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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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This report summarizes the activities of this project, which aims at design and testing a scalable, robust, and online framework that provides secure monitoring of photovoltaic generation in the face of potential cyber-attacks.
Simulation of solar array characteristics to evaluate systems designed to operate from solar cell power source by utilization of silicon diodes
A 16 parameter solar concentrator/heat receiver mass model is used in conjunction with Stirling and Brayton Power Conversion System (PCS) performance and mass computer codes to determine the effect of thermal energy storage (TES) material property changes on overall PCS mass as a function of steady state electrical power output. Included in the PCS mass model are component masses as a function of thermal power for: concentrator, heat receiver, heat exchangers (source unless integral with heat receiver, heat sink, regenerator), heat engine units with optional parallel redundancy, power conditioning and control (PC and C), PC and C radiator, main radiator, and structure. Critical TES properties are: melting temperature, heat of fusion, density of the liquid phase, and the ratio of solid-to-liquid density. Preliminary results indicate that even though overalll system efficiency increases with TES melting temperature up to 1400 K for concentrator surface accuracies of 1 mrad or better, reductions in the overall system mass beyond that achievable with lithium fluoride (LiF) can be accomplished only if the heat of fusion is at least 800 kJ/kg and the liquid density is comparable to that of LiF (1880 kg/cu m.
A 16 parameter solar concentrator/heat receiver mass model is used in conjunction with Stirling and Brayton Power Conversion System (PCS) performance and mass computer codes to determine the effect of thermal energy storage (TES) material property changes on overall PCS mass as a function of steady state electrical power output. Included in the PCS mass model are component masses as a function of thermal power for: concentrator, heat receiver, heat exchangers (source unless integral with heat receiver, heat sink, regenerator), heat engine units with optional parallel redundancy, power conditioning and control (PC and C), PC and C radiator, main radiator, and structure. Critical TES properties are: melting temperature, heat of fusion, density of the liquid phase, and the ratio of solid-to-liquid density. Preliminary results indicate that even though overall system efficiency increases with TES melting temperature up to 1400 K for concentrator surface accuracies of 1 mrad or better, reductions in the overall system mass beyond that achievable with lithium fluoride (LiF) can be accomplished only if the heat of fusion is at least 800 kJ/kg and the liquid density is comparable to that of LiF (1800 kg/cu m).
Grid-forming (GFM) inverters are a promising technology for the widespread integration of renewable energy sources in future power systems. As a key element of GFM inverter control, the primary controller governs the internal reference voltage and angle. During contingencies in the grid---such as faults, voltage drops, or frequency and phase jumps---an inverter can be forced into a current-limiting mode of operation modulating inverter dynamics, and, as a result, it is prone to losing synchronism with the grid. In this paper, we propose a novel GFM primary control method with an additional synchronization term that naturally activates during contingencies to improve the dynamic response. The method allows the inverter to remain synchronized with the grid, which improves the inverter's dynamic behavior both during and after current-limiting grid conditions and enhances grid support, including voltage support using full current capacity. The method is demonstrated for voltage, frequency, and phase jumps both in a single-machine-to-infinite-bus and a network-wide electromagnetic transient simulation of the IEEE 14-bus system with 5 GFM inverters. The simulations provide insights into the proposed synchronization method and confirm the high potential of the method, which robustly secures synchronism under severe contingencies.
High efficiency dynamic Radioisotope Power Systems (RPS) could be mission enabling for low power space applications such as small probes, landers rovers, and communication repeaters. These applications would contain science instruments and be distributed across planetary surfaces or near objects of interest where solar flux is insufficient for using solar cells. Small RPS could be used to provide power for sensing radiation, temperature, pressure, seismic activity, and other measurements of interest to planetary scientists. Small RPS would use fractional versions of the General Purpose Heat Source (GPHS) or Light Weight Radioisotope Heater Units (LWRHU), to heat power conversion technologies. Dynamic power systems are capable of three to four times higher conversion efficiency compared to static power conversion technologies, and would provide an equal amount of power using less fuel or more power using an equal amount of fuel. Providing spacecraft with more power could decrease duty cycling of basic functions and, therefore, increase the quality and abundance of science data. NASA GRC is developing a low power dynamic RPS that would convert heat from multiple LWRHU to one watt of usable direct current electric power for spacecraft instrumentation and communication. The power system could be used to charge batteries or capacitors for higher power burst usage. The initial design, called Small Stirling Technology Exploration Power (smallSTEP), is around 3 kg, 11 cm diameter X 32 cm long, and converts 8 watts of heat to one watt of electricity using a Stirling convertor. This low power conversion system represents a new class of RPS with power levels two orders of magnitude lower than prototypes currently being developed for space applications under NASA contracts. Development of the 1-watt RPS includes maturation of convertor and controller designs, performance evaluation of an evacuated metal foil insulation, and development of system interfaces. Initial demonstration of the subsystems has been completed in a laboratory environment and a higher fidelity system is being pursued for demonstration in relevant environments for use on small spacecraft needed to carry out future space science missions.
