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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Resilient Transmission Hardening Planning in a High Renewable Penetration Erra

Hardening components in transmission systems is a practice to improve system resilience against possible disturbances caused by natural disasters. In a power system with a very high penetration of renewable energy, the system hardening will be further complicated by the uncertainty and variability of renewable energy. In this paper, we study the transmission line hardening planing problem in the context of probabilistic power flows injected by the high penetration of renewable energy. We assume that the probabilistic information of renewable energy is incomplete and ambiguous and propose a data-driven approach to approximate the renewable uncertainty sets. We then extend the N - 1 security criteria to multiple simultaneous contingencies and seek to prepare a hardening plan for the worst-case scenarios. A two-stage data-driven stochastic model is formulated by considering the joint worst-case wind output distribution and transmission line contingencies. Then, we apply the Column-and-Constraints generation method to solve the proposed model. To test the effectiveness of the proposed approach, we conduct experiments on 24-bus and 118-bus test systems. We numerically show that the data-driven approach can effectively address the uncertainty ambiguity and the proposed approach can produce effective hardening plans that improve the system resilience.

Column-and-Constraint generation↗
DOE OSTI2022

Learning and Fast Adaptation for Grid Emergency Control via Deep Meta Reinforcement Learning

As power systems are undergoing a significant transformation with more uncertainties, less inertia and closer to operation limits, there is increasing risk of large outages. Thus, there is an imperative need to enhance grid emergency control to maintain system reliability and security. Towards this end, great progress has been made in developing deep reinforcement learning (DRL) based grid control solutions in recent years. However, existing DRL-based solutions have two main limitations: 1) they cannot handle well with a wide range of grid operation conditions, system parameters, and contingencies; 2) they generally lack the ability to fast adapt to new grid operation conditions, system parameters, and contingencies, limiting their applicability for real-world applications. Here, in this paper, we mitigate these limitations by developing a novel deep meta-reinforcement learning (DMRL) algorithm. The DMRL combines the meta strategy optimization together with DRL, and trains policies modulated by a latent space that can quickly adapt to new scenarios. We test the developed DMRL algorithm on the IEEE 300-bus system. We demonstrate fast adaptation of the meta-trained DRL polices with latent variables to new operating conditions and scenarios using the proposed method, which achieves superior performance compared to the state-of-the-art DRL and model predictive control (MPC) methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

A Fast Load Control System Based on Mobile Distribution-Level Phasor Measurement Unit

The increase of renewable penetration in power grids calls for loads to participate in frequency regulation to avoid under-frequency load shedding after large resource contingencies. The motivation of our work is to fulfill a fast residential load control for frequency stability enhancement. For this purpose, a novel Mobile Distribution-level Phasor Measurement Unit (MDPMU) is developed for disturbance event detection, power mismatch estimation and fast load control. First, the systematic design of the MDPMU introduced. The proposed MDPMU has the major advantages of low cost and high frequency measurement accuracy. Second, the distribution-level measurement is utilized for the Rate Of Change Of Frequency (ROCOF) calculation. Upon detection of a power system frequency event, power mismatch is estimated at the early stage of the event. Details of a robust approach to calculate ROCOF and determine the event starting point are presented. Practical issues including the measurement reporting rate and estimation time are also examined. Finally, with the proposed control system, residential load responses can be controlled coordinately based on load availability and compensation prices offered by customers, providing adaptive frequency regulation service after large resource contingencies. The accuracy of frequency measurement and power mismatch estimation are evaluated via experimental analysis. The frequency stability improvement by load control is validated via PSS/E simulation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

AMPS: An Augmented Matrix Formulation for Principal Submatrix Updates with Application to Power Grids

We present an augmented matrix approach to update the solution to a linear system of equations when the coefficient matrix is modified by a few elements within a principal submatrix. This problem arises in the dynamic security analysis of a power grid, where operators need to perform $N-x$ contingency analysis, i.e., determine the state of the system when up to $x$ links from $N$ fail. Our algorithms augment the coefficient matrix to account for the changes in it, and then compute the solution to the augmented system without refactoring the modified matrix. We provide two algorithms, a direct method, and a hybrid direct-iterative method for solving the augmented system. We also exploit the sparsity of the matrices and vectors to accelerate the overall computation. Our algorithms are compared on three power grids with PARDISO, a parallel direct solver, and CHOLMOD, a direct solver with the ability to modify the Cholesky factors of the coefficient matrix. We show that our augmented algorithms outperform PARDISO (by two orders of magnitude), and CHOLMOD (by a factor of up to 5). Further, our algorithms scale better than CHOLMOD as the number of elements updated increases. The solutions are computed with high accuracy. Our algorithms are capable of computing $N-x$ contingency analysis on a $778K$ bus grid, updating a solution with $x=20$ elements in $1.6 \times 10^{-2}$ seconds on an Intel Xeon processor.

