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At least 613 records · Page 34

Integrating Learning and Physics based Computation for Fast Online Transient Analysis

In this work, a novel method that integrates learning and physics based computation is developed for greatly accelerating the simulation of full power system transient trajectories. To solve the dynamic algebraic equations, the method replaces the time-consuming dynamic computation for generator dynamics with trained predictors, while retaining the time-efficient algebraic computation of solving AC-power flow (PF) for power systems. In particular, a predictor is trained for each generator, and the system trajectories are computed by alternating steps of calling the predictors and solving AC-PF. The proposed method also allows fully parallelizable training strategies and a flexible trade-off between training time and testing accuracy. Comprehensive evaluations of the proposed method for transient/dynamic contingency analysis of the New York/New England 16-machine 68-bus power systems demonstrate excellent performance and significant acceleration of computation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Multi-Timescale Integrated Dynamic and Scheduling Model (MIDAS-Solar)

Solar photovoltaic (PV) installations have experienced unprecedented growth in the United States. PV will become not only an energy producer but also a necessary provider of ancillary services at multiple timescales. Conventional methods to simulate power system operations - such as long-term production simulation (which typically considers schedules from hours to minutes by using an optimization framework) and short-term transient studies (which simulate dynamics from seconds to sub-seconds using state variables and differential equations) are not sufficient for studying the multiple-timescale variation of solar generation and its impact on system reliability. Long-term system economics and short-term system dynamics are highly coupled, particularly when the penetration level of renewable generation is extremely high, because the uncertainty and variability of solar generation will impact both power systems steady-state and dynamic performance. This project helps meet and exceed the Solar Energy Technologies Office goal of systems integration by directly addressing this stability and reliability challenge for electric grid planning and operation. This will be accomplished by developing temporally comprehensive, closed-loop simulation models that seamlessly simulate power systems operations from economic scheduling (day-ahead to hours) to dynamic response analysis (seconds to sub-seconds). Both a multi-timescale grid model and an integrated PV model will be developed in this project to accurately study the impacts of PV variability and uncertainty on system reliability at multiple timescales. Using quasi-dynamic simulation methods and data-driven security assessment (DSA) criteria will allow the dynamic characteristics of PV to be fed forward into longer-timescale scheduling models for a complete understanding of the effect of short-term PV dynamics on bulk systems operations (e.g., reserve scheduling and deployment). Upon completion of the proposed model, this project will help operators accurately assess system reliability by deploying energy and reserve scheduling under critical contingency conditions and studying interactions among all types of essential reliability services provided by modern PV power plants.

14 SOLAR ENERGY↗

Hardware Assessment in Support of the Dynamic Power Convertor Development Effort

Stirling Radioisotope Power Systems (RPS) are being developed by NASAs RPS Program in collaboration with the U.S. Department of Energy (DOE). Efforts ranging from 2001 to 2015 enabled development of the Technology Demonstration Convertor (TDC) for use in the 110-watt Stirling Radioisotope Generator (SRG-110) and the Advanced Stirling Convertor (ASC) for use in the Advanced Stirling Radioisotope Generator (ASRG). The DOE selected Lockheed Martin Space Systems Company (LMSSC) as the system integration contractor for both flight development efforts. The SRG-110 housed two TDCs fabricated by Infinia and resulted in the production of 16x demonstration units and 2x engineering units. The project was redirected in 2006 to make use of a more efficient and lower mass ASCs under development by Sunpower Inc. The DOE managed the flight contract with LMSSC and subcontractor Sunpower Inc. from 2007 to 2013 to build the ASRG, with support from NASA Glenn Research Center (GRC). Sunpower Inc. held two parallel contracts to produce ASCs, one with Lockheed Martin to produce ASC-F flight units and one with GRC for the production of ASC-E3 engineering unit pathfinders that were used to refine the flight design and production processes. The DOE initiated termination of the ASRG contract in late 2013. After ASRG had ended, GRC completed characterization testing of the ASRG Engineering Unit 2 (EU2) and the GRC contract with Sunpower was also completed. The NASA RPS Program Office has recently initiated a new Dynamic Power Conversion development effort which includes the potential maturation of Stirling, Brayton, and Rankine power convertors for the next generation of RPS. The effort started with the request for proposal and review of submits. Contracts are anticipated for release in 2017 and will initially focus on a design phase prior to fabrication and testing. This new effort will focus on robustness in addition to high efficiency, specific power, and reliability. Also, some requirements introduced during the ASRG contract have also been included in the new effort, such as constant lateral loading. Due to the focus on robustness and new requirements relative to the older TDC design, the Stirling Cycle Development Project has initiated an assessment of government owned hardware to help inform requirements evolution and evaluation of future designs. While lessons learned from the ASRG flight development project have been taken into consideration, the evaluation of the TDC design had not been completed for some existing environments or relatively new requirements. To further assess the TDC design, a series of tasks were initiated to evaluate degradation for units that have operated unattended for over 105,000 hours, demonstrate robustness to a random vibration environment, characterize and evaluate performance for varying lateral load profiles. The status for each task are described.