High efficiency dynamic Radioisotope Power Systems (RPS) could be mission enabling for low power space applications such as small probes, landers rovers, and communication repeaters. These applications would contain science instruments and be distributed across planetary surfaces or near objects of interest where solar flux is insufficient for using solar cells. Small RPS could be used to provide power for sensing radiation, temperature, pressure, seismic activity, and other measurements of interest to planetary scientists. Small RPS would use fractional versions of the General Purpose Heat Source (GPHS) or Light Weight Radioisotope Heater Units (LWRHU), to heat power conversion technologies. Dynamic power systems are capable of three to four times higher conversion efficiency compared to static power conversion technologies, and would provide an equal amount of power using less fuel or more power using an equal amount of fuel. Providing spacecraft with more power could decrease duty cycling of basic functions and, therefore, increase the quality and abundance of science data. NASA Glenn Research Center (GRC) is developing a low power dynamic RPS that would convert heat from multiple LWRHU to one watt of usable direct current electric power for spacecraft instrumentation and communication. The power system could be used to charge batteries or capacitors for higher power burst usage. The initial design, called Small Stirling Technology Exploration Power (smallSTEP), is around 3 kg, 11 cm diameter X 32 cm long, and converts 8 watts of heat to one watt of electricity using a Stirling convertor. This low power conversion system represents a new class of RPS with power levels two orders of magnitude lower than prototypes currently being developed for space applications under NASA contracts. Development of the 1-watt RPS includes maturation of convertor and controller designs, performance evaluation of an evacuated metal foil insulation, and development of system interfaces. Initial demonstration of the subsystems has been completed in a laboratory environment and a higher fidelity system is being pursued for demonstration in relevant environments for use on small spacecraft needed to carry out future space science missions.
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.
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The paper presents a distributed approach for operating a network of inverter-based energy storage resources embedded in a bulk power system. Departing from their traditional role of steady-state reserves, the storage assets in the network are utilized as frequency-responsive resources shaping system dynamics. The power electronics converter systems interfacing the storage resources are equipped with local controllers designed to respond under transient disturbances. To this end, a safety-constrained distributed control strategy is explored. The paper compares the performance of converter-interfaced grid-forming and grid-following storage networks for fast frequency control and disturbance containment/localization. Sensitivity studies are performed to study the impact of storage size, steady-state dispatch, and controller design on dynamic performance. The findings are presented through case studies with results from the IEEE test systems.
With the rapid digitization of the world, an increasing number of real-world applications are turning to nonEuclidean data, modeled as graphs. Due to their intrinsic high complexity and irregularity, learning from graph data demands tremendous computational power. Recently, CMOS-compatible Ising machines, i.e., dynamic systems composed of CMOS components, have emerged as a new approach that harnesses the inherent power of natural annealing within dynamic systems to efficiently resolve binary optimization problems and have been adopted for traditional graph computation, such as max-cut. However, when performing complex Graph Learning (GL) tasks, Ising machines face significant hurdles: (i) they are inherently binary and thus ill-suited for real-valued problems; (ii) their expensive all-to-all coupling network that guarantees effective natural annealing poses daunting scalability concerns. To address these challenges, this paper proposes a nature-powered graph learning framework dubbed DS-GL, which is the first effort to transform the process of solving graph learning problems into the natural annealing process within a parameterized dynamic system embodied as a CMOS chip. To tackle the two major hurdles, DS-GL first augments the Ising machine architecture to modify the self-reaction term of its Hamiltonian function from linear to quadratic, effectively serving as an energy regulator. This adjustment maintains the system’s original physical interpretation while enabling it to process continuous, real-valued data. Second, to address the scaling issue, DS-GL further upgrades the real-valued dense Ising machine by decomposing it into a mesh-based multi-PE dynamic system that supports efficient distributed spatial-temporal co-annealing across different PEs through sparse interconnects. By exploiting the inherent sparsity and component structures in real-world graphs, DS-GL is able to map complex graph learning tasks onto the scalable dynamic system while maintaining high accuracy. Evaluations with three diverse GL applications across six real-world datasets, including traffic flow and COVID-19 prediction, show that DS-GL can deliver from 102× to 106× speedups and 500× energy reduction over Graph Neural Networks on GPUs, with 5% - 20% accuracy enhancement.
The fault-induced delayed voltage recovery (FIDVR) phenomenon has been very common from the distribution system through the transmission system. It causes a delay on recovering significantly depressed local voltage after the fault is cleared, and it can also lead to more widespread cascading system failures. Mitigating this event with current control approaches is challenging and becoming a crucial issue. Here, a model predictive control-based strategy employing signal temporal logic specifications is proposed to help mitigate FIDVR. To this end, it investigates and extends a dynamic performance model allowing analytic insights into the system-wide impact of motor stalling and FIDVR. The proposed controller provides richer descriptions of voltage specifications addressing both magnitude and time simultaneously. We consider different control specifications with reactive power support from energy storage systems to prevent the voltage during/after the fault from dropping too low, and reduce the delay time of voltage recovery. The simulation results conducted with the IEEE 57 bus test network validate the proposed method and demonstrate the effectiveness of the mitigation strategy on FIDVR.