Yeung, Yu-Hong↗
DOE OSTI2015

Geographic Visualization of Power-Grid Dynamics

The visualization enables the simulation analyst to see changes in the frequency through time and space. With this technology, the analyst has a bird's eye view of the frequency at loads and generators as the simulated power system responds to the loss of a generator, spikes in load, and other contingencies. The significance of a contingency to the operation of an electrical power system depends critically on how the resulting tansients evolve in time and space. Consequently, these dynamic events can only be understood when seen in their proper geographic context. this understanding is indispensable to engineers working on the next generation of distributed sensing and control systems for the smart grid. By making possible a natural and intuitive presentation of dynamic behavior, our new visualization technology is a situational-awareness tool for power-system engineers.

Sukumar, SreenivasR.↗
DOE OSTI2017

A cascading failure analysis tool for post processing TRANSCARE simulations

This is a MATLAB-based tool to post process simulation results in the EPRI software TRANSCARE, for massive cascading failure analysis following severe disturbances. There are a few key modules available in this tool, including: 1. automatically creating a contingency list to run TRANSCARE simulations, including substation outages above a certain kV threshold, N-k (1, 2 or 3) generator outages and branch outages; 2. read in and analyze a CKO file of PCG definition, an initiating event list, and a CDN file; 3. post process all the simulation results saved in a CDN file and perform critical event corridor analysis; 4. provide a summary of TRANSCARE simulations; 5. Identify the most frequently occurring event corridors in the system; and 6. Rank the contingencies using a user defined security index to quantify consequences in terms of total load loss, total number of cascades, etc.

Source record↗
DOE OSTI2020

GridOPTICS/GridPACK

GridPACK is a software framework consisting of a set of modules designed to simplify the development of programs that model the power grid and run on parallel, high performance computing platforms. It also contains several fully developed applications, including powerflow, dynamic simulation, state estimation, Kalman filter analysis (dynamic state estimation), contingency analysis and real time path rating. These applications can be used either standalone or as components in more complicated workflows that combine several different types of application together. The framework modules are available as a combination of libraries and software templates and consist of components for setting up and distributing power grid networks, support for modeling the behavior of individual buses and branches in the network, converting the network models to the corresponding algebraic equations, and parallel routines for manipulating and solving large algebraic systems. The framework also contains a module for distributing tasks evenly amongst computing resources, even if individual tasks vary widely in their execution times. Additional modules support input and output, basic statistical analysis of contingency based calculations, distributed data structures, as well as basic profiling and error management.

Palmer, Bruce↗
DOE OSTI2023

A Surrogate-Based Asynchronous Decomposition Technique for Realistic Security-Constrained Optimal Power Flow Problems

Here we present a decomposition approach for obtaining good feasible solutions for the security-constrained, alternating-current, optimal power flow (SC-AC-OPF) problem at an industrial scale and under real-world time and computational limits. The approach was designed while preparing and participating in ARPA-E’s Grid Optimization Competition (GOC) Challenge 1. The challenge focused on a near-real-time version of the SC-AC-OPF problem, where a base operating point is optimized, taking into account possible single-element contingencies, after which the system adapts its operating point following the response of automatic frequency droop controllers and voltage regulators. Our solution approach for this problem relies on state-of-the-art nonlinear programming algorithms, and it employs nonconvex relaxations for complementarity constraints, a specialized two-stage decomposition technique with sparse approximations of recourse terms and contingency ranking and prescreening. The paper describes and justifies our approach and outlines the features of its implementation, including functions and derivatives evaluation, warm-starting strategies, and asynchronous parallelism. We discuss the results of the independent benchmark of our approach by ARPA-E’s GOC team in Challenge 1, where it was found to consistently produce high-quality solutions across a wide range of network sizes and difficulty, and conclude by outlining future extensions of the approach.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Survey of U.S. Ancillary Services Markets