Wilson, Scott D.↗

Hardware Assessment in Support of the Dynamic Power Convertor Development Effort

Stirling Radioisotope Power Systems (RPS) are being developed by NASA's RPS Program in collaboration with the U.S. Department of Energy (DOE). Efforts ranging from 2001 to 2015 enabled development of the Technology Demonstration Convertor (TDC) for use in the 110-watt Stirling Radioisotope Generator (SRG-110) and the Advanced Stirling Convertor (ASC) for use in the Advanced Stirling Radioisotope Generator (ASRG). The DOE selected Lockheed Martin Space Systems Company (LMSSC) as the system integration contractor for both flight development efforts. The SRG-110 housed two TDCs fabricated by Infinia and resulted in the production of 16x demonstration units and 2x engineering units. The project was redirected in 2006 to make use of a more efficient and lower mass ASCs under development by Sunpower Inc. The DOE managed the flight contract with LMSSC and subcontractor Sunpower Inc. from 2007 to 2013 to build the ASRG, with support from NASA Glenn Research Center (GRC). Sunpower Inc. held two parallel contracts to produce ASCs, one with Lockheed Martin to produce ASC-F flight units and one with GRC for the production of ASC-E3 engineering unit pathfinders that were used to refine the flight design and production processes. The DOE initiated termination of the ASRG contract in late 2013. After ASRG had ended, GRC completed characterization testing of the ASRG Engineering Unit #2 (EU2) and the GRC contract with Sunpower was also completed. The NASA RPS Program Office has recently initiated a new Dynamic Power Conversion development effort which includes the potential maturation of Stirling, Brayton, and Rankine power convertors for the next generation of RPS. The effort started with the request for proposal and review of submits. Contracts are anticipated for release in 2017 and will initially focus on a design phase prior to fabrication and testing. This new effort will focus on robustness in addition to high efficiency, specific power, and reliability. Also, some requirements introduced during the ASRG contract have also been included in the new effort, such as constant lateral loading. Due to the focus on robustness and new requirements relative to the older TDC design, the Stirling Cycle Development Project has initiated an assessment of government owned hardware to help inform requirements evolution and evaluation of future designs. While lessons learned from the ASRG flight development project have been taken into consideration, the evaluation of the TDC design had not been completed for some existing environments or relatively new requirements. To further assess the TDC design, a series of tasks were initiated to evaluate degradation for units that have operated unattended for over 105,000 hours, demonstrate robustness to a random vibration environment, characterize and evaluate performance for varying lateral load profiles. The status for each task are described.