As power systems transit to a state of high renewable penetration, little or no presence of synchronous generators makes the prerequisite of well-regulated frequency for grid-following inverters unrealistic. Thus, there is a trend to resort to grid-forming inverters which set frequency directly. We propose a novel grid-forming frequency shaping control that is able to shape the aggregate system frequency dynamics into a first-order one with the desired steady-state frequency deviation and Rate of Change of Frequency (RoCoF) after a sudden power imbalance. The no overshoot property resulting from the first-order dynamics allows the system frequency to monotonically move towards its new steady-state without experiencing frequency Nadir, which largely improves frequency security. We prove that our grid-forming frequency-shaping control renders the system internally stable under mild assumptions. The performance of the proposed control is verified via numerical simulations on a modified Icelandic Power Network test case.
As the integration of renewable energy resources such as wind and solar generation continues to grow, the use of hybrid power plants with both synchronous machines and power electronic inverters operating in parallel becomes more common. This paper studies the impact on small-signal stability for these pairs of devices, first as an isolated two-device system and then as part of a 9-bus test system. Each operational scenario was studied with both a grid-following inverter and a grid-forming inverter. In each scenario, the state variables associated with the synchronous generator's excitation system were found to be responsible for the inception of instability. These results underscore the importance of accurate modeling of excitation systems when modeling power systems with hybrid power plants.
Modeling failure dynamics within a power system is a complex and challenging process due to multiple inter-dependencies and convoluted inter-domain relationships. Subject matter experts (SMEs) are interested in understanding these failure dynamics for reducing the impact from future disasters (i.e., losses or failures of power system components, such as transmission lines). Contingency analysis (CA) tools enable such ’what-if’ scenario analyses to evaluate the impacts on the power system. Analyzing all possible contingencies among N system components can be computationally expensive. An important step for performing CA is identifying a set of k ‘trigger’ components, which when failed initially can significantly impact the overall system by causing multiple failures. Currently SMEs focus on identifying these trigger components by running expensive simulations on all possible subsets, which quickly becomes infeasible. Hence finding a relevant set of trigger components (contingencies) rapidly to enable efficient and useful CA is crucial.In a collaboration between computer scientists and power system experts, we propose an efficient method for performing CA by exploiting network inter-dependencies in power system components. First, we construct a network with multiple electric grid infrastructure components and dependencies as connections among them. We reformulate the problem of finding a set of trigger components as a problem of identifying critical nodes in the network, which can cascade power failures through connected nodes and cause significant damage to the network. To guide the practical CA tools, we develop a network-based model with a probabilistic edge-weights setup using intricate domain rules. Then we conduct an empirical study on real power system data in the US for both regional and national levels. Firstly, we use power system datasets for the US to create a national-scale domain-driven model. Secondly, we demonstrate that network-based model outperforms the outputs from a real CA tool and show on average 25 × improved selection of contingencies, thereby showcasing practical benefits to the power experts.
Parasitic speed controller for alternator rotational speed and frequency regulation in dynamic space power systems, investigating phase controlled loading improvement
The purpose of this grant was to support NASA in modeling efforts to predict the transient dynamic and thermodynamic response of the space station solar dynamic power generation system. In order to meet the initial schedule requirement of providing results in time to support installation of the system as part of the initial phase of space station, early efforts were executed with alacrity and often in parallel. Initially, methods to predict the transient response of a Rankine as well as a Brayton cycle were developed. Review of preliminary design concepts led NASA to select a regenerative gas-turbine cycle using a helium-xenon mixture as the working fluid and, from that point forward, the modeling effort focused exclusively on that system. Although initial project planning called for a three year period of performance, revised NASA schedules moved system installation to later and later phases of station deployment. Eventually, NASA selected to halt development of the solar dynamic power generation system for space station and to reduce support for this project to two-thirds of the original level.
Industrial motor systems make up a quarter of all electric sales in the United States. Variable speed drives (VSDs) can provide energy efficiency savings to the customer by regulating motor speed based on specific and varying needs. In addition to the benefits provided to the customer, VSDs can provide support to the grid through ancillary services. The Center for Ultra-Wide-Area Resilient Electric Energy Transmission Networks (CURENT) developed a power electronics converter-based grid emulator to allow testing of various power system architectures and demonstration of key technologies in monitoring, control, actuation, and visualization. This paper proposes using an active front-end VSD's connected motor load to provide frequency regulation to a large scale power grid. Each part of the emulator is described including motor and power electronics model and control. The proposed frequency regulation is implemented in VSDs and modeled in both a transmission system in EMTDC/PSCAD and verified on CURENT's hardware testbed.