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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Distributed Controllers Seeking AC Optimal Power Flow Solutions Using ADMM

This paper focuses on power distribution systems with inverter-interfaced renewable energy sources (RESs), and develops a distributed control framework to steer the RES output powers to solutions of ac optimal power flow (OPF) problems. The design of the distributed control algorithm is based on suitable linear approximation of the ac power-flow equations, and leverages the so-called alternating direction method of multipliers (ADMM). Convergence of the RES-inverter output powers to solutions of the approximate ac OPF problem is established under suitable conditions on the mismatches between the commanded setpoints and actual RES output powers. Overall, since the proposed scheme can be cast as an ADMM with inexact primal and dual updates, the convergence results can be applied to more general distributed optimization settings.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Online Optimization for Networked Distributed Energy Resources With Time-Coupling Constraints

This paper proposes a Lyapunov optimization-based online distributed (LOOD) algorithmic framework for active distribution networks (ADNs) with numerous photovoltaic inverters and inverter air conditionings (IACs). In the proposed scheme, ADNs can track an active power setpoint reference at the substation in response to transmission-level requests while concurrently minimizing the social utility loss and ensuring the security of voltages. Conventional distributed optimization methods are rarely feasible to track the optimal solutions in fast variable environments using a fine-grained sampling interval where the underlying optimization problem evolves with the iterations of the algorithms. In contrast, based on the framework of online convex optimization (OCO), the developed approach uses a distributed algebraic update to compute the next round decisions relying on the current feedback of measurements. Notably, the time-coupling constraints of IACs are decoupled for online implementation with Lyapunov optimization technique. An incentive scheme is tailored to coordinate the customer-owned assets in lieu of the direct control from network operators. Optimality and convergency are characterized analytically. Finally, we corroborate the proposed method on a modified version of 33-node test feeder. Benchmark tests show that the proposed method is computationally and economically efficient, and outperforming existing algorithms.

active distribution networks↗
DOE OSTI2021

A Network-Aware Distributed Energy Resource Aggregation Framework for Flexible, Cost-Optimal, and Resilient Operation

To efficiently use the ubiquitous behind-the-meter distributed energy resources (DERs) in distribution systems for providing grid services, this paper presents a hierarchical control framework for DER optimal aggregation and control. We first develop a convex optimization model to evaluate the DER flexibility, and then use a convex model-predictive-control based approach to dispatch those DERs. The hierarchical control framework consists of a utility controller, community aggregators and multiple home energy management systems. The flexibility of the DERs is evaluated by each controller in the hierarchy such that the resultant flexibility is feasible given its operational domain. Based on the determined flexibility, the hierarchical controllers then compute optimal setpoints for the DERs to help the distribution system regulate node voltages and provide other distribution grid services. Numerical simulations performed on a model of a real distribution feeder in Colorado, using actual DER data in a residential community demonstrate that the proposed approach can effectively alleviate voltage issues and support resilient operation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Occupant-Centric Demand Response for Thermostatically-Controlled Home Loads

Efficiently managing energy usage to balance supply and demand on the electric grid is crucial, especially with the widespread deployment of distributed variable renewable electricity generation. This paper introduces two duty-cycle control methods for heating systems, adjusting thermostat setpoints to limit and shift electricity demand. The control approaches employ innovative techniques, such as adaptive duty cycling, to prioritize household thermal comfort while reducing peak demand. These control methods can respond to signals from the electric grid, including demand targets and time-of-use tariffs, and were tested physically on an electric furnace and heat pump in a test home during winter conditions in 2021 and 2022. The results are given as average demand reductions and energy use impacts with respect to the average indoor-outdoor temperature difference during the control period. For heat pumps, demand limiting control reduced power by 18.5% and 23.3% for indoor-outdoor temperature differences of 30°F and 40°F. Preheating-based demand shifting achieved reductions of 34.8% and 33.2% for the same temperature differences. Electric furnace tests showed demand reductions of 33.8% and 25.3% for demand limiting, and 56.1% and 45.7% for preheating-based demand shifting. These findings highlight the potential for innovative control methods to enhance grid efficiency and reduce energy consumption.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Using Dynamic Simulation to Evaluate Attemperator Operation in a Natural Gas Combined Cycle With Duct Burners in the Heat Recovery Steam Generator

A generic training simulator of a natural gas combined cycle was modified to match operations at a real plant. The objective was to use the simulator to analyze cycling operations of the plant. Initial operation of the simulator revealed the potential for saturation conditions in the final high pressure superheater as the attemperator tried to control temperature at the superheater outlet during gas turbine loading and unloading. Subsequent plant operational data confirmed simulation results. Multiple simulations were performed during loading and unloading of the gas turbine to determine operational strategies that prevented saturation and increased the approach to saturation temperature. The solutions included changes to the attemperator temperature control setpoints and strategic control of the steam turbine inlet pressure control valve.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2018