Wilson, Scott D.↗

Development of Real-Time System Identification to Detect Abnormal Operations in a Gas Turbine Cycle

Here, we present a novel online system identification methodology for monitoring the performance of power systems. This methodology was demonstrated in a gas turbine recuperated power plant designed for a hybrid configuration. A 120-kW Garrett microturbine modified to test dynamic control strategies for hybrid power systems designed at the National Energy Technology Laboratory (NETL) was used to implement and validate this online system identification methodology. The main component of this methodology consists of an empirical transfer function model implemented in parallel to the turbine speed operation and the fuel control valve, which can monitor the process response of the gas turbine system while it is operating. During fully closed-loop operations or automated control, the output of the controller, fuel valve position, and the turbine speed measurements were fed for a given period of time to a recursive algorithm that determined the transfer function parameters during the nominal condition. After the new parameters were calculated, they were fed into the transfer function model for online prediction. The turbine speed measurement was compared against the transfer function prediction, and a control logic was implemented to capture when the system operated at nominal or abnormal conditions. To validate the ability to detect abnormal conditions during dynamic operations, drifting in the performance of the gas turbine system was evaluated. A leak in the turbomachinery working fluid was emulated by bleeding 10% of the airflow from the compressor discharge to the atmosphere, and electrical load steps were performed before and after the leak. This tool could detect the leak 7 s after it had occurred, which accounted for a fuel flow increase of approximately 15.8% to maintain the same load and constant turbine speed operations.

algorithms↗

Kilopower Reactor Using Stirling TechnologY (KRUSTY) Nuclear Ground Test Results and Lessons Learned

The Kilopower nuclear ground testing nicknamed KRUSTY (Kilopower Reactor Using Stirling TechnologY) was completed at the Nevada Nuclear Security Site (NNSS) on March 21, 2018. This full scale nuclear demonstration verified the Kilopower reactor neutronics during startup, steady state, and transient operations in a space simulated environment. This was the first space reactor test completed for fission power systems in over 50 years and marked a turning point in NASA's nuclear program. The completed reactor power system design incorporated flight prototypic materials and full-scale components in an effort to study the reactor dynamics at full power and significantly reduce follow on risk of a future flight demonstration. This design provided a unique opportunity for the power system to simulate several nominal and off-nominal mission scenarios that allowed the designers to verify that the reactor dynamics could tolerate many worst case conditions regarding reactor stability and control. The dynamic changes imposed on the reactor validated the ability of the reactor to load follow the power conversion system and passively control the fuel temperature and overall system stability. With successful completion of the KRUSTY experiment, the NASA/DOE team will evaluate the lessons learned throughout the project and apply them towards a flight demonstration of a Kilopower reactor.

Gibson, Marc A.↗

Wave Energy Converter Power Take-Off Modeling and Validation From Experimental Bench Tests

This article describes the implementation of a new numerical model of the power take-off system installed in the Monterey Bay Aquarium Research Institute wave energy converter, a device developed to provide power to various oceanic research missions. The simultaneous presence of hydraulic, pneumatic, and electrical subsystems in the power take-off system represents a significant challenge in forging an accurate model able to replicate the main dynamic characteristics of the system. The validation of the new numerical model is addressed by comparing simulations with the measurements obtained during a series of bench tests. Data from the bench tests show good agreement with the numerical model. The validated model provides deeper insights into the complex nonlinear dynamics of the power take-off system and will support further performance improvements in the future.

16 TIDAL AND WAVE POWER↗

Hybrid Modeling of Three-Phase Grid-Supporting Inverters for Dynamic Studies

Grid technologies connected by power electronic converter (PEC) interfaces continually implement grid support functions mandated by grid codes and standards. The transition to converter-based generation demands precise PEC models to assess system dynamics, which have been previously overlooked in conventional power systems. This study proposes a hybrid method for analyzing grid-connected three-phase PEC dynamics with the IEEE standard 1547-2018 Volt-VAr mode that combines physics and data-driven techniques. The physics model reflects the PEC’s internal behavior, whereas the data-driven modeling technique evaluates the grid-supporting capabilities of the smart PEC. The system identification approach is used to generate dynamic PEC models based on changing grid voltage and measured current injected into the grid by the PEC. In the Volt-VAr support mode, a detailed topological model including switches is utilized to compare the goodness-of-fit of the extracted hybrid dynamic model. The results demonstrate that the hybrid PEC model in the Volt-VAr mode accurately matches the dynamics with the topological model.

