Search NASA⌕ Search

SEARCH · Search NASA

Results for “EASTERN INTERCONNECTION”

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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Transient Stability Analysis for Offshore Wind Power Plant Integration Planning Studies - Part I: Short Term Faults

Power system planning is the process of forecasting load demand and ensuring sufficient generation and reserve capacities over some planning horizon. This process includes investigation of steady-state and dynamic operation of power system of interest. This paper addresses the transient stability (also known as large-signal stability) analysis of power systems for offshore wind power plant integration planning studies. In particular, this study develops a comprehensive practical methodology to assess transient stability of power systems, including rotor angle stability, voltage stability and frequency response for all fault types for large scale power systems. This methodology considers variability of the offshore wind power plants as well as the type of any faulted components present and is applicable to the study of both short term and long term faults, though only short term faults are considered here (long term faults are treated sequentially in a companion paper). Furthermore, this paper considers the integration of offshore wind power plants into existing power systems and demonstrates the utility of this methodology through the examination of the specific case of integrating 1,000MW of offshore wind power into the FirstEnergy/PJM service territory using a realistic model of 63k-bus test system that represents the U.S. Eastern Interconnection.

17 WIND ENERGY↗
DOE OSTI2017

Simultaneous Estimation of Electromechanical Modes and Forced Oscillations

Over the past several years, great strides have been made in the effort to monitor the small-signal stability of power systems. These efforts focus on estimating electromechanical modes, which are a property of the system that dictate how generators in different parts of the system exchange energy. Though the algorithms designed for this task are powerful and important for reliable operation of the power system, they are susceptible to severe bias when forced oscillations are present in the system. Forced oscillations are fundamentally different from electromechanical oscillations in that they are the result of a rogue input to the system, rather than a property of the system itself. To address the presence of forced oscillations, the frequently used AutoRegressive Moving Average (ARMA) model is adapted to include sinusoidal inputs, resulting in the AutoRegressive Moving Average plus Sinusoid (ARMA+S) model. From this model, a new Two-Stage Least Squares algorithm is derived to incorporate the forced oscillations, thereby enabling the simultaneous estimation of the electromechanical modes and the amplitude and phase of the forced oscillations. The method is validated using simulated power system data as well as data obtained from the western North American power system (wNAPS) and Eastern Interconnection (EI).

Electromechanical modes↗
DOE OSTI2020

Fast and Accurate Frequency Response Estimation for Large Power System Disturbances Using Second Derivative of Frequency Data

Accurate Frequency Response Estimation (FRE) is critical to reliability risk management of large power system disturbances. This letter proposes a measurement-driven approach for FRE by calculating the second derivative of frequency from synchrophasor data. Compared with conventional methods, the proposed method has major advantages of low computational burden and high accuracy, which makes it appropriate for real-time FRE in bulk power systems. The effectiveness of this method is validated with actual synchrophasor data on 96 confirmed historical power system disturbances in the U.S. eastern interconnection.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Power System Event Identification Based on Deep Neural Network With Information Loading

Online power system event identification and classification are crucial to enhancing the reliability of transmission systems. In this study, we develop a deep neural network (DNN) based approach to identify and classify power system events by leveraging real-world measurements from hundreds of phasor measurement units (PMUs) and labels from thousands of events. Two innovative designs are embedded into the baseline model built on convolutional neural networks (CNNs) to improve the event classification accuracy. First, we propose a graph signal processing based PMU sorting algorithm to improve the learning efficiency of CNNs. Second, we deploy information loading based regularization to strike the right balance between memorization and generalization for the DNN. Numerical results based on real-world dataset from the Eastern Interconnection of the U.S power transmission grid show that the combination of PMU based sorting and the information loading based regularization techniques help the proposed DNN approach achieve highly accurate event identification and classification results.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Online Power System Event Detection via Bidirectional Generative Adversarial Networks