Multicoordination Control Strategy Performance in Hybrid Power Systems

This paper evaluates a state-space methodology of a multi-input multi-output (MIMO) control strategy using a 2 × 2 tightly coupled scenario applied to a physical gas turbine fuel cell hybrid power system. A centralized MIMO controller was preferred compared to a decentralized control approach because previous simulation studies showed that the coupling effect identified during the simultaneous control of the turbine speed and cathode airflow was better minimized. The MIMO controller was developed using a state-space dynamic model of the system that was derived using first-order transfer functions empirically obtained through experimental tests. The controller performance was evaluated in terms of disturbance rejection through perturbations in the gas turbine operation, and setpoint tracking maneuver through turbine speed and cathode airflow steps. The experimental results illustrate that a multicoordination control strategy was able to mitigate the coupling of each actuator to each output during the simultaneous control of the system, and improved the overall system performance during transient conditions. On the other hand, the controller showed different performance during validation in simulation environment compared to validation in the physical facility, which will require a better dynamic modeling of the system for the implementation of future multivariable control strategies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

PhaseChange Material Melting in an Energy Storage Module for a Micro Environmental ControlSystem

An experimentally validated finite element model (FEM) was developed to analyze the design parameters of a latent heat storage device (LHSD) for a micro environmental control system ( μ X). The μ X provides local cooling to an office worker in a room whose thermostat setpoint has been elevated from 23.9 °C (75 °F) to 26.1 °C (79 °F) in order to reduce heating, ventilation, and air conditioning (HVAC) energy consumption. For this application, the LHSD is designed to provide ≥50 W of cooling for a full, 8.5 h workday to restore thermal comfort in the warm, 26.1 °C room. The LHSD comprises several parallel slabs of encased phase change material (PCM) with interposed airflow channels. The airflow rate is selected to obtain ≥50 W of cooling at the end of the 8.5 h operation. The LHSD exhibits a decreasing cooling rate over the 8.5 h period when a constant airflow is passed through it, indicating that more cooling is supplied during the day than the minimum 50 W required for thermal comfort. The parametric analysis explores the effects of PCM thermal conductivity, slab thickness, air channel width, and number of slabs on LHSD performance. Parametric cases are compared against each other on the basis of their required PCM mass and energy consumption.

Engineering↗
DOE OSTI2021

Theoretical Control-Centric Modeling for Precision Model-Based Sliding Mode Control of a Hydraulic Artificial Muscle Actuator

Artificial muscles (AMs) typically rely on pneumatic sources of fluid power. The use of hydraulics can increase the power and force to weight and volume ratios of AM actuators. This paper develops a control-centric third-order single-input single-output (SISO) lumped-parameter dynamic model and sliding mode position controller based on Filippov's principle of equivalent dynamics for a braided hydraulic artificial muscle (HAM) actuator. The model predicts the nonlinear behavior of the HAM free contraction and captures the fluid and actuator nonlinear dynamic interactions in addition to the braid deformation. Model simulations are compared to experimental results for quasi-static pressurization, isometric pressurization, and open-loop square wave commands at 0.25, 0.5, and 1 Hz. Experiments of sine wave tracking at 0.25, 0.5, and 1 Hz and continuous square wave tracking at 0.067 Hz are conducted using a sliding mode controller (SMC) derived from the model. The SMC achieves a steady-state error of 6 μm at multiple setpoints within the actuator's 17 mm stroke. Compared to a proportional-integral-derivative (PID) controller, the SMC root-mean-square (RMS) error, mean error, and absolute maximum error are reduced on average by 53%, 61%, and 44%, respectively, demonstrating the benefit of model-based approaches for controlling HAMs.

42 ENGINEERING↗
DOE OSTI2022

Air Handling Unit Shutdowns During Scheduled Unoccupied Hours: US Commercial Building Stock Prevalence and Energy Impact

Commercial buildings account for 18% of U.S. energy consumption, with 44% used for heating, ventilation, and air conditioning (HVAC). American Society of Heating, Refrigerating and Air Conditioning Engineers (ASHRAE) 90.1 requires HVAC systems to shutdown fans and outdoor air ventilation during unoccupied times, only allowing fans to cycle on, without outdoor air, to maintain thermostat setpoints. However, it is minimally understood how often existing building operations align with energy code requirements and the energy implications of not doing so. This study used building automation system data from 843 buildings containing 5706 air handling units (AHUs) to determine three unoccupied AHU shutdown control schemes ranging in efficiency and then estimated their prevalence in the U.S. commercial building stock, segmented by building type. ComStock was then used to analyze the energy savings potential of implementing the most energy efficient unoccupied shutdown control scheme in non-participating buildings across the U.S commercial building stock. Results show that only 23% of AHUs align completely with the ASHRAE 90.1 requirement. ComStock modeling results show 4% annual stock energy savings by switching all non-participating buildings to the most efficient scheme, with 19% annual energy savings demonstrated for the median building switching from the least efficient scheme to the most efficient. Findings also show 114.5 TBtu electricity and 75.8 TBtu natural gas fuel savings when converting to the most efficient scheme. Furthermore, these findings help stakeholders understand the high prevalence of buildings not aligning with the ASHRAE-90.1 requirements for unoccupied AHU shutdowns and the energy savings potential of utilizing the most efficient unoccupied AHU shutdown scheme.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Implementation of a Model Predictive Control Strategy to Regulate Temperature Inside Plug-Flow Solar Reactor With Countercurrent Flow

