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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Operational resilience metrics for power systems with penetration of renewable resources

Abstract Modern power grid is evolving towards carbon neutrality by deploying increasing amount of renewable energy resources. However, the impact of renewable generation on power system planning and operation is not sufficiently investigated, especially the capability of renewable penetrated power systems to resist and recover from major disturbances, which is a critical concern for system operators. Novel metrics and evaluation methodologies are needed to depict systems’ ability in response to events caused by natural disasters, and quantitatively evaluate system performance in various time scales. In this paper, operational resilience metrics are proposed for power systems with penetration of renewable energy resources based on transient stability principles. A systematic methodology is proposed to quantitatively assess the evolution of system performance during various stages of the disaster process. Based on the proposed metrics, a resilience‐oriented disaster management strategy is designed and validated using the modified IEEE 39‐bus test system. The simulation results demonstrate the validity of the proposed metrics and strategy, and show that the system resilience is enhanced during the mitigation of fault conditions.

Gui, Jianzhong↗
DOE OSTI2022

Allocation Mechanisms in Rationed Markets

Economic theory has come to play an important role in power system operations through the design of wholesale markets that are central to their operation. Furthermore, transactive energy places economic theory as a cornerstone in its operational concept as it seeks to integrate the technical needs of the power system with the preferences of its participants. Traditionally the mechanism employed is the continuous double-auction but de-pending on the circumstances the power system find itself in, this mechanism may or may not be the most appropriate, i.e. a one-size fits all market institution cannot be recommended without regard for the features of the underlying trading environment. This paper seeks to explain the economic rationale that guides the choice of a market institution and takes recourse to a theoretical demonstration in the context of a rationed power system scenario where demand exceeds generation (due to any number of events such as outages, microgrid operation, etc) and electrical energy must be rationed to better understand which types of mechanisms are most appropriate.

transactive energy, power system economics, econom↗
DOE OSTI2023

PSI (PowerSimulations.jl) [SWR-23-104]

PowerSimulations.jl is a Julia-based BSD- licensed power system operations simulation tool developed as a flexible and open source software for quasi-static power systems simulations including Production Cost Models. PowerSimulations.jl tackles the issues of developing a simulation model in a modular way providing tools for the formulation of decision models and emulation models that can be solved independently or in an interconnected fashion. For further information regarding the Sienna modeling framework at NREL, see: https://www.nrel.gov/analysis/sienna.html

Lara Aguilar, Jose Daniel↗
DOE OSTI2020

Grid-Following Inverters and Synchronous Condensers: A Grid-Forming Pair?

As power systems across the globe continue to achieve higher instantaneous penetrations of power electronic converter-interfaced renewable sources, the stability of these power systems is challenged because of the removal of synchronous machines, from which stability is traditionally derived. Although technological solutions to these stability challenges are on the horizon, such as the use of grid-forming inverters, they are not yet widely applied to larger power systems, which presents operational challenges for power systems achieving these high instantaneous penetrations today. A potential interim solution using existing technologies is to pair synchronous condensers with grid-following inverters, which might prolong the stability of an operating power system while synchronous generators are turned off during periods of high renewable energy availability. This work examines the transient stability of such a solution using PSCAD simulations of a two-bus system coupled to a varied-length transmission line, with a synchronous condenser at one bus and a grid-following inverter with grid-support functionality at the other. The system is exposed to load step, balanced fault, and unbalanced fault perturbations. It was found that this simple system returned to a steady state for transmission line lengths up to 125 km after 10% load steps, or a variety of fault types.

grid-following inverters↗
DOE OSTI2024

Foundations for the Future Power System: Inverter-Based Resource Interconnection Standards

As power systems evolve to become reliant on solar, wind, batteries, and other inverter-based resources (IBRs), it is essential that those resources meet certain minimum performance and capability criteria designed to ensure the power system operates stably and reliably. Because those criteria, as enshrined in interconnection standards, take years to develop and are very long lived, they need to account for not only the present state of the power system but also its expected future state over the lifetime of the power plants to which they will apply. In addition, they need to be specific enough to ensure reliability without over specifying and, thereby, impeding innovation. Because power systems are shifting rapidly from a state where IBRs make up a small to medium portion of generation to one where the generation will, at times, come predominantly from IBRs, interconnection standards are especially challenging to develop today. Good interconnection standards can make the power system more reliable and less costly to operate, whereas poorly designed standards can lead to major problems, like the famous German 50.2-Hz problem, which introduced a risk of losing many gigawatts of solar on a frequency excursion and resulted in many IBRs being retrofitted at great cost to mitigate a major system reliability risk. Readying the power system by specifying forward-looking technical minimum functional capabilities for IBRs can be an effective approach to avoid future retrofits.

