Monitoring, Control, and Protection
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Item Distributed Primal-Dual Interior Point Framework for Analyzing Infeasible Combined Transmission and Distribution Grid Networks(2025-01-07) Ali, Muhammad Hamza; Pandey, AmritanshuThe proliferation of distributed energy resources has heightened the interactions between transmission and distribution (T&D) systems, necessitating novel analyses for the reliable operation and planning of interconnected T&D networks. A critical gap is an analysis approach that identifies and localizes the weak spots in the combined T&D networks, providing valuable information to system planners and operators. The research goal is to efficiently model and simulate infeasible (i.e. unsolvable in general settings) combined positive sequence transmission and three-phase distribution networks with a unified solution algorithm. We model the combined T&D network with the equivalent circuit formulation. To solve the overall T&D network, we build a Gauss-Jacobi-Newton (GJN) based distributed primal dual interior point optimization algorithm capable of isolating weak nodes. We validate the approach on large combined T&D networks with 70k+ T and 15k+ D nodes and demonstrate performance improvement over the alternating direction method of multipliers (ADMM) method.Item A Unified Approach to Enforce Non-Negativity Constraint in Neural Network Approximation for Optimal Voltage Regulation(2025-01-07) Wu, Jiaqi; Yuan, Jingyi; Weng, Yang; Wang, GuangwenPower system voltage regulation is crucial to maintain power quality while integrating intermittent renewable resources in distribution grids. However, the system model on the grid edge is often unknown, making it difficult to model physical equations for optimal control. Therefore, previous work proposes structured data-driven methods like input convex neural networks (ICNN) for "optimal" control without relying on a physical model. While ICNNs offer theoretical guarantees based on restrictive assumptions of non-negative neural network (NN) parameters, can one improve the approximation power with an extra step on negative duplication of inputs? We show that such added mirroring step fails to improve accuracy, as a linear combination of the original input and duplicated input is equivalent to a linear operation of ICNN's input without duplication. While this design can not improve performance, we propose a unified approach to embed the non-negativity constraint as a regularized optimization of NN, contrary to the existing methods, which added a loosely integrated second step for post-processing on parameter negation. Our integration directly ties back-propagation to simultaneously minimizing the approximation error while enforcing the convexity constraints. Numerical experiments validate the issues of the mirroring method and show that our integrated objective can avoid problems such as unstable training and non-convergence existing in other methods for optimal control.Item Equivalent-circuit Models for Grid-forming Inverters under Unbalanced Steady-State Operating Conditions(2025-01-07) Baeckeland, Nathan; Seo, Gab-Su; Dominguez-Garcia, Alejandro; Ramasubramanian, Deepak; Gross, Dominic; Dhople, SairajPositive- and negative-sequence equivalent-circuit models are put forth to capture the operation of grid-forming (GFM) inverters in unbalanced steady-state operating conditions acknowledging the impact of current limiting. The particular control architecture examined adopts droop control (for primary control), nested inner-current and outer-voltage control (in the stationary reference frame), and it is adaptable to two different types of current limiting (current-reference saturation and virtual-impedance limiting). We anticipate the proposed models to be of interest in modeling, analysis, and simulation of GFM inverters in unbalanced settings that may arise, e.g., in the face of faults. Validation of the equivalent-circuit models is pursued via comparison with full-order electromagnetic-transient (EMT) simulations for representative balanced and unbalanced faults.Item Safe Control of Grid-Interfacing Inverters with Current Magnitude Limits(2025-01-07) Joswig-Jones, Trager; Zhang, BaosenGrid-interfacing inverters allow renewable resources to be connected to the electric grid and offer fast and programmable control responses. However, inverters are subject to significant physical constraints. One such constraint is a current magnitude limit required to protect semiconductor devices. While many current limiting methods are available, they can often unpredictably alter the behavior of the inverter control during overcurrent events leading to instability or poor performance. In this paper, we present a safety filter approach to limit the current magnitude of inverters controlled as voltage sources. The safety filter problem is formulated with a control barrier function constraint that encodes the current magnitude limit. To ensure