Final Design and Qualification of a Hypergolic Electrical Power System Final Report
Component and system design evaluation for hypergolic electrical power system
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Component and system design evaluation for hypergolic electrical power system
The paper presents the results of a concept development study of heat rejection systems for Space Station solar dynamic power systems. The thermal performance and weights of each of the heat rejection subsystems have been addressed in detail, and critical technologies which require development tests and evaluation for successful demonstration were assessed and identified. Baseline and several alternate heat rejection system configurations and optimum designs were developed for both Brayton and Rankine cycles. The thermal performance, mass properties, assembly requirements, reliability, maintenance requirements, and life cycle costs were determined for each of the system configurations. Trade studies were performed on each configuration with respect to the heat pipe wall thickness and the amount of redundancy to determine the effects on system reliability, maintenance requirements, and life cycle costs. An optimum design was then selected for each configuration.
A mild-hybrid energy storage system architecture is provided, comprising: a battery; an ultracapacitor connected in parallel with the battery; a passive battery pre-charge circuit connected between a terminal of the battery and a DC bus; a battery main contactor connected in parallel with the battery pre-charge circuit between the terminal of the battery and the DC bus; a passive ultracapacitor pre-charge circuit connected between a terminal of the ultracapacitor and the DC bus; an ultracapacitor main contactor connected in parallel with the ultracapacitor pre-charge circuit between the terminal of the ultracapacitor and the DC bus; and a control module configured to independently control operation of the battery pre-charge circuit, the battery main contactor, the ultracapacitor pre-charge circuit and the ultracapacitor main contactor.
The overall goal of the project is to leverage robust graphical learning and phase measurement unit (PMU) data to learn the dynamic interactions of electrical grid components in order to improve the power system resilience. Specifically, the learned dynamic interaction graphs are utilized to detect known and unknown anomalous patterns in power systems, identify high-risk operational conditions, and enable risk-based cascading mitigation.
This paper describes the Orbiting Spacecraft Shadowing Analysis (OSSA) computer program that was developed at NASA Lewis Research Center in order to assess the shadowing effects on various power systems. The algorithms, inputs and outputs are discussed. Examples of typical shadowing analyses that have been performed for the International Space Station Freedom, International Space Station Alpha and the joint United States/Russian Mir Solar Dynamic Flight Experiment Project are covered. Effects of shadowing on power systems are demonstrated.
The point-focusing distributed receiver (PFDR) concept is employed by a number of solar thermal power systems currently under development. One type of PFDR system which shows particular promise incorporates distributed energy generation. According to this concept each parabolic dish collector is a self-contained power generation module, and a conventional electrical system is used to interconnect the modules. The concept is thus modular, and any number of power modules can be combined to achieve the required plant size. Given the benefits of mass production, it appears that this type of system can produce electricity at lower cost than is projected for conventional (fossil) power systems over the next decade. An employment of organic Rankine cycle heat engines is considered.
The aeronautics industry has been challenged to increase efficiency, reduce noise and emissions, and decrease dependency on carbon-based fuels. To address these needs, NASA has identified and begun to pursue electrified aircraft as a possible solution. The power system for an electric aircraft can exist in many different forms, however; at the early design stage the engineer(s) must identify whether a hybrid- or turbo- electric solution may be best, whether the power transmission system is to be AC or DC, and to ultimately answer the question: does the electric solution provide a net system benefit compared to the fully mechanical solution? This paper describes a generalized power system architecture sizing and analysis framework to provide a mechanism to answering these questions, along with an example based on the STARC-ABL Architecture.
Optimum Mariner-class spacecraft electric power system providing improved utilization of solar array power and greater reliability
The design and development of a modular solar thermal power system for application in the 1 to 10 MWe range is described. The system consists of five subsystems: the collector, power conversion, energy transport, energy storage, and the plant control subsystem. The collector subsystem consists of concentrator, receiver, and tower assemblies. The energy transport subsystem uses a mixture of salts with a low melting temperature to transport thermal energy. A steam generator drives a steam Rankine cycle turbine which drives an electrical generator to produce electricity. Thermal and stress analysis tests are performed on each subsystem in order to determine the operational reliability, the minimum risk of failure, and the maintenance and repair characteristics.
As the power grid technology evolution and information technology revolution converge, power grids are witnessing a revolutionary transition, represented by emerging grid technologies and large scale deployment of new sensors and meters in networks. This transition brings opportunities, as well as computational challenges in the field of power grid analysis and operation. This paper presents some research outcomes in the areas of parallel state estimation using the preconditioned conjugated gradient method, parallel contingency analysis with a dynamic load balancing scheme and distributed system architecture. Based on this research, three types of computational challenges are identified: highly coupled applications, loosely coupled applications, and centralized and distributed applications. Recommendations for future work for power grid applications are also presented.
