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At least 307 records · Page 17

Probing-Based Inertia Estimation Method Using Hybrid Power Plants

With the displacement of synchronous generation by inverter-based resources (IBRs), power systems could face the challenge of reduced inertia since IBRs do not inherently contribute to system inertia. Therefore, there is rising interest in monitoring system inertia in real-time applications for situational awareness. In addition, there is a growing number of IBRs that provide fast frequency responses (FFR) in the form of synthetic inertia and P-f droop. It is desirable to quantify the contribution of these FFR controls as equivalent inertia. This paper proposes a probing-based inertia estimation method using a PV-battery hybrid power plant in the Kauai island power system. The method is validated under different operating conditions.

hybrid power plant↗

Solving Optimal Power Flow for Distribution Networks with State Estimation Feedback

Conventional optimal power flow (OPF) solvers assume full observability of the involved system states. However in practice, there is a lack of reliable system monitoring devices in the distribution networks. To close the gap between the theoretic algorithm design and practical implementation, this work proposes to solve the OPF problems based on the state estimation (SE) feedback for the distribution networks where only a part of the involved system states are physically measured. The SE feedback increases the observability of the under-measured system and provides more accurate system states monitoring when the measurements are noisy. We analytically investigate the convergence of the proposed algorithm. The numerical results demonstrate that the proposed approach is more robust to large pseudo measurement variability and inherent sensor noise in comparison to the other frameworks without SE feedback.

distirbution systems↗

A data-driven sensor placement approach for detecting voltage violations in distribution systems

Stochastic fluctuations in power injections from distributed energy resources (DERs) combined with load variability can cause constraint violations (e.g., exceeded voltage limits) in electric distribution systems. To monitor grid operations, sensors are placed to measure important quantities such as the voltage magnitudes. Here, in this paper, we consider a sensor placement problem which seeks to identify locations for installing sensors that can capture all possible violations of voltage magnitude limits. We formulate a bilevel optimization problem that minimizes the number of sensors and avoids false sensor alarms in the upper level while ensuring detection of any voltage violations in the lower level. This problem is challenging due to the nonlinearity of the power flow equations and the presence of binary variables. Accordingly, we employ recently developed conservative linear approximations of the power flow equations that overestimate or underestimate the voltage magnitudes. By replacing the nonlinear power flow equations with conservative linear approximations, we can ensure that the resulting sensor locations and thresholds are sufficient to identify any constraint violations. Additionally, we apply various problem reformulations to significantly improve computational tractability while simultaneously ensuring an appropriate placement of sensors. Lastly, we improve the quality of the results via an approximate gradient descent method that adjusts the sensor thresholds. We demonstrate the effectiveness of our proposed method for several test cases, including a system with multiple switching configurations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Operational Technology Behavioral Analytics (OTBA) (Final Technical Report DE-FE0031640)

This final report provides a summary of the methodology, findings, lessons learned, and insights from an investigation into the feasibility of the Operational Technology Behavioral Analytics (OTBA) cybersecurity approach. The concept was evaluated with data from the National Carbon Capture Center (NCCC) – a U.S. Department of Energy (DOE) funded facility that is managed and operated by Southern Company Services, Inc. at Alabama Power Company’s E. C. Gaston generating power plant in Wilsonville, Alabama. Appropriate data sources for the post-combustion carbon capture system were identified. Infrastructure was deployed to monitor, capture and archive data for the system. Critical parameters for each subsystem were identified and analyzed. Machine-learning algorithms were used to establish and characterize normal operations and subsequently identify anomalies. This effort yielded valuable insights and formed the basis of a data-centric strategy for detecting cyber-attacks along with a coordinated response philosophy. A significant takeaway is that the OTBA cybersecurity approach is quite portable; it can be applied to other critical infrastructure beyond fossil power generation.

