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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Achieving Runtime State Verification Assurance in Critical Cyber-Physical Infrastructures

Industrial Cyber-Physical Systems (ICPS) are an essential backbone of national critical infrastructures. They help monitor and control crucial cyber-enabled services such as energy generation. Commonly ICPS monitors the physical process through Supervisory Control and Data Acquisition (SCADA) systems. The SCADA ecosystem takes critical real-time and future system operational decisions based on the runtime state behavior of field sensors. Traditional SCADA systems use legacy and insecure communication protocols such as the Modbus protocol that lack adequate security mechanisms to provide robust runtime state behavior assurance of constrained field sensors. Therefore, constrained field sensors are commonly vulnerable to standard semantic attacks that gradually change the behavior state of infected devices. This paper discusses process integrity assurance techniques necessary to enhance the security of behavior-based protocols such as the Modbus protocol. The Runtime State Verification (RSV) protocol proposed in this paper aims to address semantic attacks in the SCADA ecosystem by integrating behavior-based Mandatory Results Automata (MRA) and a Hyperledger Fabric (HLF) network. The RSV protocol provides high process integrity assurance through enhanced behavior-based MRA suitable for the constrained field devices. A proof of concept of the RSV protocol has been evaluated in an emulated water-tube boiler. Preliminary evaluations of the RSV protocol aimed to measure the efficiency of the proposed protocol by monitoring an Combustion Efficiency (CE) process necessary to preserve optimal combustion, thus minimizing costs and future maintenance of water-tube boilers. We analyze the overall network overhead and latency of the proposed RSV protocol by evaluating the HLF network performance and comparing the proposed RSV protocol with the state-ofart BloSPAI protocol. Through the preliminary evaluations of the proposed RSV protocol, this paper demonstrates that the proposed RSV protocol overcomes the shortcomings and network overhead of the BloSPAI protocol by integrating behavior-based authentication through novel MRAs and HLF networks.

Rivera, Abel Gomez↗
DOE OSTI2023

Transactive Energy System Deployment Over Insecure Communication Links

Here, in this paper, the privacy and security issues associated with the transactive energy system (TES) deployment over insecure communication links are addressed. In particular, it is ensured that 1) individual agents’ bidding information is kept private throughout hierarchical market-based interactions; and 2) any extraneous data injection attack can be quickly and easily detected. An implementation framework is proposed to enable the cryptography-based enhancement of privacy and security for the deployment of any general hierarchical systems including TESs. Under the proposed framework, a unified cryptography-based approach is developed to achieve both privacy and security simultaneously. Specifically, privacy preservation is realized by an enhanced Paillier encryption scheme, where a block design is proposed to significantly improve computational efficiency. Attack detection is further achieved by an enhanced Paillier digital signature scheme, where a stamp-concatenation mechanism is proposed to enable detection of data replace and reorder attacks. Simulation results verify the effectiveness of the proposed cyber-resilient design for transactive energy systems. Note to Practitioners—This paper is motivated by addressing the issues of cyber resiliency for practically deploying transactive energy system (TES) but it is also applicable to the problem of enhancing the privacy and security for any general hierarchical control systems. TES is an emerging control approach that engages energy suppliers and customers through market operations and uses the price to optimally allocate energy resources. While it has been shown to be promising for power system applications, the underlying market-based interactions raise significant concerns of privacy (data leakage) and security (data tampering). However, existing TES works only focus on the coordination mechanism instead of privacy and security issues. This paper proposes a new cryptography-based TES design for practical deployment. Specifically, to protect privacy, individual supply and demand amounts to be exchanged are all encrypted in a particular way such that the original amounts cannot be inferred from the encrypted amounts, while the desired computation for setting the market clearing price can be carried out over the encrypted amounts, thus generating an encrypted result which, when decrypted, matches that of the same computation over the original amounts. To achieve security, for each exchanged data, its sender generates a particular digital signature which is exchanged together with the data. This enables the receiver to automatically detect the integrity by checking whether a mathematical relationship holds for the pair of data and signature. In our future research, we will investigate more challenging scenarios where some suppliers and customers themselves could be corrupted and purposely submit distorted amounts.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Can I/O Variability Be Reduced on QoS-Less HPC Storage Systems?