This paper summarizes recent advances in antenna and power systems technology to enable a high data rate Ka-band Mars-to-Earth telecommunications system. Promising antenna technologies are lightweight, deployable space qualified structures at least 12-m in diameter (potentially up to 25-m). These technologies include deployable mesh reflectors, inflatable reflectarray and folded thermosetting composite. Advances in 1kW-class RF power amplifiers include both TWTA and SSPA technologies.
Accurate real-time estimation of the four electromechanical oscillation properties, i.e., dominant oscillation modes, mode shapes, participation factors, and coherent groups, is of great importance to assess and mitigate potential electromechanical oscillations in interconnected power systems. While eigenvalue analysis can realize such estimation, it requires precise linearized dynamic models and accurate parameters, which are highly difficult to obtain in practice. Data fusion-based modal estimation methods can extract the properties of electromechanical oscillations from measurement data without the power system model and parameters, but most of the time only one or two property assessments can be accomplished each time. To overcome this challenge, this paper presents a synergistic data analytics solution to characterize the dynamic behaviors of electromechanical oscillations from real-time measurement data. Here, the proposed method uses optimized variable projection, and it is capable of estimating all four electromechanical oscillation behavior properties from measured responses. Case studies are performed using the simulated measurement data of a 16-generator 68-bus test system and the field measurements collected by the PMUs deployed in the Yunnan Power Grid. The results demonstrate that the proposed synergistic data analytics solution can achieve satisfactory performance in capturing the properties of electromechanical oscillations from measurement data and exhibit strong robustness against measurement noise when compared with existing measurement-based methods.
Despite the recent development of several scalable, robust, and resilient control approaches with superior convergence properties considering an increasing penetration of distributed energy resources (DERs), cognitive oversights often simplify several aspects of the cyber–physical power system in the controller development. Here, following the identification of the limitations of classical controller definitions, we justify alternative definitions of voltage control approaches classifiers considering three inter-disciplinary domains: (i) power system, (ii) optimization and decision-making, and (iii) networking and cyber-security, to develop a taxonomy for helping in real-world comparative performance analysis and deployability of these controllers. We observe that classical and introduced domain-based definitions together can better classify the control algorithms.
Deep reinforcement learning (DRL) algorithms have successfully solved many challenging problems in various power system control scenarios. However, their decision-making process is usually regarded as black-boxes. Furthermore, how DRL models interact with human intelligence remains an open problem. Thus, this paper proposes a policy extraction framework to extract a complex DRL model into an explainable policy. This framework includes three parts: 1) DRL training and data generation. We train an agent for a specific control task and generate data, which contains the control policy of the agent. 2) Policy extraction. We propose an information gain rate based weighted oblique decision tree (IGR-WODT) for DRL policy extraction. 3) Policy evaluation. We define three metrics to evaluate the performance of the proposed approach. A case study for the under-voltage load shedding problem shows that the IGR-WODT presents a performance enhancement compared with DRL, weighted oblique decision tree, and univariate decision tree. The proposed policy extraction method could provide an intuitive explanation of the neural network decision-making process to the dispatchers when making final decisions on power grid operation. Also, the resulted rule-based controller could replace the deep neural network-based controller in many field edge devices with limited computing resources, providing comparable performance.
NASA Lewis Research Center's Electrochemical Technology Branch has teamed with the NASA Wallops Flight Facility to demonstrate the operation of a hydrogen-oxygen proton exchange membrane (PEM) fuel cell for application in the upper atmosphere. NASA Wallops' Balloon Programs Branch has a requirement for a high-power, long-duration power system for use on a scientific balloon platform. The current power system will not meet these needs. The objective of this program is to deliver a 200-W (minimum) fuel cell system that can deliver approximately 10 kWh of electrical energy.
This SAND report collects the results from the LDRD project “SHAZAM”, which aimed to push the limits of performance for self-healing, self-assembling power systems whose sectionalizing and load-control agents rely on local measurements only (i.e., only what they can measure at their own terminals, with no data sharing between agents). This work includes self-networking microgrids. The key objectives of this work were a) to demonstrate how high the performance of local-measurement-only self-assembling power systems can be; and b) to solve certain technical problems associated with such systems, such as their inability to prevent the accidental formation of closed loops and their tendency to thermally overload some conductors. “SHAZAM” investigators a) demonstrated that the performance of such systems can be surprisingly high, b) demonstrated that such systems are quite robust to all kinds of variations, and c) developed and demonstrated solutions to several key challenges associated with this type of system.
A detailed simulation of a dc inductor resonant driver and receiver is used to demonstrate the transient characteristics of a 20 kHz resonant power system during fault and overload conditions. The simulated system consists of a dc inductor resonant inverter (driver), a 50-meter transmission cable, and a dc inductor resonant receiver load. Of particular interest are the driver and receiver performance during fault and overload conditions and on the recovery characteristics following removal of the fault. The information gained from these studies sets the stage for further work in fault identification and autonomous power system control.