feasibility of the problem, we prove the existence of a safe linear controller for a specified reference. This approach allows for the desired voltage source behavior to be minimally altered while safely limiting the current output.Item Effect of Lightning Features on Predicting Outages Related to Thunderstorms in Distribution Grids(2025-01-07) Kezunovic, Mladen; Baembitov, Rashid; Saranovic, Daniel; Karmacharya , Abinash; Obradovic, ZoranPower outages in the distribution grid profoundly impact everyday human activity and economic welfare, as numerous infrastructures rely on uninterrupted power for sustained operation. Over the past decade, there has been a significant focus on using machine learning (ML) to predict outage state of risk (SoR) in both research and applications. One of the main causes of outages is weather conditions causing equipment failure due to wear and tear, as well as lightning strikes, in this paper. Therefore, we analyzed the consequences of selecting various weather-related ML model features on the outage SoR. We first show the outage SoR prediction results with and without considering lightning features, and then rank the SoR prediction performance based on various other weather features.Item Hardware-in-the-Loop Validation of Optimal Adaptive Protection for Utility Networked Microgrid Applications(2025-01-07) Kelly, Daniel; Patel, Trupal; Summers, Adam; Matthews, Ronald; Reno, MattThe increased prevalence of distributed energy resources and microgrids has led to highly variable fault current levels and system configurations in distribution networks. To improve power system resilience during severe weather events, microgrids can be networked outside of their original boundaries to restore service to additional customers. Traditional protective relaying schemes may not be equipped to handle these contingencies. Optimal Adaptive Protection (OAP) algorithms can provide more robust system protection during such events by monitoring the network for system state changes and modifying protective relay settings in near real-time. In this paper an OAP algorithm is applied to systems from three different utilities, modeled in OPAL-RT, and connected to hardware-in-the-loop (HIL) relays. Restoration scenarios are considered starting from islanded microgrids and returning to normal operating conditions. By incorporating OAP after any network switching event, protection security is improved throughout the restoration process.Item Sensitivity Analysis and Accuracy of Multiphase Linear Power Flow Models(2025-01-07) Nudehi, Shahin; Gross, DominicWe analyze the accuracy of a linearized bus injection (LMBI) model for unbalanced multiphase networks with explicit models of common three-phase transformers and compare it to LinDistFlow, which uses simplified three-phase transformer models. First, we analytically study the sensitivity of the LMBI model approximation error to generalized load and network parameters in a two-bus network with common bus models. The analysis captures the sensitivity of the LMBI model to (i) loading, (ii) line losses, (iii) and direction of power flow. Comprehensive numerical studies of a modified IEEE 13-bus system are used to illustrate the analytical results and compare the accuracy of LMBI and LinDistFlow models. Results are presented for (i) common three-phase transformer connections, (ii) the integration of inverter-based resources (IBRs), and (iii) various load and generation profiles, including reverse power flow.Item Automated Evaluation of Power Plant Frequency and Voltage Control using Synchrophasors(2025-01-07) Follum, Jim; Mana, Priya; Mitchell-Colgan, Elliott; Faris, AnthonyReliable power system operation depends on maintaining acceptable frequency and voltage. When excursions occur, power plants must respond appropriately to restore these parameters within a suitable margin of their nominal values. Model-based post event analysis is useful for ensuring that power plant controls are functioning properly, but these analyses are labor intensive. To address this challenge, this paper proposes automated measurement-based approaches for detecting excursions and evaluating the frequency and voltage control performance of power plants as they respond. The performance of a power plant is quantified using a novel voltage response measure and a modified frequency response measure applicable to an individual power plant. These metrics gauge how much each power plant adjusts active or reactive power injection to restore frequency or voltage. The detection and analysis methods are validated using publicly available field measurements and the results from a field demonstration at Bonneville Power Administration (BPA). The field demonstration verified that the metrics effectively summarize a power plant's performance, allowing further review of plants with potential deficiencies.Item Introduction to the Minitrack on Monitoring, Control, and Protection(2025-01-07) Venkatasubramanian, Mani; Follum, Jim