In addition to providing energy to end-consumers, power system operators are also responsible for ensuring system reliability. To this end, power markets maintain an array of ancillary services to ensure that it is always possible to balance the supply and demand for energy in real-time. A subset of these ancillary services are commonly procured through market-based mechanisms: namely, Regulation, Spinning, and Non-spinning Reserves. Regulation Reserves are maintained to respond to supply/demand imbalances over short time frames, typically on the order of several seconds to one minute. Resources that provide Regulation Reserves adjust their generation or load levels in response to automatic generation control (AGC) signals provided by the system operator. Contingency reserves are maintained to provide additional generation capacity in the event that load increases substantially or supply side resources reduce their output or are taken offline. The reserves are typically segmented into two categories, 1) Spinning or Synchronized Reserves that are provided by generation units that are actively generating and have the ability to increase or decrease their output, 2) Non-spinning or Non-synchronized Reserves that are provided by generation resources that are not actively generating, but are able to start up and provide generation within a specified timeframe. Contingency reserves typically have response times on the order of ten to 30 minutes and can also be provided by demand-side resources that are capable of reducing their load. There are seven distinct power markets in the United States, each operated by a Regional Transmission Operator (RTO) or Independent System Operator (ISO) that operates the transmission system in its territory, operates markets for energy and ancillary services, and maintains system reliability. Each power market offers its own set of ancillary services, and precise definitions, requirements, and market mechanisms differ between markets. Despite the differences between markets, both in terms of services offered and system requirements, some broad trends generally apply. Regulation Reserves typically have the highest market prices, followed by Spinning Reserves and Non-spinning Reserves. Prices for Regulation Reserves have been the highest in the PJM market, since it opened in October 2012. This is partially because PJM experienced large price spikes during the period of extreme weather conditions in early 2014. ERCOT has traditionally had the highest prices for Spinning Reserves (called Responsive Reserves in ERCOT), including several periods of sustained high prices between 2010 and 2012. This can be explained in part by the relatively high penetration of variable wind resources and a similarly high requirement relative to peak load. ERCOT has also traditionally had the highest price for Non-spinning Reserves, followed by the NYISO East region. Both have experienced several periods of prolonged high prices since their inception, an occurrence that has not been regularly seen in other markets. In ISO-NE and PJM for example, the market clearing price for Non-spinning Reserves is typically $0/MWh more than 95% of the time. Market volume (in terms of the average amount of capacity of each service that is provided to a system) typically follows the reverse order of prices, as systems maintain the most Non-spinning Reserves capacity followed by Spinning Reserves and Regulation Reserves. PJM generally has the largest market for Regulation Reserves both in terms of capacity. The size of most Regulation Reserves markets in terms of capacity stay relatively constant year-to-year, as this is dictated largely by system requirements. PJM also generally has the largest Spinning Reserves market in terms of capacity. SPP, MISO, ISO-NE and SPP (beginning in 2014) all have Spinning Reserve markets with similar average capacity levels. When combined, the markets for Non-spinning and Operating reserves in ISO-NE have a comparable capacity to the market for Primary Reserves 1 in PJM. SPP, MISO, and CAISO all have smaller markets for their respective Non-spinning Reserves products that are roughly the same size as each other in terms of capacity.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Monticello Mill Tailings Site, Operable Unit lll, Annual Groundwater Report, May 2015 Through April 2016

This report provides the annual analysis of water quality restoration progress, cumulative through April 2016, for Operable Unit (OU) III, surface water and groundwater, of the U.S. Department of Energy (DOE) Office of Legacy Management (LM) Monticello Mill Tailings Site (MMTS). The MMTS is a Comprehensive Environmental Response, Compensation, and Liability Act National Priorities List site located in and near the city of Monticello, San Juan County, Utah. MMTS comprises the 110-acre site of a former uranium- and vanadium-ore-processing mill (mill site) and 1700 acres of surrounding private and municipal property. Milling operations generated 2.5 million cubic yards of waste (tailings) from 1942 to 1960. The tailings were impounded at four locations on the mill site. Inorganic constituents in the tailings drained from the impoundments to contaminate local surface water (Montezuma Creek) and groundwater in the underlying alluvial aquifer. Mill tailings dispersed by wind and water also contaminated properties surrounding and downstream of the mill site. Remedial actions to remove and isolate radiologically contaminated soil, sediment, and debris from the former mill site, Operable Unit I (OU I), and surrounding properties (OU II) were completed in 1999 with the encapsulation of the wastes in an engineered repository located on DOE property 1 mile south of the former mill site. This effectively removed the primary source of groundwater contamination; however, contamination of groundwater and surface water remains within OU III at levels that exceed water quality protection standards. Uranium is the primary contaminant of concern (COC). LM implemented monitored natural attenuation with institutional controls as the OU III remedy in 2004. Because groundwater restoration proceeded more slowly than expected and did not meet performance criteria established in the OU III Record of Decision (June 2004), LM implemented a contingency action in 2009 by an Explanation of Significant Difference to include a pump-and­ treat system using a single extraction well and treatment by zero-valent iron (ex situ treatment system). The contingency action was optimized in 2015 with the installation of8 extraction wells and 16 monitoring wells in a focused area of the aquifer, the area of attainment (AOA). Contaminated water is treated by solar evaporation at an existing facility at the LM repository.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Accurate Holdup Calculations with Predictive Modeling & Data Integration

