Search NASA⌕ Search

SEARCH · Search NASA

Results for “energy control system”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records

NASA B737 flight test results of the total energy control system

The Total Energy Control System (TECS) is an integrated autopilot/autothrottle developed by BCAC that was test flown on NASA Langley's Transport System Research Vehicle (i.e., a highly modified Boeing B737). This systems was developed using principles of total energy in which the total kinetic and potential energy of the airplane was controlled by the throttles, and the energy distribution controled by the elevator. TECS integrates all the control functions of a conventional pitch autopilot and autothrottle into a single generalized control concept. This integration provides decoupled flightpath and maneuver control, as well as a coordinated throttle response for all maneuvers. A mode hierarchy was established to preclude exceeding airplane safety and performance limits. The flight test of TECS took place as a series of five flights over a 33-week period during September 1985 at NASA Langley. Most of the original flight test plan was completed within the first three flights with the system not exhibiting any instabilities or design problems that required any gain adjustment during flight.

Bruce, Kevin R.↗

NASA B737 flight test results of the Total Energy Control System

The Total Energy Control System was developed and tested in September 1985 during five flights on the NASA Langley Transport System Research Vehicle, a modified Boeing B737. In the system, the total kinetic and potential energy of the aircraft is controlled by the throttles, and the energy distribution is controlled by the elevator. A common inner loop is used for each mode of the autopilot, and all the control functions of a conventional pitch autopilot and autothrottle are integrated into a single generalized control concept, providing decoupled flightpath and maneuver control, and a coordinated throttle response for all maneuvers. No instabilities or design problems requiring gain adjustment in flight were found, and comparison with simulation results showed excellent path tracking.

Bruce, K. R.↗

Solar energy control system

A solar energy control system for a hot air type solar energy heating system wherein thermocouples are arranged to sense the temperature of a solar collector, a space to be heated, and a top and bottom of a heat storage unit is disclosed. Pertinent thermocouples are differentially connected together, and these are employed to effect the operation of dampers, a fan, and an auxiliary heat source. In accomplishing this, the differential outputs from the thermocouples are amplified by a single amplifier by multiplexing techniques. Additionally, the amplifier is corrected as to offset by including as one multiplex channel a common reference signal.

Currie, J. R.↗

Using Semantic Web Technologies to Develop Intrinsically Resilient Energy Control Systems

To preserve critical energy control functions while under attack, it is necessary to perform comprehensive analysis on root causes and impacts of cyber intrusions without sacrificing the availability of energy delivery. We propose to design an intrinsically resilient energy control system where we extensively utilize Semantic Web technologies, which play critical roles in knowledge representation and acquisition. While our ultimate goal is to ensure availability/resiliency of energy delivery functions and the capability to assess root causes and impacts of cyber intrusions, the focus of this paper is to demonstrate a proof of concept of how Semantic Web technologies can significantly contribute to resilient energy control systems.

cybersecurity↗

Total energy control system autopilot design with constrained parameter optimization

A description is given of the application of a multivariable control design method (SANDY) based on constrained parameter optimization to the design of a multiloop aircraft flight control system. Specifically, the design method is applied to the direct synthesis of a multiloop AFCS inner-loop feedback control system based on total energy control system (TECS) principles. The design procedure offers a structured approach for the determination of a set of stabilizing controller design gains that meet design specifications in closed-loop stability, command tracking performance, disturbance rejection, and limits on control activities. The approach can be extended to a broader class of multiloop flight control systems. Direct tradeoffs between many real design goals are rendered systematic by proper formulation of the design objectives and constraints. Satisfactory designs are usually obtained in few iterations. Performance characteristics of the optimized TECS design have been improved, particularly in the areas of closed-loop damping and control activity in the presence of turbulence.

Ly, Uy-Loi↗

Flight testing TECS - The Total Energy Control System

This paper describes some of the unique features of an integrated throttle-elevator control law known as the Total Energy Control System (TECS) which has been flight tested on NASA Langley's Transport Systems Research Vehicle. The TECS concept is designed around total energy principles. It utilizes a full-time autothrottle to control the total energy of the aircraft and the elevator to distribute the energy between speed and flight path objectives. Time histories of selected parameters generated from flight data are used to illustrate the pilot-like control strategy of the system and the priority logic employed when throttle limiting is encountered.

