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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Grid-Ready Flexible Transformers for Resilient Transmission Networks

Today’s transmission networks extend for hundreds of kilometers, transferring significant amounts of electrical energy. For every country, there are sort of “back- bone” lines, where a massive failure of transformers would create serious challenges to sustain a reliable energy supply. Natural phenomena and human driven actions could be triggers of such catastrophic events. For large utilities, or groups of utilities, it would be highly convenient to count with “flexible transformers”, which could be used as replacements for different voltage levels and with impedance adjustable to match optimum local requirements of impacted substations. Currently applied “emergency transformers” are fixed-impedance devices. In this contribution, a new concept of flexible, “future-grid ready” type of power transformers, specially devised for transmission networks is explained. This transformer has adjustable impedance features, which could be on-line operated. The concept has been proven to be functional and stable in the factory lab and in the field, by means of a prototype autotransformer of of 100 MVA, 165/69 Kv.

impedance of transformers↗
DOE OSTI2025

Probabilistic Resilience-Oriented Assessment Approach for Transmission Networks Under Wildfires

The rising threat of wildfires poses significant challenges to power transmission networks, particularly in areas prone to such disasters. Traditional approaches for wildfire risk assessment neglect some potential wildfire scenarios. Here, this paper introduces a probabilistic resilience-oriented assessment approach for power transmission networks to address this gap. Initially, a probabilistic wildfire model is developed to capture uncertainties in ignition, intensity, and fire spread. Next, a spatiotemporal fragility model is constructed to assess the impact of wildfires on transmission corridors, incorporating Thermal Aging (TA) and Dynamic Thermal Rate (DTR) change. Finally, a comprehensive resilience metric is defined to evaluate system performance, leveraging the fragility model to determine component and system-level resilience. The approach employs a combinatorial enumeration method to generate potential wildfire scenarios, enhanced by an impact-increment-based state enumeration (IISE) method for computational efficiency. The proposed method provides critical insights for identifying system vulnerabilities and developing robust strategies to protect transmission networks from wildfires. The efficacy of this approach is validated through extensive scenarios of the RTS-GMLC system across Southern California, Nevada and Arizona.

Vahedi, Soroush [Univ. of Connecticut, Storrs, CT ↗
DOE OSTI2022

Rolling Optimization of Transmission Network Recovery and Load Restoration Considering Hybrid Wind-Storage System and Cold Load Pickup

A common solution to deal with the stochasticity introduced by fast-ramping wind power integration is to equip wind farms (WFs) with energy storage systems (ESSs) to formulate hybrid WF-ESSs. In addition to leveling off wind power fluctuations during normal operations, a hybrid WF-ESS can be a flexible power source to accumulate the power system restoration. In this paper, we propose a rolling optimization model for transmission network recovery and load restoration considering the contributions of WF-ESSs. The proposed model is formulated as a mixed integer linear programming problem that simultaneously optimizes the amount and location of restorable load blocks as well as the restoration lines. The cold load pickup features of interrupted loads considering the outage duration are modeled in detail. A chance-constrained method is employed to deal with the uncertainty of wind power, and a rolling horizon-based framework is adopted to reduce the influence of forecast error. Case studies are conducted on both New England 39-bus system and part of a provincial power system in China. The results show that the load restoration process can be significantly accelerated by employing the proposed method and contributions of hybrid WF-ESSs to power system restoration are validated.

chance-constrained optimization↗
DOE OSTI2024

Implementing a Hardware Testbed Using 3-Level ANPC Software Defined Inverters for Fault Analysis of a Transmission Network

In this paper, we propose the implementation of a hardware testbed using 3-level active neutral point clamped (ANPC) software-defined inverters for fault analysis. A test case transmission network equipped with two grid forming (GFM) inverters and four resistive loads is considered in this research. Firstly, grid forming control laws including PI feedback control and droop control are implemented to operate the inverters in parallel. Then, we implement a fault ride-through (FRT) logic and perform a simulation of the test system by applying a three-phase fault. Simulation results show the effectiveness of the fault recovery algorithm upon clearance of the fault. Finally, a 3-level ANPC software-defined inverter is programmed with required control laws and characterized through various lab experiments.

