Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “INTERNET”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,747 records · Page 97

Embedded Optical Sensing Systems For Distribution Transformer Monitoring

Traditional utility monitoring systems do not provide real-time visibility into the condition of transformers or accurate performance measurements. This has resulted in the use of lagging indicators, such as oil sample analysis, typically requiring expensive field visits, grid outages, and laboratory sample testing. This presentation reviews the use of optical sensing systems for managing transformers and improving grid resiliency and safety. The sensing systems allow direct internal monitoring of critical transformer components. Versatility covering different monitoring parameters of interest in embedded configurations for new transformers and a retrofittable configuration for older transformers is achieved by applying hair-thin multiplexed fiber-optic and other low-profile optical sensors in combination with a high-resolution optical readout and advanced analytics. Under an initiative funded by the DOE Office of Electricity, PARC, GE and Con Edison built, tested, and qualified commercial network transformers with embedded optical sensing systems. The parameters monitored were validated across a range of scenarios with lab instruments typically used for qualification testing. An ongoing field trial to demonstrate the robustness of the technology for remote monitoring through the industrial internet under demanding grid deployment conditions in New York City is showing promise toward scale-up of the technology. This presentation will provide an overview of the typical pain points in managing transformers and parameters for monitoring. It will also cover the requirements for highly constrained installations that need to have a larger capacity and flexible rating but that must fit into a tight space. The unique capabilities of optical sensing systems and a low-cost approach to interpreting the signals from sensors in transformers for predictive maintenance will be covered. The presentation will discuss the compatibility of the sensors in the transformer environment. It will discuss the validation testing per IEEE standards that enabled the solution to be implemented in field-deployable commercial transformers. The initial results from the field deployment and the potential for the technology to provide systematic alerts for unsafe/unexpected events will be discussed. The technology could enable utility professionals to gain information they can use to better plan for maintenance/management, and improve grid performance. This would in turn accommodate DERs and other evolving grid market dynamics.

24 POWER TRANSMISSION AND DISTRIBUTION↗

ModuleOT: A Hardware Security Module for Operational Technology: Preprint

With increasing penetration levels of distributed energy resources (DERs) on the distribution grid, as well as new technological advancements in the cyber space, new cyberattack vectors are being introduced, and the available attack surface is constantly increasing. Despite this increasing risk, the standard IEEE 1547-2018 does not yet recommend cybersecurity measures for DERs. To address this and to better protect data on the distribution grid - from the standpoints information security as well as operational security - ModuleOT has been developed. The module aims to significantly reduce cyberattack vectors by improving data privacy for user applications. This is accomplished by performing the core functions of encryption, authentication, authorization, certificate management, and user access control. The module integrates a custom security application with hardware cryptographic acceleration. The application secures all communications using Transmission Control Protocol over Internet Protocol (TCP/IP). These include the three most commonly used communications protocols for power systems information exchange: Modbus, Distributed Network Protocol 3 (DNP3), and Smart Energy Profile 2.0 (SEP2.0). These three protocols are also supported by IEEE 1547-2018 for all DER devices. This paper tests the data encryption/decryption feature on a physical networking test bed with emulated Modbus devices reporting grid data and presents the results.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Computer Security Training

Computers and the internet have changed our lives for the good in many ways, but with change comes risk. In a nuclear regime, risk must be managed appropriately, and to do so, personnel must be properly trained. There are multiple ways to train personnel; however, to properly engage learners and have the key principles transferred to their work environment within their computer security programs, there are two main instructional strategies that should be used. One is for basics concepts and principles while the other is for advanced concepts that is meant to be taken away and applied in their work environment.

Training, computer security, nuclear security, ins↗

Remote Hardware-in-the-Loop Approach for Microgrid Controller Evaluation: Preprint

Utilities have been installing microgrids due to the advancements in the distributed energy resources technologies. Microgrids also improve the resiliency of the system due to their capability to isolate themselves from the grid and run in islanded mode of operation. Microgrid controllers are management systems that can run the microgrids under varied operating condition and enable the smooth operation of microgrids under various system conditions. It is of high value to de-risk the installation of such controllers. Hardware-in-the-loop evaluation is used by controller developers and utilities to evaluate the controllers under stressful conditions to understand the performance and to understand the necessary improvements to the microgrid controller. In this research work, the team has leveraged the existing infrastructure of real-time simulation at the Energy Systems Integration Facility (ESIF) and the capability of the microgrid controller to control assets over the Internet Protocol (IP) to evaluate a university developed microgrid controller in an efficient and cost-effective manner. The full paper will provide the complete setup, the experimental use cases and the results. In this abstract, one use case will be expalined, and the results from the use case is provided.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Secure and Cost-Effective Micro Phasor Measurement Unit (PMU)-Like Metering for Behind-the-Meter (BTM) Solar Systems Using Blockchain-Assisted Smart Inverters: Preprint