For a production high-performance computing (HPC) system, where storage devices are shared between multiple applications and managed in a best effort manner, I/O contention is often a major problem. In this paper, we propose a balanced messaging-based re-routing in conjunction with throttling at the middleware level. This work tackles two key challenges that have not been fully resolved in the past: whether I/O variability can be reduced on a QoS-less HPC storage system, and how to design a runtime scheduling system that can scale up to a large amount of cores. The proposed scheme uses a two-level messaging system to re-route I/O requests to a less congested storage location so that write performance is improved, while limiting the impact on read by throttling re-routing. An analytical model is derived to guide the setup of optimal throttling factor. We thoroughly analyze the virtual messaging layer overhead and explore whether the in-transit buffering is effective in managing I/O variability. Contrary to the intuition, in-transit buffer cannot completely solve the problem. It can reduce the absolute variability but not the relative variability. The proposed scheme is verified against a synthetic benchmark as well as being used by production applications.

Huang, Dan↗
DOE OSTI2022

Commercial Building Planning and Retrofitting Strategy for Grid Services

The increasing integration of distributed energy resources (DERs) plays an important role in improving energy consumption efficiency. In September 2020, the Federal Energy Regulatory Commission (FERC) approved Order 2222 which opens wholesale electricity markets to small capacity DERs. The benefit of this new FERC Order 2222 is that DERs, such as rooftop solar panels and batteries, will be able to participate in regional electricity markets and provide grid services. Meanwhile, the planning and operation strategies of DERs are facing new challenges to account for the impact of the wholesale market with numerous uncertainty factors. Therefore, in this paper, we propose a new planning and retrofitting model for long-term commercial buildings that considers both DER investment and market participation. Specifically, we explore the capability of implementing DERs for grid services. The effectiveness of the proposed model is validated using real-world data. Simulation results also validate that participating in grid services can significantly increase revenues through appropriate building energy management and shorten the payback period of DER investments.

building energy management↗
DOE OSTI2017

A Generalized Precharging Strategy for Soft Startup Process of the Modular Multilevel Converter-Based HVDC Systems

The modular multilevel converter (MMC) has become one of the most promising converter technologies for medium/high-power applications, specifically for highvoltage direct current (HVDC) transmission systems. One of the technical challenges associated with the operation and control of the MMC-based system is to precharge the submodule (SM) capacitors to their nominal voltage during the startup process. In this paper, considering various SM circuits, a generalized precharging strategy is proposed for the MMC-based systems, which can implement soft stratup from dc or ac side. Furthermore, the proposed precharging strategy can be applicabe for various SM circuits and MMC configurations. The proposed startup strategy does not require extra measurements and/or auxiliary power supplies. The charging current is controlled by adjusting the changing rate of the number of blocked and bypassed SM capacitors. Based on the proposed startup strategy, the startup processes of MMC/MMC-HVDC systems based on various SM circuits are analyzed and a generalized startup procedure for various MMC-HVDC systems is proposed. In addition, the uncontrollable steady-state SM capacitor voltages of various MMC-based systems are analyzed and determined, potentially useful in SM design. Our performance of the proposed strategy for various MMC-HVDC systems is evaluated based on time-domain simulation studies in the PSCAD/EMTDC software environment and experimental results based on a scaled-down prototype.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2018

Quantifying Power Distribution System Resiliency Using Code-Based Metric

It is essential to improve the resiliency of power distribution systems (PDS) with the increase in extreme weather events, number of malicious threats and consumers’ need for higher reliability. Here, this paper provides a formal approach to evaluate the operational resiliency of PDS, and quantify the resiliency of a system using a code-based metric. A combination of steady state and dynamic simulation tools is used to determine the resiliency metric. Dynamic simulation tools help with analyzing impact of short-term events, which might affect operational resiliency in long term. A dynamic optimization algorithm for changing operating criteria to increase the sustainability of the most critical loads has been proposed. The proposed theoretical approach is validated using a simple power distribution system model and simulation results demonstrate the ability to quantify the resiliency using the proposed code-based metric. The time-dependent quantification of resiliency has been demonstrated on a test system of two connected CERTS microgrids.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

A New Configuration of Paralleled Modular ANPC Multilevel Converter Controlled by an Improved Modulation Method for 1 MHz, 1 MW EV Charger

In this work, a new configuration of the modular multilevel converter (MLC) based on the parallel connection of three-level active-neutral-point-clamped (3L-ANPC) cells as well as its improved modulation method is proposed for 1 MHz, 1 MW electric vehicle (EV) megacharger. In the proposed paralleled modular ANPC-MLC, only six high-frequency silicon carbide (SiC) power switches operating at 333 kHz are required to generate 1 MHz switching frequency spectrum. Moreover, the operating voltage of all power devices is halved, the magnitude of the first switching frequency harmonic cluster is decreased by the factor of five, and the load current is equally distributed between the 3L-ANPC legs by employing the proposed improved modulation method. Hence, the modularity, efficiency, and power density of the proposed converter are notably increased, whereas the value of passive components and the overall switching loss are remarkably decreased. In addition, an optimized design of the one 3L-ANPC cell of the proposed paralleled modular ANPC-MLC for 1 MHz, 1MW EV megacharger using Ansys SIwave, Icepak, and Q3D finite element method platforms is presented and analyzed in detail. The provided experimental results of the down-scaled setup verify the feasibility and viability of the proposed configuration as well as its improved switching pattern.