data models↗
DOE OSTI2022

De-Energized Line Testing Interface (DELTI) Report

To guarantee the safety of power system operations, it is crucial to understand a de-energized power line’s status before restoring power. It is hypothesized that the Grid Resonance Probe (GRP) and De-Energized Line Testing Interface (DELTI) can be utilized to identify a faulted distribution line. Therefore, the project team is targeting development of a methodology to identify faulted distribution lines by using the DELTI system. In this R&D task, two field tests on Plum Island have been conducted, including DELTI tests with multiple configurations and fault scenarios. This report provides the analysis results of distribution line fault identification from the two field tests. In the remainder of this report, Section 1 is the introduction of the DELTI system, Section 2 provides the analyses of the two field tests in June and October of 2021, respectively, Section 3 discusses the existing line fault detection devices on market and how they compare to DELTI and Section 4 includes the lessons learned and recommendations for future work.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Peer-to-Peer Energy Trading under Network Constraints Based on Generalized Fast Dual Ascent

We report the wide deployment of renewable energy resources, combined with a more proactive demand-side management, is inducing a new paradigm in both power system operation and electricity market trading, which especially boosts the emergence of the peer-to-peer (P2P) market. A more flexible local market mechanism is highly desirable in response to fast changes in renewable power generation at the distribution network level. Moreover, large-scale implementation of P2P energy trading inevitably affects the secure and economic operation of the distribution network. This paper presents a new P2P electricity trading framework with distribution network security constraints considered using the generalized fast dual ascent method. First, an event-driven local P2P market framework is presented to facilitate short-term or immediate local energy transactions. Then, the sensitivity analysis of nodal voltage and network loss with respect to nodal power injections is used to evaluate the impacts of P2P transactions on the distribution network, which ensures the secure operation of the distribution system. Thereby, the external operational constraints are internalized, and the cost of P2P energy trading can be appropriately allocated in an endogenous way. Moreover, a generalized fast dual ascent method is employed to implement distributed market-clearing efficiently. Finally, numerical results indicate that the proposed model could guarantee secure operation of the distribution system with P2P energy trading, and the solution method enjoys good convergence performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Entropy-Infused Deep Learning Loss Function for Capturing Extreme Values in Wind Power Forecasting

Extreme scenarios in wind power generation occur with higher frequency and larger magnitude in the recent years due to the ever-increasing extreme meteorological factors. Accurate forecasting of the occurrence of extreme values in wind power generation is of great concern to ensure reliable power system operation. Recently, deep learning models have surged in popularity for wind power forecasting, with the mean squared error (MSE) loss function being commonly used. However, the MSE loss function, being sensitive to extreme values, disproportionately penalizes larger errors, cannot adequately capture the extreme values present in wind energy data, and novel loss functions have seldom been tailored for wind power forecasting. To this end, in this paper, we introduce a novel loss function specifically crafted to capture extreme values in wind power forecasting. The experimental results with four fundamental deep learning methods on open source wind power dataset validate that the new loss function is efficient and superior in all cases compared to MSE in capturing extreme values while maintaining forecasting performance.

17 WIND ENERGY↗
DOE OSTI2023

Power System Wildfire Risks and Potential Solutions: A Literature Review & Proposed Metric

Several fire risk evaluation, fire tracking, and fire response resources are available. The risk metrics and fire response programs are sometimes modified to include a power system context. The risk metrics often evaluate the risk of fires causing power system faults or outages, especially on transmission systems. The response programs are modified to ensure the safety of power system equipment and first responders as well as to coordinate power system outages to both ensure safety during an active fire and prevent fire ignition during high risk periods. Although some aspects of wildfire responses have been adapted to include power system concerns, adaptations to power system operations and maintenance to include wildfire risks and responses are still nascent. In particular, a risk metric that evaluates the potential for power system components to ignite wildfires is needed to help guide power system upgrade efforts and power system fire safety measures. This document serves as a brief literature review of wildfire risk metrics and response programs and how they relate to power systems. It also includes a proposed risk metric and structure for describing the risk of a power system component igniting a fire.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Substation-Level Grid Topology Optimization Using Bus Splitting

Operations of substation circuit breakers are important for maintenance needs and topology reconfiguration in power systems. Bus splitting is one type of topology change where the two bus bars at a substation can become electrically disconnected under certain actions of circuit breakers. Because these events involve detailed substation modeling, they are typically not considered in routine power system operation and control. In this paper, an improved substation-level topology optimization framework is developed by expanding traditional line switching decisions by breaker-level bus splitting, which can further reduce grid congestion and generation costs. A tight McCormick relaxation is proposed to reformulate the bilinear terms in the resultant optimization problem to linear inequality constraints. Thus, a tractable mixed-integer linear program reformulation is attained that allows for efficient solutions in real-time operations. Numerical studies on the IEEE 14-bus and 118-bus systems demonstrate the computational performance and economic benefits of the proposed topology optimization approach.