Abstract Solar-driven thermochemical energy storage systems are proven to be promising energy carriers (solar fuels) to utilize solar energy by using reactive solid-state pellets. However, the production of solar fuel requires a quasi-steady-state process temperature, which represents the main challenge due to the transient nature of solar power. In this work, an adaptive model predictive controller (MPC) is presented to regulate the temperature inside a tubular solar reactor to produce solid-state solar fuel for long-term thermal storage systems. The solar reactor system consists of a vertical tube heated circumferentially over a segment of its length by concentrated solar power, and the reactive pellets (MgMn2O4) are fed from the top end and flow downwards through the heated tube. A countercurrent flowing gas supplied from the lower end interacts with flowing pellets to reduce it thermochemically at a temperature range of 1000—1500 °C. A low-order physical model was developed to simulate the dynamics of the solar reactor including the reaction kinetics, and the proposed model was validated numerically by using a 7-kW electric furnace. The numerical model then was utilized to design the MPC controller, where the control system consists of an MPC code linked to an adaptive system identification code that updates system parameters online to ensure system robustness against external disturbances (sudden change in the flow inside the reactor), model mismatches, and uncertainty. The MPC controller parameters are tuned to enhance the system performance with minimum steady-state error and overshoot. The controller is tested to track different temperature ranges between 500 °C and 1400 °C with different particles/gas mass flowrates and ramping temperature profiles. Results show that the MPC controller successfully regulated the reactor temperature within ± 1 °C of its setpoint and maintained robust performance with minimum input effort when subjected to sudden changes in the amount of flowing media and the presence of chemical reaction.

Engineering↗
DOE OSTI2025

Experimental Analysis of Advanced Turbine for Supercritical CO2 Power Cycle

An advanced first stage high pressure turbine blade for a supercritical CO2 power cycle is tested in the Big Rig for Aerothermal Stationary Turbine Analysis (BRASTA) annular cascade at the Purdue Experimental Turbine Aerothermal Laboratory (PETAL) high pressure blow down facility alongside a baseline blade for comparison of aerodynamic performance. Both geometries are tested simultaneously using a novel off-axis rig design to allow for the blade geometries to be scaled up to achieve higher Reynolds numbers. The off-axis design necessitates the use of discrete sectors of airfoils, which are designed and additively manufactured in house using an mSLA printer. Printing the blades allows for unique routing of passage for blade surface static pressure taps that contour to the blade shape instead of requiring a straight line view from surface tap to egress, allowing all instrumentation for 15%, 50%, and 85% span to exist in the same passage. A flow conditioning gauze [1] is placed upstream of the blade passages to impart pressure, Mach, and swirl profiles to mimic the rotor relative frame inlet conditions to the blade. Downstream, a sonic valve is used to alter the backpressure to achieve different pressure ratios for different blowdown setpoints. The design of the rig, sonic wheel, and instrumentation are discussed along with the manufacturing and GD&T of the blades with respect to the build-up of this novel experimental apparatus. Initial commissioning data is obtained from inlet total pressure and temperature rakes, blade static pressure taps, and exit total pressure rakes. Oil visualization is performed using a silicone oil mixture containing titanium dioxide and pigmented for contrast of the blade suction side surface with the hub and shroud endwalls. The viscosity of the oil is tuned so that the oil does not fully thin and blow away during the time of the test, and endoscopic cameras are placed in the rig for live monitoring and recording. The preliminary oil visualization and rake profiles are presented, showcasing the operability of this additively manufactured off-axis flow path design.