42 ENGINEERING↗
DOE OSTI2022

Novel Quadratic High Gain Boost Converter With Adaptive Soft-Switching Scheme and Reduced Conduction Loss

In this article, an improved soft-switching quadratic boost converter is proposed. Instead of inserting an additional active clamp or auxiliary zero-voltage transition circuit at the switching node, the proposed topology connects the high-voltage switching node to the input diode node by replacing one of the input diodes with a low-rated switch. The proposed topology can attain soft-switching condition for all the switches and input diode turns- off under zero-current switching (ZCS). The operation of input-side switch not only aids zero-voltage switching (ZVS) turn- on for the main switch but also helps in reducing the conduction loss. Also, the input-side switch operates under ZCS turn- on and ZVS turn- off , making it a loss economical solution. An adaptive timing scheme for driving the input switch is proposed, which can ensure soft-switching condition under varying gain and load range. The detailed operational modes, analysis, and design considerations of the proposed topology are presented. A 250 W hardware prototype is built to validate the performance of the proposed converter operating at 100 kHz switching frequency. Results with adaptive soft-switching scheme shows that the converter is modulated to achieve its best efficiency condition under various system conditions. Furthermore, a peak efficiency of 96.1% at 155 W and efficiencies above 95.75% over a wide load range are achieved using all Si devices.

14 SOLAR ENERGY↗
DOE OSTI2023

Model-Based Detection Scheme for Spoofed Sensor Data in Grid-Connected Inverters

In this article, a novel method to detect spoofed sensor data (SSD) for grid-connected inverters is proposed. First, a Kalman filter is used to estimate the inverter status in the proposed method. Then, the impact of SSD on the residual between estimation and control reference is analyzed. By leveraging the standard error of residual, an adaptive cumulative sum (CUSUM) chart is developed to achieve fast SSD detection and improve robustness. In addition, the proposed SSD detection method is verified by the hardware experiment. A comparative experiment with a conventional method also demonstrates the rapidity and robustness of the proposed method. Lastly, the performance of the proposed method under different noise covariance matrices is analyzed. Comprehensive analysis shows that the proposed method meets the detection requirement in IEEE 1547 Standard.

42 ENGINEERING↗
DOE OSTI2021

Deep Cellular Recurrent Network for Efficient Analysis of Time-Series Data With Spatial Information

Efficient processing of large-scale time series data is an intricate problem in machine learning. Conventional sensor signal processing pipelines with hand engineered feature extraction often involve huge computational cost with high dimensional data. Deep recurrent neural networks have shown promise in automated feature learning for improved time-series processing. However, generic deep recurrent models grow in scale and depth with increased complexity of the data. This is particularly challenging in presence of high dimensional data with temporal and spatial characteristics. Consequently, this work proposes a novel deep cellular recurrent neural network (DCRNN) architecture to efficiently process complex multi-dimensional time series data with spatial information. Here, the cellular recurrent architecture in the proposed model allows for location-aware synchronous processing of time series data from spatially distributed sensor signal sources. Extensive trainable parameter sharing due to cellularity in the proposed architecture ensures efficiency in the use of recurrent processing units with high-dimensional inputs. This study also investigates the versatility of the proposed DCRNN model for classification of multi-class time series data from different application domains. Consequently, the proposed DCRNN architecture is evaluated using two time-series datasets: a multichannel scalp EEG dataset for seizure detection, and a machine fault detection dataset obtained in-house. The results suggest that the proposed architecture achieves state-of-the-art performance while utilizing substantially less trainable parameters when compared to comparable methods in the literature.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Load-Dependent Soft-Switching Method of Half-Bridge Current Doubler for High-Voltage Point-of-Load Converter in Data Center Power Supplies