20 FOSSIL-FUELED POWER PLANTS↗

OPERATIONAL TECHNOLOGY BEHAVIORAL ANALYTICS (OTBA) – A DATA-CENTRIC APPROACH FOR REDUCING CYBERSECURITY RISK

This paper provides a summary of the methodology, findings, lessons learned, and insights from an investigation into the feasibility of the Operational Technology Behavioral Analytics (OTBA) cybersecurity approach. The concept was evaluated with data from the National Carbon Capture Center (NCCC) – a U.S. Department of Energy (DOE) funded facility that is managed and operated by Southern Company at Alabama Power’s E. C. Gaston generating power plant in Wilsonville, Alabama. Appropriate data sources for the post-combustion carbon capture system were identified. Infrastructure was deployed to monitor, capture and archive data for the system. Critical parameters for each subsystem were identified and analyzed. Machine-learning algorithms were used to establish and characterize normal operations and subsequently identify anomalies. This effort yielded valuable insights and formed the basis of a data-centric strategy for detecting cyber-attacks along with a coordinated response philosophy. A significant takeaway is that the OTBA cybersecurity approach is quite portable; it can be applied to other critical infrastructure beyond fossil power generation.

Black, Clifton↗

Standard Operating Procedure for Optimal Deployment of Meteorological Instrumentation Within the Solar Radiation Research Laboratory (BMS and RMS SOP)

The objective of the National Renewable Energy Laboratory's (NREL's) Solar Radiation Research Laboratory (SRRL) is to collect and use high-quality solar radiation data sets for research leading to the widespread adoption of solar technologies. To appropriately populate and track the diverse array of instruments at the NREL-SRRL, NREL has established a Standard Operating Procedure (SOP) for optimal instrument deployment within the SRRL for both the Baseline Measurement System (BMS) and the Research Measurement System (RMS). Using best practices methodologies, the NREL-SRRL maintains a varied and extensive array of solar monitoring equipment to test, evaluate, and characterize the solar sensors used by federal and international agencies as well as the solar industry to determine the solar resource. The SOP provides the industry with guidance for solar resource assessment and is used for procedures in the long-term continuous monitoring of legacy instruments alongside state-of-the-art instruments. Based on the SOP, instruments are annually evaluated for continued deployment. Instruments that do not meet the SOP criteria are decommissioned, and new instruments that meet the criteria are deployed. Streamlining and optimizing the use of this facility ensures that the lab continues to be a world-leading solar calibration and measurement facility.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Thermomagnetic generators for ultra-low-grade marine thermal energy harvesting

Low-grade thermal gradients in marine environments represent an underexploited energy source for autonomous sensing and monitoring. Converting such small temperature differences into usable electrical power remains a key challenge for ocean-deployed systems. We present a deployable thermomagnetic generator thoroughly characterized for marine-relevant energy harvesting. The device powers an internet-connected sensor and harvests ultra-low temperature differences akin to those at the ocean surface. It draws heat from water and rejects it to ambient air, operating optimally at a temperature difference (ΔT) of ~7.5 °C. Laboratory prototypes generated up to 6.7 mW at ΔT ~ 10 °C with gentle airflow (~1 m s -1 ). A separate controlled wave-tank demonstration validated stable operation and sensor powering under marine-like boundary conditions. Given its voltage and power margins, the generator could sustain multiple sensor nodes. Scalability and material assessments identify modular deployment and non-rare-earth alternatives as pathways toward practical marine energy harvesting and low-grade waste-heat recovery.

16 TIDAL AND WAVE POWER↗

Generator Frequency Response Droop Monitoring Tool

Monitoring and analyzing the frequency response performance of power generation units is essential for maintaining reliable and secure power system operation. To address this need, an automation tool has been developed to provide a pipeline for processing historical power plant generation data, including large-scale SCADA archives. The tool performs end-to-end processing, including event detection, frequency response (FR) analysis in accordance with NERC standards, and estimation of speed governor droop characteristics. The tool is designed with a modular architecture, allowing individual components of the workflow to be extended, customized, or deployed independently. In addition, the tool provides an API that enables seamless integration with other production systems and operational analytics platforms.

Etingov, PavelV [Pacific Northwest National Labora↗

TriFrame Mount Structural Performance - Period A

Long-Term TriFrame Monitoring System (LTTFMS) data collected during Period A (13 days - 10/22/20 - 11/4/20). The central component of the Verdant Power Free Flow System is a three-bladed horizontal-axis turbine. The turbine is equipped with a composite rotor with three fixed-pitch blades that rotate at a slow and regular rate (approx. 32 rpm), well below normal water vessel propeller speeds and conventional hydropower turbine blade speeds. The TriFrame mount is the structural mount that holds the three Verdant Power three-bladed horizontal-axis turbines.