bus split↗
DOE OSTI2022

Opportunities for Renewable Energy, Storage, Vehicle Electrification, and Demand Response in Rajasthan's Power Sector

To support the government of Rajasthan and inform state policy makers, regulators, planners, and system operators on power system trends, NREL undertook a long-term capacity expansion planning study. We used NREL's flagship capacity expansion planning tool for the power sector called the Regional Energy Deployment System India (ReEDS-India) to understand the generation and transmission needs of Rajasthan through 2050. NREL's modeling framework includes co-optimized decisions about generation, energy storage, transmission, and reserves investments needed to meet future demand while maintaining reliable electricity supply. Scenario analysis was conducted to assess a range of potential future scenarios, providing insight for planning agencies, utilities, and local stakeholders about key trends and sources of uncertainty.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Use of Digital Real-Time Simulation and Optimization to Identify Maximum Real Power Injection on the Banshee Distribution Network: Preprint

This study investigates the hosting capacity of the Banshee Distribution Network by optimizing the real power injection at carefully selected Distributed Energy Resource (DER) locations. The analysis is conducted within the framework of power system operational constraints, including bus voltage ranges, thermal line ratings, and transformer loading limits. A Python-based Genetic Algorithm (GA), implemented using the PyGAD library, is employed to iteratively identify the optimal power injection configuration that maximizes network utilization while preserving system reliability. The methodology integrates a real-time simulation environment using the Real-Time Digital Simulator (RTDS), allowing high-fidelity evaluation of power flow and voltage behavior under each proposed injection scenario. By coupling the optimization algorithm with real-time simulation feedback, this approach ensures that both static and dynamic constraints are enforced during the evaluation process. The GA leverages evolutionary operators such as selection, crossover, and mutation to navigate the nonlinear search space efficiently. The results of the study delineate the feasible hosting capacity at three targeted buses, reflecting maximum real power levels that can be injected without causing voltage violations, transformer overloading, or line congestion. These findings provide a decision- support tool for distribution planners and utilities aiming to integrate higher penetrations of DERs in existing infrastructure. Additionally, the work lays the foundation for extending such optimization techniques to multi-objective formulations, including economic dispatch and reactive power coordination, in future studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Use of Digital Real-Time Simulation and Optimization to Identify Maximum Real Power Injection on Banshee Distribution Network

This study investigates the hosting capacity of the Banshee Distribution Network by optimizing the real power injection at carefully selected Distributed Energy Resource (DER) locations. The analysis is conducted within the framework of power system operational constraints, including bus voltage ranges, thermal line ratings, and transformer loading limits. A Python-based Genetic Algorithm (GA), implemented using the PyGAD library, is employed to iteratively identify the optimal power injection configuration that maximizes network utilization while preserving system reliability. The methodology integrates a real-time simulation environment using the Real-Time Digital Simulator (RTDS), allowing high-fidelity evaluation of power flow and voltage behavior under each proposed injection scenario. By coupling the optimization algorithm with real-time simulation feedback, this approach ensures that both static and dynamic constraints are enforced during the evaluation process. The GA leverages evolutionary operators such as selection, crossover, and mutation to navigate the nonlinear search space efficiently. The results of the study delineate the feasible hosting capacity at three targeted buses, reflecting maximum real power levels that can be injected without causing voltage violations, transformer overloading, or line congestion. These findings provide a decision- support tool for distribution planners and utilities aiming to integrate higher penetrations of DERs in existing infrastructure. Additionally, the work lays the foundation for extending such optimization techniques to multi-objective formulations, including economic dispatch and reactive power coordination, in future studies.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Research Priorities and Opportunities in United States Wholesale Electricity Markets

The power system is currently undergoing a number of changes, including a rapidly evolving resource mix, growth of distributed energy resources (DERs), more active consumer participation, increased deployment of energy storage and hybrid resources, and more advanced communication and control requirements. These changes in the power system present numerous technical, economic, implementation, and policy challenges and research opportunities for power system operators. To help address these challenges, a collaboration among five research institutions—Argonne National Laboratory, the National Renewable Energy Laboratory, Lawrence Berkeley National Laboratory, the Electric Power Research Institute, and Johns Hopkins University—has been established to provide technical assistance to the seven U.S. Independent System Operators (ISOs) and Regional Transmission Organizations (RTOs). The 3-year project aims to leverage the advanced methods, tools, datasets, and resources of the collaborators to provide robust analytical support to address the high-priority market challenges that will be faced in the 2- to 10-year time horizon.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