Subedi, Sunil↗

Model, Design, and Control for Power Conversion in Wave Energy Converter System

Wave energy, if all been harvested along the U.S. coastline, can power around 65% of the energy consumption in U.S.. Comparing to other renewable energy sources like solar or wind, ocean wave can provide up to 90% of steady uptime. With the high energy density (2-3 kW/m 2 ), it can produce more energy with the same amount of installation area comparing to the energy density of wind turbine (0.6 kW/m 2 ) and solar panel(0.2 kW/m 2 ). The predictability of wave provides advantages like planning installation, power dispatching, and maintenance activities. Although with all these advantages, wave energy converter system is still in the research stage due to its high system cost per electricity production. One of the challenges that need to be solved is the irregularity from the wave motion that leads to high instantaneous peak power into the wave energy converter, which usually reaches up to 10 - 20 times of the average power. The high peak power will not only bring high mechanical/electrical stress but also result in an overrating design of the components in the system. Another obstacle that prevents the wave energy system from moving forward is the high testing cost from the validations in wave-energy-test sites or tank-test sites. A high-fidelity multi-disciplinary system model, including hydrodynamics, mechanical dynamics, electromagnetics, and power electronics, is needed to predict the behavior of the system and reduce the cost of design validation.

16 TIDAL AND WAVE POWER↗

Distribution System Segmented Model Simplification with Independent Dynamically Changing End-Use Loads

With more emerging technologies in power distribution systems, to support quasi-static time-series (QSTS) simulation over short time frames, accurately modeling the dynamic behavior of end-use load under various conditions is im- portant. However, time and cost can be a burden for the QSTS simulation of thousands of houses representing dynamic load behaviors on large distribution feeders. There are two main contributions of this paper in order to reduce the QSTS simulation complexity. First, the paper presents a method to stochasti- cally model the dynamic behavior of end-use load for QSTS simulations. Second, using the stochastically modeled load behavior as an input to a distribution sys- tem, and building on our previous QSTS simulation simplification/acceleration method that relies on uniform load behavior, this paper presents a segment substitution approach for the simplification of distribution system models with independent dynamically changing end-use loads. Our numerical results show that compared to GridLAB-D, a software tool that simulates end-use load be- havior through physical models, the proposed stochastic modeling approach achieved an 89.3% simulation time reduction for end-use loads, while accurately capturing the temporally changing total load behavior. Moreover, the QSTS simulation of a large test distribution system through OpenDSS showed that the proposed simplification method decreased the feeder simulation time by a factor of three at less than 0.3% voltage error. Compared to our previous method with independent dynamic loads, the voltage error is reduced by a factor of four.

Power distribution system modeling, stochastic pro↗

Multi-level optimization with the koopman operator for data-driven, domain-aware, and dynamic system security

Cyber-Physical Systems (CPSs) like the power grid are critically important but also increasingly vulnerable; ensuring reliable system operation in the face of disruptions is becoming more and more challenging. Multi-Level Optimization (MLO) is a powerful way to model adversarial interactions, which naturally makes it applicable to studying CPS security. However, MLO typically does not address underlying system dynamics, and incorporating nonlinear dynamics is generally infeasible. In this paper, we show how to combine MLO with the Koopman Operator (KO) to remedy this. The KO maps nonlinear dynamics to a lifted space in which those dynamics are linear, thus making it ideal for use with MLO. Moreover, the structure of the KO also provides convenient ways to incorporate domain knowledge into the data-driven process of learning the KO representation of a given system. Here we then demonstrate the use of MLO-KO on a small example problem taken from the power grid domain, discuss the scalability and computational cost of MLO-KO, and identify future research directions for this work.