16 TIDAL AND WAVE POWER↗

Modeling Data Flows with Network Calculus in Cyber-Physical Systems: Enabling Feature Analysis for Anomaly Detection Applications

The electric grid is becoming increasingly cyber-physical with the addition of smart technologies, new communication interfaces, and automated grid-support functions. Because of this, it is no longer sufficient to only study the physical system dynamics, but the cyber system must also be monitored as well to examine cyber-physical interactions and effects on the overall system. To address this gap for both operational and security needs, cyber-physical situational awareness is needed to monitor the system to detect any faults or malicious activity. Techniques and models to understand the physical system (the power system operation) exist, but methods to study the cyber system are needed, which can assist in understanding how the network traffic and changes to network conditions affect applications such as data analysis, intrusion detection systems (IDS), and anomaly detection. In this paper, we examine and develop models of data flows in communication networks of cyber-physical systems (CPSs) and explore how network calculus can be utilized to develop those models for CPSs, with a focus on anomaly and intrusion detection. This provides a foundation for methods to examine how changes to behavior in the CPS can be modeled and for investigating cyber effects in CPSs in anomaly detection applications.

97 MATHEMATICS AND COMPUTING↗

Mid Infra-Red Laser Sensor for Continuous Sulfur Trioxide Monitoring to Improve Coal-Fired Power Plant Performance during Flexible Operations

During the course of this project, we performed exhaustive research and development of SO3/H2SO4 sensing technology for coal-fired power plant applications (Figure 1). The development culminated in a successful field campaign of a prototype continuous real-time H2SO4 monitor at a coal-fired power plant (TRL 6) accomplishing the primary goal of the project. The developed sensors utilize tunable laser absorption spectroscopy (TLAS) operating in the mid-infrared (Mid-IR) wavelength region, which is the so-called “molecular fingerprint” region. Systems operating in the Mid-IR have orders of magnitude more sensitivity than systems operating at shorter wavelengths, such as near-infrared (NIR). However, NIR systems are more widespread due to more mature supporting technology (e.g., fiber optics, optical components, etc.). In this project, we not only produced a specific Mid-IR sensor, we also advanced Mid-IR sensor technology in general through the development and demonstration of such supporting technology. In this project, we also developed proprietary broad tuning lasers enabling the ability to effectively measure SO3, H2SO4, H2O, and SO2. Different molecular species have unique spectral signatures that can be probed with lasers operating at different wavelengths. Standard TLAS uses relatively narrow wavelength tuning distributed feedback (DFB) lasers, which can typically only target a single species with narrow features, and are not appropriate for species with broad features, such as SO3 or H2SO4. In contrast, by developing unique, broad-tuning laser technology, we were able to measure these species, as well as SO2 and H2O simultaneously. Furthermore, to enable real-time analysis at a power plant, we modified a commercially available heated gas cell to operate in the Mid-IR wavelength range and fiber coupled the lasers to enable remote delivery of the beams. To generate reference data (library spectra), our collaborators at the University of California Irvine (UCI) developed a catalytic SO3 generation facility. It is worth mentioning that representative H2SO4 and SO3 Mid-IR spectra are not a part of any publicly available database and the data generated under this project is a valuable resource in and of itself. In addition, based on the UCI study we determined that detection of SO3 is complicated by the very strong SO2 absorption. For that reason, we concentrated on H2SO4 detection. Since SO3 and H2SO4 exist in a flue gas in a state of equilibrium, which depends on temperature and humidity, by measuring water concentration and controlling the temperature of the gas cell, we developed an approach to determine SO3 concentration from the H2SO4 measurement. During the development phase of the project, we performed three testing campaigns at our collaborator’s FERCo flue gas facility with conditions representative of the coal-fired power plant (~ 40ppm SO3, 1700ppm to 2800 ppm SO2, 10% water) with the exception of particulate matter. After three test campaigns at FERCo we performed field testing at Harrison Power Station. The final system was mounted on a duct and measured H2SO4, SO2 and water. The tests were highly successful with a demonstrated real-time H2SO4 precision of 1 ppm with a 1 second update. Our collaborators at EPRI conducted an industry survey and determined that there is a very high interest for the SO3/H2SO4 monitoring in the power generation industry as well as in heavy industries in general. Furthermore, work performed by OptoKnowledge beyond the scope of this project under a synergistic DOE SBIR determined another approach to SO3 detection. We applied for Phase II on this SBIR for development a of versatile SO3/H2SO4 sensor but were not selected. We are currently looking for another opportunity to leverage all the technological advancements produced by this project including but not limited to the flue gas facility at UCI, the hardware and software developed, and relationships with FERCo, EPRI CEMTEK, and Harrison Station.