3-level ANPC inverter↗
DOE OSTI2025

Impact of Geomagnetic Induced Current Neutral Blocking Devices on Distance Relays in Sub-transmission Networks with IBR

Geomagnetically induced currents (GICs) can flow through transmission lines during geomagnetic disturbances, such as solar flares or coronal mass ejections. These currents can cause problems like transformer saturation and equipment damage. The most common method of mitigating GICs involves installing GIC neutral blocking devices (NBDs) in transformer neutrals. However, the wide application of capacitive GIC blocking devices may have unintended adverse effects on other devices, such as distance protection relays. As the number of inverter-based resources being connected to the transmission and sub-transmission systems increases, the likelihood of a sub-transmission line protected by a distance relay connected to a transformer with NBDs is increasing. Therefore, distance relays fed by IBRs and transmission lines with GIC-NBDs must be studied. This paper studies the effect of GIC-NBDs on a 69kV sub-transmission line of various lengths fed by a 25 MVA IBR and synchronous source. This work focused on the behavior of the GIC-NBDs using the measured apparent phase-to-ground and phase-to-phase impedance calculated by the relay and the source impedance ratio (SIR) during various electrical faults.

Patel, Trupal R [Sandia National Laboratories (SNL↗
DOE OSTI2024

Convex Relaxations of Maximal Load Delivery for Multi-Contingency Analysis of Joint Electric Power and Natural Gas Transmission Networks

Recent increases in gas-fired power generation have engendered increased interdependencies between natural gas and power transmission systems. These interdependencies have amplified existing vulnerabilities in gas and power grids, where disruptions can require the curtailment of load in one or both systems. Although typically operated independently, coordination of these systems during severe disruptions can allow for targeted delivery to lifeline services, including gas delivery for residential heating and power delivery for critical facilities. To address the challenge of estimating maximum joint network capacities under such disruptions, we consider the task of determining feasible steady-state operating points for severely damaged systems while ensuring the maximal delivery of gas and power loads simultaneously, represented mathematically as the nonconvex joint Maximal Load Delivery (MLD) problem. To increase its tractability, we present a mixed-integer convex relaxation of the MLD problem. Then, to demonstrate the relaxation’s effectiveness in determining bounds on network capacities, exact and relaxed MLD formulations are compared across various multi-contingency scenarios on nine joint networks ranging in size from 25 to 1191 nodes. The relaxation-based methodology is observed to accurately and efficiently estimate the impacts of severe joint network disruptions, often converging to the relaxed MLD problem’s globally optimal solution within ten seconds.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

FLEXIBLE POWER TRANSFORMERS TO IMPROVE RESILIENCY OF TRANSMISSION NETWORKS

For decades, transformer flexibility of operation has been limited to adjustable voltage ratio and, in some cases, several ratings with staged cooling. Transformers reconnectable to multiple voltage ratings have been primarily applied as emergency replacements. Other versions of “flexible transformers” were developed for continuous, long-term operation at specific sites, with application limited to large utilities. A new technology that supports today’s power systems adaptability requirements has been developed to provide not only voltage and power rating flexibility, but also an adjustable short-circuit impedance. This last, unique feature allows for a closer match to actual system operational requirements and could be used in the future to enhance resiliency and improve dynamic control of electrical grids. While the solution’s fundamentals have already been introduced in several technical forums, the intention of this article is to focus on the potential benefits of this new type of transformer and share the deployment experience of a full-scale prototype that has been in operation in a major U.S. utility since 2021

flexible transformer, resilient grid, variable lea↗
DOE OSTI2020

Evolutionary history, potential intermediate animal host, and cross-species analyses of SARS-CoV-2

To investigate the evolutionary history of the recent outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China, a total of 70 genomes of virus strains from China and elsewhere with sampling dates between 24 December 2019 and 3 February 2020 were analyzed. To explore the potential intermediate animal host of the SARS-CoV-2 virus, we reanalyzed virome data sets from pangolins and representative SARS-related coronaviruses isolates from bats, with particular attention paid to the spike glycoprotein gene. We performed phylogenetic, split network, transmission network, likelihood-mapping, and comparative analyses of the genomes. Additionally, based on Bayesian time-scaled phylogenetic analysis using the tip-dating method, we estimated the time to the most recent common ancestor and evolutionary rate of SARS-CoV-2, which ranged from 22 to 24 November 2019 and 1.19 to 1.31 × 10 -3 substitutions per site per year, respectively. Our results also revealed that the BetaCoV/bat/Yunnan/RaTG13/2013 virus was more similar to the SARS-CoV-2 virus than the coronavirus obtained from the two pangolin samples (SRR10168377 and SRR10168378). We also identified a unique peptide (PRRA) insertion in the human SARS-CoV-2 virus, which may be involved in the proteolytic cleavage of the spike protein by cellular proteases, and thus could impact host range and transmissibility. Interestingly, the coronavirus carried by pangolins did not have the RRAR motif. Therefore, we concluded that the human SARS-CoV-2 virus, which is responsible for the recent outbreak of COVID-19, did not come directly from pangolins.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