In facilities that process special nuclear material (SNM) it is important to account accurately for the fissile material that enters and leaves the plant. Although there are many stages and processes through which materials must be traced and measured, the focus of this project is material that is “held-up” in equipment, pipes, and ducts during normal operation and that can accumulate over time into significant quantities. Accurately estimating the holdup is essential for proper SNM accounting (vis-à-vis nuclear non-proliferation), criticality and radiation safety, waste management, and efficient plant operation. Usually it is not possible to directly measure the holdup quantity and location, so these must be inferred from measured radiation fields, primarily gamma and less frequently neutrons. Current methods to quantify holdup, i.e. Generalized Geometry Holdup (GGH), primarily rely on simple source configurations and crude radiation transport models aided by ad hoc correction factors. This project seeks an alternate method of performing measurement-based holdup calculations using a predictive model that employs state-of-the-art radiation transport codes capable of accurately simulating such situations. Inverse and data assimilation methods use the forward transport model to search for a source configuration that best matches the measured data and simultaneously provide an estimate of the level of confidence in the correctness of such configuration. In this work the holdup problem is re-interpreted as an inverse problem that is under-determined, hence may permit multiple solutions. A probabilistic approach is applied to solving the resulting inverse problem. This approach rates possible solutions according to their plausibility given the measurements and initial information. This is accomplished through the use of Bayes’ Theorem that resolves the issue of multiple solutions by giving an estimate of the probability of observing each possible solution. To use Bayes’ Theorem, one must have a model y(x) that maps the state variables x (the solution in this case) to the measurements y. In this case, the unknown state variables are the configuration and composition of the heldup SNM. The measurements are the detector readings. Thus, the natural model is neutral-particle radiation transport where a wealth of computational tools exists for performing these simulations accurately and efficiently. The combination of predictive model and Bayesian inference forms the Data Integration with Modeled Predictions (DIMP) method that serves as foundation for this project. The cost functional describing the model-to-data misfit is computed via a norm created by the inverse of the covariance matrix of the model parameters and responses. Since the model y(x) for the holdup problem is nonlinear, a nonlinear optimization on Q is conducted via Newton-type iterative methods to find the optimal values of the model parameters x. This project comprised a collaboration between NC State University (NCSU), the University of South Carolina (USC), and Oak Ridge National Laboratory (ORNL). The project was originally proposed in seven main tasks with an eighth contingency task to be performed if time and funding permitted; in fact time did not permit commencement of the contingency task and it was not performed. The remaining tasks involved holdup analysis with gamma detection strategies and separately with neutrons based on coincidence counting. Early in the project, and upon consultation with experts in coincidence counting it became evident that this approach is not viable for holdup applications and this task was replaced with an alternative, but valuable investigation that was carried out by the USC partner. Nevertheless, the experimental 4 measurements at ORNL of both gamma and neutron sources for the purpose of constructing Detector Response Functions (DRFs) with the associated uncertainties were indeed completed.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

