The Use of Triphenyl Phosphate as a Flame Retardant Additive in Lithium-Ion Battery Electrolytes Designed for High Voltage Systems
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improved safety of li-ion batteries↗
SEARCH · Engineering Papers
Results for “system voltage”
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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Sampling Rate Comparison for Distribution System Voltage Measurements
Measurement of the voltage delivered by an electric distribution is a relatively straight forward task. When determining the harmonic distortion in the voltage, matters associated with what orders of the 50/60 Hz harmonics to be analyzed dictate the sampling rate. A study addressing this matter is presented.
42 ENGINEERING↗
Distribution System Voltage Prediction from Smart Inverters using Decentralized Regression
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Mathematics and Computing, Energy - Solar↗
Programmed multiplexing system simultaneously monitors several voltages
System consists of digital voltmeter with binary coded decimal output, programmer, multiplexer, and two to six gated digital displays. Maximum number of circuits monitored is determined by digital voltmeter, rate of change of parameter being measured and complexity of multiplexer design.
Wright, L. S.↗
Conservation Voltage Reduction (CVR) via Two-Timescale Control in Unbalanced Power Distribution Systems
Voltage control devices are employed in power distribution systems to reduce the power consumption by operating the system closer to the lower acceptable voltage limits; this technique is called conservation voltage reduction (CVR). The different modes of operation for system’s legacy devices (with binary control) and new devices (e.g. smart inverters with continuous control) coupled with variable photovoltaic (PV) generation results in voltage fluctuations which makes it challenging to achieve CVR objective. This paper presents a two-timescale control of feeder’s voltage control devices to achieve CVR that includes (1)a centralized controller operating in a slower time-scale to coordinate voltage control devices across the feeder and (2) local controllers operating in a faster timescale to mitigate voltage fluctuations due to PV variability. The centralized controller utilizes a three-phase optimal power flow model to obtain the decision variables for both legacy devices and smart inverters. The local controllers operate smart inverters to minimize voltage fluctuations and restore nodal voltages to their reference values by adjusting the reactive power support. The proposed approach is validated using the IEEE-123 bus (medium-size) and R3-12.47-2 (large-size) feeders. It is demonstrated that the proposed approach is effective in achieving the CVR objective for unbalanced distribution systems.
optimal control, distributed generation, fluctuati↗
High voltage divider system Patent
High voltage divider system for attenuating high voltages to convenient levels suitable for introduction to measuring circuits
Mealy, G. E.↗
Machine Learning-based Cyber-Physical Anomaly Detection in Wide Area Voltage Control Systems
Wide-area voltage control systems (WAVCS) are widely deployed in power grid to improve the voltage stability in transmission system using Flexible AC Transmission System (FACTS) devices. The WAVCS relies on wide-area measurement and control signals for closed-loop control of FACTS devices to improve the transient voltage stability in power grid in real-time. Since the WAVCS utilizes a cyber-layer communication during its normal operation, they are susceptible to cyber attacks from adversaries which can lead to a voltage collapse if the attacks go undetected and unmitigated. This paper proposes a supervised machine learning (ML)-based anomaly detection algorithm for detecting various stealthy cyber attacks in the context of WAVCS cybersecurity. In particular, a fuzzy logic-based wide-area controller, as proposed by the Bonneville Power Administration (BPA), is implemented on the Kundur’s four machine two-area system that is integrated with a static var compensator (SVC) to improve voltage profile on sensitive buses. Later, different types of data integrity attacks, including pulse and ramp attacks, are considered on the wide-area measurement and control signals to analyze the performance of the proposed anomaly detector. Our experimental evaluation shows a promising performance with a high true-positive rate (more than 99%) and low false-negative rate (less than 1%) while exhibiting a small prediction time.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Robust Medium-Voltage Distribution System State Estimation using Multi-Source Data
Due to the lack of sufficient online measurements for distribution system observability, pseudo-measurements from short-term load or distributed renewable energy resources (DERs) forecasting are used. However, the accuracy of them is low and thus significantly limits the performance of distribution system state estimation (DSSE). In this paper, a robust DSSE that integrates multi-source measurement data is proposed. Specifically, the historical low-voltage (LV) side smart meters are used to forecast load and DERs injections via the support vector machine (SVM) with optimally tuned parameters. By contrast, the online smart meters at LV side are utilized to derive equivalent power injections at the MV/LV transformers, yielding more accurate pseudo-measurements compared to the forecasted injections. Furthermore, to deal with bad data caused by communication loss, instrumental errors and cyber attacks, robust DSSE that relies on generalized maximum-likelihood (GM)-estimation criterion is developed. The projection statistics are developed to adjust the weights of each measurement, leading to better balance between pseudo- and real-time measurements. Numerical results conducted on modified IEEE 33-bus system with DG integration demonstrate the effectiveness and robustness of the proposed method.