Kelly, James R.↗

Fuzzy Integration of Support Vector Regression Models for Anticipatory Control of Complex Energy Systems

Anticipatory control systems are a class of systems whose decisions are based on predictions for the future state of the system under monitoring. Anticipation denotes intelligence and is an inherent property of humans that make decisions by projecting in future. Likewise, artificially intelligent systems equipped with predictive functions may be utilized for anticipating future states of complex systems, and therefore facilitate automated control decisions. Anticipatory control of complex energy systems is paramount to their normal and safe operation. In this paper a new intelligent methodology integrating fuzzy inference with support vector regression is introduced. Our proposed methodology implements an anticipatory system aiming at controlling energy systems in a robust way. Initially a set of support vector regressors is adopted for making predictions over critical system parameters. Furthermore, the predicted values are fed into a two stage fuzzy inference system that makes decisions regarding the state of the energy system. The inference system integrates the individual predictions into a single one at its first stage, and outputs a decision together with a certainty factor computed at its second stage. The certainty factor is an index of the significance of the decision. The proposed anticipatory control system is tested on a real world set of data obtained from a complex energy system, describing the degradation of a turbine. Results exhibit the robustness of the proposed system in controlling complex energy systems.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

HVAC & Building Management Control System Energy Efficiency Replacements

The project objective was the replacement of an aging, un-repairable HVAC system which has grown inefficient and a huge energy consumer with low energy and efficient HVAC units, and installation of energy efficient building control technologies at City's YMCA Community Center.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Energy Management Control Systems: Tools for Energy Savings and Environmental Protection

The change in the price of energy has encouraged the increase of energy efficiency. This report will discuss a tool to promote energy efficiency in intelligent buildings, energy management control systems (EMCS). In addition to the online control of energy production, supply, and consumption, the function of the EMCS is to support short- and long-term planning of the system operation as well as to collect, store, and regularly evaluate operation data. The strategies behind planning and implementing the EMCS as well as the manipulating the resulting data are discussed in this report.

Zsebik, Albin↗

Reinforcement Learning for Intelligent Building Energy Management System Control *

A building energy management system (BEMS) is a computer-based system designed to monitor and control a building's energy needs. Modern BEMS rely on the sensing and connectivity capabilities of Internet of Things (IoT) technology to intelligently adjust the energy consumption to reduce cost while respecting the consumers' preferences. Increasingly, control decisions are made based on predictions by models trained using supervised machine learning methods, which still requires control policies to be formulated in a rule-based fashion. When using reinforcement learning (RL) instead, control policies are learned by observing the utility in terms of cost and comfort associated with actions such as a change in the heating system's setpoint. The resulting RL-based controllers can capture not only the dynamics of the building and the associated electrical devices, but also fluctuations in electricity prices and user demand, avoiding the need to combine multiple predictive models with tailored control policies. This chapter will provide an overview of RL-based approaches for BEMS. After sketching the taxonomy of general RL methods, we discuss the implications of relying on the individual methods in a BEMS context. Existing work applying RL is presented along the key devices controlled by BEMS systems. Finally, we summarize the state-of-the-art and sketch limitations and open research directions.

Kotevska, Olivera↗

Impact Analysis of Data Integrity Attacks on FACTS-based Wide-Area Voltage Control System