Recently, there is increasing interest in using behind-the-meter (BTM) solar systems for grid services. However, providing visibility and operational situational awareness of BTM solar systems mainly operated by small-scale solar inverters is challenging due to the requirement of relatively expansive networked observation tools (e.g., micro phasor measurement units (uPMUs)) and consequent cybersecurity threats through networks. This paper presents a secure, cost-effective, uPMUs-like metering method using a blockchain-assisted smart (BAS) inverters for a BTM solar system. The proposed BAS inverter consisting of an internet-of-things device as a node of a local blockchain network enables the secure provision of inverter measurement data for grid services. The BAS inverter sends the encrypted local measurement data with a timestamp to a local blockchain miner. Once the blockchain miner generates a tamper-resistant metering ledger including the measurements, it is used to assess the situational awareness of the BTM solar system. The concept of the proposed metering using the BAS inverters is validated by experimental studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Broadband Communications Using High Voltage Transmission Lines - A Review

The possibilities afforded by using an existing transmission line infrastructure for the transport of broadband communications are many ranging from (conventional) A-to-B point-to-point links, to integration of Wi-Fi access points mounted at defined network (power and communications) locations, to operation as a fault-tolerant, rollover backup communications fabric (in conjunction with other transport media, such as optical fiber or terrestrial microwave). As stated by RCR Wireless reporter Jeff Kagan – regarding an ongoing in-field demonstration - “This is so much more cost effective for the company and so much easier for them to deliver an ultra-fast, gigabit speed, wireless internet connection anywhere there are power lines.” The same situation arises for a utility looking to augment or simply deploy a communications fabric in their region via treating the transmission line infrastructure as a communication fabric thereby reducing the cost and complexity of deployment. A circa 2020 review of broadband over powerlines (BPL) is presented here.

42 ENGINEERING↗

Adaptive Neuro Fuzzy Inference System for Cyber-Intrusion Detection in a Smart Grid

The evolution of the power grid has brought increasing deployment of advance metering infrastructure, penetration of intelligent electronic devices, and integration of physical power system components with information and communications technologies. With the fast-expanding connectivity, cyber vulnerabilities arise due to the use of internet-based communication systems. These systems are targets of cyber-intrusions which attempt to disturb the normal power system functions. Traditional intrusion detection algorithms have been developed without an explicit model of the cyber components. In this paper, an algorithm to detect false data injections in the power system is proposed considering both cyber and physical models of the power system. The algorithm is based on an Adaptive Neuro Fuzzy Inference System (ANFIS) which collects information from state variables of the cyber-physical system to meet the performance requirements of the grid. Simulations of the proposed approach using the IEEE 13-bus test system validate the effectiveness of this artificial intelligence-based algorithm.

Adaptive Neuro Fuzzy Inference System (ANFIS), cyb↗

Joint Channel Equalization and Symbol Detection for IoT Devices in Severe Multipath Channels

Internet of Things (IoT) devices often transmit very short message blocks without strong error correction coding or pilots for channel equalization. When the transmitted signals encounter a severe multipath channel, the receiver is often unable to equalize the resulting inter-symbol interference (ISI) via traditional methods, leading to a high retransmission rate. This paper proposes a joint channel equalization and symbol detection scheme for this scenario by utilizing the preamble sequence as a training pilot for equalization and the relatively weak cyclic redundancy check (CRC) 8-Dallas code for error correction. By assuming a sparse channel impulse response, the proposed joint channel equalization and symbol detection scheme formulates an l1 norm constrained optimization problem and solves it by a saddle-point algorithm. The proposed algorithm is applied to a set of real-world underwater animal tracking IoT data, and the results show improvement of correct message detection rate from 21:5% to 41:6%.

Jing, Shusen↗

"Science First" - the best path to quantum supremacy

The potential of quantum computing seems limitless. It promises faster internet searches, lightning-quick financial data analysis, shorter commutes, more effective cancer drugs, revolutionary new materials, and much more. New work at Los Alamos National Laboratory is finding ways to develop algorithms that get the most out of today’s very limited quantum computers.