distribution system state estimation↗
Short-Term State Forecasting-Based Optimal Voltage Regulation in Distribution Systems: Preprint
A novel short-term state forecasting-based optimal power flow (OPF) approach for distribution system voltage regulation is proposed in this paper. An extreme learning machine (ELM) based state forecaster is developed to accurately predict system states (voltage magnitudes and angles) in the near future. Based on the forecast system states, a dynamically weighted three-phase AC OPF problem is formulated to minimize the voltage violations with higher penalization on buses which are forecast to have higher voltage violations in the near future. By solving the proposed OPF problem, the controllable resources in the system are optimally coordinated to alleviate the potential severe voltage violations and improve the overall voltage profile. The proposed approach has been tested in a 12-bus distribution system and simulation results are presented to demonstrate the performance of the proposed approach.
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NASCAP modelling of high-voltage power system interactions with space charged-particle environments
The NASA Charging Analyzer Program (NASCAP), an engineering tool capable of analyzing the impact of the charged particle environment on spacecraft surfaces and systems, is described. NASCAP is a quasi-static computational program which analyzes the charging of a 3-dimensional complex body as a function of time and system-generated voltages for given space environmental conditions. The material properties of the surfaces are taken into account; the surface potentials, low energy sheath, potential distribution in space and particle trajectories are calculated. An application of NASCAP to a simple space solar power station consisting of two 6 m by 18 m solar array wings surrounding a central body is presented. Each solar array wing is considered to be divided into three regions operating at 2000 volts. Results of NASCAP analysis of the system for a normal environment and a moderate geomagnetic substorm environment are discussed.
Stevens, N. J.↗
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.
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Photovoltaic Impact Assessment of Smart Inverter Volt-VAR Control on Distribution System Conservation Voltage Reduction and Power Quality
This report presents an impact assessment study of distributed photovoltaic (PV) with smart inverter Volt-VAR control on conservation voltage reduction (CVR) energy savings and distribution system power quality. CVR is a methodology of flattening and lowering a distribution system voltage profile in order to conserve energy. Traditional CVR relies on operating utility voltage regulators and switched capacitors. However, with the increased penetration of distributed PV systems, smart inverters provide the new opportunity to control local voltage and power factor by regulating the reactive power output, leading to a potential increase in CVR energy savings. This report proposes a methodology to implement CVR scheme by operating voltage regulators, capacitors, and autonomous smart inverter Volt-VAR control in order to achieve increased CVR benefit. Power quality is an important consideration when operating a distribution system, especially when implementing CVR. It is easy to measure the individual components that make up power quality, but a comprehensive method to incorporate all of these values into a single score has yet to be undertaken. As a result, this report proposes a power quality scoring mechanism to measure the relative power quality of distribution systems using a single number, which is aptly named the 'power quality score' (PQS). Both the CVR and PQS methodologies were applied to two distribution system models, one obtained from the Hawaiian Electric Company (HECO) and another obtained from Pacific Gas and Electric (PG&E). These two models were converted to the OpenDSS platform using previous model conversion tools that were developed by NREL. Multiple scenarios including various PV penetration levels and smart inverter densities were simulated to analyze the impact of smart inverter Volt-VAR support on CVR energy savings and feeder power quality. In order to analyze the CVR benefit and PQS, an annual simulation was conducted for each scenario.
14 SOLAR ENERGY↗
Photovoltaic systems with voltage limiting devices
A photovoltaic system includes voltage limiting devices that are connected in series. A voltage limiting device clips a corresponding photovoltaic string to limit a voltage of the photovoltaic string. Unclipping of clipped photovoltaic strings is coordinated by a central controller or in a distributed fashion by the voltage limiting devices based on monitored string conditions.