With the increased cloud computing and digital information storage, the energy requirement of data centers keeps increasing. A high-voltage point of load (HV POL) with an input series output parallel structure is proposed to convert 400 to 1 VDC within a single stage to increase the power conversion efficiency. The symmetrical controlled half-bridge current doubler is selected as the converter topology in the HV POL. A load-dependent soft-switching method has been proposed with an auxiliary circuit that includes inductor, diode, and MOSFETs so that the hard-switching issue of typical symmetrical controlled half-bridge converters is resolved. The operation principles of the proposed soft-switching half-bridge current doubler have been analyzed in detail. Then, the necessity of adjusting the timing with the loading in the proposed method is analyzed based on losses, and a controller is designed to realize the load-dependent operation. A lossless RCD current sensing method is used to sense the output inductor current value in the proposed load-dependent operation. In conclusion, experimental efficiency of a hardware prototype is provided to show that the proposed method can increase the converter's efficiency in both heavy- and light-load conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Current-Source Solid-State DC Transformer Integrating LVDC Microgrid, Energy Storage, and Renewable Energy Into MVDC Grid

Solid-state DC transformer to integrate low-voltage DC (LVDC) microgrid, wind turbine (WT) generator, photovoltaic (PV), and energy storage (ES) into medium-voltage (MV) direct-current (MVDC) distribution grids is attractive. This paper proposes current-source DC solid-state transformer (SST) for MVDC collection system in WT, PV, and ES farms or as an interface between the MVDC grid and the LVDC microgrid. Compared to conventional current-source converter (CSC) based SSTs, a switch reduction scheme on reverse-blocking device bridges is proposed to reduce device count and the number of devices on the DC-link current path. Importantly, the proposed switch reduction scheme is generic and can be applied to the DC ports of DC-AC, AC-DC, or DC-DC hard-switching or soft-switching CSC-based SSTs. Based on this scheme, the proposed current-source DC SSTs are derived, which have reduced electrolytic-capacitor-less DC-link. The proposed DC SSTs also achieve single-stage isolated DC-DC or DC-AC conversion, full-range zero-voltage switching (ZVS) for main switches, zero-current switching (ZCS) for resonant switches, and controlled dv/dt. The proposed DC SSTs, operating principles, predictive control method, the ZVS, and the controlled dv/dt under voltage buck-boost ranges are verified with MV simulations and an experimental prototype based on SiC MOSFETs, diodes, and a nanocrystalline transformer.

14 SOLAR ENERGY↗
DOE OSTI2022

DC-Link Current Minimization Control for Current Source Converter-Based Solid-State Transformer

This article proposes a fast predictive control method and a small DC-link inductor to minimize the DC-link current in current-source converter (CSC)-based solid-state transformer. The DC-link current minimization can significantly reduce power loss and improve efficiency. The challenge of this problem is on improving both steady-state and dynamic performance. PI control methods and large DC-link inductors are conventionally used in the CSC but have limited dynamic performance. A model predictive control (MPC) method is proposed to achieve switching-cycle-level settling time, and the DC-link inductor is sized for 40% ripple to enable fast current change. Importantly, this article also proposes to minimize the DC-link current by varying the current even within a line cycle under single-phase load to improve the steady-state performance, in contrast with the reduction to a constant value in the literature. The proposed MPC features a constant switching frequency without weighting factors. The MPC does not have a high computational burden and is implemented in a regular digital controller for a prototype of soft-switching solid-state transformer (S4T) with reduced conduction loss. The effectiveness of the proposed method has been experimentally verified on the SiC S4T prototype during steady-state and dynamics under different multiport power flow conditions up to 2 kV peak. Here, the DC-link current in the experiments is close to the minimum current with a short zero-vector duration, which further verifies the performance of the proposed method.

14 SOLAR ENERGY↗
DOE OSTI2019

Exact Optimal Power Dispatch in Unbalanced Distribution Systems With High PV Penetration

Smart inverters provide additional control capability to help optimize the operation of distribution systems. This paper proposes a framework for exact optimal active and reactive power dispatch of distributed photovoltaic (PV) generation, switched capacitors, and tap changers in large multi-phase unbalanced distribution systems. The objectives of the optimal dispatch are minimization of the energy loss, PV active power curtailment, and capacitor and tap changer switching operations, in addition to elimination of voltage violations and reverse power flow. The optimization problem is formulated in rectangular coordinates as a nonlinear, nonconvex problem. Effective computational strategies are proposed to allow the application of predictorcorrector primal-dual interior point method to solve optimization problems in real-time with a large number of constraints and variables, including discrete variables corresponding to switched capacitors and tap changers. The accuracy of the numerical solution and the ability to implement the proposed framework are validated using the unbalanced multi-phase IEEE 34-bus and EPRI 2,998-bus distribution systems with 15-minute load and PV data. The results show a significant loss reduction and complete removal of both voltage violations and reverse power flow.