A Lyapunov Function Based Remedial Action Screening Tool Using Real-Time Data

This report summarizes the outcome of a research project that comprised the development of a Lyapunov function based remedial action screening tool using real-time data (L-RAS). The L-RAS is an advanced computational tool that is intended to assist system operators in making real-time redispatch decisions to preserve power grid stability. The tool relies on screening contingencies using a homotopy method based on Lyapunov functions to avoid, to the extent possible, the use of time domain simulations. This enables transient stability evaluation at real-time speed without the use of massively parallel computational resources. The project combined the following components. 1. Development of a methodology for contingency screening using a homotopy method based on Lyapunov functions and real-time data. 2. Development of a methodology for recommending remedial actions based on the screening results. 3. Development of a visualization and operator interaction interface. 4. Testing of screening tool, validation of control actions, and demonstration of project outcomes on a representative real system simulated on a Real-Time Digital Simulator (RTDS) cluster. The project was led by Michigan State University (MSU), where the theoretical models including homotopy-based screening, trajectory correction using real-time data, and remedial action were developed and implemented in the form of research-grade software. Los Alamos National Laboratory (LANL) contributed to the development of energy margin sensitivity dynamics, which constituted a part of the remedial action portfolio. Florida State University (FSU) and Southern California Edison (SCE) developed a model of the SCE system that was implemented on FSU's RTDS cluster to simulate real-time data that was streamed over the internet to MSU where the L-RAS tool was executed and remedial actions were communicated back to FSU to execute stabilizing controls on the simulated system. LCG Consulting developed the visualization and operator interaction interface, based on specifications provided by MSU. The project was performed from October 2012 to December 2016, at the end of which the L-RAS tool, as described above, was completed and demonstrated. The project resulted in the following innovations and contributions: (a) the L-RAS software prototype, tested on a simulated system, vetted by utility personnel, and potentially ready for wider testing and commercialization; (b) an RTDS-based test bed that can be used for future research in the field; (c) a suite of breakthrough theoretical contributions to the field of power system stability and control; and (d) a new tool for visualization of power system stability margins. While detailed descriptions of the development and implementation of the various project components have been provided in the quarterly reports, this final report provides an overview of the complete project, and is demonstrated using public domain test systems commonly used in the literature. The SCE system, and demonstrations thereon, are not included in this report due to Critical Energy Infrastructure Information (CEII) restrictions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Dynamics Informed Optimization for Resilient Energy Systems

Optimal mitigation planning for highly disruptive contingencies to a transmission-level power system requires optimization with dynamic power system constraints, due to the key role of dynamics in system stability to major perturbations. We formulate a generalized disjunctive program to determine optimal grid component hardening choices for protecting against major failures, with differential algebraic constraints representing system dynamics (specifically, differential equations representing generator and load behavior and algebraic equations representing instantaneous power balance over the transmission system). We optionally allow stochastic optimal pre-positioning across all considered failure scenarios, and optimal emergency control within each scenario. This novel formulation allows, for the first time, analyzing the resilience interdependencies of mitigation planning, preventive control, and emergency control. Using all three strategies in concert is particularly effective at maintaining robust power system operation under severe contingencies, as we demonstrate on the Western System Coordinating Council (WSCC) 9-bus test system using synthetic multi-device outage scenarios. Towards integrating our modeling framework with real threats and more realistic power systems, we explore applying hybrid dynamics to power systems. Our work is applied to basic RL circuits with the ultimate goal of using the methodology to model protective tripping schemes in the grid. Finally, we survey mitigation techniques for HEMP threats and describe a GIS application developed to create threat scenarios in a grid with geographic detail.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Electron Cloud Simulations for the Electron-Ion Collider in Brookhaven National Laboratory

For high-intensity circular accelerators and storage rings, if the secondary electron emission yield (SEY) of the vacuum chamber surfaces is high, an EC (Electron Cloud) could build up with the passage of the circulating beam. The presence of EC can strongly affect the beam quality, such as transverse instabilities, transverse emittance growth, and beam loss. Furthermore, the heat load from EC can exceed the available cryogenic capability. For the RHIC superconducting (SC) arc magnets, to be used for the hadron storage ring of the Electron-Ion Collider (EIC), the dynamic heat load budget is 0.5 W/m to the 4.5 K stainless steel beam pipe. This can limit the maximum beam bunches or intensity of the EIC, hence diminishing the luminosity provided by the EIC. The EC has affected the beam instability and significantly contributed to cryogenic heat load in the Large Hadron Collider (LHC). Positron storage rings for which ECs have been a critical factor in the design and performance include KEKB in Japan and EC buildup remains one of the concerns for future high-intensity accelerators design. EC considerations have driven the SuperKEKB collider design and the positron damping ring for the proposed International Linear Collider (ILC). The LHC luminosity upgrade is contingent on reducing the bunch spacing to 25 ns; at this bunch spacing, severe EC buildup has been observed. The success of the upgrade is likely contingent on limiting EC buildup. To study the EC heat load, we did some EC simulations with PyECLOUD code for the dipole, quadrupole, sextupole magnets, and the warm (drift) section of the EIC hadron storage ring. PyECLOUD is an EC simulation code developed by CERN. The code has been validated and used to study EC in the LHC, SPS, and PS. To eliminate EC buildup, the sources of electrons must be minimized. First, we will reduce the production of electrons due to residual gas ionization by specifying the maximum gas density, which requires a vacuum chamber with low electron-stimulated desorption (ESD) yields and a sufficient (preferably distributed) pumping speed. Second, we should reduce the secondary electrons with a lower secondary electron yield (SEY) material.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