01 COAL, LIGNITE, AND PEAT↗

Adaptable Monitoring Package Development and Deployment: Lessons Learned for Integrated Instrumentation at Marine Energy Sites

Integrated instrumentation packages are an attractive option for environmental and ecological monitoring at marine energy sites, as they can support a range of sensors in a form factor compact enough for the operational constraints posed by energetic waves and currents. Here we present details of the architecture and performance for one such system—the Adaptable Monitoring Package—which supports active acoustic, passive acoustic, and optical sensing to quantify the physical environment and animal presence at marine energy sites. we describe cabled and autonomous deployments and contrast the relatively limited system capabilities in an autonomous operating mode with more expansive capabilities, including real-time data processing, afforded by shore power or in situ power harvesting from waves. Across these deployments, we describe sensor performance, outcomes for biological target classification algorithms using data from multibeam sonars and optical cameras, and the effectiveness of measures to limit biofouling and corrosion. On the basis of these experiences, we discuss the demonstrated requirements for integrated instrumentation, possible operational concepts for monitoring the environmental and ecological effects of marine energy converters using such systems, and the engineering trade-offs inherent in their development. Overall, we find that integrated instrumentation can provide powerful capabilities for observing rare events, managing the volume of data collected, and mitigating potential bias to marine animal behavior. These capabilities may be as relevant to the broader oceanographic community as they are to the emerging marine energy sector.

16 TIDAL AND WAVE POWER↗

Transmission Data-Driven User-Defined Model for Inverter-based and Conventional Power Plants

Recent events in Odessa [1], [2] have shed light on the complexities of integrating large Inverter-Based Resource (IBR) plants with the transmission system, prompting NERC to stress continuous performance monitoring by transmission operators. Challenges such as plant control updates, IBR model revisions, Phase-locked loop loss of synchronism, and protection events have been identified, underscoring the need for enhanced monitoring protocols by regulatory bodies. The recent FERC 901 order underscores the importance of accurate data exchange regarding IBRs for reliability studies. However, limited access to IBR plant-related data hampers effective decision-making for transmission operators (TOP). This paper proposes a method for constructing data-driven User-Defined dynamic Models (UDM) for power plants for validating multiple-event data using field measurements from interconnection bus locations. The problem is formulated as a power plant model identification problem and a multi-task learning approach under partial input observability assumptions is proposed in this work. This approach aims to predict aggregated responses of conventional and IBR power plants during various dynamic physical events which is useful for planning studies under diverse disturbance conditions. Ultimately, this methodology emphasizes the importance of plant visibility to operators in addressing power system challenges, facilitating improved planning and operational studies.

Mahapatra, Kaveri [BATTELLE (PACIFIC NW LAB)]↗

An Enhanced Computational Framework for Energy Storage Participation in Transmission Planning with Electricity Market Participation: Dynamic Market Participation Restriction Estimation

