 240-bus WECC model reflects the generation resource mix of the Western Interconnection as of 2018. Moreover, the developed dynamic model is validated against field frequency events measured by FNET/GridEye and preserves the dominant inter-area oscillation mode in WECC.

dynamic simulation↗
DOE OSTI2025

Flexible Resource Scheduler for FAST-DERMS (FRS-FASTDERMS) v0.9

The Flexible Resource Scheduler is a hierarchical controller that manages the distributed energy resources in a distribution substation or distribution feeder to provide a firm commitment of power flow at the substation or feeder head to be scheduled in transmission-level markets as an aggregated demand resource. It is the reference controller for the FAST-DERMS Architecture, developed in tandem with the architecture under the DOE FAST-DERMS project. It is comprised of a day-ahead stochastic optimization, which schedules substation power flow and reserves, a intra-hour MPC, which generates dispatch base points for DER, and a real-time PID controller maintaining that dispatches DER to maintain the substation power around the base points. The repository also includes a representative aggregator controller, and all of the necessary components to run a simulation using PNNL's GridAPPS-D software with the controller.

MacDonald, Jason [Lawrence Berkeley National Labor↗
NASA NTRS1976

Space-based solar power conversion and delivery systems study. Volume 2: Engineering analysis of orbital systems

Program plans, schedules, and costs are determined for a synchronous orbit-based power generation and relay system. Requirements for the satellite solar power station (SSPS) and the power relay satellite (PRS) are explored. Engineering analysis of large solar arrays, flight mechanics and control, transportation, assembly and maintenance, and microwave transmission are included.

Source record↗
DOE OSTI2020

Improving operational flexibility of integrated energy system with uncertain renewable generations considering thermal inertia of buildings

Insufficient flexibility in system operation caused by traditional "heat-set" operating modes of combined heat and power (CHP) units in winter heating periods is a key issue that limits renewable energy consumption. In order to reduce the curtailment of renewable energy resources through improving the operational flexibility, a novel optimal scheduling model based on chance-constrained programming (CCP), aiming at minimizing the lowest generation cost, is proposed for a small-scale integrated energy system (IES) with CHP units, thermal power units, renewable generations and representative auxiliary equipments. In this model, due to the uncertainties of renewable generations including wind turbines and photovoltaic units, the probabilistic spinning reserves are supplied in the form of chance-constrained; from the perspective of user experience, a heating load model is built with consideration of heat comfort and inertia in buildings. To solve the model, a solution approach based on sequence operation theory (SOT) is developed, where the original CCP-based scheduling model is tackled into a solvable mixed-integer linear programming (MILP) formulation by converting a chance constraint into its deterministic equivalence class, and thereby is solved via the CPLEX solver. We report the simulation results on the modified IEEE 30-bus system demonstrate that the presented method manages to improve operational flexibility of the IES with uncertain renewable generations by comprehensively leveraging thermal inertia of buildings and different kinds of auxiliary equipments, which provides a fundamental way for promoting renewable energy consumption.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2026

The relative influences of hydrologic information and dams’ hydropower scheduling decisions on electricity price forecasts

Price dynamics in wholesale electricity markets are driven by supply and demand. In markets with hydroelectric dams, the timing and amount of hydropower offered can influence prices in similar ways to wind and solar power. Unlike variable renewable energy, however, the supply of hydropower in wholesale markets is a function of both water availability and operational decisions at dams. Dam operators maximize revenues in wholesale markets by aligning generation with the periods of highest expected prices, and these scheduling decisions may in turn influence prices. Here, we examine the relative importance of two types of information in predicting forward electricity prices: a) water availability at dams, in the form of short-to-medium-range hydrological forecasts; and b) hourly scheduling decisions at dams. Using softly coupled hydrologic, hydropower scheduling, and power systems models spanning the U.S. Western Interconnection, we quantify the importance of hydrologic forecast accuracy in correctly predicting wholesale electricity prices and compare this with the influence of dam operators’ own hourly scheduling decisions on realized market prices. We find that aligning hydropower generation schedules with the periods of high forecasted prices causes larger, inadvertent price forecast errors than imperfect hydrologic forecasts. This suggests that knowledge of how water is managed by dam operators within the week is more important than weekly inflow forecast errors when predicting forward electricity prices. Our findings have implications for optimal hydropower scheduling by region. Specifically, accounting for price effects is critical in markets dominated by hydropower capacity.

Electricity markets↗
NASA NTRS1981

Magnetohydrodynamics MHD Engineering Test Facility ETF 200 MWe power plant. Conceptual Design Engineering Report CDER. Volume 3: Costs and schedules

The estimated plant capital cost for a coal fired 200 MWE electric generating plant with open cycle magnetohydrodynamics is divided into principal accounts based on Federal Energy Regulatory Commision account structure. Each principal account is defined and its estimated cost subdivided into identifiable and major equipment systems. The cost data sources for compiling the estimates, cost parameters, allotments, assumptions, and contingencies, are discussed. Uncertainties associated with developing the costs are quantified to show the confidence level acquired. Guidelines established in preparing the estimated costs are included. Based on an overall milestone schedule related to conventional power plant scheduling experience and starting procurement of MHD components during the preliminary design phase there is a 6 1/2-year construction period. The duration of the project from start to commercial operation is 79 months. The engineering phase of the project is 4 1/2 years; the construction duration following the start of the man power block is 37 months.