A nonsmooth nonconvex optimization algorithm for two-stage optimization problems

An optimization algorithm for a group of nonsmooth nonconvex problems inspired by two-stage stochastic programming problems is proposed. The main challenges for these problems include (1) the problems lack the popular lower-type properties such as prox-regularity assumed in many nonsmooth nonconvex optimization algorithms, (2) the objective can not be analytically expressed and (3) the evaluation of function values and subgradients are computationally expensive. To address these challenges, this report first examines the properties that exist in many two-stage problems, specifically upper-C 2 objectives. Then, we show that quadratic penalty method for securityconstrained alternating current optimal power flow (SCACOPF) contingency problems can make the contingency solution functions upper-C 2 . Based on these observations, a simplified bundle algorithm that bears similarity to sequential quadratic programming (SQP) method is proposed. It is more efficient in implementation and computation compared to conventional bundle methods. Global convergence analysis of the algorithm is presented under novel and reasonable assumptions. The proposed algorithm therefore fills the gap of theoretical convergence for smoothed SCACOPF problems. The inconsistency that might arise in our treatment of the constraints are addressed through a penalty algorithm whose convergence analysis is also provided. Finally, theoretical capabilities and numerical performance of the algorithm are demonstrated through numerical examples.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Library of Advanced Models of large-scale PV (LAMP) (Final Technical Report)

A suite of dynamic models of photovoltaic (PV) systems is developed in this project to accurately capture PV system dynamics during different contingencies. The following models are included: (i) quasi-dynamic, (ii) high-fidelity electromagnetic transient (EMT), (iii) advanced, and (iv) baseline. The models have the flexibility to consider different control functionalities at different controller levels. The study’s requirements determine the type of model needed. For example, high-fidelity EMT models are recommended for contingency studies. Advanced models are recommended for online or real-time implementations with resource constraints, whereas quasi-dynamic models are useful for studying the impact of weather variations.

14 SOLAR ENERGY↗
DOE OSTI2024

An Iterative Approach for Solving the SCOPF Problem Applying LP, SOCP, and NLP Subproblems

We propose to develop efficient algorithms and software for the SCOPF problem. We will employ an iterative approach that will: a) use linear subproblems and other active set filtering techniques to identify the most important contingencies and drastically reduce the SCOPF model size; b) solve SOCP relaxations of the reduced SCOPF to converge to the neighborhood of the global optimal solution and establish a lower bound on the solution, and; c) use a non-convex, nonlinear interior-point solver, Artelys Knitro, to converge quickly to the optimal solution. To identify the most effective approach, we will experiment with several techniques to identify the tradeoffs between contingency subproblem complexity and fast solvability.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Transmission Operator Workflows for Real-Time Reliability Studies: A Review of Control Room Practices and Naturalistic Decision Making

This report provides an overview of real-time reliability study tools and their use by power system operators in the control room environment. After introducing some of the nuances of the control room environment and the differences in perspectives between power system engineers and operators, the roles and responsibilities of key entities involved in RTCA workflows are introduced. These are specifically the transmission system operator (TOP) and reliability coordinator (RC), which are required to run tools such as real-time contingency analysis (RTCA) as part of a real-time reliability assessment every 30 minutes, as dictated by a series of standards issued by the North American Electric Reliability Corporation (NERC). The process by which power systems operators operate the grid is discussed in terms of naturalistic decision making (NDM) and the recognition-primed decision-making (RPD) model. This cognitive model describe how experts working in high-risk, high-stress environments make safety-critical decisions under uncertainty and time pressure. For power system operators, the mental simulations involved in the traditional RPD model are supplemented by physics-based simulations using numerical tools, such as RTCA, to improve situational awareness and effectiveness of control actions. Next, a generic workflow is introduced to describe operator decision making for running RTCA tools and responding to system violations on a pre-contingent basis. The types of analysis performed and control actions chosen by power system operators are described in detail. The overall high-level workflow is then expanded in subsequent sections, with special attention given to high-voltage violations, low-voltage violations, and thermal overloads. Each type of violation is described in detail, with explanations of common causes, impacts on equipment and customers, and mitigation strategies. An additional workflow diagram is provided for each type of violation.

24 POWER TRANSMISSION AND DISTRIBUTION↗