In the previous study and report, we developed a computational framework to explore the technical and economic viability of the dual use of pumped storage hydropower (PSH) for both transmission assets and market participation. The rationale for the dual-use application is to improve the resource utilization rate and reduce the cost recovery burden. A PSH-based transmission solution generally has a large capacity, which corresponds to a higher investment cost compared to a traditional line solution. Market participation may allow the PSH asset to offset part of its high investment cost. A critical question is whether it is economically and technically viable to allow dual use of a PSH-based transmission project without jeopardizing transmission system reliability. And a more specific follow-up question is how to improve market participation performance while maintaining transmission reliability. In this study, we extend the computational framework by updating the method to determine transmission service obligation requirements dynamically based on the possibility of the need for transmission service in operation. Specifically, we correlate the need for transmission service with the probability of thermal overloading on a monitored transmission line, which is essentially based on the probability distribution of power flow and its probability of exceeding the line rating based on system dispatch and operational uncertainties. In addition, the need depends on the level of risk that a system operator is willing to take. The higher the risk tolerance, the lower the requirement that the system operator would apply to the PSH project as a transmission asset. The requirements are updated every day before the PSH project determines its market participation strategy. With the updated transmission service requirements, it is expected that a PSH project can serve as a transmission asset when the transmission system is at risk and really needs it, while it can participate in a market with sufficient information and certain restrictions. In this way, the transmission service quality and market participation performance can both be improved.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Multi-Area Distribution System State Estimation Using Decentralized Physics-Aware Neural Networks

The development of active distribution grids requires more accurate and lower computational cost state estimation. In this paper, the authors investigate a decentralized learning-based distribution system state estimation (DSSE) approach for large distribution grids. The proposed approach decomposes the feeder-level DSSE into subarea-level estimation problems that can be solved independently. The proposed method is decentralized pruned physics-aware neural network (D-P2N2). The physical grid topology is used to parsimoniously design the connections between different hidden layers of the D-P2N2. Monte Carlo simulations based on one-year of load consumption data collected from smart meters for a three-phase distribution system power flow are developed to generate the measurement and voltage state data. The IEEE 123-node system is selected as the test network to benchmark the proposed algorithm against the classic weighted least squares and state-of-the-art learning-based DSSE approaches. Numerical results show that the D-P2N2 outperforms the state-of-the-art methods in terms of estimation accuracy and computational efficiency.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Rootkit detection system

A system and method (referred to as the system) detect infectious code. The system injects a repetitive software code that causes malware in a monitored device to render a detectable direct current power consumption profile. A guide wave generator generates a guide wave signal that establishes an observational window that is applied to data that represent a direct current source power consumption of the monitored device. An extraction device extracts a portion of the data that represent the direct current source power consumption of the monitored device. A deviation engine identifies the malware on the monitored device without processing data associated with a prior identification of the malware or identifying a source of the malware or identifying a location of the malware on the monitored device.

Dawson, Joel↗

A Persistence Meter for Nimble Alarming Using Ambient Synchrophasor Data

Persistent oscillations in the power grid are often indicative of fragility, and may be harbingers of systemic or cascading failures. Modernization of the grid, including increased penetration of intermittent renewables and integration of new power electronics, is making the oscillatory swing dynamics of the network both more complex and variable. In this project researchers from the University of Wisconsin-Madison (Bernard Lesieutre, lead), Washington State University (Sandip Roy, lead), and the Electric Power Group (Neeraj Nayak, lead) have developed technologies that monitor persistent oscillations in the grid and provide operators with alarms and analytics when concerning oscillations are detected. Some of the algorithms have already been implemented in EPG’s PGDA software and integrated into their RTDMS system for use in control rooms.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Power distribution estimation method for SMR using ex-core detectors: experimental demonstration by plural control rod patterns at KUCA

The power distribution estimation method based on the ex-core detectors, or PHOEBE, was demonstrated at Kyoto University Critical Assembly, KUCA. Generally, core monitoring systems use in-core neutron detectors. Since inside the core is a harsh environment, the maintainability and reliability of the detectors are deteriorated. On the other hand, the environment outside the core is milder: core monitoring by the ex-core detectors improves the maintainability and reliability especially for small modular reactors and micro-reactors. However, neutron information from the inner region of the core is lost at the ex-core detectors. To recover the information, the authors proposed to utilize the power correlation between the fuel regions. PHOEBE concept was demonstrated at KUCA with distorted power distributions simulated by control rod patterns. The relative power distribution estimated by PHOEBE agreed with that calculated by Monte Carlo simulation code MVP. PHOEBE approximately reproduced the trend of the distorted power distributions calculated by MVP code. By contrast, the case of without power correlation between fuel regions produced significant different power distributions. Therefore, the advantage of considering the power correlation between fuel regions was also demonstrated. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