42 ENGINEERING↗

Dynamic Restoration Strategy for Distribution System Resilience Enhancement

In electric power distribution systems, distributed energy resources (DERs) can act as controllable power sources and support utility operators to minimize power outages after extreme weather events (e.g., hurricane, earthquake, wildfire) and thus help enhance the grid's resilience. Meanwhile, the influences of extreme events and the capabilities of DERs are dynamic and difficult to predict. Hence, the desired distribution system restoration strategy should be able to evolve according to real-time fault/dis-turbance information and the availability of DERs. In this paper, we propose a new dynamic restoration strategy for distribution systems to enhance system resilience against potential hazards. An efficient reconfiguration algorithm is developed to eliminate the use of integer variables to relieve the computational burden. Model predictive control is implemented to adjust the system topology and DER operation set points based on the updated fault information and DER forecasts. The effectiveness of the proposed restoration model in enhancing distribution system resilience is validated through an IEEE 123-bus test system. Simulation results also validate that the proposed restoration model can mitigate the occurrence of unexpected events and the fluctuations of DERs.

distributed energy resources (DERs)↗

Neural Lyapunov Control for Power System Transient Stability: A Deep Learning-Based Approach

We report that power system control and transient stability analysis play essential roles in secure system operation. Control of power systems typically involves highly nonlinear and complex dynamics. Most of the existing works address such problems with additional assumptions in system dynamics, leading to a requirement for a complete and general solution. This paper, therefore, proposes a novel control framework for various power system control and stability problems leveraging a learning-based approach. The proposed framework includes a two-module structure that iteratively and jointly learns the candidate Lyapunov function and control law via deep neural networks in a learning module. Meanwhile, it guides the learning procedure towards valid results satisfying Lyapunov conditions in a falsification module. The introduced termination criteria ensure provable system stability. This control framework is verified through several studies handling different types of power system control problems. The results show that the proposed framework is generalizable and can simplify the control design for complex power systems with the stability guarantee and enlarged region of attraction.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Structural Dynamic Assessment of the GN2 Piping System for NASA's New and Powerful Reverberant Acoustic Test Facility

The National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) has led the design and build of the new world-class vibroacoustic test capabilities at the NASA GRC's Plum Brook Station in Sandusky, Ohio, USA from 2007 to 2011. SAIC-Benham has completed construction of a new reverberant acoustic test facility to support the future testing needs of NASA's space exploration program and commercial customers. The large Reverberant Acoustic Test Facility (RATF) is approximately 101,000 cubic feet in volume and was designed to operate at a maximum empty chamber acoustic overall sound pressure level (OASPL) of 163 dB. This combination of size and acoustic power is unprecedented amongst the world s known active reverberant acoustic test facilities. Initial checkout acoustic testing was performed on March 2011 by SAIC-Benham at test levels up to 161 dB OASPL. During testing, several branches of the gaseous nitrogen (GN2) piping system, which supply the fluid to the noise generating acoustic modulators, failed at their T-junctions connecting the 12 in. supply line to their respective 4 in. branch lines. The problem was initially detected when the oxygen sensors in the horn room indicated a lower than expected oxygen level from which was inferred GN2 leaks in the piping system. In subsequent follow up inspections, cracks were identified in the failed T-junction connections through non-destructive evaluation testing. Through structural dynamic modeling of the piping system, the root cause of the T-junction connection failures was determined. The structural dynamic assessment identified several possible corrective design improvements to the horn room piping system. The effectiveness of the chosen design repairs were subsequently evaluated in September 2011 during acoustic verification testing to 161 dB OASPL.

McNelis, Mark E.↗

A modern control approach to the design of the SPS control system

The structural dynamics of the solar power satellite were considered. The requirements on the vibration of the microwave antenna and the possibility of thermal induced vibration and severe structural-thermal interactions were considered. The possibility of using an active control system and modern control methods to mitigate structural problems is discussed.

Gran, R.↗

Artificial intelligence approaches in space power systems automation at Marshall Space Flight Center

Various applications of AI to spacecraft electrical power systems are described. Particular attention is given to NICBES (nickel-cadmium battery expert system which is interfaced with the Hubble Space Telescope electrical power system test bed); the SSES; the three cooperating AI systems in the Space Station module power management and distribution system test bed; and I-DARE, the intelligent data reduction expert. It is found that the utilization of AI approaches permits comprehensive fault management and dynamic rescheduling capabilities for the electrical power system.

Weeks, David J.↗