Accurate and speedy detection of power system events is critical to enhancing the reliability and resiliency of power systems. Although supervised deep learning algorithms show great promise in identifying power system events, they require a large volume of high-quality event labels for training. This paper develops a bidirectional anomaly generative adversarial network (GAN)-based algorithm to detect power system events using streaming PMU data, which does not rely on a huge amount of event labels. By introducing conditional entropy constraint in the objective function of GAN and graph signal processing-based PMU sorting technique, our proposed algorithm significantly outperforms state-of-the-art event detection algorithms in terms of accuracy. To facilitate the adoption of the proposed algorithm, a prototype online platform is also developed using Apache Hadoop, Kafka, and Spark to enable real-time event detection. Here, the accuracy and computational efficiency of the proposed algorithm are validated using a large-scale real-world PMU dataset from the Eastern Interconnection of the United States.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Detection of Synchrophasor False Data Injection Attack using Feature Interactive Network

The synchrophasor data recorded by Phasor Measurement Units (PMUs) plays an increasingly critical role in the regulation and situational awareness of power systems. However, the widely installed PMUs are vulnerable to multiple malicious attacks from cyber hackers during data transmission and storage. To address this problem, a Modified Ensemble Empirical Mode Decomposition (MEEMD) is proposed first to extract the intrinsic mode functions of each Synchrophasor Data Attacks (SDA). The frequency-based adaptive screening criterion embedded in MEEMD is used to eliminate the false intrinsic mode functions. Next, a Multivariate Convolutional Neural Network (MCNN) is proposed to identify multiple SDA by utilizing the extracted intrinsic mode functions and original SDA as input vectors. A fusion block as the main structure of MCNN is also leveraged to increase the diversity of features and compress the model parameters. Integrating MEEMD and MCNN, a framework with automatic feature extraction and multi-source information fusion capability, referred to as Feature Interactive Network (FIN), is proposed to detect multiple SDA. Based on the proposed FIN framework, six types of SDA are explored for the first time using actual synchrophasor data in FNET/Grideye that was collected from different locations in the U.S. Eastern Interconnection. Finally, a large quantity of experiments with different attack strengths are used to evaluate the adaptability and classification performance of the proposed FIN.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2015

Seismic Retrofit for Electric Power Systems

Our paper develops a two-stage stochastic program and solution procedure to optimize the selection of seismic retrofit strategies to increase the resilience of electric power systems against earthquake hazards. The model explicitly considers the range of earthquake events that are possible and, for each, an approximation of the distribution of damage experienced. Furthermore, this is important because electric power systems are spatially distributed and so their performance is driven by the distribution of component damage. We also test this solution procedure against the nonlinear integer solver in LINGO 13 and apply the formulation and solution strategy to the Eastern Interconnection, where seismic hazard stems from the New Madrid seismic zone.

58 GEOSCIENCES↗
DOE OSTI2020

Impact of simultaneous activities on frequency fluctuations — comprehensive analyses based on the real measurement data from FNET/GridEye

Simultaneous human activities such as the Super Bowl game would cause certain impacts on frequency fluctuations in power systems. With the help of FNET/GridEye measurements, this work aims to give comprehensive analyses on the frequency fluctuations during Super Bowl LIV held on Feb. 2, 2020, so as to better understand several phenomena caused by simultaneous activities and help system operation and control. First, recent developments of FNET/GridEye are introduced briefly. Second, the frequency fluctuations of Eastern Interconnection (EI), western electricity coordinating council (WECC), and electric reliability council of Texas (ERCOT) power systems during Super Bowl LIV are analyzed. Third, frequency fluctuations of Super Bowl Sunday and ordinary Sundays in 2020 are compared. Finally, the differences of frequency fluctuations among different years during the Super Bowl and their change trend are also given. Furthermore, several possible explanations including the simultaneity of electricity consumption at the beginning of commercial breaks and the halftime show, the increasing usage of the Internet, and the increasing size of TV screens are illustrated in detail in this work.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2016