Nguyen, Quan (ORCID:0000000347769557)↗
DOE OSTI2019

Availability Assessment Based Case-Sensitive Power System Restoration Strategy

Increasingly frequent severe weather events in recent years threaten the security of power systems and result in major power outages throughout the world. The development of reasonable power system restoration (PSR) solutions is therefore urgently needed to speed up the recovery of the power supply while at the same time steering clear of vulnerable and risky equipment. This paper aims to develop a case-sensitive PSR model for power transmission systems that can adjust restoration solutions according to the evaluated availability of outage equipment in specific blackout scenarios and weather conditions. A novel PSR model that integrates the startup of generating units, formulation of the restoration network, renewable energy sources, and availability assessment of devices is proposed. A reformulated model is also proposed to relieve the computational burden of complex PSR problems. The availability of outage equipment is comprehensively assessed based on historical operating records, fault diagnosis results, and weather conditions. The assessed availability results are sensitive to the characteristics of real blackout cases and will support system operators generate case-sensitive PSR solutions while mitigating the vulnerable equipment. The feasibility and effectiveness of the proposed PSR model and its reformulations are verified through case studies.

availability assessment↗
DOE OSTI2021

Advanced Performance Metrics and their Application to the Sensitivity Analysis for Model Validation and Calibration

High-quality generator dynamic models are critical to reliable and accurate power systems studies and planning. With the availability of PMUs, measurement-based approach for model validation has gained significant prominence. In this approach, the quality of a model is analyzed by visually comparing measured generator response with the model-based simulated response for large system disturbances. This paper proposes a new set of performance metrics to assess the model validation results to facilitate automation of the model validation process. In the proposed methodology, first, the slow governor response and comparatively faster oscillatory response are separated, and then a separate set of performance metrics is calculated for each of these two components. These proposed metrics quantify the mismatch between the actual and model-based response in a comprehensive manner without missing any information enabling automation of the process. Furthermore, in this paper, we are also proposing that the sensitivity analysis for model calibration be performed with respect to the proposed metrics for the systematic identification of key parameters. In this work, results obtained using both simulated and real-world case-studies validate the effectiveness of the proposed performance metrics for model validation and their application to the sensitivity analysis for model calibration.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

DGs for Service Restoration to Critical Loads in a Secondary Network

During a major outage in a secondary network distribution system, distributed generators (DGs) connected to the primary feeders as well as the secondary network can be used to serve critical loads. This paper proposed a resilience-oriented method to determine restoration strategies for secondary network distribution systems after a major disaster. Technical issues associated with the restoration process are analyzed, including the operation of network protectors, inrush currents caused by the energization of network transformers, synchronization of DGs to the network, and circulating currents among DGs. A look-ahead load restoration framework is proposed, incorporating technical issues associated with secondary networks, limits on DG capacity and generation resources, dynamic constraints, and operational limits. The entire outage duration is divided into a sequence of periods. Restoration strategies can be adjusted at the beginning of each period using the latest information. Numerical simulation of the modified IEEE 342-node low voltage networked test system is performed to validate the effectiveness of the proposed method.

Xu, Yin (ORCID:0000000209459024)↗
DOE OSTI2019

Analytic Estimation Method of Forced Oscillation Amplitude Under Stochastic Continuous Disturbances

This paper proposes an analytic method for the amplitude estimation of the forced oscillation under stochastic continuous disturbances (SCDs). There is considerable interest in the integration of intermittent renewable energy resources into a power system, which leads to the power system in an environment with SCDs. Thus, the forced oscillation issues under SCDs are of concern. In this paper, the SCDs are described as continuous-time stochastic processes, and then the systems under SCDs are modeled by stochastic differential algebraic equations. Furthermore, by employing stochastic theory, an efficient analytic method for calculating the statistics of system states during the forced oscillation is proposed. Moreover, a novel forced oscillation phenomenon, which presents system states oscillate with stationary distributions under SCDs, is clearly characterized and theoretically explained. Based on the proposed analytic method, a scheme is put forth to estimate amplitudes of system states during forced oscillation under SCDs. Finally, compared to Monte Carlo simulation, the proposed scheme has two significant advantages. First, the proposed scheme offers a fast and effective solution for engineering applications. Second, the impact mechanism of SCDs on forced oscillation in power system is clearer, by the proposed scheme.

42 ENGINEERING↗