Tuite, Logan [Purdue University]↗
DOE OSTI2015

SU-E-T-136: Assessment of Seasonal Linear Accelerator Output Variations and Associated Impacts

Purpose: Application of process control theory in quality assurance programs promises to allow earlier identification of problems and potentially better quality in delivery than traditional paradigms based primarily on tolerances and action levels. The purpose of this project was to characterize underlying seasonal variations in linear accelerator output that can be used to improve performance or trigger preemptive maintenance. Methods: Review of runtime plots of daily (6 MV) output data acquired using in house ion chamber based devices over three years and for fifteen linear accelerators of varying make and model were evaluated. Shifts in output due to known interventions with the machines were subtracted from the data to model an uncorrected scenario for each linear accelerator. Observable linear trends were also removed from the data prior to evaluation of periodic variations. Results: Runtime plots of output revealed sinusoidal, seasonal variations that were consistent across all units, irrespective of manufacturer, model or age of machine. The average amplitude of the variation was on the order of 1%. Peak and minimum variations were found to correspond to early April and September, respectively. Approximately 48% of output adjustments made over the period examined were potentially avoidable if baseline levels had corresponded to the mean output, rather than to points near a peak or valley. Linear trends were observed for three of the fifteen units, with annual increases in output ranging from 2–3%. Conclusion: Characterization of cyclical seasonal trends allows for better separation of potentially innate accelerator behaviour from other behaviours (e.g. linear trends) that may be better described as true out of control states (i.e. non-stochastic deviations from otherwise expected behavior) and could indicate service requirements. Results also pointed to an optimal setpoint for accelerators such that output of machines is maintained within set tolerances and interventions are required less frequently.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2019

Topology Reconfiguration and distributed Volt Var Control (TR-dVVC) v1

Topology Reconfiguation is a simple algorithm to choose a network configuration with the least losses in a system with high penetration of renewable energy. It uses a linearized optimal power flow algorithm to identify the optimal setpoints of PV in a system, then performs an exhaustive search of switch configurations to find the loss minimizing solution, it repeats this process until convergence. At the end, the operator has a switch schedule for a 24 hour period that should minimize losses. VVC is a distributed algorithm in which PV units drive voltage at points within the network to 1 per unit through reactive power control. The VVC algorithm relies on extremum seeking control to provide the control. The software package is a simulation of VVC on a standard IEEE 34 bus three phase network.

MacDonald, Jason↗
DOE OSTI2022

PyChargeModel (Oriented Programming Based Electric Vehicle and Electric Vehicle Supply Equipment Charging Model in Python) [SWR-22-39]

The PyChargeModel creates two classes called "ElectricVehicles" and "evse_class", which can be used to create multiple instances of electric vehicles (EVs) and electric vehicle supply equipment (EVSE or charging ports) and simulate charging behavior. These objects can be instantiated with several properties such as battery chemistries, battery pack sizes, cell sizes, charging port power, dc or ac chargers etc. The objects can communicate with each other by calling different methods built within the classes. Through these methods, each EV object can be assigned to an EVSE, charged either using a default protocol or using setpoint values communicated from a site controller via the EVSE object.

Mishra, Partha↗
DOE OSTI2018

Predictive Control of Residential Heat Pump Water Heaters [SWR-13-35]

Heat pump water heaters (HPWH) in the United States typically feature both a heat pump and at least one electric resistance element for heating. The heat pump is much more efficient than the element but cannot heat the water as quickly. The combination of these two heat sources makes HPWH a perfect candidate for implementing advanced control algorithms to achieve additional energy savings. NREL's Predictive Control of Residential Heat Pump Water Heaters introduces a novel predictive control method that provides optimal setpoint profile for both heat sources based on the patterns discovered from users' hot water use data. A simulation study indicates the Predictive Control of Residential Heat Pump Water Heaters is able to achieve significant energy savings without impacting users' thermal comfort.

Christensen, Dane↗
DOE OSTI2021

IMMM-SFA/tempset

Generates new temperature set point schedules from base schedules. The software provides a systematic, automatic method to generate temperature setpoint schedules from a base schedule and a small set of modeling parameters. The software will be open-sourced, and can easily be accessed by energy modelers.

Vernon, Chris↗
DOE OSTI2024

HP-FLEX MPC v0.1.0

HP-FLEX MPC is control software developed by Lawrence Berkeley National Laboratory with support from the California Energy Commission (CEC) through EPIC-19-301. HP-FLEX aims to provide load flexibility for heat pumps (HPs) in response to dynamic grid signals (including Time-of-Use, Dynamic Pricing, and Critical Peak Pricing) while maintaining thermostat temperatures within user-specified bounds. The software includes a system-identification module, which models the dynamics of the building envelope with thermostat data, and a control module based on a model predictive controller (MPC) to make optimal decisions. HP-FLEX receives forecasts of outdoor air temperature, solar irradiation, and internal gain (if available), as well as trajectories of energy price, temperature lower and upper bounds over a prediction horizon. It then optimizes heating and cooling capacities to minimize energy cost and peak power (with a user-defined weight on peak power) over the prediction horizon, while maintaining room air temperature within the temperature constraints, and outputs the optimal thermostat setpoints.

Kim, Donghun↗