Electric Grid Expansion Planning with High Levels of Variable Generation

Renewables are taking a large proportion of generation capacity in U.S. power grids. As their randomness has increasing influence on power system operation, it is necessary to consider their impact on system expansion planning. To this end, this project studies the generation and transmission expansion co-optimization problem of the US Eastern Interconnection (EI) power grid with a high wind power penetration rate. In this project, the generation and transmission expansion problem for the EI system is modeled as a mixed-integer programming (MIP) problem. This study analyzed a time series creation method to capture the diversity of load and wind power across balancing regions in the EI system. The obtained time series can be easily introduced into the MIP co-optimization problem and then solved robustly through available MIP solvers. Simulation results show that the proposed time series generation method and the expansion co-optimization model and can improve the expansion result significantly after considering the diversity of wind and load across EI regions. The improved expansion plan that combines generation and transmission will aid system planners and policy makers to maximize the social welfare. This study shows that modelling load and wind variations and diversities across balancing regions will produce significantly different expansion result compared with former studies. For example, if wind is modeled in more details (by increasing the number of wind output levels) so that more wind blocks are considered in expansion planning, transmission expansion will be larger and the expansion timing will be earlier. Regarding generation expansion, more wind scenarios will slightly reduce wind generation expansion in the EI system and increase the expansion of other generation such as gas. Also, adopting detailed wind scenarios will reveal that it may be uneconomic to expand transmission networks for transmitting a large amount of wind power through a long distance in the EI system. Incorporating more details of renewables in expansion planning will inevitably increase the computational burden. Therefore, high performance computing (HPC) techniques are urgently needed for power system operation and planning optimization. As a scoping study task, this project tested some preliminary parallel computation techniques such as breaking down the simulation task into several sub-tasks based on chronology splitting or sample splitting, and then assigning these sub-tasks to different cores. Testing results show significant time reduction when a simulation task is split into several sub-tasks for parallel execution.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Great Lakes O shore Wind Project: Utility and Regional Integration Study

This project aims to identify transmission system upgrades needed to facilitate offshore wind projects as well as operational impacts of offshore generation on operation of the regional transmission system in the Great Lakes region. A simulation model of the US Eastern Interconnection was used as the test system as a case study for investigating the impact of the integration of a 1000MW offshore wind farm operating in Lake Erie into FirstEnergy/PJM service territory. The findings of this research provide recommendations on offshore wind integration scenarios, the locations of points of interconnection, wind profile modeling and simulation, and computational methods to quantify performance, along with operating changes and equipment upgrades needed to mitigate system performance issues introduced by an offshore wind project.

17 WIND ENERGY↗
DOE OSTI2017

Ensuring Reliable Natural Gas-Fired Generation with Fuel Contracts and Storage - DOE/NETL-2017/1816

This report finds that natural gas-fired power plants purchase fuel both on the spot market and through firm supply contracts; there do not appear to be clear drivers propelling power plants toward one or the other type. Most natural gas-fired power generators are located near major natural gas transmission pipelines, and most natural gas contracts are currently procured on the spot market. Although there is some regional variation in the type of contract used, a strong regional pattern does not emerge. Whether gas prices are higher with spot or firm contracts varies by both region and year. Natural gas prices that push the generators higher in the supply curve would make them less likely to dispatch. Most of the natural gas generators discussed in this report would be unlikely to enter firm contracts if the agreed price would decrease their dispatch frequency. The price points at which these generators would be unlikely to enter a firm contract depends upon the region that the generator is in, and how dependent that region is on natural gas. The Electric Reliability Council of Texas (ERCOT) is more dependent on natural gas than either Eastern Interconnection or Western Interconnection. This report shows that above-ground storage is prohibitively expensive with respect to providing storage for an extended operational fuel reserve comparable to the amount of on-site fuel storage used for coal-fired plants. Further, both pressurized and atmospheric tanks require a significant amount of land for storage, even to support one day’s operation at full output. Underground storage offers the only viable option for 30-day operational storage of natural gas, and that is limited by the location of suitable geologic formations and depleted fields.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2017