97 MATHEMATICS AND COMPUTING↗

Putting Our Industry's Data to Work: A Case Study of Large-Scale Data Aggregation: Preprint

With increasing deployment of Advanced Metering Infrastructure (AMI), Building Automation System (BAS) controls, Internet of Things (IoT) network devices, and data-driven evaluation, measurement, and verification studies, the building sector is currently generating a staggering amount of energy-related data. In the right hands, these data sets can contribute to increased comfort and energy savings for building occupants and a more reliable electrical grid; however, due to a combination of factors, including significant privacy concerns, much of the data that are presently generated and stored are not used outside of basic operational applications. In the past year, our team has dedicated over 2,000 person-hours to accessing building energy data for a project funded by the U.S. Department of Energy (DOE) Building Technologies Office. We sought whole-building or end-use (e.g., lighting) timeseries data at the individual-building or equipment level where possible or aggregated information, such as timeseries averages and quartiles by building type (e.g., office, retail, hospital), where sharing individual building information was not an option. We are additionally working with IoT and BAS data sets to derive information important to the project. We have assembled an extensive data set that will enable the development of publicly available end-use load profiles to benefit the U.S. building and electricity industries. Here we present an overview of the data set that we have assembled to date, the motivators and approaches that got us here, and the lessons we learned through our efforts. We also discuss work underway that presents additional options for future data access.

building energy data↗

DIGITAL APPLICATIONS USING REAL-TIME VEHICLE EXHAUST INFORMATION

Vehicle emission is a major source of air pollution that causes a significant number of deaths globally. It has a profound impact on energy and the environment as well. The existing vehicle emission monitoring system is unable to help mitigating the pollution properly and therefore, requires precise real-time pollution measurement. The purpose of this paper is to discuss novel applications using the real-time measurement of pollutants from a vehicle tailpipe where exhaust gases enter the environment. Today, it is possible to measure such emission due to the emergence of affordable digital technologies such as the Internet of Things (IoT), wireless connectivity, cloud platform, and artificial intelligence. This paper discusses how digital technologies can be used for real-time monitoring of NOx gas as a measure of vehicle emission and predictive analytics applications. A description of data collection and pre-processing methodologies, actual collected data, and an approach to identify patterns between inputs such as vehicle speed and altitude and output such as NOx emission are included. Applying a simple neural network has produced promising results and is a first step towards developing predictive applications.

Digital, Vehicle Exhaust, IoT, AI, 1.4.2, Predicti↗

FNET/GridEye: A Tool for Situational Awareness of Large Power Interconnetion Grids

This paper gives an overview of a wide-area measurement system deployed at the distribution level: FNET/GridEye, which consists of hundreds of sensors, communication and a data center. The sensors are utilized to take frequency, voltage phase angle and magnitude measurements from the ordinary 110 or 220V outlets in offices or residential houses. These measurements are continuously transmitted to the data center via Internet. Many applications have been implemented to monitor large-scale interconnected power grids, and interpret grid operation status to improve system operators' situational awareness capability. Some representative online and offline applications are presented in this paper, as well as several recently developed new applications.

Zhu, Lin↗

Multiple Document Representations from News Alerts for Automated Bio-surveillance Event Detection

Due to globalization, geographic boundaries no longer serve as effective shields for the spread of infectious diseases. In order to aid bio-surveillance analysts in disease tracking, recent research has been devoted to developing information retrieval and analysis methods utilizing the vast corpora of publicly available documents on the internet. In this work, we present methods for the automated retrieval and classification of documents related to active public health events. We demonstrate classification performance on an auto-generated corpus, using recurrent neural network, TFIDF, and Naive Bayes log count ratio document representations. By jointly modeling the title and description of a document, we achieve 97% recall and 93.3% accuracy with our best performing bio-surveillance event classification model; logistic regression on the combined output from a pair of bidirectional recurrent neural networks.

language analysis, Biosurveillance, document class↗

Monitoring Based Commissioning: Step-by-Step Approach to Implementation in Chiller Plants

Chilled water systems consume a significant portion of the energy in manufacturing, and inefficient operation could significantly influence utility bills and the environmental footprint of a facility. One way to ensure long-term energy-efficient plant operation is to ensure that chilled water system equipment, such as chillers, cooling towers, and pumps, are running at their best. Periodic operational assessments help to meet efficiency objectives for cooling plants. However, occasional set point and operational changes resulting from short-term fluctuations cause the plant operation to deviate from optimal. These changes accumulate over time, and operational efficiency deteriorates. Significant energy efficiency improvement potential in chilled water systems can be achieved by operational changes alone. Recent developments in information technology and the industrial internet of things data processing ability have overcome traditional problems and given rise to a new paradigm: monitoring-based commissioning (MBCx). Commissioning platforms and fault detection and diagnostics capabilities have evolved over time and presented more sophisticated abilities to efficiently control process cooling plants. The typical architectures of the MBCx process and a detailed approach to implement the process for chilled water systems are presented. A case study highlighting the energy-and cost-savings potential of MBCx systems is also presented.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Companion Assisted Software Based Remote Attestation in SCADA Networks