Truong, Tuan↗
Optimal Voltage Reference for Droop-Based DERs in Distribution Systems
Due to the newly issued standards on distributed energy resources (DERs), the droop-based operation modes (Q-V and P-V droops) become a requirement for all the interconnected DER units at the distribution level. Voltage references of the DER units can be assigned to improve the operational behavior of the distribution system in the smart grid context. This paper presents a novel formulation for optimally setting voltage reference of the droop-based DER units in distribution systems with the objective of minimizing the system ohmic loss. This problem is formulated as a mixed-integer quadratic convex optimization problem in MATLAB and solved by the MATLAB and CPLEX solvers. The IEEE 123-bus system and the EPRI test system Ckt5 are used to validate the proposed formulation. The result obtained from the proposed formulation is compared with the result of the original problem solved by the heuristic method. Based on the numerical study results, system loss can be reduced after the proposed voltage reference assignment. The computational expense of the new formulation is also much lower than that of the heuristic approach.
distributed energy resource integration↗
Design and development of a voltage regulator- exciter for the SNAP-8 nuclear-electrical power-conversion system
Voltage regulator-exciter developed for alternator used in SNAP 8 Rankine cycle nuclear space system
Bradley, S. L.↗
Over-voltage protection system and method
An over-voltage protection system includes an electronic valve connected across two terminals of a circuit and an over-voltage detection circuit connected across one of the plurality of semiconductor devices for detecting an over-voltage across the circuit. The electronic valve includes a plurality of semiconductor devices connected in series. The over-voltage detection circuit includes a voltage divider circuit connected to a break-over diode in a way to provide a representative low voltage to the break-over diode and an optocoupler configured to receive a current from the break-over diode when the representative low voltage exceeds a threshold voltage of the break-over diode indicating an over-voltage condition. The representative low voltage provided to the break-over diode represents a voltage across the one semiconductor device. A plurality of self-powered gate drive circuits are connected to the plurality of semiconductor devices, wherein the plurality of self-powered gate drive circuits receive over-voltage triggering pulses from the optocoupler during the over-voltage condition and switch on the plurality of semiconductor devices to bypass the circuit.
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Anomaly Detection and Mitigation in FACTS-based Wide-Area Voltage Control Systems using Machine Learning
With the increasing deployment of Flexible AC Transmission System (FACTS) devices in wide-area voltage control systems (WAVCS) for achieving improved voltage stability of bulk power systems, the possibility for cyber attacks on these systems is also increasing. Successful stealthy cyber attacks that are difficult to detect by traditional informational technology (IT)-based cybersecurity solutions or threshold-based bad data detectors can lead to a voltage collapse in power grid. This paper presents the testbed-based attacks implementation and real-time evaluation of machine learning (ML) algorithm for detecting and mitigating stealthy cyber attacks on FACTS-based WAVCS on a hardware-in-the-loop (HIL) testbed. Initially, we discuss the implementation of a fuzzy logic controller (FLC) that controls a Static VAR Compensator (SVC) device deployed in a two-area four-machine Kundur power system for improving transient voltage stability. Later, the ML-based Anomaly Detection and Mitigation (ADM) system is implemented on the cyber-physical HIL testbed to detect and mitigate various stealthy cyber attacks, which are injected in real-time over the wide-area network (WAN). The experimental results show accurate and effective performance of ADM system in detecting and mitigating anomalies while keeping the grid stable and within the system operating limits, as defined by the North America Electric Reliability Corporation (NERC).
24 POWER TRANSMISSION AND DISTRIBUTION↗
Data-Driven Multi-agent Deep Reinforcement Learning for Distribution System Decentralized Voltage Control with High Penetration of PVs
This paper proposes a novel model-free/data-driven centralized training and decentralized execution multi-agent deep reinforcement learning (MADRL) framework for distribution system voltage control with high penetration of PVs. The proposed MADRL can coordinate both the real and reactive power control of PVs with existing static var compensators and battery storage systems. Unlike the existing DRL-based voltage control methods, our proposed method does not rely on a system model during both the training and execution stages. This is achieved by developing a new interaction scheme between the surrogate modeling of the original system and the multi-agent soft actor critic (MASAC) MADRL algorithm. In particular, the sparse pseudo-Gaussian process with a few-shots of measurements is utilized to construct the surrogate model of the original environment, i.e., power flow model. This is a data-driven process and no model parameters are needed. Furthermore, the MASAC enabled MADRL allows to achieve better scalability by dividing the original system into different voltage control regions with the aid of real and reactive power sensitivities to voltage, where each region is treated as an agent. This also serves as the foundation for the centralized training and decentralized execution, thus significantly reducing the communication requirements as only local measurements are required for control. Comparative results with other alternatives on the IEEE 123-nodes and 342-nodes systems demonstrate the superiority of the proposed method.
14 SOLAR ENERGY↗