Models and methods for assessing the value of HVDC and MVDC technologies in modern power grids

This report reflects the results of U.S. Department of Energy’s (DOE) Grid Modernization project 0074 “Models and methods for assessing the value of HVDC [high-voltage direct current] and MTDC [multi-terminal direct current] technologies in modern power grids.” The work was done by the Pacific Northwest National Laboratory (PNNL) and Oak Ridge National Laboratory (ORNL) in cooperation with Mid-Continent Independent System Operator (MISO) and Siemens. The main motivation of this study was to show the benefit of using direct current (DC) systems larger than those in existence today as they overlap with the alternating current (AC) systems. Proper use of their flexibility in terms of active/reactive power control and fast response can provide much-needed services to the grid at the same time as moving large blocks of energy to take advantage of cost diversity. Ultimately, the project’s success will enable decision-makers and investors to make well-informed decisions regarding this use of DC systems. This project showed the technical feasibility of HVDC macrogrid for frequency control and congestion relief in addition to bulk power transfers. Industry-established models for commonly used technologies were employed, along with high-fidelity models for recently developed HVDC converter technologies; like the modular multilevel converters (MMCs), a voltage source converters (VSC). Models for General Electric Positive Sequence Load Flow (GE PSLF) and Siemens Power System Simulator (PSS/E), widely used analysis programs, were for the first time adapted to include at the same time both Western Electricity Coordinating Council (WECC) and Eastern Interconnection (EI), the two largest North American interconnections. The high-fidelity models and their control were developed in detail for MMC system and extended to HVDC systems in point-to-point and in three-node multi-terminal configurations. Using a continental-level mixed AC-DC grid model, and using a HVDC macrogrid power flow and transient stability model, the results showed that the HVDC macrogrid relieved congestion and mitigated loop flows in AC networks, and provided up to 24% improvement in frequency responses. These are realistic studies, based on the 2025 heavy summer and EI multi-regional modeling working group (MMWG) 2026 summer peak cases. This work developed high-fidelity models and simulation algorithms to understand the dynamics of MMC. The developed models and simulation algorithms are up to 25 times faster than the existing algorithms. Models and control algorithms for high-fidelity models were designed and tested for point-to-point and multi-terminal configurations. The multi-terminal configuration was tested connecting simplified models of EI, WI, and Electric Reliability Council of Texas (ERCOT). The developed models showed up to 45% improvement in frequency response with the connection of all the three asynchronous interconnections in the United States using fast and advanced DC technologies like the multi-terminal MMC-DC system. Future work will look into developing high-fidelity models of other advanced DC technologies, combining high-fidelity models with the continental-level model, incorporating additional services. More scenarios involving large-scale HVDC and MTDC will be evaluated.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Reliability, Resilience and the Oncoming Wave of Retiring Baseload Units, Volume I: The Critical Role of Thermal Units During Extreme Weather Events

This study examines the cold weather event now known as the Bomb Cyclone that blanketed much of the eastern half of the United States from Dec 27, 2017 through Jan 8, 2018. Analyses focus on six areas of organized markets administered by independent system operators in the US Eastern Interconnection and Texas. This report finds: (1) Combined, fossil and nuclear energy plants provided 89% of electricity during peak demand across all the ISOs; (2) Coal provided the most resilient form of generation in PJM; (3) The value of fuel-based power generation resilience in PJM during this event was estimated at $3.5 billion; (4) Natural gas price spikes, increased demand, and pipeline constraints led to significant fuel oil burn in the US Northeast; (5) Renewables imposed a resilience penalty on the system as output decreased as demand increased; (6) Underestimation of coal and nuclear retirements could give rise to reliability concerns and an inability to meet projected electricity demand.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Clean Grid Vision: A U.S. Perspective - Chapter 1. Clean Grid Scenarios