A Solar-assisted Voltage Optimization Method for Transmission Solar Network Power System

This paper proposes a new formulation and solution algorithm that uses transmission level solar inverters to address the security-constrained optimal power flow (SCOPF) problem. The goal is to stabilize voltage fluctuations in transmission networks in base case and contingency scenarios, by using bulk solar power plant with a minimal number of post-contingency corrections. To achieve this goal, a two-stage volt/var optimization method is proposed to first correct all voltage violations with the volt-var alternating current optimal power flow (ACOPF) algorithm for a base case. Then a linearized SCOPF volt-var control algorithm is proposed to identify the corrective actions for all potential voltage violations in all contingency scenarios. The proposed method was tested and validated on a modified IEEE 118-bus system with solar photovoltaic (PV) data.

Photovoltaic, Volt/Var Control↗
DOE OSTI2024

A Resilient Integrated Resource Planning Framework for Transmission Systems: Analysis and Optimization

This article presents a resilient Integrated Resource Planning (IRP) framework designed for transmission systems, with a specific focus on analyzing and optimizing responses to High-Impact Low-Probability (HILP) events. The framework aims to improve the resilience of transmission networks in the face of extreme events by prioritizing the assessment of events with significant consequences. Unlike traditional reliability-based planning methods that average the impact of various outage durations, this work adopts a metric based on the proximity of outage lines to generators to select HILP events. The system’s baseline resilience is evaluated by calculating load curtailment in different parts of the network resulting from HILP outage events. The transmission network is represented as an undirected graph. Graph-theoretic techniques are used to identify islands with or without generators, potentially forming segmented grids or microgrids. This article introduces Expected Load Curtailment (ELC) as a metric to quantify the system’s resilience. The framework allows for the re-evaluation of system resilience by integrating additional generating resources to achieve desired resilience levels. Optimization is performed in the re-evaluation stage to determine the optimal placement of distributed energy resources (DERs) for enhancing resilience, i.e., minimizing ELC. Case studies on the IEEE 24-bus system illustrate the effectiveness of the proposed framework. In the broader context, this resilient IRP framework aligns with energy sustainability goals by promoting robust and resilient transmission networks, as the optimal placement of DERs for resilience enhancement not only strengthens the system’s ability to withstand and recover from disruptions but also contributes to efficient resource utilization, advancing the overarching goal of energy sustainability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Joint scheduling of energy, fast and primary frequency response reserves in integrated transmission–distribution networks

Inverter-based distributed energy resources (DERs) connected to distribution networks (DNs) can provide fast frequency support, but their reserve deliverability depends on feeder constraints and differs from synchronous primary frequency response (PFR). Existing transmission–distribution coordination studies usually treat reserve generically or neglect feeder-level feasibility, while frequency-security scheduling studies rarely represent distribution feeders explicitly. This paper develops a bi-level day-ahead scheduling framework for integrated transmission–distribution networks that jointly clears energy, transmission-side PFR, and distribution-side fast frequency response (FFR) under exogenous hourly inertia and largest-loss inputs from an external unit commitment (UC) schedule. The transmission problem is modeled with DC-optimal power flow (OPF) and closed-form second-order cone (SOC) frequency-security constraints, whereas each DN is represented by a reserve-aware branch-flow AC-OPF so that scheduled fast reserves remain deliverable during activation. The bi-level problem is reformulated through Karush–Kuhn–Tucker (KKT) conditions into a mixed-integer SOC program, and a penalty term is used to tighten the distribution-network relaxation. In the reduced test system, lower exogenous inertia increased the required primary response from 179.64 MW to 191.08 MW, distribution-side fast response reduced total frequency-response procurement by up to 4.9%, and neglecting distribution constraints overstated the combined distribution-side energy and reserve award by up to 18%. In the expanded study, the largest case was solved in 2.02 s with a 0.00% optimality gap. Time-domain simulations kept the frequency nadir above 59.0 Hz in all tested hours. These results demonstrate the value of fast-response modeling and distribution-feasible reserve delivery in coordinated market clearing.