Source record↗
NASA NTRS1992

Scheduling lessons learned from the Autonomous Power System

The Autonomous Power System (APS) project at NASA LeRC is designed to demonstrate the applications of integrated intelligent diagnosis, control, and scheduling techniques to space power distribution systems. The project consists of three elements: the Autonomous Power Expert System (APEX) for Fault Diagnosis, Isolation, and Recovery (FDIR); the Autonomous Intelligent Power Scheduler (AIPS) to efficiently assign activities start times and resources; and power hardware (Brassboard) to emulate a space-based power system. The AIPS scheduler was tested within the APS system. This scheduler is able to efficiently assign available power to the requesting activities and share this information with other software agents within the APS system in order to implement the generated schedule. The AIPS scheduler is also able to cooperatively recover from fault situations by rescheduling the affected loads on the Brassboard in conjunction with the APEX FDIR system. AIPS served as a learning tool and an initial scheduling testbed for the integration of FDIR and automated scheduling systems. Many lessons were learned from the AIPS scheduler and are now being integrated into a new scheduler called SCRAP (Scheduler for Continuous Resource Allocation and Planning). This paper will service three purposes: an overview of the AIPS implementation, lessons learned from the AIPS scheduler, and a brief section on how these lessons are being applied to the new SCRAP scheduler.

Ringer, Mark J.↗
DOE OSTI2022

Robust Scheduling of Microgrids Considering Unintentional Islanding Conditions

This paper proposes a robust scheduling model for microgrids considering the stochastic unintentional islanding conditions. The proposed model minimizes the total operating cost of the microgrid by efficiently coordinating the supply of power from local distributed energy resources and the main grid. To capture the prevailing uncertainties in renewable generation and demand as well as unintentional islanding conditions, a two-stage adaptive robust optimization model is formulated to minimize the total operating cost under the worst realization of the modeled uncertainties. The column and constraint generation (C&CG) method is used to solve the problem in an iterative manner. The solution of the proposed scheduling model ensures robust microgrid operation in consideration of all possible realization of renewable generation, demand and unintentional islanding condition. Numerical simulations on a microgrid consisting of a wind turbine, a PV panel, a fuel cell, two micro-turbines, a diesel generator and a battery demonstrate the effectiveness of the proposed approach.

Liu, Guodong↗
NASA NTRS1986

The design of a turboshaft speed governor using modern control techniques

The objectives of this program were: to verify the model of off schedule compressor variable geometry in the T700 turboshaft engine nonlinear model; to evaluate the use of the pseudo-random binary noise (PRBN) technique for obtaining engine frequency response data; and to design a high performance power turbine speed governor using modern control methods. Reduction of T700 engine test data generated at NASA-Lewis indicated that the off schedule variable geometry effects were accurate as modeled. Analysis also showed that the PRBN technique combined with the maximum likelihood model identification method produced a Bode frequency response that was as accurate as the response obtained from standard sinewave testing methods. The frequency response verified the accuracy of linear models consisting of engine partial derivatives and used for design. A power turbine governor was designed using the Linear Quadratic Regulator (LQR) method of full state feedback control. A Kalman filter observer was used to estimate helicopter main rotor blade velocity. Compared to the baseline T700 power turbine speed governor, the LQR governor reduced droop up to 25 percent for a 490 shaft horsepower transient in 0.1 sec simulating a wind gust, and up to 85 percent for a 700 shaft horsepower transient in 0.5 sec simulating a large collective pitch angle transient.

Delosreyes, G.↗
DOE OSTI2020

Distributed Cooperative Control of Hybrid AC/DC Microgrid

This paper presents a distributed cooperative control-based power management algorithm for a hybrid AC/DC microgrid. The proposed algorithm for a hybrid microgrid system controls the power flow through the interface converter between the AC and DC microgrids. This algorithm allows power sharing between the distributed generators in the microgrid according to their power ratings. Moreover, it enables the fixed scheduled power delivery through the interface converters in both directions at different operating conditions while maintaining voltage regulation and improving the frequency profile. The effectiveness of the controller is confirmed by simulation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

High-Resolution Synthetic Solar Irradiance Sequence Generation: An LSTM-Based Generative Adversarial Network

The rapid growth of renewable energy resources penetration is bringing more challenges to power system planning and operation. Relevant renewable energy integration studies, such as the capability and dynamic performance of inverter-based resources' primary frequency response and fast frequency response, require high-resolution renewable generation output data that are representative of renewable energy resources. This paper focuses on creating synthetic but realistic solar irradiance data and proposes a long short-term memory-based generative adversarial network to generate high-resolution (second-level) solar irradiance sequences from low-resolution (minute-level) measurements. Combined with a classifier to recognize the solar irradiance patterns, the proposed model is trained using multi-loss functions to accurately capture the temporal correlations among both high-resolution and low-resolution sequences. Verification of the proposed approach is performed on the data set of the Oahu Solar Measurement Grid collected through the National Renewable Energy Laboratory. The results of the case studies demonstrate the proposed approach's capability to capture the statistical characteristics of different solar irradiance patterns and to generate high-quality synthetic solar irradiance sequences in high resolution.

dynamic scheduling↗