Chapter 1: Clean Grid Scenarios serves as a broad introduction to the type of future power systems envisioned in the Clean Grid Vision: one with high penetrations of variable renewable energy generation (for example, more than 53% nationally and up to 73% in the Eastern Interconnection) and significant share of natural gas. Our study shows that the conterminous United States has adequate resources to support such systems with current technologies, and these systems can be operated cost-effectively to meet all sub-hourly demand and reserve requirements.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Developing a Power Plant Suitability Model for the Energy Zones Mapping Tool

This report provides an example of designing, developing, and running a power plant suitability model in the Energy Zones Mapping Tool (EZMT), a public, web-based mapping tool with a large spatial database focused on energy infrastructure, energy resources, and related siting factors. The example focuses on natural gas combined cycle (NGCC) power plants, which have several unique and interesting characteristics. NGCC plants typically provide peaking power to the electrical grid. Such plants can be started or stopped relatively quickly and are often used to supplement base load plants (such as nuclear or coal) during times of peak electrical consumption or to counterbalance lulls in variable power generation (such as wind or solar). Due to these and other factors, NGCC plants have been projected to increase in number under energy planning studies such as Hadley et al. The scope of the Hadley et. al. study is the Eastern Interconnection (EI), the electrical transmission grid serving much of the United States and Canada east of the Rocky Mountains. Results in the study are organized according to 22 Multi-region National—North American Electricity and Environment Model (NEEM) regions within the EI. NGCC plants usually have lower water requirements than other thermoelectric power plants they may replace; therefore, they are expected to have an interesting role in reducing the overall water requirements of energy generation.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

Big Data Synchrophasor Monitoring and Analytics for Resiliency Tracking (BDSMART)

This report contains key findings from a project titled Big Data Synchrophasor Monitoring and Analytics for Resiliency Tracking (BDSMART), which was carried out through a collaborative effort of a team of researchers from Texas A&M Engineering Experiment Station, Temple University, and Quanta Technology, LLC. The in-kind support came from OSIsoft (acquired by AVEVA), which provided their PI Historian software to demonstrate the use case of streaming PMU data. The first section of the report describes the project goals and objectives related to the development of Machine Learning (ML) models capable of detecting and classifying events by processing phasor measurements captured in the field by Phasor Measurement Units (PMUs). The data for this study was contributed by the utilities/ISOs from the Western and Eastern interconnects and ERCOT, further referred to as Interconnect B (IC B), Interconnect A (IC A), and Interconnect C (IC C), respectively. The approach that the BDSMART Research Team proposed and the key research tasks defined by the team are outlined in this section. The next section describes the technical approach. We first discuss the data constraints related to the PMU measurements and data interpretation constraints imposed by the data contributors. They provided neither the topological information of the grid nor PMU placement locations and captured recorded data at very few locations in the system with the reporting rate of either 30 or 60 fps. The recordings are mostly positive sequence voltage, frequency, and ROCOF, and in some limited cases, three-phase voltages and currents. We then reflect on the bad data issues that stem from poor recording practices and vague definitions of the PMU status bits to supposedly be used for bad data identification. Finally, the data discovery points to imprecise time stamps with incomplete event start/end time, as well as inconsistent and incomplete event labeling, which combined make the implementation of the data models using supervising learning quite challenging. Following the data discovery study, we hypothesize that because the IC B data has the most complete labels, we should focus our model development on that data and then test it on data from other interconnects. We also define the common metrics used to evaluate the results from the ML algorithm tests. We concluded this section by summarizing the common ML models we used and explaining how we implemented and tested them. The issues from this section are expanded in the Training Dataset Report from this project. The final section of this report deals with the accomplishments and conclusions. As the accomplishments, we formulate the problem we are solving and what is achieved by solving the problem. We then reflect on each of the analytics tools we developed and point out the performance of each tool when applied to solving the mentioned problems. We reference this work for further details to the papers we published on each tool. In the conclusions, we give recommendations on how to improve future PMU recording practices to facilitate the ML algorithm implementation and guidance for the future standardization work aimed at clarifying the ambiguities associated with the PMU status bits. We finally list future tasks that can bring about further improvements in the proposed algorithms. The issues from this section are expanded in the Training, and Test Dataset Report filed at the project completion date.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