Noh, Seung-Gil↗
DOE OSTI2026

Techno-Economic Analysis of Repurposing Natural Gas Transmission Pipeline Networks to Accommodate Hydrogen Blends

Blending hydrogen into natural gas infrastructure could supplement natural gas supply and increase resilience for applications such as ammonia production, peaking and load-following power plants, and heating. The United States has an extensive network of natural gas pipelines, but the feasibility of employing this infrastructure to transport hydrogen is unclear. We analyze the costs associated with repurposing three distinct natural gas transmission pipelines in different locations within the United States to carry blends of hydrogen up to 100% via three different pipeline network modification methods and compare against the cost of building a new dedicated hydrogen pipeline. We conduct a sensitivity analysis on the hoop stress limit of the existing pipe, techno-economic parameters, emissions, and relative capacity. The results show that the capital costs required to upgrade a pipeline can vary from tens of millions to billions of dollars depending on the length and capacity of the existing pipeline section, whether the existing pipeline already operates at or below its maximum allowable operating pressure, whether future demand is expected to increase or decrease, the network modification method selected, and pipe material costs. The delivered cost of energy to end users is impacted less by the levelized cost of transporting hydrogen blends than by the cost of the natural gas and hydrogen fuels being transported. The emissions impact of blending hydrogen into natural gas transmission networks scales proportionally with the amount of energy displaced with low-emission hydrogen (such as from natural gas with carbon capture and sequestration or electrolysis powered by nuclear, renewable, or geothermal electricity), therefore low blend ratios (e.g., < 20% vol. hydrogen) will result in low emissions impacts. Factors such as permitting and right-of-way costs, the proximity of the pipeline to hydrogen demand and production, and the compatibility of and/or retrofitting costs of end-use gas-fueled technologies will likely be greater drivers in determining whether converting a particular natural gas pipeline to carry hydrogen makes economic sense.

08 HYDROGEN↗
DOE OSTI2024

Average Incremental Cost Pricing for the AC Unit Commitment Problem [Rev. 1]

Unit Commitment (UC) problems that consider the Alternating Current (AC) model of the transmission network have long been considered intractable to solve at scale by the power system community. Recently, the Grid-Optimization (GO) Competition held by the Advanced Research Project Agency-Energy (ARPA-E) has facilitated the development of the first algorithms to solve large-scale ACUC problems. This new capability opens a path towards the explicit consideration of the AC transmission network model in UC problems used to clear day-ahead electricity markets. This calls for the analysis of electricity market structures that accommodate both the continuous non-linearity of the AC transmission network and the discrete non-linearity of the UC problem simultaneously. This paper serves as an initial effort to do so by proposing an Average Incremental Cost (AIC) pricing structure that is designed around the ACUC problem. In particular, an AIC one-pass pricing problem is proposed that represents a continuously constrained variant of the ACUC problem and allows for the computation of Locational Incremental Prices (LIPs) for both real and reactive power as the local optimal Lagrange multipliers of the power balance constraints. To avoid degeneracy, the pricing problem includes a small parameter ϵ > 0. Under certain assumptions market participants are shown to realize profit that converges to a non-negative value as ϵ approaches zero, practically ensuring profitability for small values of ϵ. We additionally provide many simple and important examples that provide intuition and insights into the proposed prices. Examples illustrate the basic concept of AIC pricing, the derived profitability results, the existence of multiple LIPs, the importance of including reactive power in the dispatch and pricing problems, the need for reactive power prices, and the improved incentives exhibited by LIPs as compared to traditional Locational Marginal Prices (LMPs). We additionally indicate many directions for future work including analysis of larger test cases.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Smart Data Mapping for Connecting Power System Model and Geospatial Data

Knowing the geospatial locations of power system model elements is the foundation for analyzing system vulnerability to natural hazards and connecting loads with end users and their communities. However, power system models and geospatial data for power grid assets may have been developed asynchronously without close coordination. Creating a direct mapping between the two may be a challenging task, considering heterogeneous data structures, target uses, historical legacies, and human errors. This work aims to build an automatic data mapping workflow to connect power system model elements and geospatial data for transmission network, and to support energy grid resilience studies for Puerto Rico. The primary steps in this workflow include constructing graphs using geospatial data, and aligning them to the transmission networks defined in the power system data. The results have been evaluated against existing manual mapping practices for part of the Puerto Rico Power Grid model to illustrate the performance of such auto-mapping solutions.

Resilience, geospatial data, grid transmission net↗