Critical infrastructure such as power generation and water distribution systems have become a priority target in cyber warfare because of their recent computerization and introduction to the internet. As a result, Supervisory Control and Data Acquisition (SCADA) system security has become a hot topic in academic and industrial research. Among these topics, Remote Attestation is a security method intended to detect the presence of fileless malware in remote devices as they continue to operate. This allows for the detection of malware in the absence of long-term storage artifacts before symptoms of compromise begin to appear. In general, a trusted device (the verifier) makes a request for evidence of innocence from the untrusted device (the prover). In software-based schemes, the verifier can then measure the delay between its request and the prover’s response. If this delay is greater than the known computational time of the evidence gathering algorithm performed by the prover, then evidence may have been forged. Multi-hop networks often introduce too much network jitter to allow accurate measurement of prover response time, which limits the effectiveness of software based Remote Attestation in a real-world setting. In this work, we introduce a companion device that the verifier can trust to perform a subset of attestation, thereby removing any network jitter. This device is a Field Programmable Gate Array (FPGA) that is physically connected to the prover. We provide a communication protocol between the verifier, prover, and companion. To evaluate our scheme, we simulate it in a common SCADA network environment under normal and heavy traffic loads. Our simulations are performed in the discrete event network simulator NS-3, and we perform statistical analysis over our results to show that our scheme allows for tight timing constraints to be placed on the prover such that the verifier can more easily determine the validity of the evidence that it receives.

Johnson, William A.↗

EMERGING CYBER-PHYSICAL LANDSCAPE OF TRANSPORTATION TECHNOLOGY

Technology is rapidly progressing in transportation and shipping industries across the globe, including the nuclear, radioactive and hazardous material transportation sectors. With this progress comes unprecedented opportunities for improved transparency, safety, and security in transportation, as well as novel threat surfaces and attack vectors. Therefore, the transport safety and security interface is affected through the application of these technologies. We provide an investigative overview of the developing fields of “trans-tech” or “freight- tech” with a look towards technology development and adoption over the next 3-5 years across three primary categories: Transportation IoT (Internet of Things), Smart Infrastructure, and digitization of transportation management. We also investigate the safety and security implications of utilizing these technologies. Each of these categories presents novel threats as well as opportunities. We examine the role of technology in each as an emerging cyber-physical threat to nuclear and radioactive material transportation security, and plausible mitigation considerations at both the state and operator levels in additional to opportunities for addressing the interface between safety and security.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Long-term trends in connected thermostat performance

Internet-connected thermostats (CTs) control heating and cooling systems in about 30% of North American homes, and capture half of annual thermostat sales. In 2017 the U.S. Environmental Protection Agency created a program to certify the performance of ENERGY STAR® Connected Thermostats. To demonstrate compliance with energy-saving criteria, thermostat vendors must submit performance summaries for a representative sample of up to 1250 homes. Vendors must then re-submit results from a new, representative sample every six months in order to maintain their ENERGY STAR certification. This procedure has created a unique record of each thermostat’s long-term performance in response to changes in weather, customer demographics, building stock, and algorithms. Our analysis covers submissions from 13 different vendors, who submitted data up to 7 times over four years. We found that these semi-annual samples generated relatively stable trends for comfort temperatures and Heating, Ventilating and Air Conditioning (HVAC) runtimes over the study period. However, some vendors achieved consistently more energy-conserving comfort temperatures and shorter HVAC runtimes than others. The most recent submission runtimes averaged 700 hours for heating and 1,300 hours for cooling, but some vendors achieved runtimes as much as 17% below the mean. This implies lower energy consumption is due in large part to more successful algorithms and control strategies used by those vendors.

Meier, Alan↗

The Future of Energy Efficiency for U.S. Buildings - Drivers and Market Scenarios

This paper identifies likely drivers of building efficiency over the next ten years and expectations for how efficiency markets may evolve over this period. To prepare these predictions, we conducted an extensive literature review, interviewed 22 experts, reviewed legislation and executive orders in 12 states, and implemented a detailed questionnaire completed by 41 efficiency practitioners. The two most important drivers revealed by our research are (1) public policies and regulations, particularly those associated with climate change mitigation and adaptation and (2) the cost of energy relative to the cost of delivering efficiency. Other important drivers are technology changes, economic conditions, social priorities, and industry (including utility) business practices for increasing the uptake of efficiency in buildings. Our research indicates that efficiency markets will increasingly focus on supporting building decarbonization and enabling demand flexibility through the use of controls in grid-interactive efficient buildings and communities. Efficiency improvements for specific technologies (e.g., heat pumps, controls, and windows) and technological advances not specific to energy technologies (e.g., interoperability, artificial intelligence, and universal internet access) will improve the efficacy of efficiency measures and actions. Marketing of efficient products and services will increasingly focus on grid services, decarbonization, non-energy benefits for consumers, and integration with other distributed energy resources (DERs). We anticipate increased investment in disadvantaged and historically underserved communities, recognizing the social, health, and safety benefits of efficient energy usage and remediating historical biases. Lastly, we predict that while state and local government actions will vary, jurisdictions will increase their efficiency goals overall.

Schiller, Steven R↗