The Building ENergy Demand (BEND) Model: A Comprehensive Composite Building Energy Modeling Framework

The Building ENergy Demand (BEND) model was developed at Pacific Northwest National Laboratory (PNNL) to simulate climate-dependent hourly building energy demand with the ability to disaggregate down to or aggregate up to any geographic area of interest, including counties, states, electric utility service territories, and census regions. The BEND modeling framework is designed to study the effects of climate change, economics, technology advancement, and various mitigation policies on aggregate building energy demand. To make the process computationally feasible, BEND reduces granularity in building characteristics and weather forcing while maintaining enough detail to minimize systematic differences (biases) between BEND results and data from the Energy Information Administration (EIA). Based on the Commercial Building Energy Consumption Survey (CBECS) and Residential Energy Consumption Survey (RECS) databases, BEND establishes a set of representative buildings with predefined sets of building types, sizes, and vintages. These representative buildings are defined for each of the four U.S. census regions and the five climate zones used by the EIA for building surveys (hereafter “EIA climate zones”). BEND’s representative buildings are based on a statistical analysis of the CBECS and RECS databases that infers detailed parameters such as construction type, thermal properties, internal loads, equipment and mechanical systems, and operation schedules from the high-level descriptors in those databases (building type, vintage, size, and location). The representative buildings are simplified and consolidated into a set of prototype buildings for the purpose of simulating building energy demand. Combining the prototype buildings with weather files from selected locations and years, BEND creates a set of simulation-ready building models to be run using the EnergyPlus simulation engine (EnergyPlus). The base spatial unit of each BEND simulation is a subregion that is the intersection of an International Energy Conservation Code climate zone, a census region, and an EIA climate zone; analysis for each spatial unit is influenced by the weather file BEND selects to represent the climate-similar area. The major simulation outputs of interest to BEND are hourly energy consumption values for each simulated year, possibly for multiple fuel types. Based on building-stock weights derived from the CBECS/RECS data, the hourly output streams are aggregated to a single, 8760-hour load profile for each of the major building categories—residential and commercial—with the possibility of segregating by fuel types. To correct for biases inherent in the use of a limited suite of representative buildings, BEND is calibrated against observational targets of total annual building energy consumption and hourly load profiles (including peak demand) obtained for the decision-relevant geographic scales of interest (e.g., total electric load data for individual balancing authorities available from EIA). Based on available data such as population distribution, BEND is able to aggregate both up and down scales, allowing the study of building energy demand over a range of spatial scales (e.g., states or counties within the Western Electricity Coordinating Council, Eastern Interconnection, or the entire U.S.) and/or subsets of building types (e.g., office buildings with particular size ranges).

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Interpreting Forced Oscillation Notifications from ESAMS: General Guidance for Reliability Coordinators

The Eastern Interconnection Situational Awareness Monitoring System (ESAMS) project demonstrated the feasibility of aggregating synchrophasor measurements from across an interconnection, analyzing them, and providing real-time wide-area situational awareness to system operators who may have excellent visibility within their footprint but lack an interconnection-wide view. An application within ESAMS that has garnered industry interest involves detecting forced oscillations visible across multiple areas, identifying the region where the oscillation originated from, quantifying the uncertainty in source localization results, and notifying users in real-time if the detected oscillation amplitudes cross a specified threshold. It is expected that system operators will utilize their internal SCADA/EMS/synchrophasor systems in conjunction with information provided by ESAMS to take effective mitigation actions if forced oscillation notifications are received. This report provides some general guidance on how the ESAMS information can be used for source localization and coordination among multiple reliability coordinators; and also identifies potential enhancements to ESAMS notifications for improved interpretability.

24 POWER TRANSMISSION AND DISTRIBUTION↗