Energy management system (EMS) consists of several wide-area control applications that serve as a backbone for security, stability, and reliability of the power system. Wide-area voltage control system (WAVCS), one of the critical wide-area applications, operates in coordination with local Flexible AC Transmission System (FACTS) devices to provide voltage security and optimal management of active and reactive power resources. Since the WAVCS relies on wide-area communication and data sharing devices, possible cybersecurity vulnerabilities have to be addressed to ensure the closed-loop operation of WAVCS. In this paper, we present a methodology for performing an impact analysis of cyber-attacks in WAVCS cybersecurity. In particular, different types of data integrity attacks, such as malicious tripping, fault replay, and signal altering attacks, are considered, and detailed impact analysis is conducted in a testbed environment using the Kundur's four machine two-area system. For performing an impact analysis, the transient voltage stability of the sensitive bus voltage is studied, followed by the quantitative assessment and severity ranking using the voltage profile index. Our experimental evaluation reveals that the data integrity attacks on control signals exhibit a higher attack severity than on the measurement signals. Further, the severity of these attacks varies with nature (static or dynamic), location, and types of attacks.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Simulation of Flywheel Energy Storage System Controls

This paper presents the progress made in the controller design and operation of a flywheel energy storage system. The switching logic for the converter bridge circuit has been redefined to reduce line current harmonics, even at the highest operating speed of the permanent magnet motor-generator. An electromechanical machine model is utilized to simulate charge and discharge operation of the inertial energy in the flywheel. Controlling the magnitude of phase currents regulates the rate of charge and discharge. The resulting improvements are demonstrated by simulation.

Truong, Long V.↗

System for controlling a hybrid energy system

A method includes identifying a first operating sequence of a repeated operation of at least one non-traction load. The method also includes determining first and second parameters respectively indicative of a requested energy and output energy of the at least one non-traction load and comparing the determined first and second parameters at a plurality of time increments of the first operating sequence. The method also includes determining a third parameter of the hybrid energy system indicative of energy regenerated from the at least one non-traction load and monitoring the third parameter at the plurality of time increments of the first operating sequence. The method also includes determining at least one of an energy deficiency or an energy surplus associated with the non-traction load of the hybrid energy system and selectively adjusting energy stored within the storage device during at least a portion of a second operating sequence.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Tool coupling for the design and operation of building energy and control systems based on the Functional Mock-up Interface standard

This paper describes software tools developed at the Lawrence Berkeley National Laboratory (LBNL) that can be coupled through the Functional Mock-up Interface standard in support of the design and operation of building energy and control systems. These tools have been developed to address the gaps and limitations encountered in legacy simulation tools. These tools were originally designed for the analysis of individual domains of buildings, and have been difficult to integrate with other tools for runtime data exchange. The coupling has been realized by use of the Functional Mock-up Interface for co-simulation, which standardizes an application programming interface for simulator interoperability that has been adopted in a variety of industrial domains. As a variety of coupling scenarios are possible, this paper provides users with guidance on what coupling may be best suited for their application. Furthermore, the paper illustrates how tools can be integrated into a building management system to support the operation of buildings. These tools may be a design model that is used for real-time performance monitoring, a fault detection and diagnostics algorithm, or a control sequence, each of which may be exported as a Functional Mock-up Unit and made available in a building management system as an input/output block. We anticipate that this capability can contribute to bridging the observed performance gap between design and operational energy use of buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Renewable Energy Positioning System: Energy Positioning: Control and Economics

GENI Project: The University of Washington and the University of Michigan are developing an integrated system to match well-positioned energy storage facilities with precise control technologies so the electric grid can more easily include energy from renewable power sources like wind and solar. Because renewable energy sources provide intermittent power, it is difficult for the grid to efficiently allocate those resources without developing solutions to store their energy for later use. The two universities are working with utilities, regulators, and the private sector to position renewable energy storage facilities in locations that optimize their ability to provide and transmit electricity where and when it is needed most. Expanding the network of transmission lines is prohibitively expensive, so combining well-placed storage facilities with robust control systems to efficiently route their power will save consumers money and enable the widespread use of safe, renewable sources of power.

ARPA-E↗

Distributed reinforcement learning and consensus control of energy systems

Disclosed herein are methods, systems, and devices for utilizing distributed reinforcement learning and consensus control to most effectively generate and utilize energy. In some embodiments, individual turbines within a wind farm may communicate to reach a consensus as to the desired yaw angle based on the wind conditions.

King, Jennifer Rose Rose↗